Data Is Everywhere -- But For Sponsorship, It Isn't Enough

In the age of a crazy granular digital media world, things are lacking when it comes to sponsorship measurement -- specifically, no standardized method for evaluating the return on those investments.

Recent ANA research found that only 37% of respondents reported having a standardized process for measuring their return on sponsorship.

Sounds strange. But here’s what is worse: Marketers are in the dark when it comes to comparing sponsorship spending versus impressions of buying paid media.

Sponsorship sales executives might tell you not to worry, and they may show you some specifics: a lift in website visits, social media activity around the sponsorship, including likes, and possibly some foot traffic in stores.

On TV, a sponsorship may include an on-screen billboard of an automaker or smart fitness watch advertiser right after an ad and right before a return to some sports action. It seems like big value. Maybe there are some results.



But in this digital data world, it is neither granular nor standardize enough. Can you repeat the same thing for the advertiser -- or perhaps for their competitor?

There is a need for “more sophisticated sponsorship measurement and valuation practices,” says Tony Pace, president and CEO of Marketing Accountability Standards Board.

Should we be surprised?

Sarah Jane Kelly, executive director of Sports Analytics, believes sponsorship measurement should replicate how futures contracts are valued. This can be achieved by constructing an index.

That index, she says, should include social media mentions, brand prominence (based on third-party surveys), sales and advertising spending, and data from the sport being sponsored. The total should be turned into a single number that can be compared against a benchmark, to assess how a particular sponsorship is doing.

The ANA study says sponsorships are up 22% since 2013 -- now totaling $24.2 billion in 2018. An IEG study says there was $62.80 billion spent of sports sponsorship on a worldwide basis in 2017.

We are passed the days of just buying in -- even when something is working. We need to know why -- and that's where all those data details come in.

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