Everybody knows what they’re doing isn’t right, but they’re not exactly sure how to make it better
julia di clemente, Neo@Ogilvy
Marketers in the U.K. and U.S. are increasingly recognizing the advantages of algorithmic attribution, but Canadian organizations have been slow to follow.
According to a recent study by Forrester Consulting and Visual IQ, three quarters of marketing decision markers in the U.S. and U.K. use algorithmic attribution-informed insights to develop more precise reach, 71% are using it to target more effectively and 67% are using it to better allocate their budgets between search and display.
As opposed to a last-touch attribution model, which credits a user’s ultimate conversion to the last touch point with a brand, algorithmic attribution uses precise modelling to acknowledge all elements of the customer journey.
So while the older method would note that a customer clicked on an online coupon before making a purchase and ascribe all value for the transaction to that single action, the algorithmic model assigns value to, say, the promo webpage they visited at length before that and the initial display ad that brought them there.
“What this technology is meant to do is give credit to items that occur on that same user path, so advertisers are better able to understand what collective steps helped lead to the consumer action, versus only focusing on the very last thing they did,” said Julia Di Clemente, managing director of Neo@Ogilvy Canada.
“The last click was a one-size-fits-all model when it came out, but now this weighing of different points differently becomes incredibly valuable, because it allows every advertiser to ultimately have their own custom solution versus this blanket solution,” said Di Clemente. “It will probably give a greater sales pitch for things like video and homepage takeovers that typically are not the last thing that a user does before they convert, but it influences them a lot, because they’re more awareness-focused.”
This newer method uses sophisticated statistical models that can be customized for each individual campaign, while improving daily channel optimization. Algorithmic attribution can not only help advertisers better understand the customer journey and focus their spending more effectively, but may also provide some much-needed relief to the publishing community.
“It’s win-win,” said Di Clemente, “because it allows advertisers to get a better idea of how users are engaging with their messaging, and its also great for publishers because publishers for the first time are able to vocalize their value in a world that was previously very narrow minded.”
While advertisers in the U.S. and U.K. are relying more heavily on algorithmic attribution, however, Di Clemente fears Canadian publishers are still relying on old methods.
“There are a lot of Canadian advertisers that are still relying on last-click attribution,” she said. “That is interesting, because everybody knows what they’re doing isn’t right, but they’re not exactly sure how to make it better.”
Some of the main barriers to entry for Canadian marketers, according to Di Clemente, include the cost of adoption as well as a lack of education and understanding.
“I think it’s an incredibly valuable technology, so that education is critical, and that needs to come from the decision makers,” she said.
