Video: These AI bots are solving customer problems
I've known Mitch Lieberman for a long time -- more than a decade. In all that time, there are two things I knew I could always count on: First, that he'd be a cutting edge thinker. Second, he'd be a good person. And, to this day, I can still count on both.
When you read what he says below, not only will you realize what I can count on is true and something that you can count on too, you will also get a real sense of how human communications and customer behavior is being transformed as we ride the 21st century to its middle. Which is something that you not only need to know, but will be glad that it was Mitch Lieberman who told you.
Alexa, tell Mitch to take the mic!
Customer Relationship Management (CRM) is like an old friend. We have been on a long journey together. For many who read this blog, we have all had the pleasure of listening to Paul serve as an expert guide in this space since 2001, with the first of his landmark books, keynote speaking engagements, and in-person discussions. I am still waiting for the famed 360-degree customer view. I know we will get there eventually!
The very first Paul post from November 2008, on ZDNet, is titled CRM 2.0 = The Conversation - But First... The Intro. In describing CRM, Paul stated: "It is a science of business that attempts to duplicate the art of life. That means, aside from the lovely poetic considerations, that CRM is the business strategy that attempts to understand, involve, and benefit customers in ways that benefit the individual business trying to accomplish that." My hope to continue from that point, and push the ball forward.
In the very early days (well before 2008), CRM mostly focused on customer service. This was soon followed by salesforce automation, marketing automation, social selling, account-based marketing, and more. The CRM world continues to evolve, and its journey is a twisted path that serves many masters. Practitioners are now charged with managing customer communications across a nearly uncountable number of interaction channels.
My goal here is not to create a new top-level domain, but rather to return to CRM's early roots to look at an opportunity missed. Starting around 1999, the concept of conversations as a focal point was talked about, but it was not cool, nor sexy, and it did not resonate with the right folks. Well, the time has come to go back and focus on conversations. Conversations are at the core of all of the basic relationship ideas for the past 20 years -- even 2000 years.
Here are some key ideas I hope you will take away from this article:
- Conversations are markets of one
- Precision is more important than personalization
- Machines deliver insight, while people require understanding
- In the business world, people [still] buy from people
I have no intention of criticizing important key concepts such as social interactions or customer engagement. Further, I consider Customer Experience (CX) to be a critically important area of focus for organizations. However, I hold a strong belief that we cannot manage our customers' experiences, as they are perceived and cannot be given. Experiences are perceived in the aggregate, but a customer experience is made up of many individual moments; this is where we need to do better. By focusing and understanding the components that make up experiences at a more granular level -- a conversation with a customer and the intelligence required to direct the conversation -- we will be more effective in our efforts to create better interactions, stronger engagements, and memorable experiences.
Conversations are Markets of One
A conversation is the most straightforward and easily described form of communication. Very few people raise an eyebrow and suggest, "I am not sure what you mean by conversation." Within the CRM domain, many other similar words serve as discussion points about how individuals would define them. From engagement, interactions, even relationships to customer experience itself -- everyone has an opinion. Conversation is more straightforward. It is not a strategy. It is simply a conversation. Something everyone understands and can support.
Customers are individuals looking to accomplish something from gathering information to taking action; this is referred to as the customer-job-to-done. Individuals have wants and needs and possess unique personalities. An individual engaging in a conversation with a company has a purpose. Focusing on the conversation allows for the natural progression -- from providing assistance and guidance to a discussion about a service issue or a product information request. Focusing on the conversation is similar to basic research in science. It is important to understand things at the most granular level possible before you can extrapolate the knowledge gained to apply to practical applications and advancement.
One conversation: One individual within a market of one.
This concept is not new. It has been around for a very long time. It is where we all started:
"For thousands of years, we knew exactly what markets were: conversations between people who sought out others who shared the same interests. Buyers had as much to say as sellers. They spoke directly to each other without the filter of media, the artifice of positioning statements, the arrogance of advertising, or the shading of public relations."
"[A] Conversation is a profound act of humanity. So once were markets." -- Doc Searls and Chris Locke, circa 1999, The Cluetrain Manifesto.
As Dan Miller stated in 2004, "We live in a world where both public and private discourse is carried on independent of time and modality through text-messaging, e-mail, 'blog-and-respond' or voice mail." Fast forward to 2018, and this list needs to include messaging, chat, chatbots, digital assistants, and virtual Assistants, along with the inescapable IVR. Conversations are hard enough between two people, even before we start to consider conversations between a person and a machine or an artificial intelligence (AI) system.
At a practical level, one that ignores social or linguistic complexities, a conversation can be simple. No technology is required -- just air. It is simply two people, sitting at a table, having a conversation. However, conversations can also be technologically complex, requiring advanced capabilities such as natural language processing (NLP), conversational intelligence (CI), machine learning (ML), or other advanced AI capabilities. Conversations are increasingly taking place between non-human actors (machine or systems) on one side and customers on the other side.
Precision Is More Important Than Personalization
Conversations focus on precision, while engagement concentrates on personalization. There are many technology vendors who have customer engagement embedded within their messaging and go-to-market strategy. This is not wrong. It is correct. It is the direction these vendors need to go -- the area that needs attention. Conversations are one of the basic building blocks required for customer engagement that creates a memorable connection with your customer, with your market of one. Given the premise that markets are moving toward a conversation of one, we need to treat each conversation with precision. Whether we are discussing engagement or experience, the objective should not be about personalization but rather precision.
Within the world of CRM sales, service, and marketing, we can learn a thing or two from how the medical field is moving from the idea of personalization to that of precision. While I am not saying the medical profession has conquered CRM, it is headed in the right direction. Let's think about patients as a particular type of customer that require engagement bound by the many rules and regulations associated with General Data Protection Regulation (GDPR). This engagement must ensure privacy, meaning that data protection measures must be implemented across all data processing activities and endpoints within the patient's customer engagement from preventative measures to treatment plans.
"Precision Medicine refers to the tailoring of medical treatment to the individual characteristics of each patient." (National Research Council, Precision Medicine.)
This is the ability to classify individuals into subpopulations. The word 'personalized' could be, and has been, misinterpreted to imply that treatments and preventions are being developed uniquely for each individual. In precision medicine, the focus is on identifying which approaches will be effective for which patients based on genetic, environmental, and lifestyle factors (check this out here).
If I were to alter the words above to emphasize Precision Communications, to work within the practice and strategy of CRM, it would look something more like this:
"Precision Communications refers to the practice of tailoring conversations to the needs of the individual customer by classifying individuals into subpopulations (customer segments). In precision communications, intelligence will determine the most effective conversational approach, based on both purpose and context, toward helping the customer to get their customer-job-done."
Machines Deliver Insight, while People Require Understanding
Understanding is more important than insight -- for now.
"The greatest enemy of knowledge is not ignorance, it is the illusion of knowledge." -- Stephen Hawking
This statement shows amazing insight and is prescient given today's academic, political, and social environment. In order to be precise, the enterprise side of the conversation needs to be intelligent. We need to know and hopefully understand the person on the other side of the conversation. This may go a bit deep for some, but we all need to work within a shared data dictionary, as Precision Communication is predicated on both basic human understanding and machine intelligence.
Within an enterprise, customer-facing employees crave insight; they want an accurate or intuitive understanding of a person or object. As we increase our reliance on machine systems in the modern enterprise, are we doing ourselves a disservice? Are people losing the capability to recognize patterns? When a person has insight, they understand. People gain insight from recognizing patterns of information. Machines are taught to find patterns in data without insight. This is one of the biggest differences between people and machines. When machines or systems provide insight into people that is simply based on data, it should not be assumed that there is understanding.
I am going to take this one level deeper down the rabbit hole. Where do intelligence or wisdom fit into this simplified discussion? Maybe it is not so simple. If we want to have meaningful, dare I say, intelligent conversations, we need to be able to make the leap from insight and understanding to intelligence. The best path for the enterprise may not be the best path for the individual employee. I am going to side with the employee and suggest that machine systems or AI are simply not smart enough at this point to get the job done well, because they still cannot understand. We need people to understand so conversations are meaningful. When people are intelligent and apply judgment, they are wise. When machines are intelligent, the knowledge is artificial. Machines are not wise.
Purposeful conversations lead to action. Action requires understanding. Currently, only simple conversations can be accomplished with machine systems. Soon, they will be able to handle more complex conversations. Conversational Intelligence is a program designed and built to help organizations direct conversations toward optimal customer outcomes. Precision is a necessary part of CI, responsible for the 'directing' action. People will need to augment machines in the near-to-medium term, as machines cannot do all that is required. Your teams will need to do the following. Are they ready?
- Interpret insight
- Apply knowledge
- Take action based on intelligence
In the Business World, People (Still) Buy from People
Why the big deal? The difference between insight and understanding is more than a discussion of semantics. In the modern enterprise, machine systems are increasingly providing insight through patterns of recognition within massive amounts of data. The systemic path to insight skips understanding, and may even skip information, taking the direct path from data to insight. This may be beneficial to the enterprise in the short term, but it is dangerous in the long term. This goes against the premise that 'people buy from people.' We should not be willing to make this leap, not yet anyway. Insight by people is still necessary in order to have productive conversations.
A person who can see patterns in information often understands what the information represents, what insights can be gleaned. Pattern recognition takes experience. Advancement will require systems to add context to data in a way that people understand. I am not only referring to mathematical equations, rather human centered issues, sociological in nature. The critical question is whether smarter machines are making people less smart, thus losing our intuitive capabilities.
When a person understands something, this is based upon their own time and energy spent working to learn and apply skills. When a person does this, recognizing patterns, this is earned insight. This is what makes good sales people great and great customer support agents awesome. When insight comes from software or a machine, there is still value in the insight -- but something is lost. Insight provided by a machine system or AI does not always help people to understand.
Do we have time to understand? Is understanding always important?
Focus on the Customer
Whether we take the perspective of a marketer, sales, support, operations or an executive, customers need to be central to our day-to-day thinking. We should strive to exceed the expectations of our customers and work hard to keep them happy. When both company and customer feel that there has been a fair exchange of value, the relationship is positive for all. A relationship with customers is based on trust, the 'look you in the eye' kind of trust. Customers, for better or worse, judge us through every engagement and interaction and every conversation. Judgement can be explicit and vocal, or implicit and reserved. Some might call this the customer experience; the perception based on expectations. My view here is that as practitioners we have lost sight of the importance of the conversation; the market of one. On websites, through emails, and short-form messages, our attempts at personalization come close, but they often miss the mark. We can do better.
We are at the next decision point. Increasingly we are considering handing responsibility, of the conversation, to virtual agents, interactive agents, and chatbots. We need to think very carefully about how, when, and where we should take the machine-based approach and when the personal touch is still required. I am an advocate, make no mistake. I am suggesting that we take the path that keeps trust and the customer relationship sacred, as it should be. As we increasingly rely on machines, we need to be confident that our organizations do not lose the human touch, such as empathy and understanding. But we can, and should, add precision. Many things change. Many things stay the same. People buy from people.
I am looking forward to hearing your thoughts. Let's have a conversation.
Also, a reminder: The CRM Watchlist and the EMI Awards are open for registration right now. If you are interested in either, please email me at email@example.com for the registration form.
Previous and related coverage
Changes in the CRM world have led to major changes in the CRM Watchlist and the new Emergence Maturity Index Awards. See how the customer-facing technology market correlates to these changes, and how you can register and submit to these.
I promised that I would cover my speculations about Oracle and SAP, and to fulfill my obligations for 2017, here they are -- in 2018. The best way to put it is, when it comes to both Oracle and SAP, I'm very cautiously optimistic for very different reasons. But caution rules the day, and these are speculations, not deep analysis. More of that later. For now, read it, and tell me why you weep or laugh or nod.