Commentary

Customer engagement is about the journey, not just the destination

Jean Belanger, co-founder and CEO of Cerebri AI, offers insight on how artificial intelligence has a unique role to play in allowing retailers to take advantage of the opportunity in the new era of customer experience.

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January 11, 2019 by Jean Belanger — CEO, Cerebri AI

By Jean Belanger, co-founder and CEO, Cerebri AI

We live in the 'age of the customer'; a time when customers use multiple channels to interact with your brand, spend more, and have access to more information about you, than ever before. It is a time when customers are two swipes away from a list of reasons why they should switch to your competitor.

Banks, global vehicle OEMs, major enterprises, even governments, used to wait and react to customer interactions when customers visited their stores, dealers, branches, or offices. They were, in other words, reactive in dealing with customers.

Enter the new era of customer experience. A successful customer engagement strategy needs to go beyond a one-off scenario and make each stage of the customer journey a priority. But why bother turning "customers" into "customer journeys"?

Two major technical discontinuities have coalesced to turn the world of marketing, sales and support upside down:
● The internet has made competitive information for goods and services universally available.
● Mobile phones make this information available on demand, anytime, anywhere in the world.

Can a company or public organization in today's mobile age afford to wait for customers to come to them? The answer is emphatically no.

So, what to do? To turn reactive enterprises and public organizations into proactive ones, we must change how they carry out day-to-day activities in the basic blocking and tackling of business and government. To understand customers and users better, it is crucial to gather as much information as practical and use it.

For decades, pundits have told us we are drowning in data created by the internet. As artificial intelligence penetrates our economy, we are moving from a world where we think we have too much data to a world where we will never have enough. AI models learn from ‘relevant' data. When we introduce new 'events', we are never sure if the events are relevant to the outcomes we are trying to predict. With so many new sources of information which may be 'relevant', being proactive in customer-related activities is harder than it looks.

Measuring customer commitment

The first priority is to understand customer commitment to a brand, product or service. Apple is one of the world's largest companies in terms of market capitalization. No one disputes that their brand is one of their biggest assets. But how do you measure this at the individual level? The most commonly used method to measure commitment to a brand or product is net promoter scores. You know this method as the ubiquitous question, "Would you recommend us to a friend?"

The problem with NPS is that few customers answer these questions. Usually less than 5 percent do so. The second problem is ‘gaming' the system. How many times have you had your car serviced and the staff tells you that a score of 8 out of 10 is a pass, so you should rate them an 8 or higher?

That's why it makes sense to get more customer interactions in our conversation about commitment to a brand, making it far more comprehensive a measure, and less likely to be manipulated. Where do we get more customer interaction, while at the same time ensure accuracy?

The fact is, all data is not equal. Some data is factually correct in all aspects, but many data sources have inaccuracies, mis-filings, errors in attributions, and human bias. A more difficult type of error or bias is data resulting from an emotional release. For example, when a customer is unhappy with a car service, or their credit card was refused at a restaurant in error. This makes it crucial to have more customer interactions to judge commitment both as to the facts and the sentiment.

Turning customers into customer journeys

A customer's experience represents a series of events that reflect many details, such as demographics and changes over time like marriage, salary increases, and changing homes. This also includes sales, marketing, support, social media, and macroeconomic events. Life-changing events, such as a new baby, retirements, are also important pieces of the puzzle. Cerebri AI, for instance, has determined that the more we track these events, the more we can understand a pattern of behavior and subsequently, brand commitment. We assign a number to each customer journey that indicates its value.

However, commitment to a brand and products is not the only key performance indicator that companies and organizations are concerned about. A great example of this is the wireless business. This industry has had massive growth in revenue for decades, yet it still struggles with relatively high churn rates, easily reaching 2 percent per month. These companies worry about their brand, but their number one revenue KPI in many cases is reducing customer defections, especially when considering that there are more mobile phones in operation than there are people in most advanced and emerging economies. It is tough to find a new wireless customer who does not already have a phone personally, or in a family plan already.

Again, customer journeys help to increase positive results in all customer-related KPIs, but in the enterprise, as with public entities and organizations, the rule is if you cannot measure it, you cannot improve it. In other words, assigning a value is essential.

A report by McKinsey stated that customer journeys are 30 percent more predictive of customer satisfaction than measuring individual interactions and that using customer journeys can increase customer satisfaction by up to 20 percent. This in turn has a positive impact on revenue and churn. Moreover, a premier automotive OEM recently indicated that every 1 percent increase in sales retention translates to a $700 million increase in revenue annually, which is an average of $150,000 per dealer.

Artificial intelligence has a unique role to play in allowing companies and organizations to take advantage of the opportunity in the new era of customer experience, bridging the existing gap between the customer as an individual and their journey, to unleash profitable growth.

Customer Experience AI Consumer Behavior

About Jean Belanger

Cerebri AI develops CVX, applying AI and reinforcement learning to draw insights from customer journeys. CVX’s Next Best Action{set}s insights are driven by patent-pending, object-oriented AI & reinforcement learning modelling that times, values, and sequences up to 4 events, rendering both rules-based and AI-lite technologies obsolete.

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