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iMedia Editors

Pinpointing your multi-dimensional audience iMedia Editors

May 15, 2015

Identifying a brand's target audience is an essential part of any advertiser's job. We often break our audiences down into demographics: 18-24, female, middle-class, single, etc. But how much do these insights really tell us about the consumers whom we hope to reach?

This question was posed by Digilant during a Spotlight presentation at the iMedia Agency Summit. Krishna Boppana, chief data scientist, and Kim Riedell, SVP of product and marketing, gave a presentation that outlined the core issues agencies run into when dealing with analytics and identifying a brand's true audience, and how Digilant's unique insights can provide a solution to these problems.

Riedell first addressed the concerns that frequently ail agencies and their clients:

Who are the consumers I need to be targeting?

Am I using the right tools to find them?

Are these the right people -- or the wrong people disguised as the right people?

Special attention should be paid to that final question. Oftentimes, a client might think that it has identified its consumers, but those people aren't converting -- meaning they're the wrong people. They might fit into the basic demographics you've identified, but they're not who you're really looking for.

Riedell explained this further by showing a clip from an Esurance ad: Lindsey Lohan pulls up in a minivan to pick up "her child" from school, but she isn't actually his mother -- just someone who possesses some of the same identifying qualities as the child's mom. The tagline? "Sorta you isn't you."

So how can you definitely say who you're reaching -- and do so in a consolidated fashion that is digestible and actionable for your clients? What Digilant proposes are detailed consumer personas, showcasing the grouping of multiple segments (or characteristics) each of us possess and where these segments overlap, to find your target audience.

Let's look at an example: A popular upscale cosmetics brand, which sells its product in its own stores as well as through major retailers like Nordstrom. Digilant used segmentation information from third-party data, first-party data (client CRM), and Digilant proprietary audience segmentation to create a thorough consumer persona . Among other interesting findings, it discovered a 10 percent lift from the demographic of holiday shoppers and travelers -- which had no connection to any of its advertisements.

What Digilant deduced is that this could be attributed to those who only purchase from the retailer once a year, during the winter holidays, because they are buying a gift for someone who has given them a list containing a specific item. This find showed the agency and retailer exactly where not to target, as the ads have no effect on whether or not these people purchase.

The takeaway from all of this? No consumer is created equally -- they can sit in across multiple segments at any time during the day. An in-depth profile will give you: