Image Credit: FilmWise

I remember really getting a kick out of the FilmWise Invisibles quizzes where you have to guess the movie based on a scene – but the actors have been erased. The more of these I saw, I realized how much we take certain visual queues for granted.

The same can be said for what data tells us about audiences. You may see that someone’s in a certain city. Maybe you have a good idea of where they shop or that they’re in a relationship. But without the whole picture, all you can really do is guess.

The companies that know for sure are the customer aware organizations that will have an edge in a marketing environment that increasingly favors smart engagement with real people.

Personas aren’t predictive

Turns out people are a lot more than where they’ve been or what they wear. The fewer the attributes, the more people look the same. Or maybe the same person starts showing up over and over in your audience, but you have no way of knowing for sure.

Let’s say you’ve got five different personas representing the same person in an identity graph. Some of these attributes may be incorrect, dated, or in conflict from one persona to the other. Because they’re based on personas and not actual people, there’s no way to actually deduplicate these profiles and standardize on one version of the truth related to that buyer.

So you guess and make assumptions. And waste a lot of time, money, and effort in the process. Not to mention, potentially squander an opportunity to make a real connection to a real customer.

We know that people are the totality of what they are, not just a few fleeting attributes. So we go through painstaking effort to put guardrails in place to validate that data in our audience profiles is accurate. That’s why for any given campaign, there can be certain attributes that end up unlocking success.

We recently worked with a highly-specialized company that struggled to attract new customers with a generic outreach campaign.

We developed an audience testing strategy to determine if certain selectors made sense relative to the weighted values we assigned. Regression analysis was conducted against all selectors, revealing which were most indicative or predictive of being a lookalike customer based on existing customer profiles.

Without this testing, it would not have been obvious at all which selectors were going to be most predictive of behavior. For instance, people who hunted and fished were highly predictive. As were people over a certain age.

We were able to rank the most accurate predictors from highest to lowest and with a high degree of confidence. Then, based on matching current customers to the new profiles we tested against and overlaying the most predictive attributes, we’re able to produce a strong growth campaign audience.

Bottom line: if data is actionable, timely, and complete and we know who your customers are, we have a high probability of being able to find your next customer. On the other hand, if the data is not tied to a person, but rather a persona with attributes linked incorrectly, the probability that anyone will find your next customer drops. Then it’s all one big guessing game.

In our engagement with customers, we see time and again the benefits of people-based approaches based on accurate attributes:

• Better engagement. There’s a higher probability that people will actually respond, improving opportunities to drive higher revenues.
• Path to profitability. Records can be scored based on metrics that predict customer profitability to determine who should be targeted, where the targeting should take place, and what channels should be used.
• Retargeting for customized communication. Once customers buy, they can be targeted appropriately with timely messages to increase profitability and reduce churn.

It’s all about customer awareness

If you’re aware of why customers buy, what profitable customers look like, trends that lead customers to churn or stick around, then you’re on your way to becoming customer aware.

Companies that are customer aware are 2-3 times more profitable than those that aren’t.

Customer-aware companies will thrive in the digital age because they’ve taken the time to boil engagement down to a science.

What steps are you taking to become more customer aware?