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How to Make Your Brand Tracker Predict the Future

Posted On  December 14, 2020
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Brand trackers are a staple of modern day marketing research. Companies rely on them for market intelligence, descriptive statistics, and as a competitive yardstick on which to base performance evaluations. But is that really as far as you can take them?  Is that all you can get from your tracking data?

For many, the answer is no. There is more insight, and more value, to squeeze out of your tracking data when it’s integrated with other data sources to provide a comprehensive, competitive view of your market landscape.  When the right data comes together and pairs with your tracking data, you can predict the future. You create a new way to understand how each of the components of your marketing ecosystem—brands, customers, and marketing—interact with one another, and how changes to one may impact the others in the future.

In short, you can create a marketing crystal ball.

The Benefit of Shifting Brand Tracking Data to Focus on the Future

Standard brand tracking data focuses on a point in time, and it does a great job of helping you understand how your brand’s value and perception stands today. But it is generally less effective at telling you where the brand is heading. Nor is it useful in getting a brand from where it is to where it wants to go.

But this doesn’t have to be the case.  Integrating brand tracking data with marketing activity, like client behavioral data, ad testing, word-of-mouth, and segmentation data can help you create a predictive platform that is not only firmly forward-looking, but that also learns over time.

And as new tracking (and other) data becomes available, it can be ingested into the system to update predictions on an annual, bi-annual, quarterly, or even monthly basis. The implication? Even more precise predictions that reflect the ever-changing realities of your market.

The Value of Integrated Brand Tracking Data

Integrating data from multiple sources, including your tracker, allows you to build a virtual replica of your market, a simulated market, if you will.  A market in which you can make changes to media plans, product offerings, innovation strategies, pricing strategies, demographic patterns, and consumer beliefs at the push of a button, and at no cost to you, in order to understand their effect on the thing you care about most – sales.

This virtual market built from your tracking and other data is the engine to run a powerful predictive tool that allows you to test an infinite number of “what if” scenarios for any number of marketing problems. Questions ranging from the optimal allocation of marketing spend for maximizing revenue, to identifying the best message and channel for growing brand love, to understanding the differing impact of marketing touchpoints on driving brand consideration, brand equity, and brand sales, to identifying the optimal pricing strategy for driving brand consideration.

It’s impossible to answer any of these questions with standard tracking data alone. And because you are capturing the entire market, the focus of your analysis can go beyond just your brand. Imagine understanding the impacts of shifts in your marketing strategy on your competitors’ sales. And what if you were able to plan against potential changes to a competitor’s marketing activities?

The future of brand tracking and market research requires us to move beyond simply measuring attitudes and behaviors and into the realm of predicting future customer behavior. This is sophisticated analytics and deep human understanding at its best, and we predict it represents the future of brand tracking.

Written by Charles Ellis
SVP, Marketing and Data Science
Charles studies people: how they choose, why they make the choices they do and what forms of persuasion are most effective when it comes to shifting their preferences. He is the resident expert on brand health at LRW, a Material Company, and leads all research and development into innovative ways to measure how brands perform. Charles has been providing marketing and public opinion research to clients for over 25 years. Prior to joining LRW, he led marketing science teams at Ipsos, MAi and ThinkVine. Originally trained as a political scientist, he holds degrees from the University of Colorado, University of Florida and Ohio University.

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