Monday, November 12, 2007

TiVo to the Rescue?

Hot on the heals of the Google/Nielsen partnership, TiVo has entered the measurement fray with its announcement that it will begin providing advertisers with data on the viewing (and skipping) habits of consumers using TiVo’s panel of 20,000 set-top boxes. This has the potential to be far more illuminating than the Nielsen data as TiVo can provide insight into who is skipping ads (both on the demographic/lifestyle segment level and on the individual-addressable level) and which ones they are skipping. The result could be a wealth of information on ad performance, sliced and diced on many dimensions.

Even more interesting, TiVo will offer advertisers the ability to learn (on a blind basis) the viewing habits of their actual customers. By providing TiVo with a customer file, marketers can get insight into exactly how many (and which types) of customers are skipping their ads, which should help both fine-tune message execution and enhance negotiations with networks.

TiVo still can’t tell us who is watching the ads – only who isn’t. But with its jump on the interactive feature options, TiVo may be faster to offer advertisers the back-end direct response element of the engagement chain.

This is a promising frontier for advertisers seeking to understand the actual payback of their advertising investments. It’s not in itself a magic bullet, but another step forward in getting the objective insight we need to draw credible conclusions.


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Monday, November 05, 2007

Google to Dominate Dashboards?

Having conquered the worlds of web search and analytics, is Google about to corner the market on marketing dashboards?

Hardly.

What Google is doing is coordinating online ad display data with offline (TV) ad exposures. Google is partnering with Nielsen to take data directly from Nielsen’s set-top-box panel of 3,000 households nationwide and mash it up with Google analytics data to find correlations between on- and off-line exposure. The premise is, I’m sure, to help marketers integrate this data with their own sales information and find statistical correlation between the two as a means of assessing the impact of the advertising at a high level. By using data only from the set-top box, Google is able to present offline ad exposure data with the same certainty as it does online – e.g., we know that this ad was actually shown. Unfortunately, we don’t know if the ad (online or off) was actually seen, never mind absorbed.

However, with the evolution of interactive features in set-top boxes, it won’t be long before we begin to get sample data of people “clicking” on TV ads, much like we do online ads. So we’ll get the front end of the engagement spectrum (shown) and the back end (responded). But we won’t get anything from the middle to give us any diagnostic or predictive insights to enhance the performance of our marketing campaigns.

A full marketing dashboard integrates far more than just enhanced ratings data and looks deeper than just summary correlations between ads shown and sales to dissect the actual cause of sales. Presuming that sales were driven by advertising in the Google dashboard model would potentially ignore the influence of a great many other variables like trade promotions, channel incentives, and sales force initiatives.

Drawing conclusions about advertising’s effect solely on the basis of looking at sales and ratings would quickly undermine the credibility of the marketing organization. So while the Google dashboard may be a welcome enhancement, it’s not by any stretch a panacea for measuring marketing effectiveness.

It seems to me that Google has created better tools. But through their lens of selling advertising, they’re perpetuating a few big mistakes.