Time To Hit The Reset Button On Your Audience Segmentation

January is a unique time in marketers’ calendars, beginning with the recovery from a hectic fourth quarter and usually ending with the rollout of a yearlong plan. It’s the perfect time to review their marketing performance over the past 12 months and put all of the new data they’ve gathered into action. For many marketers, that presents an opportunity to hit the reset button on what they know about their target audience.

Refreshing marketing personas right now could be crucial for 2016 marketing plans and beyond for several reasons. Marketers might be using segmentation frameworks designed for other industries, using outdated data for their segmentation, or could only be scratching the surface when it comes to understanding their audience. Reexamining the framework and data right now will help better set them up for success throughout the year.

The place to start is by looking at the segmentation framework itself. Many marketers may find that they’re using pre-built solutions that don’t necessarily match their business goals or fit their customer audience. While these tend to be easy to adopt, they very likely won’t deliver desired optimal results. 



Some marketers counter this by custom-building segmentation frameworks, but they run the risk of working with old, outdated data, especially if they don’t refresh their frameworks at least annually. If the segmentation model was built two years ago, using data from the three prior years of marketing efforts, then the marketer could be relying on data from three to five years ago to build their new 2016 plan! Customers and their media habits have changed dramatically in the past half-decade. While the marketer may have achieved good results in the past, they may be unlikely to grow if they continue to use a model with potentially stale data.

A new year requires a new vision. Marketers can start by building a new segmentation model that accounts for the past three years of marketing. That model identifies more recent audience trends and can be used to better predict the future audience segments that marketers might pursue with their promotions, products and services. From there, they’ll need to factor in additional insights to better market to specific segments throughout the year, especially within the affluent population.

To understand how this works, let’s look at affinity and loyalty. Conventional thinking says that loyal customers are the best customers to focus on, but the definitions should generally be reexamined every year.

Take two hypothetical consumers: Consumer 1 spends $500 a month on average at a luxury retailer, while Consumer 2 spends $300. On the surface, Consumer 1 appears to be more valuable, but a marketer’s own transactional data might not tell the full story around affinity or capacity. What happens if we bring in other economic measures like credit, spending habits, financial capacity, and share of wallet? 

Consumer 1’s $500 may only account for 10% of their spending capacity, meaning that the remaining 90% may be divided among other retailers. Meanwhile, Consumer 2, who spends less on average, may be devoting 80% of their capacity to the retailer. Consumer 2 is the one exhibiting the strongest signs of brand loyalty. 

Building tailored marketing efforts around these loyal customers can be a relatively easy way to grow potential revenue. With more tailored messages and offers, the retailer may capture a larger percentage of its loyal consumers’ spending capacity, and that additional percentage growth could result in millions of dollars of additional revenue. 

That kind of growth looks great in a year-end report, but it may only be achievable if marketers review their data and segmentation strategies now. No marketer wants to get stuck using outdated information for marketing planning. 

Segmentation should provide something marketers don’t already have, above and beyond their own transactional data, and allow them to build frameworks that identify audiences they might not have previously considered. The data used to build a marketing plan should help enable the company to grow its revenue and sustain that growth in the long term. Using old or limited data can leave the marketer missing entire groups of consumers. A better way to move forward is by expanding upon the past.

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