But you can apply the same approach to revenue attribution. Here at Optimove, we usually use the term incrementality when discussing the real impact of campaigns, as opposed to measuring vanity metrics like opens and clicks. We call it “Incrementality,” and it’s based on the good ol‘ test and control measurement. and that measures itself against the baseline behavior of your customers (i.e., doesn’t take credit for purchases that would have happened anyway, even without these campaigns)? Multi-touch attribution models are based on assigning “weights” (credit) to touchpoints in proportion to their impact on outcomes for example, 20% of the credit goes to email campaigns, 30% to Facebook ads, etc.īut the problem is that assigning attribution weights can be error-prone, as identifying the touchpoints that have the most impact on conversions is challenging.Īnd so, what if we told you there’s a better way to go about it? One that accurately measures the impact of each touch point and the aggregate impact of the entire journey that doesn’t require assigning weights that is continuously updating itself to reflect changes in customer behavior, campaign fatigue, seasonality, etc. But what if the customer made a purchase after being targeted for 3 months with emails, SMSs, Google and Facebook ads, and mobile push notifications – and was influenced by all the content and promotions sent to him/her/them? How can you give all the credit for the purchase just to the last campaign? Incrementality, my dear WatsonĪ more sophisticated approach would be to measure each campaign’s relative and combined impact, using a multi-touch attribution model.
In the last-touch attribution model, 100% of the credit for the purchase goes to the final touchpoint before a prospect converts. But think about it: can you really attribute the purchase to the first campaign and completely dismiss the campaigns that follow it? Of course not. In the first-touch attribution model, 100% of the credit for the purchase goes to the campaign that drove the customer to come in contact with your brand. First-touch and last-touch attribution are the simplest and least accurate models. Several models try to help marketers get it right, but they all have their share of deficiencies. The main question of revenue attribution is how do you accurately measure each campaign’s and touchpoint’s relative impact on customer behavior? Getting the answer wrong – i.e., attributing outcomes to the wrong campaigns or touchpoints – is a dangerous proposition, as the ultimate goal is to optimize your marketing spend and campaign setup. Unfortunately, attribution errors are something marketers know all too well, especially when dealing with one of marketing’s toughest challenges: revenue attribution. According to Heider’s theory, all people are naïve psychologists who try to find the causes behind actions and behaviors, and we are all susceptible to making errors in judgment when trying to attribute outcomes. It began in 1958 when Fritz Heider, an Austrian psychologist, published a book called “The Psychology of Interpersonal Relations,” which included the first attribution theory. The study of attributions is relatively young.
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