AI customer experience: Doing AI versus actually being an AI organization
The truth nobody wants to say out loud: To be an AI organization, you will fail if you don’t change.
For two decades now, customer persona development has been part of customer experience management. It’s become standard practice for companies to build an understanding of their customers using an archetypal representation of existing subsets of the customer base. Meant to describe the subset’s unique needs, companies use personas to guide the design of marketing communications, customer journeys, and solutions.
What’s missing in customer persona work is situational segmentation based on an understanding of the common situations that most people find themselves in.
Companies spend far too much time dividing their customers into subsets based on demographics, psychographics, and attitudes—none of which necessarily represent differences in needs — and too little time considering their needs based on their situation.
From personas to situational segmentation
Differences in needs largely grow out of common situations that people find themselves in. This is especially true today, where roles that people play are far more overlapping.
Fifty years ago, it made sense for Procter & Gamble to describe its customer base as primarily women. They were the buyers of home goods. Today, that’s a dated stereotype. In fact, most personas are not really archetypes at all. They’re inflexible stereotypes.
What distinguishes one need from another isn’t the person who has the need, it’s the situation in which the need arises.
Imagine that two friends decide to go biking together. The first friend has all of the equipment. He loves to road bike and can explain a lot about the activity. The second person doesn’t really know if she likes road biking, but she does enjoy cruise biking on paved, coastal trails.
To the customer persona writer, what we have here are two personas. The first is an expert road biker. The second is a road bike learner—or, perhaps, a beach biker. The persona writer is likely to probe the attitudes of both and determine that people, mostly women, who prefer paved trails near beaches, are one type of customer. They can learn to road bike, but that’s not their primary interest. Thus, road bikers have different attitudes and different needs from coastal cruisers.
Taking a different perspective
If, however, we look at the same scenario, but focus on situational segmentation, different details pop out. When two people decide to road bike and one’s an expert while the other’s still learning, the following needs arise:
- Finding a path that will accommodate both riders’ expectations
- Communication between riders, what to say and when to say it
- Helping the expert explain the fundamentals that have become habits
- Helping the learner develop an appreciation for the activity
- Distance to travel on first trip
- What to do if something goes wrong
- Learner comfort and additional equipment requirements
Based on a company’s ability to support the situation, the learner’s attitude toward road biking might change. This doesn’t mean that she’ll stop enjoying coastal cruising. It just means that when she’s road biking the next time, it’ll be more enjoyable.
“When” is the key word here. It’s the difference between an inflexible stereotyped persona and a situation-based description of needs.
- People riding alone may have a different set of needs from people riding together.
- People who ride on weekdays may have a different set of needs than those riding on weekends.
- Those riding for a commute may have another subset of needs than those riding for fitness or pleasure.
- Weather changes may impact all rider types.
Segmentation and persona work are meant to help companies identify new needs and therefore new markets.
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Supporting the situation that fits the need
We don’t have to subdivide needs based on attitudes, demographics, or preferences. We can instead identify needs and markets based on common situations that people find themselves in. These “situational markets” help companies to see future needs without creating stereotypical customers.
Situational segmentation can replace persona work. We can create data-driven, empathetic, descriptions of common situations. Companies can segment situations based on common contextual data, like time of day, weather, number of people present, location, difficulty, use of tools/channels, milestones, and so forth.
Of course, attitudinal data may still be important—if, from our example, someone doesn’t like biking, they’re probably not the bike manufacturer’s primary target. But that brings us to another benefit of situational markets: We don’t have to find the people who are interested.
Instead, companies do an excellent job of supporting the situation that fits the need, and with the tools at their fingertips, the people who have the need will regularly find the solution.
