Inside Adwords: Diving into Google’s Data-Driven Attribution Model
Consumers often click on multiple ads before making a purchase or taking action, but many commonly used attribution models give credit entirely to the last click. This poses a challenge because the highest-performing paid search keywords eventually hit a threshold of eligible impressions and “max out.” For this reason, it is essential for advertisers to take a look at all of the clicks leading up to a conversion to understand which ones drive success.
In May 2016, Google AdWords shook things up by introducing data-driven attribution (DDA), which uses machine learning technology to calculate the contribution of each search ad click along the conversion path so that advertisers can invest more in the clicks that feed their businesses.
Because it opens up wider visibility into performance drivers in an actionable way, DDA has recently become Google's recommended attribution model. After studying its impact for over a year, Google has concluded that advertising performance really does improve significantly when using DDA over last-click attribution.
How Does Data-Driven Attribution Work?
Using Google's machine learning technology, data-driven attribution calculates and assigns credit to each click that contributes to a conversion. It determines which ads, keywords, and campaigns have the most impact on converting customers so advertisers can adjust spend accordingly. By crediting top-of-funnel search marketing, marketers have insight into which efforts drive results and can maximize return on AdWords investment.
In some cases, DDA has delivered a 60% increase in conversions at the same cost-per-conversion and a 36% increase in conversions at a lower cost-per-conversion.
Who Should Use DDA?
AdWords requires a certain amount of data to create a precise model. Marketers whose accounts have reached the minimum number of required clicks and conversions in the past 30 days (generally 15,000 clicks and 600 conversions) are best able to take advantage of DDA.
DDA can be especially beneficial to marketers advertising products and services with a longer or more complex consideration phase, such as expensive one-time purchases like life insurance policies. A longer path to purchase is evident when customers have a relatively high number of clicks on various keywords before making a purchase.
If you are interested in learning more about how using DDA can help optimize the performance of your campaigns, reach out to Rise for more information.