by Nancy Smith, President & CEO

I recently purchased soccer shoes (AKA “football boots” in the UK) for my 11-year-old son.

I bring this up not because I wanted to post a photo of the garish shoe, but because my path to purchase is instructive. This shoe is part of Adidas’ Battle Pack of shoes and equipment designed specifically for the 2014 FIFA World Cup in Brazil this summer.

My 11-year-old son, Max, is a big soccer fan and player. As such, he was riveted to the TV during the UEFA Champions League final (European football’s competition to crown the best league team in Europe) on 24 May 2014. He quickly noticed that many of the players were wearing shoes with striking designs that he had never seen before. He pointed the shoes out to me, and I tried my best to mirror the same excitement that he was experiencing.  I asked him what company makes the shoe, and he wasn’t sure as these shoes looked nothing like ones he had seen before. Before long, the UEFA’s LED perimeter advertising system informed Max of the manufacturer.

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Max didn’t need the hashtag, he had all the information he needed to plead for me to buy him a pair of the Adidas shoes.

Max is constantly growing out of his shoes, and he was in need of new soccer cleats anyway, so I agreed. The next day I dutifully went online to find these Adidas shoes. I went to Google and searched for “soccer shoes champions league 2014” and clicked on some websites. On one of the sites, I was immediately served a banner advertisement for Adidas Battle Pack line of shoes:

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The banner was marginally helpful because it informed me that this line of shoes was called “battle pack” but did not otherwise persuade me to buy the shoes since the purchase decision had been made yesterday when Max saw Athletico Madrid’s Koke wearing the shoes.

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Why does my path to purchase matter? Because Adidas spent sponsorship and marketing dollars to persuade me to buy their new soccer shoes, and therefore, attributing the sale correctly means that Adidas can make better informed marketing decisions.

In the above scenario, I am certain that Adidas digital media agencies and Google would like credit for the sale. Likewise, Adidas’ player sponsorship managers would like credit for the sale. Let’s not forget the stadium perimeter display advertising managers who would like credit. In many scenarios like this, where each channel is evaluated in a silo, the CMO and CFO will receive reports from each channel claiming full dollar amount credit for the sale. When you add up all of these dollars, the business appears to be much bigger than it actually is! It is therefore critical to understand and analyze the whole ecosystem in order to accurately attribute the sales to the correct marketing bucket or buckets so that companies can make better marketing investment decisions.

One of the issues with my experience in buying the Adidas shoes is with Digital Attribution and what is known as “last-click” attribution. The common, and accurate, criticism of last-click attribution is that the final click before you buy something online gets credit for the sale despite the fact that you might have seen many other advertisements for the product before your last click. In this instance, the fact that I saw the banner before buying the shoes could be used to inaccurately attribute the sale to the banner display ad that was served to me immediately before my purchase.

In order to overcome the last-click attribution problem, many firms that conduct digital attribution analysis have come up with novel approaches with names like fractional attribution, algorithmic attribution, and probabilistic attribution. While these newer models are superior to giving all credit to the last-click, they miss the offline component of marketing that often contributes to online sales. In my Adidas example, within Digital Attribution the Google search and Banner Ads might take full credit for the shoe sale because I did indeed search and subsequently view their banner before my purchase. However, I know that the sponsorship deal that Adidas has with some world-class soccer players is actually what sold my son on their new shoe. Also, the stadium display ad played a role in informing the buying decision.

For decades, marketers have been using Marketing Mix Modeling (MMM) to evaluate marketing investments and to make budgeting decisions. Leveraging advanced analytics to capture the direct and indirect impacts of Paid, Owned and Earned media, comprehensive Marketing Mix Models provide insight into how incremental marketing is to sales (e.g. what sales can be attributed to each activity vs. sales from consumers who would have bought anyway). With companies allocating more resources to digital marketing, Marketing Mix Modeling has evolved to incorporate digital channels and more granular digital data. In the meantime, a number of digital agencies have sprouted up and they focus their analytics on the digital channels. Naturally, companies are pressed to:

(a)  Decide how much analytics time and resources to allocate between Marketing Mix Analytics and Digital Attribution, and

(b)  What to do when the different analytics provide different metrics and performance figures.

Digital Attribution has great traction in the marketplace as marketers can use the granular data to inform tactical decisions and improve the effectiveness of their digital spend. Marketing Mix retains the benefit of evaluating the offline as well as online marketing returns on investment. Marketing Mix also addresses incrementality (sales from people who purchased the product due to seeing the banner ad versus those sales from people who saw the banner ad but who would have purchased the item anyway).

In the above example, Digital Attribution would reveal the online path I took to purchase highlighting the role of Search query and the exposure to Banner Ads, but it would not capture the impact of the Sponsorship. The ideal solution is to tap the synergies created by layering Digital Attribution with a comprehensive Marketing Mix Analysis. At Analytic Partners we have developed an approach which integrates Digital Attribution with MMM. In the above Adidas example, MMM will reveal the importance of sponsorship in driving purchases in the context of the whole ecosystem. In addition, MMM will add valuable insight to the Digital Attribution purchase path learnings by capturing how incremental those exposures online are at driving purchases.

You might think that this is the end of the tale on Max’s new soccer shoes. As Max has now worn the shoes to his soccer games and practices, all of his teammates and parents have expressed surprise, wonder and sometimes polite admiration for the striking shoes. There is no doubt that the word of mouth my son’s footwear has generated will result in even more sales (and perhaps criticism) for Adidas. But word of mouth marketing is the topic of another post…

For a related post on marketing and the World Cup see FIFA World Cup Sponsorship: Is it Worth It?