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The Four Biggest Upside Advertising Attribution Opportunities in 2018

Author: SMI Team

Here at SMI, we believe that the most important conversation in the advertising industry is around advertising effectiveness, and ROI attribution. As the need to justify marketing and advertising budgets becomes critical – the need to truly understand how effective specific ads and media mixes are, becomes even more critical.

With technological advances and attribution solutions being heralded from some of the biggest, and best, companies in the world, it seems like a question we as an industry should have already been able to answer quite concretely. Of course, finding real attribution is easier said than done. The consumer herself is exposed to hundreds of stimuli each day and has no idea which ones lead to which buying decisions. What we are attempting to measure has its roots in undiscovered parts of human psychology. But, we are making real advancements, many of which SMI is proud to be leading.

From moving the conversation away from just one method, albeit one that helped move the branding part of the industry into ROI in the first place, marketing mix modelling, to expanding models into Multi-Touch Attribution and hybrid methods, way beyond only measuring CPG companies, and a re-focus on single-source that started with TRA, the attribution community is at an interesting crossroads.

To get an even better sense of the advancements in attribution we’ve made in 2017, and the upside opportunities moving into 2018, we sat down with SMI advisor, founder of TRA, and creator of the first automated MMM system back in the 20th Century, Bill Harvey, who shared his top four attribution advancements he’s most excited about.


As Bill notes, even the most sophisticated models are going to give bad results without the actual data. The best estimates are going to give you inflated, or deflated numbers and distorted relationships. And, can get you going in the wrong direction. Precision is important within attribution – a few percentage points here, or there, can make all the difference from finding what’s working. This is one is of course close to SMI’s heart – we believe actual spend data is not only important, but the only way to come up with accurate information. With the ability to now input real costs into attribution models, we’re seeing more in-depth information and clear-cut, accurate and actionable results.


When folks like David Poltrack made a stand, and demanded the industry make marketing mix modelling transparent, and clean up the media data used, many companies responded. However, at the time, MMM was based on manual, analyst led decisions. Out of many models with equal statistical goodness the analyst would pick the one he or she felt to be the most likely. Bill notes that this worked for a long time, providing an ROI framework for advertisers to use in making the decisions about the largest chunks of budget going into specific media types. However as the process has matured the next opportunity is to be able to syndicate continuous fully-automated reports minimized the use of analyst subjective judgement, on all brands that compete against one another, rather than the periodic slow, and narrow, one-off views of just one’s own brand.


Some might argue that you can do some of the above already – and you’d be partially right if you were talking about just looking at your own data. Companies have their own spend data, and know enough about their company, to set up automated reporting. But, as Bill argues, what good is that if you can’t benchmark that against your competitors. If your studies are showing an increase in sales based on advertising efforts, you might want to stop there – it seems things are working. But, what if your competitors have increased sales 50% more than you have, based on a different advertising mix. That’s something you need to know. With a view into what your competitors are doing and how it is working – against your own brand – you can learn from the mistakes and the successes of your competitors, not just your own. This is another point in which we believe strongly. Our mission is to bring clarity to the advertising industry – and we’ve been working hard, in partnership with other best-in-class data providers, to develop competitive attribution capabilities. We believe, it’s one of the key movements that needs to happen within attribution. And of course, it’s vital to do this across both digital and traditional media.


Bill shares that one of the least discussed, but most important, issues in current attribution models are assumptions made about the decay curve in time related effects. For example, some models use a curve which says after 48 hours most of the effect of an ad has worn off. In reality, Bill says, this is likely not true for all ads in all media, and needs more empirical studies and methodology behind it. By now everyone knows that last-touch attribution is naïve, yet the attribution of credit toward making a sale is still most distributed based on the proximity to the purchase event, even though the very first ad the person saw may have set their foot on the path to that purchase of that brand with more impact than any subsequent exposure. This is one area where Bill believes were on the cusp of a breakthrough, and close to identifying a more accurate decay curve, that could change how we look at attribution models. He sees this as a key opportunity as we move into 2018.

These are just a few of the significant changes happening as conversations around attribution only heat up. And, it will continue to be an evolving industry, but Bill, as well as all of us at SMI, believe we’re in the middle of some exciting discoveries, and are thrilled to be a part of what’s next. To join the discussion, and learn even more about what SMI is doing with partners like Analytic Partners and Alphonso, come join in with us at the Attribution Accelerator conference on Thursday, October 12.

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