{"id":20748,"date":"2026-10-15T01:50:00","date_gmt":"2026-10-15T05:50:00","guid":{"rendered":"https:\/\/advertisingweek.com\/aw360\/?p=20748"},"modified":"2026-10-12T20:53:14","modified_gmt":"2026-10-13T00:53:14","slug":"how-much-do-you-not-know-about-your-customers-3-ways-to-close-the-gap","status":"publish","type":"post","link":"https:\/\/advertisingweek.com\/aw360\/news\/how-much-do-you-not-know-about-your-customers-3-ways-to-close-the-gap\/20748\/","title":{"rendered":"How Much Do You Not Know About Your Customers? 3 Ways to Close the Gap"},"content":{"rendered":"\n

By Phuong Ta, <\/a>Senior Vice President of Analytics & Intelligence at RADaR Analytics<\/em><\/p>\n\n\n\n

Every brand I meet believes it knows its customers. The dashboards are full. The reports are current. The segments are named. The confidence is real.<\/p>\n\n\n\n

I used to share that confidence, until I spent real time inside a customer intelligence project for a higher-education client, working at the level of individual journeys. What struck me was not how much the data revealed. It was the opposite: how little the brand actually knew about its own customers as people. Not as segments or conversion rates, but as human beings with motivations, hesitations, and reasons for behaving the way they did.<\/p>\n\n\n\n

The brand was not data-poor. It ran the two things most serious organizations run to understand their customers, and, like most organizations, it ran them in separate rooms that never spoke.<\/p>\n\n\n\n

On one side: perception research. The brand survey, the market study, the work that tells you what people think and how they would describe you against a competitor. Valuable, but a snapshot of where the audience stood the day the survey closed.<\/p>\n\n\n\n

On the other side: behavioral analytics. Web data, CRM, every click and session, continuously and at scale. But on its own, it cannot tell a skeptic clicking out of doubt from an advocate clicking out of loyalty. On a dashboard, the two are identical.<\/p>\n\n\n\n

So the brand knew what people thought, in the abstract, once a year. It knew what people did, in enormous detail, every second. What it could not do was connect the two, and that connection is the entire why.<\/p>\n\n\n\n

That is the gap worth measuring. Not how much you know about your customers, but how much you do not. Here are three ways to start closing it using data you already own.<\/p>\n\n\n\n

1. Overlay what customers say onto what they do<\/strong><\/h2>\n\n\n\n

Pull your most recent brand or customer survey and identify the top three things respondents said they valued. For each one, name a single observable behavior that would serve as a reasonable proxy: a specific page visited, a document downloaded, a comparison tool used, a return visit within seven days.<\/p>\n\n\n\n

Tag those behaviors as events in your analytics platform. You now have a continuous read on something you previously measured once a year, and a way to see which stated values actually predict who moves forward. Expect surprises. The value customers rank highest in a survey is frequently not the one that correlates with conversion.<\/p>\n\n\n\n

This costs nothing beyond the analytics you are already paying for. The work is interpretive, not technical.<\/p>\n\n\n\n

2. Sort your stuck prospects on two human axes<\/strong><\/h2>\n\n\n\n

Every brand has a population sitting in mid-consideration limbo. On the surface they are indistinguishable, all just unfinished journeys. Underneath, they are usually two entirely different kinds of people.<\/p>\n\n\n\n

With the higher-education client, a behavioral model scoring roughly 1,500 active prospects a week surfaced exactly that split. Some were persistent, pushing through friction because the decision was emotional, tied to an identity they had already claimed for themselves. Others gave up at the first obstacle, evaluating the option on purely practical footing, ready to walk the moment it stopped being convenient.<\/p>\n\n\n\n

You can approximate that split in a spreadsheet. Score each stalled prospect on two axes:<\/p>\n\n\n\n

Determination:<\/strong> did they push through friction? Look for return visits, retried forms, repeat pricing or requirements views.<\/p>\n\n\n\n

Motivation:<\/strong> is the interest emotional or practical? Look at which content they engaged with, aspirational and identity-driven versus cost, logistics, and comparison.<\/p>\n\n\n\n

Four quadrants, four different people. Someone emotionally committed but stuck on a logistical wall needs a human phone call and a cleared obstacle. Someone quietly comparison-shopping needs a reason to believe, and needs it this week. Sending both the same reminder email wastes the only moment either one was reachable.<\/p>\n\n\n\n

3. Give the “why” an owner<\/strong><\/h2>\n\n\n\n

In most organizations, no one owns the understanding of the customer as a whole person. It is split into fragments, one per team, and the customer feels every seam.<\/p>\n\n\n\n

Fix the ownership before you fix the org chart. Name one person accountable for a single living document, updated monthly, that answers three questions: what do we now believe about why our customers behave the way they do, what changed this month, and what would we bet on next. Circulate it to every team that touches the customer, including external partners.<\/p>\n\n\n\n

It is close to free. Its value is that it forces someone to answer a question most organizations never assign to anyone.<\/p>\n\n\n\n

The compounding asset<\/strong><\/h2>\n\n\n\n

A tool depreciates from the day you buy it. Understanding does the opposite. It gets richer every week you feed it real behavior and real feedback, and each thing you learn sharpens the next decision.<\/p>\n\n\n\n

That is worth remembering the next time a vendor demo tempts you. The highest-leverage investment is rarely the newest capability. It is usually the connective tissue that finally lets the capabilities you already own see the same person at the same time.<\/p>\n\n\n\n

Your dashboards will happily overstate how much you know about your customers. The harder and more useful question is how much of the why is still invisible to you, and what you would do differently if it were not.<\/p>\n\n\n\n

About the Author<\/em><\/p>\n\n\n\n

Phuong Ta<\/em> serves as Senior Vice President of Analytics & Intelligence at<\/em> RADaR Analytics<\/em><\/a>, where she architects the next evolution of measurement frameworks. She focuses on translating the disjointed signals of modern marketing into clarity\u2014fusing media inputs, intricate behavioral journeys, and high-level outcomes into a singular, reliable source of truth. As part of True Independent Holdings within the Meet The People agency group, RADaR provides marketers with the insights, predictive analytics, and performance measurement capabilities needed to make confident, data-driven decisions in an increasingly complex marketing landscape.<\/em><\/p>\n\n\n\n

<\/p>\n","protected":false},"excerpt":{"rendered":"

Your analytics capture everything customers do and almost nothing about why. 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