Personas for innovationAre Personas Dead? According to a recent blog post  on the Convince & Convert blog, they would have you believe they are.

Here’s why that’s wrong:

If I tell you “the king died,” that’s a single-event data point. Information, if you will.
And if I tell you “the king died and then the queen died,” that’s two data points. It’s still information.

But if I tell you that “The king died and then the queen died of a broken heart,” that’s a story.
I’ve taken the two data points and connected them with causality, which makes the data meaningful.

What does this have to do with Personas and Big Data?

All data records events. Little factual tidbits of what happened. At best, sophisticated analytics can record chronological records or patterns of events.

The website visitor did this. Then this. Then that.

Or, patterns: male customers tended to buy this instead of that.

But notice that the reported chronologies and patterns are absent causality and intention. A series of events for a Web or store visit remain nothing more than an itinerary. And a pattern remains nothing but a correlation. There is no visible cause-and-effect relationship. There is no underlying shopper intention, and no meaning recorded by the data itself. That all remains for the marketer to provide via interpretation.

Humans cannot transform data points to insight about causality, intention, and meaning.  To do so they must turn the data into a story.

Stories with the buyer as the protagonist.

And “buyer as protagonist” is another way of saying “persona.”

Formal Vs. Informal Personas

Are we really saying that all marketers use personas and tell stories when interpreting data?

Yes.  

The data might be as straightforward as “the all-inclusive bundle is our most popular product,” combined with “A/B testing proves that a satisfaction guarantee boosted conversions by 30%”

And the story might be as simple as “this category of buyer chooses the satisfaction-guaranteed, all-inclusive bundled option because of its convenience and promise of risk reduction.”

Yet as simple as that interpretation of the data is, it still represents the creation of a story centered around a character in the form of a buyer.  

Unfortunately, because the creation of the buyer’s persona was implicit and ad-hoc, it was also under-developed.

And that’s where the problems come in.

The Downside of Implicit, Informal and /or Ad-Hoc Personas

So what’s wrong with letting one’s personas remain implicit or unconscious? After all, we process intuitively as we make sense of the data?

Short answer: Our Baked-In Cognitive Glitches.

We have two cognitive biases when we rely on ad-hoc implied personas:

1) We assume everyone is like us. They value what we value, they make decisions like we make decisions, and what appeals to us also appeals to them.

2) We work off of stereotypes and then engage in the fundamental attribution error.  When we see someone doing something, we tend to think it relates to their personality rather than the situation the person might be in.

Well-designed Personas help marketers avoid these cognitive biases. They show how a different temperament might engage in a different decision-making process. They look beyond stereotypical attributions to see the context.

The most important reason to use well-designed personas is prediction.

With a well-designed persona like a TV character, you can predict how they’ll behave.  Character explains a scenario better than demographic and even psychographic data.

For example, suppose a white, middle-aged, middle-classed, white-collar New Yorker found a lost wallet, stuffed with cash. What would you predict he’s likely to do?

Well, based on that, you’d have no clue, right?

There’s no way you can confidently predict behavior based on the demographics provided unless you assume that the person in question would do what you think a typical person would do. Which is to say what you’d do.

That’s exactly the situation with implicit personas that are usually drawn from demographics or based on our own intuitions of how we or typical person would behave.  

Now, if instead of giving you demographics, I told you that George Costanza found that wallet…

Now you can picture exactly what Costanza would do, even though it’s probably not anywhere near what you — or even a typical person — would do in the same situation.

That’s the kind of prediction those properly designed personas bring to the table.

And when it comes to crafting and optimizing customer experiences, that’s all the difference in the world.

Increased Data = Increased Need for (Better) Personas

Data and advanced analytics don’t and can’t change our hardwired need for a story as a sense-making tool.  

In fact, the more complex and unstructured our data sets become, the more robust our storytelling chops need to be to help us not only analyze, but make sense of that data.

The disadvantage of structured data is that the structure limits the answers you can pull from it. The advantage of structured data is that the structure suggests the questions the database is capable of answering.

So while unstructured Big Data presents greater opportunities for marketers, it also increases the burden of coming up with and framing the right questions to ask.

The better designed the persona, the easier it is to interpret the data as narrative. Personas help frame and ask questions about intent, motivation, and cause and effect.  These questions can then be posed to the data sets for not only answers but insights.

This is the only way to move from having data to being able to use that data to increase sales, market share, customer loyalty, etc.

Personas Increase Empathy and Move Marketing Past “Optimization” to Innovation

Without personas, marketers can certainly optimize what already exists to a local maximum. You don’t have to generate deep insight into the customer to run multivariate tests on different alternatives to the established patterns. Different color buttons. Slightly different calls to actions, hero images, page layouts, etc.

But you also can’t move past optimization to true innovation without thinking seriously about customer drives, frustrations, motivations, etc. Great customer experience design requires empathy.

And for empathy to be predictive, it requires fully fleshed out characters with which to work, just like you experienced with the Costanza example.

You can’t do customer design with just data alone and advanced analytical methods alone. In fact, neuroscientists have proven that analytical thinking inhibits empathy.

Your mind can do either one of these things, but it can only do one of them well at any given time. A marketers ability to generate customer insights come to live while in emotional storytelling mode, but fall dead while in number crunching analytics mode. And vice versa of course.

The point is, good marketers need both sets of skills, as well as advanced, rigorous processes for supporting and exercising those skill sets.

No one would ever argue that marketers don’t need or benefit from accurate and advanced customer data. Or sophisticated methods of statistical analysis aimed at sifting and sorting through that data, looking for patterns.

But that same level of rigor and defined tool sets also need to be brought to the storytelling side of the equation. Meaning that implicit and ad hoc personas just aren’t good enough.

And the more context-sensitive the situation, the more important simulation through storytelling and the use of formally developed personas becomes.

In other words, personas aren’t in opposition to data, they are the other half of the coin. Personas are a contextual tool for making data relevant and actionable. They are a bridge to understanding customers at a human level.

Without this, marketers are doomed. Without well-designed personas, it’s difficult to focus on customer experiences, rather than just products, price points, placement, and promotions.

So are personas still relevant in an age of data-driven companies?

Not only are they “relevant,” they’re becoming increasingly necessary for survival.

Jeff Sexton (3 Posts)


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