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Measuring the Long-Term Effects Of Television Advertising

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Measuring the Long-Term Effects Of Television Advertising
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The general rule of thumb for calculating the total influence of television advertising is to multiply the short-term effect by two.

Though an average effect may be helpful for a general understanding of how advertising works, measuring and monitoring the actual long-term multiplier is critical to developing further insights.

The size of the long-term effect has a direct effect on the return an advertiser can achieve through advertising and the balance in value between all marketing vehicles.

Learning how to increase the long-term effect, therefore, will have a direct impact on how well an advertising campaign will perform now and in the future.

Scholars for decades have grappled with measuring advertising effectiveness. In the 1970s and early 1980s, they focused on lag effects, decay rates, adstock, lag coefficients, and half-lives (Spaeth and Sylvester, 2014). In the 1990s, game-changing work demonstrated that the long term is roughly equal the short term and that advertising should be valued at twice the short term (the “two-times” multiplier; Lodish, Abraham, et al., 1991; Lodish, Abraham, et al., 1995). A time-series regression model also estimated these effects (Mela, Gupta, and Lehman, 1997), which is now used widely among marketing mix modelers.

The potential of single-source data was identified, and the concept of repeat purchases and loyalty influences was developed (von Gonten and Donius, 1997; Ambach and Hess, 2000). In addition, the value of price elasticity was explored as it related to long-term effects (Ataman, Van Heerde, and Mela, 2010).

The current study leveraged single-source data to measure the exposure of television advertisements to households and their purchases across time. Using that single-source data, the researchers measured the increases in future brand spending as households were moved to trial (hereafter referred to as “Trial”) and as advertising moved households to higher levels of repeat purchasing (“Depth of Repeat”).

Consumers today have many more options for researching, understanding, and selecting brands, thanks to unlimited digital access to information and a plethora of choices. These choices surely must challenge a brand’s ability to maintain and build brand loyalty. Having the ability to track and measure the impact of advertising on long-term purchases provides insights into how large these changes are and among which customers they are taking place.

The direct effects of advertising are measured in the short term:

Advertising builds sales in the short term by increasing penetration, basket-size, and buy-rate.

Penetration is increased by attracting new customers and getting Trial.

Basket-size is increased through having existing consumers buy more each time they buy, and buy-rate is increased by having consumers purchase more often.

Basket-size is calculated by taking the total sales divided by the number of “purchase occasions.”1

Buy-rated is the increase in the number of purchase occasions.

Advertising, however, is designed to build stronger emotional and behavioral connections to consumers over time. Through these connections, advertising builds brand equity and brand value.

One way to quantify equity and brand value is through loyalty. Most advertising models show that the largest contributor to what a consumer buys is based on what he or she bought the last time (Aaker, 1995). Thus, loyalty is the largest driver of brand choice—both in the current campaign period and across future brand purchases.

Long-Term Effects of Ads on Loyalty
The key to measuring the long-term effects of advertising is to identify a measure of loyalty that discriminates among consumers based on their future dollars purchases so that they can be segmented. Then, it is possible to measure how advertising changes the size of those segments. The current study identified the key discriminating factor as “Trial and Depth of Repeat.” The depth of Repeat is a measure of a household’s brand loyalty.

This method identifies the incremental value of long-term dollar sales of moving a household into Trial or to a higher level of Depth of Repeat. The incremental value is reported as a multiplier that can be applied to the short-term sales lift measures.

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