Commentary

Q&A: Marketing Attribution's Role In Demystifying Television Conversions

Although they’re still a work in progress, the rapid, granular ad performance metrics available in digital media have unquestionably raised the accountability stakes for television, and all traditional media.

One result has been the emergence of new independent media or marketing attribution companies. Alison Lohse, co-founder and COO of one such ad tech firm, Conversion Logic, shared some thoughts about the roles of attribution platforms in the shifting television metrics landscape with Audience Buying Insider.

How would you describe traditional television metrics?
Until relatively recently, marketers had two options for measuring impact: audience reach for brand advertising or 800# conversions for direct response advertising. Both provide some data to help gauge the effectiveness of advertising spending, but both also leave a lot of holes, requiring guesswork. 

In terms of reach, the industry has long been aware of the limitations of relying on panel measurement to report on how many people tune in. The single, often inaccurate data point has been how many viewers may or may not have seen the ad, depending on whether they were actually watching, got up to get a snack, or changed the channel.

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The advent of the DVR and other technologies designed to circumvent ads has made reach even more challenging as a metric. And even when it works, reach measures a value that’s several steps removed from measuring conversions to sales, or other desired customer behaviors. Television advertising is indisputably effective, but it’s notoriously hard to measure how exposure translates to sales — and almost impossible to say which ad, on what date, on what channel, during which show, led to a specific conversion or other action.

In contrast, measuring the impact of direct response TV ads, or infomercials, used to be a clear-cut matter of counting the direct sales generated by driving people to an 800 number.

But the Internet immediately altered that paradigm. Now, even if you manage to get people to watch some of an infomercial, amid the myriad screens competing for their attention, the touchpoints to conversion have multiplied. A consumer may now watch five minutes of a 30-minute infomercial, check out the company’s Web site a few days later, and make the purchase via smartphone the following weekend.

In any scenario, brand or direct response, the impact of TV on sales has become increasingly hard to measure accurately.

But marketers and agencies are impatient with excuses like “the paths to purchase have become more complex.” They want greater accountability now.
Marketing executives now expect data and insights from TV advertising to match the level of detail and precision delivered by digital campaigns. Television no longer has “permission” to be a nebulous, high-funnel tactic. And with today’s big data, innovative technology and cross-channel modeling, there’s no reason that TV can’t be as accountable as its digital counterparts.

In general terms, how do marketing attribution platforms attempt to address these demands for precise, timely metrics?
Today’s technology uses complex data science to determine the correlation between exposure and purchase. Drawing from digital, time series, decay rate and residual effect models, attribution solutions go beyond media-mix modeling to show proven interaction effects between and across all marketing channels employed.

The methodologies and processes are complicated, but the results are straightforward.

Attribution puts new metrics around old media, including channel-on-channel lift; cross-channel exposure; customer journey insights; attributed performance by channel; overall conversion lift; short- and long-term TV spot impact; time- and creative-based analyses; and baseline definition for improved model learning and crediting.

In a nutshell, attribution provides the granularity and the filters to easily understand what’s working in television, where, and for how long, so that marketers can use that information to further improve results. 

3 comments about "Q&A: Marketing Attribution's Role In Demystifying Television Conversions".
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  1. Ed Papazian from Media Dynamics Inc, July 22, 2016 at 12:25 p.m.

    All very nice in theory but how do you apply these methods to "linear TV" when you don''t have viewer by viewer audience or sales response data? Even assuming that the only metric that counts for a branding campaign is whether the targeted viewer ran out and bought your product---what, the same night, the next day, a week later, a month later. etc.--how do you you account for the many interacting variables? What data is employed? Or are we really talking about a research panel operation where "viewing" is interfaced with purchase?

    I have seen numerous attempts to correlate TV household set usage data with UPC scanner data on product purchase from the same homes. Such investigations are nothing new and they show that TV advertising, like most advertising, works. However, when they tried to evaluate specific components of a TV campaign---like brands using more or less primetime, relative to other daypart mixes, the findings were often inconclusive. Obviously, breaking it down on a show by show basis would be even more problematical----or have we found a solution that allows us to definitively isolate the effect of every ad exposure?

    I am not against the core idea, but I would like to see an explanation of how it would actually work  for an ongoing "linear TV' ad campaign.

  2. Robert Barrows from R.M. Barrows, Inc. Advertising & Public Relations, July 22, 2016 at 5:58 p.m.

    The best way to measure the effectiveness of any kind of advertising is with some advertising math called “The Barrows Popularity Factor.” It shows you how you can actually QUANTIFY the relationship between your advertising and sales and it can help your company make a lot more money. Plus, the math is extremely easy to use and all of the calculations can be done by one person, in moments, with just a simple calculator. You can read all about it in a booklet called “The Barrows Popularity Factor.”


     

  3. Haren Ghosh from Analytic Mix Inc., July 29, 2016 at 1:56 a.m.

    “Today’s technology uses complex data science to determine the correlation between exposure and purchase. Drawing from digital, time series, decay rate and residual effect models, attribution solutions go beyond media-mix modeling to show proven interaction effects between and across all marketing channels employed” – this summarizes the true innovation in the TV ROI measurement arena. This is not a dream any more, there are few companies in the market (including ours, Analytics Mix Inc.) that are executing this approach across media channels, and providing buying recommendations by shows, dayparts, syndications, and local-national splits.

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