![]() ![]() That Slack group where someone recommended your product? Also unattributable. That LinkedIn post that didn’t link to your website? Unattributable. ![]() That podcast that had your CEO as a guest? Unattributable. In other words, any offline touchpoints, dark social, and impressions are entirely left out of most models. The reason why attribution fails to account for many of the touchpoints along the customer journey is that attribution models typically measure clicks, and clicks alone. Attribution measures clicks-and clicks alone What should you do with the data you’re collecting, then? Well, we’ll get to that later. And as a result, you might end up making some pretty terrible decisions that ignore the most important (?) 30% of your customer journey. The problem with this argument is that no matter how you slice it, you’ll end up overvaluing the channels you can, in fact, measure. Sidebar: The proponents of multi-touch attribution would argue here that collecting data about 70% of customer touchpoints is better than collecting 0% of that data. In fact, the death of the cookie and the introduction of iOS 14 actually mean that the number of trackable touchpoints is declining, making attribution even more difficult. And for legal, ethical, and technical reasons, we’ll never be able to either. We simply never were able to track every person’s every impression and click. The problem is, that promise was made in bad faith. Let’s start with the biggest issue: multi-touch attribution is built on a false promise that every single touchpoint on every single device is trackable. Let’s look at some of the reasons why attribution modeling often fails on its promise. However, the keyword here is ‘theoretically’. Theoretically, attribution models should help marketers allocate their budgets more effectively to the channels, campaigns, and activities that have the largest impact on revenue. On paper, the promise of attribution modeling is attractive: it helps marketers dissect the customer journey and understand how each touchpoint contributes to a sale. Position-based attribution: the first and last touchpoints contribute to revenue more than the touchpoints in the middle of the customer journey.Time-decay attribution: more recent touchpoints along the customer journey contribute to revenue more than earlier touchpoints.Linear attribution: each (trackable) touchpoint along the customer journey has equal revenue contribution.This is done to estimate the revenue contribution of marketing.Ĭommon multi-touch attribution models include: What is attribution modeling?Īttribution modeling is the process of setting rules that determine how much each touchpoint along the customer journey contributes to a sale. Most marketing teams have some kind of data problem.Įither they don’t have enough data, they have too much of it, or most commonly, they don’t know what to do with it.Īnd that’s why in this post, we’ll evaluate two of the most common ways businesses are currently putting their marketing data to work: attribution modeling and marketing mix modeling. ![]()
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