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With over 14 years of interactive marketing experience, Nancy Hall is the vice president of platform services for ValueClick Media, leading the goCart retail advertising product. goCart blends data and online advertising tactics to effectively increase sales, ROI and average order value in addition to decreasing cart abandonment. Using data from thousands of campaigns across dozens of verticals, goCart provides retailers cross-campaign learnings and insights to make retail campaigns more effective.

Nancy is a noted speaker on retail advertising, most recently presenting at ad:tech San Francisco in April 2011.

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Construing Consumer Motivation Through Data

Written on
Jun 29, 2011 
Author
Nancy Hall  |
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Construing Consumer Motivation Through Data

ADOTAS – In the offline world, when a customer walks into a store, an expert salesperson can size her up immediately — her clothes, accessories, cell phone and car keys are all indicators of her past purchases, interests and lifestyle choices. Armed with instantaneous info, the salesperson quickly determines the approach most likely to motivate that customer to action.

The sort of personal, interactive contact between sales people and customers that helps influence purchase decisions doesn’t exist in the online shopping environment. However, meaningful data that gives insights into consumer behavior, interests and proclivities does exist, and is readily available to retailers.

This kind of information about a customer is more insightful than even the best salesperson could ever surmise. By understanding the motivations of your target audience a retailer can get closer to the holy grail of online advertising — serving the right messaging to the right person at the right time.

According to research conducted by DIGIDAY and PubMatic, 97% of display advertisers will use audience targeting in 2011 to create a more personalized and effective advertising campaign for their target markets, in turn helping to drive brand awareness, reduce cart abandonment and increase average order value.

The Data Dashboard

Many of the largest online advertising and marketing companies have access to millions of anonymous user profiles that supply advertisers with the data they need to create a targeted campaign. This data can come from proprietary or third party sources. The key tools to driving product awareness and sales through data-driven targeting are:

  • Knowing customers’ past purchases;
  • Recognizing those who frequently buy a product;
  • Understanding lifestyle choices and life stage; and
  • Finding other purchasers who look like your top-valued customers.

A key point to be aware of is that in order to protect consumer privacy, and to ensure anonymity, online marketing providers target data that is non-personally identifiable (non-PII) and anonymous.

Past Purchases

One of the best gauges of what customers might buy in the future is analyzing what they’ve bought in the past. For instance, if they’ve recently purchased a digital camera, they’re more likely to have an interest in camera accessories like memory cards, tripods, carrying cases, etc. An electronics retailer should serve advertisements for accessories, perhaps suggesting a bundled package or coupon, to recent camera purchasers.

Additional marketing opportunities come from upsells, promotional items and discounts. Marketing to these high-value customers helps create a continuous dialogue that in turn, can create repeat purchasers.

Frequent Buyers

Another indicator of potential customers is purchase frequency. Many online shoppers are frequent shoe buyers, for example. With this knowledge, a shoe retailer can message upcoming shoe releases, the season’s hottest trends and other offers to avid shoppers. Informing and educating a product enthusiast can help drive desire — and conversions that may not have otherwise occurred.

Frequent buyers are excellent candidates for package deals and loyalty discounts. Recurring messaging to these customers helps ensure they return to your site when they’re next ready to buy and that they become your brand advocate.

Lifestage

One of the goals of data-driven targeting is to message the right audience based on who they are and their current stage of life in order to drive awareness. Data collected and used in targeting includes certain demographic information like gender as well as geographic location, automobile type and lifestyle.

An example of effective lifestage targeting is reaching and messaging to moms by associating her gender with her suburban lifestyle, three or more people in her household, recent kids’ clothing purchases and SUV ownership. This combination of data points tells a marketer that it is likely that she is in-market for back-to-school gear. Knowing consumers’ lifestyle choices and life stage can be one of the most powerful and informative data points a retailer can use for campaign targeting.

In Market and Interests

The knowledge of a consumer’s interests combined with her in-market desires allows a marketer to engage with a consumer with products that she is very likely to purchase. This method is a successful way of delivering new customers to an advertiser’s retail site or store location, and for increasing sales.

For example, a woman who spends multiple visits viewing luxury fashion content and is subsequently searching for designer handbags is likely to interact with an ad for aspirational fashion items like high-end shoes and accessories.

This consumer will interact with the advertisement, remember the product and land at the online or offline front door shortly thereafter. She could possibly then become a new and repeat customer of the retailer.

Look-Alike and Act-Alike

The concepts of look-alike and act-alike targeting are based on the principle that people who have similar browsing and/or purchasing behavioral patterns will likely be interested in similar products. This strategy is commonly seen on a retail site like Amazon.

Today the interactive marketplace is fortunate enough to take this methodology one step further. Similar to offline direct marketers, we can now build out look-alike models at scale by analyzing the behavioral attributes of high-value customers and then find many more users that possess those same high-scoring attributes to whom we then message in a relevant fashion. This is all done anonymously with non-PII as well to ensure user privacy is preserved.

The Impact

Data-driven targeting allows advertisers to make smarter decisions on who their audience is and when and how to market to them most effectively. But it’s sifting through massive amounts of data points to make the best assumptions, and then testing those assumptions, where the real magic of data-driven targeting lies.

With ever-evolving optimization algorithms and the perpetually expanding database of user information, audience targeting can only get more effective and efficient, getting advertisers closer and closer to the ultimate goal of reaching the right audience, in the right place at the right time.

 





Reader Comments.

Hi Nancy, It’s surprising you don’t mention the “recommendation power” of a customer as a crucial criteria. RFM and soft “birds of a feather get together” will remain important but the fact that a minority of influencers directly influences 20%-50% of the sales is so striking that more and more retailers use it as a segmentation tool.

Posted by Jan Van den Bergh | 10:09 pm on June 29, 2011.

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