There’s an industrial revolution under way in businesses across the world, and it is all about automation. Businesses are embracing machine learning and artificial intelligence to make better decisions automatically. And the reason for this revolution is the comparative strengths of humans and computers.
Computers are strongest at repetitive tasks, mathematics, data manipulation and parallel processing. So long as a task can be defined as a procedure, a computer can do that task over and over again, without getting tired, giving the same results each time. Computers can manipulate numbers and data in volume much faster than any human.
Several years ago I went back to university to do a masters degree, and after a 25 year break from university I was out of practice at mathematics. Imagine my excitement and relief when I discovered that now there is software that will do algebra and calculus for me! And computers can do more than one thing at a time. Have you ever tried to rub your belly and tap your head at the same time? I can’t do both actions simultaneously. But modern computer networks are powerful, able to routinely do dozens of different processes at once.
This does not mean that humans are obsolete. What humans are much more skilled than machines at are communication and engagement, context and general knowledge, creativity and empathy. When I have a frustrating problem, I want to talk to a human. Someone who will understand my exasperation, listen to my experience and make me feel valued as a customer, whilst also solving my problem for me. Humans are much better at common sense than computers, instantly recognizing when a decision doesn’t make sense. And humans can be creative. I recently heard music composed by a computer, and I’m sure that song won’t make it into the Top 40!
Customer Service
Recently I had a conversation with the manager of a call centre that dealt with hundreds of customer service issues each day. In order to ensure the quality of the service and advice, the call centre operators were given scripts and were commanded to follow those scripts without changing a word. The problem was that both staff and customers became frustrated. Staff felt bored and unchallenged, and customers with non-standard problems felt like they weren’t being heard. Staff turnover increased, and customer satisfaction levels dropped.
Customer Satisfaction
The manager then tested using chatbots to answer simpler questions from customers, freeing up the human operators to deal with non-standard enquiries. This was a situation where computers had a comparative advantage over humans. The call center processes were fully defined, operating at scale, and the scripted answers were correct. The results spoke for themselves. Computers were much better at helping with the repetitive enquiries, and humans were better at dealing with the unusual enquiries. Staff engagement increased, as did customer satisfaction.
This has implications for human resources and process innovation. Processes that require humans to do repetitive, well defined tasks can be replaced by artificial intelligence. This frees up staff to do what humans are best at:
asking the right questions,
applying common sense,
creating new solutions,
evangelising new ideas, and
generating sales and profit.
Let your humans be human. Free them from repetitive tasks. Change job descriptions to focus on human strengths, and hire people who best embody the comparative advantages of humans. Look for human processes that are well defined and repetitive, and enhance the process by introducing artificial intelligence. Some ways company have started to incorporate artificial intelligence and machine learning into their processes include:
There are even some companies out there that have started automating the automation, like DataRobot. Instead of hiring and training up a data scientists, the arcane process of building predictive models, once the sole domain of data scientists, can all be automated. The system automatically builds predictive models based on your data, freeing up your humans to be human, to be better conversational AI specialists.
Based in Singapore, Colin is the Director, Customer Success and Lead Data Scientist, APAC for DataRobot, where he advises businesses on how to build business cases and successfully manage data science projects. Over his career, Colin has held a number of CEO and general management roles, where he has championed data science initiatives in financial services, healthcare, security, oil and gas, government and marketing. He frequently speaks at various global conferences. Colin is a firm believer in data-based decision making and applying AI. He is passionate about the science of healthcare and does pro-bono work to support cancer research.
The other day, my 73-year old father, was grumbling about something he read in the news about automation of processes at the local bank.
“People don’t talk anymore. In my day, customer service meant talking to someone, saying hello, asking how your day was. Now it’s a recorded voice or reading tiny print online. Customer service is dead.”
That got me thinking. The role of a traditional customer service representative has evolved over the years. Once the domain of primarily the service and hospitality staff, the role of customers and our relationships with them has seen several costume changes — the phone IVR, surveys, forms, smiling uniformed people, you name it. But even as the modes change, the role of customer services and engagement has only just increased. Today customer relationships have become a full-fledged industry. 70% of buying experiences are based on how the customer feels they are being treated. The more people feel they’re being listened to, the happier they are and the more money they’ll spend — or that’s the hope. An Adobe report even suggests that customer service can deliver a higher ROI than marketing. Customer service, once upon a time, used to be about happy people, lots of solicitous questions and a solution with a smile. While it’s certainly true that the human factor seems to have declined over the years, the key tenets of a human interaction customer service have remained — conversations, solutions and a smiling demeanor.
So can a bot — the latest entrant into the customer service role — actually deliver these admittedly-human qualities?
Chatbot as the perfect concierge
Businesses that recognize how much time consumers spend on messaging apps such as Facebook Messenger and Slack have developed automated messaging technology. In 2015 messaging apps surpassed social networking apps, and chat apps have higher retention and usage rates than most mobile apps. Today, brands are looking at bots to become the next concierge, to understand what the customer wants, which direction they’re headed on, to involve them in interesting content, spread brand awareness and indeed, carry on conversations with a smile. But is all of that realistically possible?
On paper, it’s the perfect solution. Bots are machines, easily duplicated and incapable of human drama. They can be taught to function perfectly with a specific set of rules or through machine learning. These capabilities, limited as they are, can be trained to emulate the perfect customer service person’s skills — kindness, patience and solution-oriented. A machine can be taught to never be sarcastic and to always have a listening ear. And because it doesn’t have human failings such as fatigue or just being an asshole, it’s becoming an increasingly widespread phenomenon.
Any company with a chatbot interacting in the marketplace has the opportunity to gain valuable customer information. This has benefits in several areas — more personalization, targeted marketing, sales strategies as well as manpower allocation.
Not there yet
While bots were also a hot topic at the recent Corporate Social Media Summit, the jury were admittedly slightly skeptical. Bots are still very much in their nascent stage. And there have been several failures. In the rush to develop the next Siri or Cortana for their businesses, what most companies have ended up with are simplistic, underdeveloped tech with limited capabilities and faulty data. Of course there are the filthy people of the internet. It took less than 24 hours for Microsoft’s Tay to turn into into a filthy Nazi racist troll and two weeks for the cute little hitchbot to become roadside shrapnel. Even if the world were a perfect place, everyone was sunshine and unicorns and keeping empathy and other qualities aside, the actual functions and solutions given to customers by these bots need to work. That requires very skilled developers — but even they aren’t free of error.
Having said that, the possibilities for a bot are immense. Even though the big tech companies haven’t quite cracked how to make it work. Our co-founder Chris has a strong vision on the problems with Conversational AI, and perhaps more importantly — he offers solutions. He will share his vision 26th August on Startup Friday (still some spots left) and will start to share his vision in our blog series about Conversational AI that’s coming up here on Medium.
I know I will be paying attention. My own life have tons of bots — from the local Asian store from online magazines to Facebook to even my fitness wearable. Chatbots might very well be the face of the future one day. Now if they only knew how to smile.
I remember reading an article almost ten years ago talking about how teens were sending over 40 texts a day on average. The tone of the article was incredulous, but the statistic pales in comparison to how we exist online now. Speaking personally, it’s not implausible I send off 40 messages before 10 AM in my morning inbox check in. Sarah Guo, a partner of Greylock, expressed it succinctly when she took to Medium: “More than a decade ago, academics such as Thurlow described a “communication imperative”—human beings are driven to maximize their communication volume and satisfaction. More recently, researchers have described it as compulsion.”
While constant connectedness is old news, technology has finally achieved a point it can leverage this behavior. As with all big shifts, there will be survivors and those who don’t adapt fast enough. Companies will need to change to a conversational mode of thought to maintain the experiences users expect and deliver the individuality anticipated.
People Always Talk
Nearly 25 years ago, Harvard Business Review wrote “today if you’re not on the phone or talking with colleagues and customers, chances are you’ll hear, “Start talking and get to work!” In the new economy, conversations are the most important form of work.” Conversations are how we track knowledge flows. Conversation flows are how people create value, share information, and illustrate how companies operate.
A cited example is McKinsey. McKinsey prides itself heavily on the intelligence of its members, and by an extension the true value of McKinsey over other firms is its extensive knowledge base. That knowledge is curated and developed through internal conversation and shared through internal conversation. In short, McKinsey is conversation.
We are entering a new age for product development – one dictated by the conversational economy. Broadly, the conversational economy is the catchall phrase for companies, products, and ideas built on, alongside, or relying heavily on a conversational interface. More simply, they are services that leverage conversation.
This definition is board, and intentionally so. While some apps like iMessage, Snapchat and email obviously fit into this definition, conversation works as a backbone in services like Facebook, customer service complaints, and online advertising as well. Finding a common backbone helps derive a working model for these services.
Between the myriad of mobile apps used every day, access to the internet, and the seemingly innate human need to feel connected, conversation based platforms are dominating our lives. We have effectively destroyed the asynchronous quality of day to day life. We persist online, and, consequently, our conversations with one another never really begin or end. This data stream is a jackpot for product creation.
Smarter Everyday
Artificial intelligence, in the eyes of the public, has snuck past an important threshold. Presentations by titans like Facebook and Google have assured that we are moving away from the robotic idea of natural language processing in a rigid sense to natural language understanding. In other words, instead of responding to a keyword or a phrase, computers are beginning to be able to understand sentence, paragraphs, and intent.
There are a variety of causes for this – improvement of machine learning and deep learning, Moore’s Law, and rate of mobile and app data collection, to name a few. Algorithms and software are taking on their own intelligence. Just the idea that failed outcomes can make systems better is an astounding twist compared to five years prior.
Additionally, we’re in the middle of the boom of ambient computing, the idea that our environments and surroundings are responsive. We don’t have to open our phone or flip open a laptop to be connected. On the way to work I may pass a few smart cameras, a plethora of listening iPhones and Galaxy phones, an Alexa, Chromecasts, and more. Despite this, I would characterize myself as one of the less connected people in my demographic. At every step of my day my voice can be heard, position tracked, and activity monitored. Being connected no longer has much to do with if our phone is on our person or if we’re behind a keyboard.
Although passive collection has subtly pushed past our natural aversion to share information with technologies we don’t understand and people we don’t know, this one-sided trade has come with the expectation of usability. When software doesn’t work or apps crash, we no longer blame ourselves, we blame companies. We are inundated with choices, but that means that we have little tolerance of poor experiences. Users are more empowered than ever in that they don’t have to subject themselves to experiences they don’t want or content they’d rather avoid. We so demand these freedoms that events like net neutrality rapidly cause public outcry and social faux pas by companies like EA tank sales.
Computing, connectedness, and data almost completely undermine how product managers need to think about designing products. The need to leverage conversation to deliver value has emerged as one of the most critical company problems. IDEO acquiring a data analytics company, giants like Apple acqui-hiring boutique companies with human-centric software, and Salesforce pushing Einstein all serve as mine canaries that even the most established companies are racing and struggling to adapt.
Buying In and Cashing Out
As George Box famously cited – all models are wrong, but some are useful. Where is the utility of viewing products as ongoing conversations?
A helpful place to start is in how companies have historically fended off competition. These ‘moats’ include things like brand loyalty, unique data sources, and intellectual property. However, as technologies like AI are more readily available via open source projects, cloud hosting and computing are only a few clicks away, and systems of engagement continually emerge, the traditional ideas of tech defensibility are evaporating. In a Greylock article on Medium, they wrote “In all of these markets, the battle is moving from the old moats, the sources of the data, to the new moats, what you do with the data.”
In another words, companies are now finding defensibility through the experiences they create. To create these experiences for customers in the conversational era, companies will have to harness existing behavior, respond personally, and work faster.
Harnessing existing behavior is an exercise in invisibility. The real frontier for conversational companies to generate solutions for problems before the consumer is even aware. For example, Facebook realized that people asked for recommendations on their newsfeeds. Instead of creating a new service, they had posts automatically update with reviews and locations. They created a new card that changed automatically depending on what a user wrote. As expressed by a product designer at Facebook: “We didn’t try to invent a completely new behavior; rather, we found an existing one and made it way better.”
To cite an example within my own career, food industry companies often lose hours if not days within food recall investigations. Tracking a faulty shipment through several distributors can be tricky. We worked to create a product that reads the complaint before the owner may even be aware it exists and start and investigation. By the time an owner is even aware there is a problem, a report is ready. By approaching complaints, invoices, and shipments and messages between companies, value can be created seamlessly in a second layer.
As I’ve written about before, personalization is an increasingly critical element of producing customer lifetime value. Harvard Business Review started to notice this trend in their research on customer service: “Even as artificial intelligence becomes embedded in everyday interactions; human conversation remains the primary way people make complex purchases or emotional decisions.” The fatal error in a lot of software products is focusing on company efficiency over consumer experience. While these changes may boost bottom line in the short term, they encourage competitor entry and consumer drop off.
Conversational AI apps have an obvious outlet for personalization, and the power behind them allow easy switching between automation and human elements. More simply: “these intelligent agents will facilitate one-on-one conversations between consumers and sales or customer service representatives rather than simply replacing human interaction.” Imagine a case where someone sits on a delayed flight and sends out an angry tweet. A conversational built system could find the message, tag it, and route it to an agent. While the agent delivers a personal response with an update, the system has already sent an alleviating reward of extra miles to the customer. The captain may be alerted of sentiment on the plane and deliver an announcement. While an autoresponder may have been cheaper, the customer will now remember the exceptional level of immediate service and is more likely to return. As information and computing become free, the real commodity becomes the personality of the person on the other end of the line.
In the shorter term, there’s a simpler way to think about AI adoption – people don’t trust what they don’t understand. In the classic product management advice, it’s best to start with a problem and move to solution. Leveraging conversation is a means to building a better product, but that doesn’t change what the bottom lines should be. In other words, “Bots do not need to be human to be human centered.”
Outside of the shift in new product priorities, another major implication is how we use the technologies we use currently. In a blog post, Dan Rover (sp?) declared that bot won’t replace apps, but inboxes were the new home screen. Our email, text messages, and more were queues demanding our intention and driving our usage.
Companies leveraging platforms like WeChat have been able to effectively create micro services and apps for things like ordering that have integrated seamlessly with how we act now. Bot companies that are able to daisy-chain onto conversations to do scheduling and commuter planning have shone in venture capital funding. It’s not inconceivable the next unicorn will have nothing to do with creating a new platform but layering effortlessly onto the ways we talk with those platforms now.
Speak Now
We talk online all the time, but computing has finally let us create value from that. Companies need to invest in ways to leverage these conversations to deliver seamless and personal content. This means focusing on personnel and focusing on alleviating frictions than automation. Companies that don’t value the communication imperative and connectedness of customers will soon find themselves lagging in experience, and, later, sales.
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A prime example of this is Amazon Web Services’ fast climb to dominance. Legacy systems like Oracle required costly deployments and developers, and setting up cloud instances on AWS is only a few clicks away. IaaS records have shown Amazon’s sheer dominance. Oracle, trying to defend by housing data and curating an elite brand, couldn’t compete with Amazon’s engagement accessibility.
Perhaps the most obvious implication of smart conversational apps is efficiency. However, despite all the news and hype around an artificial intelligence singularity, businesses – and their customers – still revolve around the interactions person to person. This means that products needs to be resolved around facilitating conversation, collecting information, and iterating form that information. The AI boom has made it easier than ever to facilitate personal conversations no matter where customers are online.
A must-read guide for enterprises with billions of conversations and millions of customers.
Modern call centre with millions of customers.
Enterprises are much more overwhelmed with conversations than ever before. Not only do they have to actively respond to customers over a myriad of channels like email, phone, social and livechat, they’re expected to give personal, relevant and fast responses. To tackle this problem, many organizations are looking at new technology to help them meet customer expectations. Some of the most notable are AI chatbots, self-service knowledge bases and good old Interactive Voice Response (IVR) systems. The problem? These all aim to lessen the time customers spend with agents.
While people do like self service for speed and convenience, majority still want to be able to talk to a person in times of need, or at important turning points in their life. Curiously, while we’re moving more towards a more digital and self-service world, most consumers still want the ‘human touch’ in their service communications.
Human touch is more important than just automation.
The challenge is to provide highly personalized and relevant offerings to meet both customer and business goals, all the while delivering the experience through the customer’s natural mediums of interaction. Counterintuitively, the likeliest solution to bring the human element back into customer conversations is though technology and big data. So, what should you look for in a technology that will give you both customer satisfaction and maximize revenue?
Multichannel Conversations
At the basics, an organization’s communication channels should be in one view. That means a business should be able to see and reply to customers by email, phone, livechat, social media, forums and wherever they could be talking to you, or about you, on one platform. Why? Convenience and transparency.
Convenient Conversations
A single platform for the entire range of conversation channels is much more efficient for customer-facing agents. Often, they have to switch between multiple channels to check for new customer interactions, and unfortunately, miss some communications here and there. With one view for conversations, they save on time, and reduces the chance they will miss communications from less monitored channels.
The convenience isn’t just for agents. Customers want to interact with brands through their medium of choice. 51% of U.S. consumers are loyal to brands that interact with them through their preferred channels of communication. Younger consumers especially, want to interact with large organizations via instant messaging channels where they can use natural language. Having all channels on one platform allows agents to have visibility across all channels, instead of doing well on a few and lagging on others.
Transparent Conversations
In so many organizations, a different team handles a different channel. They are responsible for that channel, and that channel only. But the customer is dynamic. They might reach out on one channel, and upon finding that it isn’t fast enough or substantial enough to resolve their problems, they will switch channels.
The ‘different team, different channel’ approach doesn’t account for the customer’s flexibility, resulting in multiple replies or inconsistent replies from two different people, both creating bad customer experiences. With multiple channels on one view, conversations are transparent. Conversations from the same customer are stitched together, and the same person can handle issues without making the customer’s journey difficult.
Holistic Customer View
In an enterprise with multiple departments, systems and channels, it’s necessary to have a collective view of the customer. A single customer view (or a 360 degree view) is a complete profile of a customer, created from aggregated data points within an organization’s systems and channels. It collates data from multichannel communications and customer data platforms (like CRMs, analytics, marketing and legacy systems).
Customers often complain about the lack of continuity in their conversations and having to repeat themselves. Problems like this arise because agents have no visibility on what customers have said on a separate channel, or what customer information exists on a separate system. As such, interactions are treated as a completely new “ticket”, and in the worst cases, existing customers are seen as a new customer. With a single customer view, an agent can see a given customer’s conversational, transactional and behavioral data in one place. This not only improves time-to-answer by 20% – 80%, it also ensures customer information flow is consistent and continuous, reducing awkward moments like the ones above.
The use of a single customer view can even go beyond customer care activities. Integrated systems mean that there could be a seamless blend of sales, marketing and service activities through conversation. Having this feature marks the start of being able to use critical sources of data collectively. The key however, lies in how the customer intelligence is used. The following presents ways customer intelligence can be used to take control of conversations in providing exceptional customer experience and maximize revenue.
AI-assisted agents
Use of artificial intelligence (AI) in enterprises is not new. For decades they have been used to automate heavily manual processes to increase efficiency, accuracy and decrease costs. What is new, is the use of AI beyond processes to interactions. Use of AI opens up the potential to deliver personalized interactions and hyper-relevant offerings that are scalable.
Whether it’s the AI itself doing the talking, or an algorithm providing assistance to a human representative, online, or face-to-face, AI holds incredible potential to re-establish the human-to-human connection in an increasingly digital world. Check out some examples below.
Deliver relevant content and information with AI
Many organizations have invested heavily into user experience, self-service and knowledge management tools. Yet, it is still difficult and time-consuming for customers to find the right information when they need it. Companies like Zendesk have developed AI-powered virtual assistants that help customers self-serve. By processing natural language, the technology suggests articles in the knowledge base to help them resolve their problems on their own. Research has found that most people are open to using self-serve AI technology like this, and see it as faster and more convenient.
Other organizations like Woveon have built AI-powered response assistants to help agents have more productive conversations in real-time. As agents talk with customers, the response assistance helps guide conversations so better results can be achieved for both the customer and the business. It would suggest opportunities like ‘other customers like her also bought’, or ‘he mentioned credit cards, link to these articles from our blog to help him decide’.
Speed up resolution times
On average, a customer care specialist spends 20% of their time looking for information and context to resolve a customer’s problem. That’s one whole day in a work week! AI can help organize information so that it’s easily digestible and relevant to a customer’s enquiry. Woveon’s Intelligent Response framework for example, will change the information it displays to assist agents based on the flow of conversation. If a customer talks about their personal loan, their loan details pop up. If the conversation shifts to their lost credit card, their shipping details will surface and agents are prompted to cancel the lost card.
Instead of wasting time looking for information, AI assistance leave agents more time to build a relationship and take up on untapped customer opportunities. Customers also love a quick and productive interaction. 69% attributed their good customer service experience to quick resolution of their problem.
Reduce repetitive admin tasks to open doors for higher value interactions
Administrative tasks like After-call work (ACW) have been a constant headache for employees in customer-facing roles. Though they are necessary, it’s tedious, repetitive and and takes up too much time. Technology can help to reduce time spent on these menial tasks, leaving agents more time to build customer relationships and, in the process, make their jobs more productive and meaningful.
For example, Avaya has a natural language summarization tool to help agents process customer information post-call. Talkdesk automates call routing, where the customer is automatically paired with an agent with the best ability to solve their problem. Woveon can prioritize conversations real-time, based on customer importance, value, urgency, or a mixture of all factors.
Freeing up employee time away from menial tasks allow them to participate in higher-value activities.
Intelligent Analytics
There’s no doubt that data analytics is incredibly beneficial for customer conversations. The trick is knowing what data to use, how, and when.
Whatdata is being used matters because not all data is created equal. For example, rather than looking at metrics at a point in time (customer rated the agent 4 out of 5 for resolution), it’s much more important to look at the larger picture (that it took 3 calls and an hour on hold to get there).
Howdata is used is arguably more critical to conversational success. The key lies in knowing what datapoints to tie together, and what analysis to draw from it. A mesh of marketing and service data can show how a recent marketing campaign has affected conversation volume and NPS. A cluster analysis of related keywords in customer conversations can lead to discovery of a huge logistics flaw.
Whento use what data is of particular importance to customer-facing agents. 74% of Millennial banking customers for example, want their financial institutions to send them information about services exactly when they need to see it. This could be information about personal loans when they’re starting to look for a house, or travel insurance before they intend to travel.
Companies these days have a wealth of data on their customers. In theory, organizations should have the ability to know who they are, what they need and what makes them defect to another company. However, lack of visibility on the holistic customer journey and customer intelligence tools stunt their ability to provide such excellence.
The following section will delve into three types of analytics particularly useful for managing customer conversations — predictive, clustering and revenue-generating.
Predictive Analytics
Predictive analytics provide foresight into potential customer problems and opportunities. Extracted from existing historical conversational, transactional and behavioral data, it can help agents better prepare for customer outcomes and trends.
A pretty common example is prediction of when influxes of customer conversations come in. For eCommerce businesses, holiday seasons generally see a spike in customer conversations and steadily reduces till the next holiday season. In a more complex scenario, predictive analytics can find that customers with a particular occupation, a certain concern and at a similar stage in their lives is actually a niche the organization hasn’t capitalized on.
Cluster Analysis
Now this one isn’t as common in a conversational technology, but is definitely worth mentioning. Cluster analysis involves conversations and customer information to be tagged, then for similar or related tags to be clustered together to draw insights.
Cluster analysis can draw out how topics in conversations can be relevant, or how particular customer segments can be feel about a product. This customer intelligence can then feed into other parts of the business. It could be used to help create a new automated customer workflow for upsells, or contribute to a new marketing campaign for a newly discovered customer segment.
Revenue-generating analytics
As repetitive and menial conversations are moving towards being solved by self-service solutions, agents must also move from a traditional support role to a hybrid service-to-sales model. This category of analysis is as the name suggests, analysis that serves to generate revenue for the business within conversations.
For example, Woveon’s Intelligent Response Framework suggests ways customer specialist representatives in banks can sell more products to their customers. A customer who fits the profile of ‘customers who typically get a black American express card’ will prompt a suggestion for the agent to talk the customer into an upgrade from their current card. A customer who is at a stage in their life where ‘customers like him are looking at buying a property’ will prompt a suggestion to link some home loan webpages, or a free session with a financial planner.
In the best possible scenario, this analysis is also delivered at the right time for an agent to capitalize on the opportunity, like in an intelligent response framework.
Be a data geek, not creep
Of course, it’s important to know that use of data should be “cool”, not “creepy”. There’s a fine line between the two that should never be crossed. Also, everyone’s fine line is drawn differently, so what one customer may think is cool, can be perceived as creepy by someone else.
Enterprises should have enough data about their customers to track and understand individual preferences, and see how customers respond to different use of their information at different points in the customer journey. Conversational intelligence and analysis tools can help create better relationships without overstepping the customer’s boundaries.
On a whole, customers don’t mind companies using their data for personalizing their experience and suggesting products and services that benefit them.
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While human contact is diminishing in volume, the quality and importance of each interaction increases. Forward-thinking organizations should be balancing quantity with quality to maintain a competitive advantage in customer experience. Technology can be a great booster to that end.
Have more ways you think businesses can improve on their customer conversations? Reach out to us to add to the article. We love chatting to like-minded people!
The hype around Artificial Intelligence technologies is at its peak. According to the 2017 Gartner Hype Cycle, emerging technologies such as deep learning, machine learning and virtual assistants are at the “peak of inflated expectation”. Cognitive expert advisors have passed this peak and are now descending towards the “trough of disillusionment”. This occurs when interest wanes as experiments and implementations fail to deliver.
The benefits of AI for customer experience management are potentially game changing. AI has the capability to analyse vast amounts of data in real time from various sources, including human behaviours and emotions. Expectations are high because this capability can then be used to create seamless and personalised customer experiences that are optimised to the device and channel of choice.
Pragmatists and battle hardened cynics will recall that when automation was first introduced into customer service channels, the results were often spectacularly underwhelming. So, is the application of AI to customer experiences destined to fall into the trough of disillusionment before climbing the slope of enlightenment? Or is there a path to follow to avoid the pitfalls of unmet expectations?
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Intelligently using Artificial Intelligence for Customer Experience
In order to find out whether the application of AI to your business’ customer experience will take a downturn, it is necessary to first ask yourself: What is driving your organisation’s AI strategy? Is it because:
AI is all the rage in your industry and your organisation is fearful of being left behind?
If you take the lead in implementing AI, it will make you look smarter/cooler than your colleagues?
It sounds like a cool and fun toy to experiment with?
Your organisation needs to catch up with your competitors who have been early adopters of AI?
AI is a great opportunity to reduce the cost to serve our customers?
If the answer to any of the above is Yes, then the trough of disillusionment beckons.
Alternatively, if you are deploying or considering AI because…
AI can enable your people and optimise your processes to operate more intelligently and efficiently, in order to provide individualised and predictive experiences for your customers at scale
…..then a brighter future awaits.
For these technologies to have any chance of success you should have a clear sense of purpose of how to you intend to deploy AI to drive CX in your business. Here are three ways you can use AI in a purposeful way to create meaningful customer experiences.
1. Use AI to Enhance your Knowledge of the Customer
An example would be using data analytics to anticipate the needs of individual customers at each moment of truth and key stage of their journey. Some specific examples oh how businesses are using AI to enhance customer knowledge:
2. Use AI to create stronger emotional connections with your customers
Using AI to recognise a customer’s emotional state helps agents better respond to the customer during an interaction, thereby creating stronger emotional connections.
Not only can AI empower agents with emotional intelligence to reply appropriately to customers, it can be used as a tool to connect service agents with the right information in the organisation’s knowledge base in real time. Examples of why this can be powerful to a business:
As a result, nearly two thirds of CX leaders say their organisation’s revenue growth outperforms their industry counterparts, compared with only a quarter of CX laggards. The proof is therefore clearly in the pudding: when applied in a purposeful and meaningful way, AI technology can enable organisations to increase agility and overcome competitive threats and leverage this advantage to drive acquisition.
Written by Dr Steve Nuttall – Head Of CX Research, Fifth Quadrant. Steve has worked in various leadership roles as a market research insights professional for over twenty years in Europe, Asia and Australia. He leads Fifth Quadrant’s program of CX strategy research and is an international speaker and presenter on best practice customer experience. Steve assists organisations to deliver their customer-centric strategies and business performance goals including designing and implementing programs to help optimise the customer experience.
We had the pleasure to have a conversation with Jon Sculley, the former CEO of both Pepsi and Apple
Thank you so much for your time. You have been at the helm of two legendary companies, Pepsi and Apple. Do they have a common denominator? Can you break down the recipe for their success?
John Scully: In 1970 I was 29 years old and Pepsi was out sold 10 to 1 by Coca Cola in 50 percent of the U.S. At the time, I was in charge of the U.S. operations and we realized that Coca Cola was the most valuable brand in the world. So we saw that Coca-Cola owns reality but perception leads reality, so if we can own perception, then maybe we can change the ground rules of competition, and we did that by creating a campaign called the ‘Pepsi Challenge’, which was quite different than anything that anyone was doing in marketing at that time. Instead of the company saying, look how good my product is, we did just the opposite. We said, take the Pepsi Challenge, let your tastes decide, and we had a blind taste test that would run all over the country and people would see that it was a real taste challenge between Pepsi and Coke. By the end of the 70’s, Pepsi had passed Coco Cola and become the largest selling consumer packaged goods in America.
When I first met Steve Jobs in the early 80’s, he came up to me and said, “How did you do that? You had no money to speak of it, Pepsi. “How did you pass Coca Cola?” And I responded, “Well, we call it experience marketing.” The focus was on selling the experience, not the product. Jobs expressed that he wanted me to Apple and teach him how to do that. Steve was building a product at that time, and it was under development. It wasn’t brought to life yet, to be called ‘Macintosh’, and it was for creative people — non-technical people, to do amazing creative things. He stated that he wanted to learn how to sell the experience such as I did previously. The experience is more important than the product.
The thing I learned in both Pepsi and Apple was that you always start with the customer experience. Steve said, “I don’t focus on the technology. I focus on what’s in it for the customer. I want to give the customer an incredible experience.” He used to call it an ‘insanely great experience. Whether it was the “Pepsi Challenge” or whether it was the Macintosh.
The early advertising project we worked on started with the 1984 Super Bowl commercial, which was the first a mega commercial ever done on the Super Bowl. We were always starting from the perspective of what’s in it for the customer.
You look at people today, like Jeff Bezos, he does the same thing and focuses on what’s in it for the customer. He always says, “My customers are amazingly loyal until someone else offers them a better deal. With so many tech companies that start with cool technologies tend to forget that the technology ultimately mock commodities. So it’s always what’s in it for the customer, always the experience.” I find that the great companies can turn into legendary companies.
I think so because back when Steve was, I remember I met him when he was 26 years old and he was still forming his principles and the foundational principles. The early 1980s can be found and is still the foundational principles of Apple today.
Steve believed that you had to do what he called a ‘zoom in, zoom out.’ You connect the dots, zoom in to simplify and if you look at Apple, the innovation always takes place at the convergence of different industries. So here was Kodak in 2007, who had actually invented the digital camera and was actually the largest photo finisher printer in the world. They doubled down on silver halide manufacturing because they were in a marketing battle with WalMart with a single use film camera.
Steve Jobs was looking beyond and he said, I can connect the dots between 3G wireless, which was just coming into the world of wireless. 2G was fax, 3G could do other things, including photos. He understood miniaturization of consumer electronics because he built the iPod before the iPhone. He said, “Do you know if I can connect the dots and put a phone chip in an ipod to make the screen bigger, I think that will give the ability for people to be able to send photographs, wirelessly.
It seems so obvious, right?” So most of the brilliant people that I’ve had a chance to work with are really seeing possibilities ahead of the rest of us that are completely obvious when we understand them and if you think about what Steve Jobs created during his lifetime, all this success, it seems so obvious today. They weren’t obvious in the context of the world that he was living in at that time.
When he brought me to Silicon Valley, nobody was talking about marketing. Nobody was talking about a consumer experience. Nobody was talking about the creative tools for non-technical people and yet it’s obvious today. That’s what the world is largely about. I always remember one of my favorite professors at MIT media lab was Marvin Minsky, and Marvin is known by many as the father of artificial intelligence, but he also, had to bring an insight that I still remember. He said, you don’t really understand something well until you understand it more than one way and just going back to Steve Jobs, Steve had a curious mind. He was curious about everything. He was not actually an engineer.
If you saw the first Steve jobs movie that Ashton Kutcher was in, I remember Ashton came up to me, a month and a half ago. We were at an event together and he said what you think of my Steve jobs and I said, well, actually it was OK, but I said it really hurt Wozniak his feelings. He said, what do you mean? I said, you made Wozniak into a service tech and you made Steve Jobs an engineer. Steve wasn’t the engineer. Steve was the brilliant genius who conceptualized and had a great sense of design, all Wozniak ever wanted to be was the world’s greatest engineer. You crushed him. So you have to appreciate that. What makes people like Leonardo Da Vinci and Steve Jobs, along a few others, could work with her left brain and work with their right brain to start connecting the dots. Steve, who founded and led the most valuable technology company in the world, said that, the lesson he learned is how important the humanities are in leading and creating a great company and meeting that, art, design are just as important as the technology.
Rarely Apple is the first at doing anything in technology. Most of Apple’s technology is actually gotten from somebody else, Bill gates used to come to me and said, I just don’t understand why Steve gets so mad at us copying the Macintosh user interface when he stole everything that Apple has from Xerox, Palo Alto Research Center.
One of the things you find with talented people is they have no embarrassment about borrowing great ideas from someone else and why should they? You stand on the shoulders of the people who came before you.
Which social impact issues are important to you? How do you bring your values to your work?
John Scully: Well, I am really maybe the last person standing in my generation from high tech who’s still actively working. I don’t run companies anymore, but I mentor talented people who I think have the potential to change the world. So for instance, up in Boston, I spent a great deal of time up there now because I’ve been working with the founder of a company called RX advance . He’s building an absolutely amazing company in healthcare and it all starts with a noble cause.
So many people start with a business plan. No, you start with a noble cause. You start with something that’s going to make a difference in the world. It almost made you want to start with the people who are going to use whatever you are creating a product or service which was following the customer and it always starts with having a curiosity that has to be a better way. So I’m inspired by anything that will stimulate curiosity, anything that will show that the power of diversity is so incredibly important to innovation. I’m only involved with companies that have the potential to be transformative in their industry sector. So when I see that there is discussion in the government that we want to shut out immigrants to come into the United States and when I know that in Silicon Valley, maybe 70 percent of the leadership of companies in Silicon Valley are actually immigrants. It just sounds like, wow! How could anyone even think that way? So I think that what makes America great and I’m proud to be an American, is that we have been a country with an open mind, a country that has been willing to, invite people of talent and merit, who will work hard to come in and participate. So I hope we will be able to say that in the future. I hope that we realize that our education system is still designed for a different century and a different economy, and that if America is going to be as successful in this century as it was in the last century, then we need an educational system that has foundational context with the exponential technologies that are available.
I grew up in Silicon Valley, in the early days of Moore’s law for a while. We have robots, we have artificial intelligence, we have precision medicine, we have driverless cars where you had the world of sensors and all these things are growing at an exponential rate or change. So simply put that compounding math that means you go 2, 4, 8, 16, and 32. So the speed at which exponential algorithms compound is hard for most people to absorb because we’re all used to linear time, we’re not used to exponential time and yet the world we’re living in today. Anyone who was young and is going to be living through the rest of the century is going to be better understood in exponential time, which puts a stress on learning, on curiosity, on education, on diversity, thinking about things in a different way and so I try to mentor when I can, people who are going to be part of that world.
Throughout our careers, we’ve all run into roadblocks, so can you tell me about a time that you failed and how did you motivate yourself to get back up and keep going?
John Scully: What you will discover is if you believe in making a difference, you’re bound to make a lot of mistakes and some people would just risk averse. They don’t like making a mistake. They don’t like to be humbled, embarrassed. They don’t like to have to pick themselves back up and try again, maybe they aren’t going to want to participate in the entrepreneurial life, but for a lot of us we know that you can’t be a successful entrepreneur unless you were prepared to make mistakes. The thing that takes awhile to really understand is that you’re probably more trapped in your successes. We often become a victim of our success because we often misinterpret why we were successful. Now a good deal of the time people are successful just because they were in the right place at the right time and so something goes well which will lead them into thinking they are genius. They misunderstand why they were successful. So it’s only when you fail that you actually get a chance to kind of get the wind knocked out of you and say, OK, that didn’t work. Why didn’t it work? What did I do wrong? So failure is so integral to the process of deep learning. Success actually can be a distraction and it can take you off in a different way. So my advice is get comfortable with making mistakes.
Now, many countries have cultures where making mistakes is not acceptable. If you’ve been to Germany and spend any time there, Germans don’t want people to believe that made mistakes. It’s a very competent economy. It’s much disciplined. It’s very process centric, it plays by the rules, but it doesn’t have much of a place for people who make mistakes. That’s quite different than our culture where we say, OK, you made a mistake. If you’re in Silicon Valley and you say, boy, I made a mistake, I blew it. The first thing somebody will ask you is, well, what did you learn? And so culture is a very big part of being successful. It’s not that the U.S. has smarter people than the rest of the world; it’s just that we have a culture that’s very forgiving in terms of making mistakes and picking yourself back up and try again. So I’ve made lots and lots of mistakes.
I’ll give you some examples. I remember when we were at the end with the 68,000 microprocessor, which Motorola made and the Macintosh was based on a system processor, which meant there was a complex instruction set computer and if you look at what was happening back in the late 80’s, there was a lot of attention going on with risk reducing instructor set computing. So when I went to our best engineers and I asked, what should we do? We were at the end of life on this microprocessor. They said, well, actually you can choose any risked machine you want, doesn’t make a difference which one. Risk is the future. Just don’t pick a system process. At that time, Andy Grove was coming over and making a pitch that we ought to adopt the Intel processor and in those days Intel was not a floating point processor. It was integrated based, meaning he was integer arithmetic and it wasn’t designed to do graphic algorithms. So we made a mistake. I made the mistake because I was the CEO, we didn’t go with Intel and we ended up going with the power pc, which was a joint venture between Motorola and IBM. The big mistake was that we didn’t consider that the huge industry that Intel had created for all kinds of blue chips and other components, but things around it which will all available by various companies along South East Asia. That it wasn’t just the microprocessor that we should be focusing on. When we made the decision to go from one to another, it was the entire system and the reality was by going to the IBM power pc, which at the time technically may have been better microprocessors than the Intel assist processor. The reality was the economics couldn’t even come close to the complete system bill of what you could do with an Intel processor because of all those other related components that sat around it to make it a complete computer. So that was a terrible mistake because it set Apple on course in a direction that was eventually going to mean that it was going to be less and less competitive with the rest of the computing world.
Steve Jobs was running Next, at that time, he made the same mistake. He went with the power pc as well with next. Next was not a very big company and unfortunately for Next almost went bankrupt. They had to drop out of the hardware business, but kept going with its software operating system, which ironically when Steve came back to apple years later, ended up becoming the Kernel for the Mac operating system.
Who is your hero in your business or personal life and how do they inspire you to become the person that you are today?
John Scully: My biggest hero is my wife Diane. Diane is a computer scientist. She’s also a mathematician, but what she has done for me is that for many years after I left Apple, I sort of disappeared. I was working in investing in startup companies, sort of staying out of the limelight and just going on with my life then when I met Diane, it was about 10 years ago and then we got married five years ago, she completely changed my life, really our life. She said, John you’ve been so lucky, you’ve been working with some of the most talented people on the planet and you need to share those experiences with other people. So we started going around the world that we had various invitation.
So we were invited to Chinua University to speak there, same lecture that Steve Jobs, Elon Musk, Mark Zuckerberg were invited to ETH in Switzerland, which is the top technical school. We were invited to MIT many times. I’ve been involved with at MIT for many decades through the MIT media lab and what I realized was that I wasn’t out of date, that actually the things that I had experienced were actually of interest and of some value to the next generation, so when I say I’m sort of the last person standing from my generation because everyone else is either retired or dead, I’m still very, very active and I spend my day, I am up every morning at about 5:00 AM, reading a lot and communicating with people. I love talking with people as we’re doing right now and my goal in life now is to work on a few noble causes, but also to be able to mentor and to pass on what I experienced in hopefully useful ways to people in your generation.
My company is celebrating its 10 years in business and we’ve always had perpetual growth. One thing that really struck a chord with me, which you’re talking about, was the challenges and how you face those. I’m in the Whitewater right now. I don’t know if you’re familiar with that terminology, but I’m about $5,000,000. I’m trying to break through 10 or 15. I’m really trying, but there’s this barrier here and I’m ready for that and I know you have much bigger business experience, but I feel like the principals in the set and so I don’t know what kind of advice or things that you recommend for me, how to look at myself, our company maybe introspective with find a way to break through that because it’s something I really would like to do.
John Scully: So here’s what I’d say is that people who are in big traditional corporations have very, very little personal experience if any, with true innovation, and it’s not that they aren’t smart people or hard working people or competent people, it’s that they’re trapped in cultures. The one thing that every large company has in common, it’s culture, is that it empowers middle managers with the authority to say no and being an entrepreneur is all about the thinking of the possible ways you can get to yes and so it always amazes people in big companies to realize that when I was working with Steve Jobs in the early days of Apple and Apple was still in a several houses, it had tilt up building with a pirate flag flying over, which was Steve Jobs office for the Macintosh, the average age of the people on the Macintosh team, they were over 100 of them in total, including manufacturing and everything else was 22.
People just assume that companies like Apple and Microsoft were always big companies. They weren’t always big companies. They were at one point they were $1,000,000 companies. There were $5,000,000,000 companies. The Silicon Valley has an old saying, what got us here, won’t get us there, meaning when you’re starting out and you’re trying to get to $1,000,000 revenue, let’s say, you have to get through proof of concept. You got to recruit enough talent around the table to be able to deliver something that’ll get revenue and the bigger question then becomes, so how do we get from 1,000,000 or 5,000,000 to 10,000,000 to 20,000,000 or even larger? And you realize that you sometimes have to go back and deconstruct what you’re doing and think about when we solve this business at a $20,000,000,000 business the same way we’ve been solving it successfully as a $5,000,000 business and what’s so important about what I learned working with Steve Jobs was that you lay down foundational principles. One of Steve’s principles was you have to have a very clear focus. This focus was how do we build bicycles for the mind? Now that’s what he was really building bicycles for the mind. He didn’t think of it as building personal computers, he thought about he’s going to enable people to have this incredible accelerator which is going to help them think and do things that you couldn’t do before the Macintosh came around and why was the Mac so important to Steve? You know, the Apple 2 had been a huge success. He said, well, the Apple two was so limited because you require that someone, you know, learn how to use a keyboard. They had to learn how to use alpha-numeric commands. He said with the Macintosh, they don’t need to know anything about technology. So he had to re-conceptualize what is a personal computer and he said it’s all about point and click and he would use metaphors, he’d say, well, you know, we need to have a desktop metaphor. We need to have file folders. We need to have, ways of thinking about paper and putting objects on paper and things like that. Well, those sound so obvious to us today, they weren’t obvious almost 40 years ago. So I would say think about why you’ve been successful as a $5,000,000 business, and then say will a $5,000,000 business be solving the same problems when it’s a $20,000,000 business as it is at a $5,000,000 business. Will it be a different customer? Will the customer be using your service or product differently? Are there other things going on around the world, around the economy, which will make things possible for you to solve even bigger problems? And you have to stretch your mind. Always be curious, always observing.
I know a lot of people have said, John, you’re so lucky. You got to work with all these talented people. You were working in different industries. You’re still doing it. How come you’re so much luckier than the rest of us? And the answer is because I’m constantly observing, constantly curious. I think about learning is much more important to me than making money and you’ll find that particularly in the century you’re going to live the rest of your life in this 21st century, that the ways that we think about things are going to be so fundamentally different than anything that was around when you were born.
Think of something as simple as this. The prior industrial age was enabled by two things. The distribution of electricity, now going back to a Tesla and Westing house, with alternating current and it was enabled by the fractional horsepower electric motor and if there hadn’t been a fractional horsepower electric motor and it hadn’t been distributed electricity, there wouldn’t have been any in the twentieth century industrial age. So what did that lead to? It lead to mass production, it led to mass channels about the mass marketing and now we’re in a different century and you say, so what is the comparative to electricity and the fractional horsepower electric motor? And what are the, the rebuttable effects out of those comparables? Well, I think that artificial intelligence, that’s both machine learning and deep learning and how that progress progresses in the future. Artificial intelligence is going to be foundational to everything that goes on in the world for the rest of the century and it will become more apparent, it’ll become commoditized and it will be as fundamental as electricity and oil were in the last century, meaning that they can be delivered as a service, now embedded in all kinds of different things.
Second of all, I would say that platforms are as important in this century as mass production factories were in the last century. Remember, most of the US economy in the early part of the last century was around manufacturing. Today, the majority of successful companies that’ll be around in the middle of the 21st century will be platform based companies. So it won’t just be Microsoft or Amazon or Google, few companies, what they called Fang. Every company will have incorporated in platform architecture and so things that seem unique are just going to become obvious mainstream.
I remember when I was in college, there was something called the interstate highway act that President Eisenhower put through and sign the bill for which enabled the interstate highway system and it was intended to be able to move missiles around during the Cold War so that the Russians wouldn’t know where our missiles were. They could be moved around on trucks at nighttime over the interstate highway system. The interstate highway system became as foundational to the economy in the 1960’s, 70’s, and 80’s as the Internet is foundational to us today. Now to think about if we’re going to redesign the internet, we would really design it the way it’s designed today. Remember, it was designed back in the early 1970’s, so the Internet today would have much greater security. It would be a much more thoughtful in terms of how it integrated into sensors. The sensors didn’t exist, obviously when the Internet was first created and there will be tens of billions of sensors connected with everything, even by 2020. So the Internet would be far more secure. It would be far more integrated into all kinds of things, it would be integrated into the platform architecture companies that would be, you know, into all kinds of devices, not just with flat screens, but images that can be seen like Holograms, a hollow lens if you notice something that Microsoft’s been working. The possibilities of what the fundamental will be for any kind of business, in the middle of this century are just in the eyes of the beholder right now.
They haven’t really been deployed yet and yet they’re going to be so obvious. When you’re my age, you’re going to sit back and be explaining to people your age, that there was a time once when there wasn’t a broad-scale artificial intelligence, when every industry was a platform company, when the sensors were connected to everything, when block-chain was built into every transaction and then people will look at you and say, really? There was a time like that? And yet this is all going to happen and it’s going to happen in exponential time meaning that it’s not going to take a 10, 20, 30 years for these things to happen. It’s got to happen over the next five years, 10 years, to an exponential time, you know, its compounding math. Keep thinking about and don’t be afraid to ask other people say, like what do you think about this? And don’t be afraid that someone’s going to say Michael, that’s a really dumb idea.
Did you plan to end up where you are, or did that “just happen”?
Well, when I was very young, I really didn’t want toys. All I wanted were electronic parts so I could build things and I discovered I was better at taking things apart and turning them into something else but when I put them back together, I always had parts left over. So I realized I was not going to be a great engineer. I didn’t have a precise, detailed mind like my wife who was an engineer. I was more of a designer, I like to figure out different ways of doing things, with the idea of there had to be a better way and I was interested in designing things ever since I was a child. So I would be building things. I built a go kart. I built early television sets, I built one of the first color television sets when they were sending out signals that was called few sequential television where you had a spinning wheel of red, green and blue and then when I was 14, I invented a color television cathode ray tube and I applied for the patent on it and eventually got knocked out by Dr. R Lawrence, who eventually Lawrence Livermore labs was named after and he invented something that knocked out about 8 of my 12 claims and he eventually sold his invention to ABC paramount. ABC and paramount studios were combined in those days and then they eventually sold it to Sony or became Sony Trinitron too so years later when I met Akio Morita, the founder of Sony, he had remembered the story that when I was a kid, I had invented something very similar to what Dr Lawrence did. So he introduced me to the team who were still at Sony, who were the original Sony Trinitron team and so I was always inspired by ideas and I was always curious. Curiosity was who I was. I was not a particularly good athlete; I was like, OK, so I was much more interested in, thinking about things in my head and building things.
I had a really bad stammering problem, I couldn’t talk. So when I was a kid I couldn’t even talk on the telephone. I couldn’t even talk in the classroom when I was at school, I stammered so badly and I was very embarrassed and the teachers would say I was stupid because I couldn’t answer the questions. So it was very humbling to put it mildly but then it turned out that I eventually went to a medical hypnotist and learned how to get over my stammering and by the time I got to college, I discovered I was actually very good in mathematics and so I was an exceptionally good student at a higher math and when I was in graduate school, I was doing a Monte Carlo Game Theory and mark off chain analysis and basic statistical modeling and things like that. Didn’t seem to have any purpose in those days but as we know today, they’re kind of fundamental algorithms. So sometimes things happen and they don’t seem quite full at the moment. Um, as things that happened s things happened to me in my childhood but so much of what I do today, Tracy spatter, I was interested in when I was very young and the things I was doing when I was very young.
You had a remarkable career thus far. I was curious what it is that it takes to build like a career like John Scully in general if there is such thing.
John Scully: It’s not very complicated. It takes an incredible curiosity, it takes a willingness to work extremely hard and it takes, I think, respect that there are other people who can do things better than you can and if you can work together, you know, and great companies are always built by teams. It’s not, it’s not one individual, but it’s always a team and so the team doesn’t have to be exactly like you.You have to say, so what am I good at? What’s missing in the company? How do I find someone who’s good at the things which I’m not as good as they are? And they will find that the most successful companies that they always have a leader who has a very clear vision of what she or he, you know, wants to accomplish and that’s why the noble cause is so powerful. The more you can conceptualize the company in terms of something that is noble for the world and the fact that it makes money is one of the outcomes is not the sole purpose. That’s what attracts the best talent because the best work from people. The brilliance of Steve Jobs was as much about his ability to articulate what he thought could be possible, not probable but possible and his ability to recruit talent. He was an amazing recruiter of talent.
You’re one of the great minds of business. You definitely got to work with one of them as well and Steve Jobs. What is it that you saw that, I mean from your relationship with him, from what you saw that it takes to build a Steve Jobs if there is such a thing for that or to build a career as such as this?
John Scully: It always starts with that there has to be a better way. You think about something and it may be something very small. When Steve did the ipod, it wasn’t the first MP3 player. There were a lot of MP3 players before the ipod, but what Steve realized was, it was when Siemens came out with this little tiny rotational disc drive that can hold a lot of content on a small miniaturized, no powered product that he came up with the idea of the ipod working with Tony Fidel, and Tony was the one who actually designed it and Steve was the one who knew how to explain it in ways that non-technical people would really appreciate it. So he didn’t say, here’s the best MP3 player you’ve ever seen, look how powerful it is, look how small it is. No! He said, how’d you like to have a thousand songs in your pocket? How would you like have a thousand songs in your pocket? And people said, wow, I never thought of that and he was very clever. He went to one of the most powerful industries in the world at that time, the Hollywood music industry and was able to convince them to stop selling songs as an album, but to sell them individually for 99 cents a song and of course that’s what the whole idea of itunes, it became the ipod and things like that. So the ability to connect dots to see things that weren’t obvious to other people was part of his brilliance. So we can all learn from that.
You spoke about the principles. What are principles? could you detail more about them specifically?
John Scully: I’ll give you Steve’s principles. Always start with the customer, not with the technology and other one is, it’s more about design and cool technology. Steve actually couldn’t draw, when he came up with an idea…I went to Rhode Island School of design and School of architecture and so I would draw his ideas often because he couldn’t draw, but he can visualize them, he was a very visual person. Steve loved to use metaphors because when something didn’t exist, he could explain it by using metaphors to explain it, well, it’s like this, and it’s like that. You believe in, no compromise and so his designs… I remember when the first Macintosh was getting ready to go to market and the first Mac was inside a sealed case because Steve didn’t want people tempering with it inside and wanted to be in complete control and one of the engineers was just finishing up the motherboard and Steve looked at it and said, I don’t like this motherboard. I don’t like the way it’s laid out. I want you to go back and do it again and the engineer said but Steve, we don’t have any time left. We’ve got to ship the product and anyway, no one’s going to see it. It’s inside a steel case, no one’s going to know, and he said, “I’ll know” and that was Steve Jobs. Now the original Apple logo that looks like a four color logo because Apple was the first color computer, it has color logo on those days and Steve insisted that it’d be printed with 6 colors, not with four colors and I remember someone saying, Steve, he realized how expensive it is to print a logo in 6 colors as opposed to four colors and nobody will know. He said, “I’ll know”.
Many years ago a Chilean gentleman named Fernando Flores developed an interaction model that modelled workflows as conversations. At it’s core was the concept that there were four distinct phases to a conversation, but that in general, organisations did not model these phases accurately or with enough granularity. It was the breakdown in the integrity of the conversation between people that led to the breakdown in the business process because we were not being specific enough where we needed to be, and were probably being overly prescriptive where it didn’t matter to the ultimate delivery.
From the diagram above, some of you may recognise this way of thinking from your exposure to The Lean Start Up. It’s basically a methodology for running a discovery process.
I was very ready to be persuaded as to the usefulness of such methodologies after a three year masters in new product development processes and buyer supplier relationships in the automotive industry, a theory based on lean manufacturing and lean enterprise. My research involved disentangling the effects of good internal new product processes from the attributes of buyer supplier relationships. Foremost here was the importance of getting the design specification right up front, but not defined “too tight”, such that you lock out the expertise of the supplier. Many times, you defined the “outcome” such as “this switch must work in environmental temperatures ranging from -40 to +40. How you achieved this as the supplier, was up to you.
The relationship, communication and trust factors between the car company and it’s suppliers were then really important in guiding and steering through course of inevitable adjustments and adaptations. Getting to market in a much shorter development cycle time, and then iterating faster than the competition made Toyota a learning machine. The same factors are at play when people collaborate. We need to understand the nature of our relationship, we need a “common background of obviousness” in our communications, we need a history of interaction that has built a base of trust. Only then do we trust to iteration.
CEBP — Communications Enabled Business Processes
In 2003 Graham Brierton and I were co-founding team at a first generation SaaS company. We recognised that automated communications could be used to address the millions of “small interactions” between companies and their customers that could be better managed through more accurate preparation, negotiation, performance, and acceptance routines. With the rest of our team we identified a range of “lags and drags” in business processes, where if they could be handled more efficiently at scale, it would free up organisational resources. We saved companies millions of dollars. We won a global innovation award, national and European customer service awards, but yet, we felt that there were bigger “conversational problems” out there that we had not yet tapped. The problem was that we couldn’t “get to” the granular data that was locked in the enterprise, voice recognition wasn’t good enough at that stage, and there was still a chasm between the communications channels and the emerging, enterprise digital infrastructure. We could see all this potential “white space” in the enterprise, but there was no way of “wiring it all up”.
Martin Geddes — The Ten Conversation Gaps
Around 7 years ago I was at a Future of Voice workshop run by Martin Geddes and Dean Bubley and the concept of “Conversation Gaps” was advanced. Again, this was an example of modelling out a typical process and demonstrating how telecommunication services could be used to remove friction, and help business processes complete more efficiently. I’m going to quote it in full.
The cost gap: The difference in operational cost between human labour and an automated system is several orders of magnitude, and errors introduced by humans cascade into further cost.
The confidentiality gap: Human beings are asked to handle sensitive data, and such data can leak.
The customer experience gap: The customer’s time is wasted on tasks that do not create value. The ‘cost’ of the service to the user is the combination of its price, and the effort to use it; thus poor customer experience is a form of cost shifted on to the customer that reduces demand and willingness to pay.
The capability gap: Our tools of conversation assume a one-size-fits-all and do not provide features reflect the diverse roles people adopt in their daily lives, and the different demands that arise as a result. For instance, a next-generation Caller ID would command different levels of caller information disclosure for each of ‘child’, ‘friend’, ‘customer’, and ‘stranger’.
The co-presence gap. Ideally conversational media would provide parties with an experience as good as ‘being there’ together. If the conversation is locked into a narrow range of media types with weak interactivity, then it falls short of ‘being there’.
The coverage gap: The ‘coverage’ is the range of situations in which the media make the conversation possible at all, despite ‘not being there’ together in the enterprise’s retail outlet. If a customer’s available modality of conversation is Skype, and the enterprise cannot originate or terminate Skype calls, then they cannot converse, and the enterprise loses business.
The capacity gap: Each tool has to be able to scale to meet the needs of enterprise use. This is not just a question of networks scaling to accommodate load, but also of the user experience being able to scale to prioritise, filter and route an ever-rising number of requests for interaction.
The conformance gap: The tools of conversation fail to meet the legal and social norms of each jurisdiction, and thus limit their use in commerce. The current controversy over encrypted BlackBerry messenger use that cannot be intercepted by the governments of the UAE, Saudi Arabia and India is an example of this.
The culture gap: Each society has different norms and historical associations with communications, such as Americans having a higher propensity to use voice compared to text-centric Europeans. What is acceptable and ordinary use of personal data in the USA is regarded as unethical in Germany, even if it conforms to legal constraints. Tools of conversation need to reflect these differences.
The ‘cool’ gap: The other gaps address functional shortcomings of our tools of conversation. However, an increasing proportion of the value we receive from goods and services is provided by non-functional aesthetic and social value. People want to use communications services that make them feel and look good. If teens are tweeting and texting, then asking them to talk might as well be asking them to telex — it just isn’t going to happen.
Digital Conversations
Around 5 years ago, we noticed more widespread adoption of “customer journey”. The digital glue for this journey was going to be “social”, but at the customer level and at the organisation level (employees). Social didn’t turn out to be great for engaging and collaborating across all environments and businesses. Gaps were emerging between online digital and the traditional sets of communications tools at the contact centre. While there is still a great deal of promise in the community model of customer support there is little actual adoption of it.
My Personal Mobile Experiences
For me, three customer experiences seemed to be fascinating me, and seemed important.
(1) Instant, Visual, Services: Hailo was an app that I used a lot. I opened it, it found my location, showed me little icons of cabs, showed me arrival times. I hit one button, and I had booked a cab. The cab drivers were unfailingly polite, the journey route and choices were always explained to me in advance, and the bill was always so easy to deal with. I just stepped out of my car and caught my train. Why weren’t digital interactions with all companies this simple I thought?
(2)Private Social Networks: WhatsApp: I was speaking with a long time friend and former colleague who was running a small service company, entirely on WhatsApp. What I said? yeah, we open up different groups for each subject. Basically he was nearly able to run his business, and his customer interactions, from a mobile messenger app. combined with what I was already witnessing with the adoption of Slack, I could see a new assisted interaction paradigm emerging.
(3) Customer Empowerment: I was in a hospital and found that I had absolutely no record of my conversation, and no way to capture the record of my interaction with that hospital. There were many errors made, and the hospital was the only party to the interaction that was “allowed to keep the official record”. Why?
Conversational Commerce
The bridge between your communications and digital infrastructures turns out to be the Messaging app on your phone. If you could @ message a company and have them respond over Messenger, you save a lot of time, effort and frustration. I don’t have to look up my flight information because KLM not only shares my ticket with me in my Messenger, but also my updated gate number, and the time it will take me to get to my gate. The conversation is the service. When I want an Uber it can be summoned from within my Messenger. When I want a receipt it can be shared into our messenger conversation. When I want to remember what was said or agreed, I can scroll back in our conversation. I can absolutely see that in many professional services interactions I would want to keep a record of the preparation, the negotiation, the performance, and the acceptance stages of an interaction.
What we are sure about at Webio is that the future of interaction will use all the capabilities of mobile, from icons and emoji, to micro-sites and bio-metrics. It will us the camera and it will use augmented reality. It will use intelligent messaging, messenger apps, disposable apps, instant apps, sms, webrtc voice and video. The availability of this channels “everywhere” gives companies the ability to bridge many of the conversation gaps originally proposed by Martin Geddes.
Powerful Artificial Intelligence (A.I.) engines such as Tensorflow are also coming on stream at the same time as all these channels, bringing the possibility of predictive interaction to conversational interfaces. For simple, easy to formulate questions, for which there are simple, structured, easy to present response options conversational interfaces should be easy to implement. Where there are more complicated questions, that requires data from numerous enterprise applications, the ability to generate these response options is more difficult.
But, What’s So Interesting About This, Really?
Chatbots are the trojan horse for artificial intelligence products. They are really augmented conversations. They will start simple and small in places like customer service. What devices will do for us “automatically” is only in it’s infancy. Using image recognition on x-rays is one of the areas where A.I. assists doctors and behind that is the fact that A.I. is capable of keeping the alternative diagnoses “in mind”, their potential interdependencies, and their risk weightings. While human experts may be right 95–99% of the time, A.I. is helping chase down that last 1–5% and weighting it for potential impact. If A.I. is assisting doctors in diagnosis, and assisting drivers to remain safe on the road, it is hard to think of an area that will remain untouched by A.I.
In 10 years, machines that help us keep these options in mind, and help us to better exercise our judgement will be the norm. Today we think that Google Assistant is pretty good at recognizing our voice search requests. We mostly think Siri is funny but not as good as Google. We really haven’t seen mixed reality solutions such as Hololens used in our day to day lives yet, but can you imagine going back to a world without Google Maps? Could the whole “on demand Economy” work without Google Maps? At the moment not really.
The conversational interface will be like maps of conversations. At first it helps us get from A. To B. Future generations of services will be built upon this this basic metaphor. If maps were about locations, their killer app was “step by step turn instructions”. It was about the navigation. So if our conversational interfaces are mostly about our “intents” what services will emerge based on these intents? What is our turn by turn navigation equivalent? What is the killer app for augmented conversations? For me, it’s personalization. Conversations are where we explore, create, define, and share our preferences. While these may start out being functional and factual preferences such as remembering our shoe size, and our color palette preferences, they may evolve into preferences that surprise us, that delight us. Spotify can play your favorite album all day long, but all anyone talks about is how amazing their Discovery Weekly playlist is. How many of us get up on a Monday morning and hit that first thing? It’s now “a thing” that many of us do on a Monday. What if we had our “banking conversation” on the first Monday of the month? What if we had a target of having at least “four hours of direct conversation with my child” every week? What would happen if there was some way to know that “25% of people you work with don’t seem to want to communicate with you”?
In an era of quantified communications, we will have augmented conversations, assisted by artificial intelligence that holds a repository of our preferences.
Marketing and social media should be best friends. They have to be for most products and services to reach a mass market of any significance at a relatively low cost.
I’m a ‘supermarketaholic’ and enjoy visiting the biggest store close-by. Walking the lanes recently was both nostalgic and different. Nostalgic because I know this experience will change in the future as it has from my childhood. Different because I was seeing the products through a different set of eyes on that day. In the past I would be looking out for the new highly advertised product ‘seen on the television or newspaper’. Now, I’m checking out the deals and new products flittering across my mobile as I check my Facebook messages. Yes its different.
Facebook advertising works so well one does not even associate it with advertising. The images we see sometimes can draw us in with very few words. If it’s good, then the comments will get a brief review. Sometimes I will comment if I really like a product or feel interested in finding out more. If I have a bad experience, its shared by writing a negative buzz /response, that’s my act of community service to people I know.
What drives consumer spending now is much more than a hyped-up, interesting product and disposable income. It goes beyond the borders of influence and up the alley of social media marketing and promotion. Its that defining comment which resonates and reminds of a feeling!
How to reach consumers through Social Media conversations?
1. Social media marketing & promotion
From my experience, social media marketing can be described as a mixture of penetrating a marketing image with a social media conversation strategy. The product promotion takes place in the ‘comments’ of a thread. This is then shared, over and over, by consumers who can effectively describe a ‘feeling’ of value in a few words. Indeed it is the trigger from these conversations which cannot be easily monetized as advertising, for commercial gain by a hosting platform. This has helped many brands in introducing new products. In the case of ‘the platform’ like Twitter and Facebook capturing the real commercial value is difficult based on the nature of the promotional asset — online subscribers.
There are very few ads on Facebook which will generate a feeling from me, to look further, in their present format. They give me that feeling from the past, of getting up during the commercial breaks to go for popcorn or a drink!
I’m sure the ads are pretty and relevant and I may miss a deal or two, but hey they do not impact on what I’m going to buy or where I will shop in many instances. So what is wrong with the present ‘validated promotions’ (commercial FB ads), and why don’t they appeal to many consumers like me?
2. Storytelling in social media marketing & promotion
One of my theories on why some ads on social media do not appeal, has to do with ‘verified experience/value added’!
The comment threads can act as a storyteller! Yes. It’s like opening a book and reading a dialogue, complete with human feelings and stimuli. I’ll share a couple examples from my consumer vision;
The Pub — There is a new outdoor mall with a pub I wanted to visit every-time I passed and saw its sign. I was caught by the name and graphics on the sign. As I scrolled one day on Facebook I glimpsed a comment on the pub, shared by a friend of a friend. There was a dissatisfied heading announcing ‘poor service at $200 per meal’. I scrolled back, and read the few lines posted on the consumer experience, and then noted a few comments listed, mainly negative feedback. As I read, I thought — “I won’t be spending $200 to be insulted anytime soon, or ever!” That was instinctive. A few days later on another thread, I read an experience one of my closest friends had at the same pub, and she keeps going there. I’m not convinced I want to give it a try, having noted the time she and the dissatisfied customer visited were very different. She also appears to know the owners, and could be getting preferential treatment. Full story ending indicates, I’m not convinced to go!
Soaps — I’ve been noting a few friends keep sharing this ad about a new line of bath soaps with herbal and natural extracts. I like Dove, but as I read the comments I’m catching a scent and feel of a different experience. Something soft, mild and without a lot of additives, and it smells divine based one comments from people I don’t know. As I hunt the lanes in search of this product, I can only recall the name and the experiences driving me not to give up! Its not on the shelves, and I go to the supervisor to ask if they carry the product line. She says “no”, but asks for a description — I pulled it up on my Facebook screen for her to see (I shared it on my timeline to have easy access)! I can check back with them on my next visit, and they will try to get some in the store! Wow, I will be going there soon.
Marketing and social media can deliver an experience, which is replicated through the buyer/consumer conversations. Good or bad, everything can get validated through the stories we hear via comments. At the end of the day, marketers need to move the customer to exchanging cash for product/service. That is the objective.
Facebook sharing is big and can lead to great success and feedback insights before a brand can be severely damaged. It should be a part of most product marketing strategies. Going beyond the superficial is the new generation marketing challenge for those able to create the authentic /real stories consumers want to read and act on. A marketing savvy person/company shares user experiences effectively. Let’s get those consumers to feel our brands, through conversations!
About the Author
Donna Luisa is a a corporate business veteran, with practical experience in a diverse range of industries — Safety/ HVAC / FMCG /Industrial Equipment /and much more . Sales, Marketing, Business Development & Coaching are combined to deliver over 30 years experience.
Customer service is often overlooked by many companies because it’s hard to measure the direct value of providing great customer experience.
In today’s highly competitive market, businesses have to make tough calls on what to focus on next to survive, and unfortunately, providing customer satisfaction is usually on the lower end of the list.
Learn the Importance of Customer Service. Request a FREE Woveon Conversation Software demo today!
Without being able to properly quantify the direct value of great service, many businesses can’t justify spending time and resources on providing it. Other businesses just see customer service more as a pain, and choose to be reactive, rather than proactive to customer expectations. However, the truth is, great customer service is absolutely crucial to the long-term survival of the business.
Customer Service Importance and its Value
You can argue that price is the main reason your customers choose you, so you focus your energy and resources on being the most affordable. I’m telling you, there will come a day when a competitor comes in with a better product for a cheaper price.
In the the same way, you can also argue that you focus on innovative developments and that’s why your customers buy from you. Again, there will come a day a competitor swoops in and take your customers from you because they made better innovative progress. Do you know what you can invest in that your competitors can’t take away from you? Loyalty. Good old customer loyalty.
The best way to gain customers’ loyalty? You charm them with your service.
By continuously engaging with them through customer service and marketing efforts, you are fostering a relationship with them. It’s hard for people to walk away from someone or something they have formed an attachment to.
So now you know why it’s important, what’s the value of providing great customer experience and service to create highly engaged customers?
The Value of Customer Service
1. Retaining customers is much less expensive than acquiring new ones
It’s true. Acquiring a new customer can be anywhere from 5-25 times more expensive than keeping a current one. You don’t have to spend so much time and resources finding a new customer and converting them. Instead, you just have to make sure they’re satisfied and will repurchase from you.
Customer support contributes a large portion to the retention and satisfaction of customers. Many companies put a lot of time and resources in their sales and marketing teams, when just as much emphasis should be put in support or success teams. When done right, they can have a bigger impact on your bottomline than new acquisition activities.
2. Repeat customers generally spend more than new ones
A study by McKinsey found that eCommerce spending for new customers on average is $24.50, compared to $54.50 for repeat customers. Even better, highly-engaged customers buy 90 percent more often and spend 60 percent more per transaction.Making a customer happy shouldn’t be a one time thing at the beginning of the relationship. Most relationships are more valuable the longer they are. Businesses should be putting more emphasis on their customer service, success and support teams because the financial growth potential is much larger than in newly acquired customers. Plus, the probability of selling to an existing customer is 60 – 70%, whereas the probability of selling to a new prospect is only 5-20%.
2. Great service reduces the severity of overall problems.
We’ve all had problems with companies before. In the moment, you might be upset, angry, annoyed or all of the above. If you had to talk to a rude customer service rep on top of all that…I’d imagine you wouldn’t be too happy. What originally may have been a small problem would go from 0 – 100.
In the same way bad service can escalate problems, good customer service can reduce them. When delivered well, customer service can diffuse negative emotions from the customer and the situation. Excellent customer service can turn the situation around into a positive. Small things like apologizing, empathizing and being genuine can go a long way to reduce a customer’s negative emotions and the severity of the overall problem.
82% of satisfied customers will “likely” or “very likely” keep shopping with a company and give it another chance if something goes wrong.
3. Builds brand awareness with minimal effort.
Customers are being more and more vocal about how a company treats them and how a company makes them feel. Considering your customer service team are likely to be the only people in contact with a customer, they play a crucial role in shaping their customer experience, and by extension, whether they have good or bad things to say about the company.
It is therefore important that every interaction with a customer should make them feel valued, listened to and supported. Extra points for going beyond expectations like Paul from Zappos. It was a simple response to a customer whose shoes were falling apart, but he made it so much more. This ended up being shared on Reddit, Hubspot and Helpscout and championed as customer service at its best.
4. People remember the service a lot longer than they remember the price.
Think back to a purchase you made a couple of years back. Heck, think back a couple of months even. I can’t even remember the price of something I bought in the last few months!
What I do remember though, is the service, the delivery and the effort I had to put in to make the purchase. It’s not about the destination, it’s about the journey. And in this case, the price you paid is the destination, and all that leading up to the purchase, is the journey. People will talk. If they liked the journey, they will recommend it to others.
5. It’s a competitive advantage no one can take away
With rapid innovation reducing differentiation between one product and another, and competitors just a click away, customer service is one of the last frontiers of sustainable competitive advantage for businesses.
Many businesses will pay lip service to the value of customer service, all the while cutting costs and resources to provide it. This will only ensure they provide the bare minimum to support customers, it doesn’t mean it’s anywhere near good enough to be a advantage. When normal customer service standard means going above and beyond for a customer, that is when customers will choose your business over someone else’s.
Customer Service Takeaway: Customer service is becoming more important than ever as competitors increase and are closer than ever. A customer is 4 times more likely to defect to a competitor if the problem is service related than price or product related. No one wants to do business with someone they don’t like. The product or service doesn’t matter anymore. They can easily substitute with other products or services that function similarly. Customers would rather deal with the slight inconvenience that the competitor’s product or service doesn’t function the same way, than to deal with the huge inconvenience of not being supported by your business.
Customer service, when delivered to the satisfaction of customers, not only creates a powerful marketing opportunity for the business, but also helps with the bottomline. Not only are return customers easier to sell to, they will spend more per transaction and would pay extra to guarantee better service.
The one key area that you need to look at when you want to run a successful business is ensuring that you can keep your clients happy. When your clients are happy they will look at your lead generation, customer service and marketing efforts as a source of validation that all the hard work your team is doing is paying off! Businesses who understand this, then end up having many repeat customers, because people like surrounding themselves and working with successful businesses. This is why customer success is paramount. How can you manage this effectively?
The Customer Success Factor
So, why is success for clients so important? It is because every major business needs to realize the value of helping their partners achieve success as well. The fundamentals of business haven’t changed over time, but the only thing that has changed is that now businesses must ensure that their clients are successful. This can be tricky sometimes because you must do business with a company that wants to work with yours to ensure complete success in their industry.
This means that every business strategy that you come up with, must also include how it affects the success of the client. This is done to ensure that all aspects are covered, and there are no disappointments after business is concluded. There are multiple strategies that you can employ with the right vision and commitment at the forefront to ensure that your business partners and clients are happy and satisfied. It is important to take the success factor into account, because you need to create love between your business and your customers.
The Customer is Always King
Any business that places the interests of its customers above their own is going to be a successful business, because they are going to go out of their way to make sure that the customer is happy. Most businesses that fail, do so because they stop caring about their customers. This fact alone that 60% of consumers stopped doing business with a brand due to poor customer service should ring alarm bells for a few . Depending on the reports, this number can jump to over 82% of consumers. It is important that you always treat the customer properly, and remember that they are always the king.
If your business is failing to win over more customers, you should probably look at what kind of customer experience you are offering to your clients. There is enough data around that points to the importance of great customer experience in helping businesses retain and attract new clients.
It also states that 90% of businesses will go to a direct competitor if they are given poor customer experience.
Nearly 60% of clients are willing to pay more to receive better customer experience.
Businesses that fail to value their clients, and don’t care about their success are likely to lose out, and not get ahead in their industry. Therefore, it is imperative that you find out creative ways to ensure that you give priority to customer success. We want you to succeed, which is why we are going to provide you with 3 creative ways you can ensure that your clients always succeed.
1. Genuine Interaction – Treat them right
Make sure that you have genuine interactions with your customers, because it is the only way that you are going to help them feel at home. There is no secret about the fact that happy clients are much more willing to work with you and provide you with better word of mouth regarding your business. By treating your customers properly, you will ensure that you build a genuine interaction with them, and they will feel better in doing business with you.
2. Don’t come across as too strong
You need to always respect your clients if you want to keep them happy and satisfied with your services. That is the main reason why you should always treat your clients with respect, because if they are upset with you, then your business is the one that is going to suffer. Disgruntled customers are not good for business, and that is where you need to be patient, have empathy and listen to the customer.
You should do everything in your power to get your client in a better mood and try to resolve their issues. There aren’t going to be many clients lining up to work for your business if you don’t work with your clients in a respectful manner.
3. Hear their problems
Listen, listen, listen. You should always be listening to your customer’s problems so that you can help them in times of trouble. There are not many businesses that would work with a company that doesn’t take their feedback on board. You should have good communication with your client and always take everything they say into account, because that is the only way you are going to improve your situation and guarantee customer success.
Based in Singapore, Colin is the Director, Customer Success and Lead Data Scientist, APAC for DataRobot, where he advises businesses on how to build business cases and successfully manage data science projects. Over his career, Colin has held a number of CEO and general management roles, where he has championed data science initiatives in financial services, healthcare, security, oil and gas, government and marketing. He frequently speaks at various global conferences. Colin is a firm believer in data-based decision making and applying AI. He is passionate about the science of healthcare and does pro-bono work to support cancer research.
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