Measure Early and Often to Improve Ad Campaign Results

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Measure Early and Often to Improve Ad Campaign Results

By Jennifer Pelino - 08/01/2018
Measure Early and Often to Improve Ad Campaign Results Personalization IRI
Ecommerce has added a new dynamic as retailers and agencies attempt to measure advertising performance

This is the fifth and final article on applying personalization strategies to generate increased revenue and shopper loyalty. Here, we review the potential of artificial intelligence (AI) to optimize the impact of planning, targeting, activation and measurement strategies discussed in the first four articles. You can read part one herepart two here and part three here.)

“Measure what is measureable and make measureable what is not,” was advice from Galileo that is as true today as when he wrote it. To achieve the precision necessary to maximize the potential of personalization, retailers and their agencies must build measurement into every facet of a campaign. Did you know that marketers who invest more than 10 percent on sales measurement are three times more likely to beat their sales targets by as much as 25 percent?

In the first three articles of this series on personalizing the retail experience, I’ve focused on approaches for creating effective planning, more precise targeting and increased shopper activation. In this article, I will debunk a few long-held myths about campaign measurement and share several best practices.

There are many misconceptions about when measurement should take place, what it should measure and which types of measurement are most effective. The three most salient myths that deserve refutation are:

  • It’s an end-of-campaign activity
  • It’s focused primarily on how many clicks are earned or coupons redeemed
  • Advertisers can’t link campaign results with actual sales

Today’s Landscape Challenges Retailers

Consumers expect a much higher degree of personal attention than they’ve received in the past. Forrester’s recent “State of the Consumer” report notes that 72 percent of consumers expect companies to understand their unique needs, and 70 percent say that this understanding affects their brand loyalty. Further, consumers’ wants and needs are always changing, meaning that retailers are attempting to personalize campaigns focusing on moving targets.

On the retailer and agency side of the equation, omnichannel campaigns have added complexity to the measurement function. When a consumer makes a purchase online, is it based on an online ad or a print ad, or even an ad she saw in a movie theater or on the bus home?

Retailers and agencies know that they need to measure better. One proof point: Venture capital investment in ad measurement companies is growing despite the fact that investment in other advertising technologies is drying up.

With digital ad spending surpassing TV for the first time in 2017, c-level management teams at retailers are demanding more sophisticated measurement and continuously improving return on ad spend (ROAS).

Adding to this challenge is the growth of ecommerce. Some examples of the ecommerce dynamic are the consumer behaviors known as “showrooming” and “webrooming.” Showrooming consumers research products in-store and then purchase them online. Shoppers who webroom do the opposite – research products online and then buy them in-store. How does a retailer measure the effectiveness of a campaign against these behaviors? It might succeed in driving the shopper to the store, but is that success if the shopper then returns home to buy the product online, potentially from another retailer?

Clearly, advertisers and agencies need much more sophisticated approaches to measuring campaigns to achieve the levels of personalization that they’re promising shoppers.

Consumers’ wants and needs are always changing, meaning that retailers are attempting to personalize campaigns focusing on moving targets.

the Key to Unlocking Effective Personalization

To optimize campaigns, advertisers and agencies must measure every activity involved in the campaign, not simply the final ROAS after the campaign is over. For example, as noted in the first article in this series, advertisers must evaluate the quality of the data on which they will build the campaign in the initial planning phase. Then they need to find out whether the data provider passively or actively collected the data from consumers.

It’s also important to measure accurately and to compare the retailer’s campaign to other relevant information. One approach includes measuring the retailer’s campaign against rest of market (ROM). In this scenario, a retailer can compare its lift versus that of rest of market, as well as national lift, to determine consolidated campaign results. Measuring campaign by device type as well as omnichannel provides additional insights.

Speed when measuring campaigns has also become invaluable. As noted in the third article in this series, in-flight optimization (IFO) is based on the ability to measure each discipline within a campaign, such as message or media, and make adjustments in as little as four to five weeks. IFO can boost sales uplift by 20 percent or more when executed aggressively.

A recent innovation in measurement is unifying two well-known approaches that provide complementary information: marketing mix modeling and attribution. This concept, known as Unified Marketing Measurement, can be defined as blending statistical techniques that assign business value to each element of the marketing mix at both a strategic and a tactical level.

Research conducted by IRI and Forrester/Burtch Works has revealed that just 45 percent of marketers employ marketing mix modeling techniques and 42 percent work with attribution modeling. As a result, there’s a significant upside opportunity for retail marketers to improve campaign performance through unified measurement.

Marketing mix modeling informs high-level strategic decisions within marketing planning across different tactics that show the best return on investment. It answers key questions such as “What is the right level of investment across brands to achieve my portfolio objective?”

Attribution modeling is a bottom-up approach at the individual user or household level that enables the decomposition of individual marketing tactics within a given campaign. Attribution solutions answer key questions such as “What campaign message is most likely to activate this targeted set of households?”

Unifying marketing mix and attribution solutions can provide retailers the end-to-end insight to make strategic and tactical decisions through a single solution and with one set of facts so that retailers and agencies work from a “single version of the truth.” It achieves this through four performance cornerstones:

  • Accuracy: Unified measurement provides highly accurate and precise results, informed by store-level observations and highly personalized shopping behavior.
  • Speed: It offers quick measurement results – within as little as five weeks of campaign launch – and on-the-fly audience creation.
  • Granularity: Deeper, more precise and granular views, enabled by the number of households captured paid with casual, POS and panel data sets, are another advantage of unified measurement.
  • Ongoing Course Correction: Unified measurement offers advanced simulation and reporting capabilities to report results across multiple levels of a retail marketer’s decision hierarchy.

In an environment where nine out of 10 new products fail, negatively affecting a retailer’s revenues and suboptimizing use of shelf space, enhanced measurement executed throughout the ad campaign process can provide the critical information necessary for retailers, along with their brand partners, to increase new product success and achieve a win-win for retailer and brand alike.

About the Author

Jennifer Pelino

Jennifer Pelino

Jennifer Pelino is SVP, omnichannel media at Chicago-based Information Resources Inc. (IRI). Read More

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