Some Thoughts on Measuring Consumer Marketing’s Affect on the Path to Purchase

January 27, 2012
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For Consumer Goods companies it’s getting harder to argue with the value of knowing consumers and shoppers at an individual level. It’s simply best practice for any industry, but a relatively new idea in Consumer Goods where the historical emphasis has been brand marketing and trade promotions. Both of these very significant investments have been relied upon to drive sales absent direct relationships or detailed knowledge of individual consumers.

For Consumer Goods companies it’s getting harder to argue with the value of knowing consumers and shoppers at an individual level. It’s simply best practice for any industry, but a relatively new idea in Consumer Goods where the historical emphasis has been brand marketing and trade promotions. Both of these very significant investments have been relied upon to drive sales absent direct relationships or detailed knowledge of individual consumers. That has to change, as noted in posts like this one.

The challenging part of the discussion begins with how difficult this visibility is to achieve given the lack of an existing consumer or shopper database that has a real person’s name at the center. Few Consumer Goods companies have complete visibility into the data generated across every agency, promotion, campaign, channel or brand. It’s a data integration and agency-process issue Teradata has worked hard to solve for some of the largest Consumer Goods manufacturers. The lens then focuses quickly on what consumer actions can be captured, measured, and improved upon to increase sales.

One idea to explore is mapping all consumer interactions to a “state-based” path to purchase which can be tested, validated then optimized. Consider all the ways both offline and digital marketing efforts have targeted consumers over the past several years and how these relate to different markers along the path.

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    • Offline to online interactions out of store (television advertising, newspapers or magazines, presumably at or near home, featuring a call to action to register, scan or text).
    • Desktop web experience – register or log-in (presumed to be at or near home).
    • Email read on a desktop client (presumed to be at or near home).
    • Email read on a mobile device (“on the go”).
    • SMS text message interaction (“on the go”).
    • In-store interactions (QR code scan, unique SMS shortcode, unique email or mobile web, mobile application interaction data).

If you start with the assumption that certain interactions are inherently performed at-home, “on the go” or in the store environment you can begin to paint a picture of how digital marketing efforts affect the path to purchase. You start by asking relatively basic questions, such as:

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    • How many consumers have you interacted with in these ways?
    • What consumers have interacted with you across these ways? A segmentation or profile emerges.
    • How have consumers interacted with you across these ways – the data provided and captured, the sequence and timing. Does an observable path emerge?
    • What patterns exist among the interactions that are especially insightful – in terms of moving a consumer through a hypothetical “buy pipeline” or along the path? What campaigns, incentives or creative ideas were responsible?

And that’s just the beginning. All interactions can be related to geographies, markets and individual retail locations to begin gauging a more direct impact consumer marketing has on sales than ever before possible.

How else might Consumer Goods marketers leverage consumer data to understand and shape the path to purchase in their favor?

 

Gib Bassett