What Is an Attribution Model? Last-Click vs Data-Driven, and Which Is Right for Your Business

In a world where customers see your brand on Facebook, Google, TikTok and LINE before they buy, one question is often overlooked: “Which channel should get credit for this sale?” The answer depends on the attribution model you use, and choosing the wrong one could lead you to cut the very channel that generates the most sales for your business.

Last-click attribution gives all the credit for a sale to the final touchpoint before purchase. For example, if a customer's last action before ordering was clicking a Facebook ad, the whole sale is credited to Facebook Ads, even if that customer had seen Google or TikTok ads earlier. This model is popular because it's easy to understand and is the default on most ad platforms.

The main problem is that last-click ignores the channels that build awareness and consideration early in the customer journey, such as TikTok ads that introduce people to your brand, or Google Display ads that remind them several times. They may not be the last click, but they play an important role in closing the sale. If you cut these channels because they don't seem to generate sales, you may lose the awareness that feeds your entire funnel.

Data-driven attribution uses machine learning to analyse every touchpoint in real customer journeys and calculate how much each one influences the purchase decision, by comparing paths that lead to a purchase with paths that don't. The resulting credit weights reflect real behaviour better than fixed rules. Google Ads and Meta have both made DDA the default in many accounts, but the model needs enough conversion data to be accurate.

As individual user tracking becomes harder under privacy policies, MMM has made a comeback. It uses aggregate data, such as weekly ad spend, weekly sales, seasonality and external factors, to build a statistical model of how much each channel affects sales, without relying on cookies or the Pixel at all. It suits businesses with large ad budgets that want a long-term view.

• Last-click suits small businesses that want simple measurement
• Data-driven attribution suits businesses with enough conversions (generally in the hundreds per month or more)
• MMM suits high-budget businesses that want to plan budgets at a big-picture, long-term level
• No model is 100% right. The best approach is to use several models to inform decisions instead of relying on a single number.

The Markettung team usually recommends that clients start with the data-driven attribution already built into their ad platforms, alongside periodic incrementality tests, to confirm that the numbers on the dashboard reflect real sales growth and not just credit that looks good on paper.