A narrower definition of the TRP could provide a panacea for advertisers and agencies that are hard-pressed to increase budgets to match the price increases media owners have introduced in the current upfront marketplace. Better-defined TRPs will drive business outcomes more cost-effectively.

CBS and Nielsen have found that advertisements reaching a high concentration of consumers who purchase specific product categories have a significantly higher correlation with sales outcomes. Thus, advertisers facing budgetary constraints could benefit by using better-defined TRPs in their media negotiations.

By contrast, advertisers that continue to focus on broadly defined GRPs reaching audiences outside of their targets may only satisfy general awareness outcomes among audiences ill suited to becoming good customers. Advertisers who pour their media budget into better-defined, TRP-focused inventory will reduce waste. The corollary to this is that, when an advertiserb?s goal is increased product sales, buying GRPs without a narrow target produces significant waste.

Several steps are required to shift to more narrowly defined TRPs as a core media negotiation focus. Many of these steps were impossible to accomplish until recent advances in data collection and processing. They include:

• Aggregation of sales data, which may come from a syndicated data provider or a retailer
• Aggregation of granular viewing data, using either respondent-level or set-top box-based data sets
• Identification of best- fit statistical models correlating audiences and sales data
• Development of predictive algorithms which identify future audience behaviors
• Negotiation of units of inventory which over-index against those target audiences

Buyers and media directors alike know that the traditional response to increases in the price of media is to downgrade the mix of programming on a media plan, using less network inventory and more run-of-schedule cable inventory. Clearly, using better-targeted TRPs is superior at both a tactical and strategic level, although it will inevitably require different competencies, technology providers and ad sales models. But advertisers looking to manage against the very real constraints they face will work to make this model happen and significantly improve the efficiency of their media budgets as a result.

Elasticity is a measure of responsiveness. In the realm of television promotion, program elasticity is the ratio of marginal increase in viewers to the marginal increase in promotional effort*:

It tells us the increase in ratings to be expected for each gross rating point (GRP) increase in promotional exposure.

The measure of promotional elasticity may vary between different programs, as well as within the same program depending on the stage of its life cycle. For example, it is certainly possible to drive additional viewers to American Idol, a mature program with an established core audience.B It would have been easier to do so, however,B during the show’s nascent stages at the beginning of the decade. Some other factors that influence program elasticity are day part, month, cast, and theme.

We examined elasticity in practice by looking at promotion level and corresponding program rating for the first several weeks of Kendra, a recently-launched E! reality series.

From this data we can estimate promotional elasticity as a coefficient of linear regression, where the dependent variable is the programbs average reach and the independent variable is the amount of promotional effort. The coefficient of elasticity went from 0.01 in June down to 0.004 in July, indicating that in order to add 1 unit of average reach we would need an additional 100 GRPbs of promotional exposure in June and 250 GRPbs one month later.B The graph below illustrates that the promotional efforts for Kendra were appropriately curbed down from week to week, responding to the reduction in promotional elasticity.

Network marketing departments have heuristic models for estimating a programbs promotional elasticity (see this amusing example from ABC). B They rely on their professional wisdom and marketing smarts to estimate the effort required to entice enough viewers to various programs.B It is open to investigation whether such heuristic approaches are on par with explicit modeling of program elasticity using statistical methods.

An accurate estimation of elasticity is critical for a cost-effective optimizing of promotions. For example, programs with elasticity close to zero are not susceptible to program promotion, and marketers should be cognizant of that information when designing their promotional plans.

For future research, we could examine program elasticity in the context of audience segments. Different audience segments might require different amounts of promotion to make them tune in to a program. The logical step then would be reducing frequency of promos in the spots with large relative concentrations of bhigh elasticityb segments.

*Aiyer, J. P., and J. Rajgopal, “Managing Cable TV Commercial Inventories via Program Promotion,” Marketing Intelligence and Planning, Vol. 19, No. 1, pp. 45-54, 2001.