2023 is a tough year for marketing managers. The economic slowdown has dictated that many of us cut our budgets. This was also the case for Expondo, who had to lower its social ad budget by 40%.
Expondo is a leading retailer in the domain of professional gastronomy and is active across 19 countries.
Expondo uses more than 80 different ads channels which makes marketing attribution quite challenging, but it was especially challenging for Expondo to properly evaluate top of funnel campaigns like Facebook display ads.
The challenge of top of funnel ad evaluation
Evaluating top of the funnel is often a challenge. There are typically 2 options:
- blinding trust in the data from the walled gardens like Facebook
- rely on click attribution models
None of these options is good. Let’s take a simple example: a prospect sees a carousel ad on Facebook and browses it, one day later he googles the name of the shop and makes a purchase.
If you look at a click-based attribution model, this conversion will be 100% credited to organic.
On the other hand, the interaction with the Facebook ads didn’t lead to a click toward the website, so it cannot be accounted for in attribution.
This is a common issue with the click-based attribution model; they aren’t able to account for interactions outside of the website. Click-based attribution models will therefore tend to underestimate conversion from social ads like Facebook.
Alternatively, you can rely on conversion data from Facebook. Deploy a Facebook pixel on your website. Facebook will claim conversion for anybody who interacted with Facebook ads even if the interaction didn’t result in a website visit. So, data from Facebook pixels tends to overestimate conversions.
None of the 2 attribution methods gives accurate views. This makes evaluating the ROI of an ad campaign really challenging. This is especially true for top –of funnel campaigns as those display and video ads do not usually aim at generating clicks and will be widely underestimated by click-based attribution.
Synthetic impressions: A true “game changer”
That is where ROIVENUE Synthetic touch comes into play. ROIVENUE aggregates data conversion from Google Analytics with data from Facebook and other walled gardens. ROIVENUE then works with time stamps of conversion in each data source to build an attribution model.
This was a “game changer” for Expondo as it allowed them to get a full picture of ad performance. This attribution model shows that Facebook ads were more effective than what click-based attribution reported. Depending on the country, the cost of sales was from 7% to 73% better than previously reported.
These insights didn’t only help Expondo to make informed decisions about the budget cut, it showed them that Facebook ads were highly profitable for some markets. This helped the Expondo Marketing team to build a business case to expand the Facebook channel. Expondo is now planning to run some test campaigns to scale up Facebook ads. ROIVENUE Synthetic touch will be used as a base line to evaluate those test campaigns.
It took only 2 weeks for Roivenue to reassess their marketing budget. ROIVENUE Synthetic Touch is leveraging data from 3rd party tracking tools like Facebook pixel, which makes the deployment really easy:
- ROIVENUE Synthetic Touch doesn’t require deploying new code on the website. The tool is collecting the data directly from existing tags
- It is possible to work with historical data. As soon as you set up Synthetic Touch you can start digging into attribution. There’s no need to wait for collecting new data.
ROIVENUE Synthetic Touch in short
ROIVENUE Synthetic Touch is a game changer when it comes to walled garden attribution. It allows going beyond click-based attribution. In Expondo’s case, it showed the cost of sales on Facebook was up to 73% better than previously reported.
ROIVENUE Synthetic Touch is fast to deploy as it relies on existing tracking tags and can work from historical data.
We needed to cut the upper-funnel campaigns. Now that we have access to impression data with ROIVENUE we can see that Facebook is actually more efficient and we can re-evaluate the budget for the end of the year. This is somewhat of a game-changer. There are no other tools that offer such analytics.