It goes without saying, that measurement is only as good as the data it’s based on. Marketers use metrics daily to demonstrate success and quantify the results of our campaigns. We do so to make informed decisions and choose how and where to invest our dollars. But how can we be assured the figures we use are correct?

Marketers traditionally track digital conversion and sales through attribution models. While the pace of our industry moves at lightning speed, the same can’t be said for these models - making it inevitable for a gap to generate between real results and what’s being tracked. We can see this in how the data is interpreted, often overvaluing search compared to other online touchpoints, including social media.

While we’re all aware that these tools are only able to give an approximate representation of marketing value and return on investment, what the data shows is that this gap might be bigger than many of us expect.

Data gaps on channel-specific metrics

Industry changes such as the introduction of ad blockers and opt-outs, especially prevalent on iOS devices, have impacted all aspects of our industry, with some metrics becoming more inaccurate as a result.

Traditional attribution models are missing a wealth of data. According to research from Mix Modelling firm, Analytic Partners, attribution metrics fail to account for all the different touchpoints in a customer’s journey that contribute to each sale, and fail to address other marketing campaigns’ KPIs.

Analytic Partners estimates on average that 30%^[1] of ROIs attributed to search clicks are generated by other types of marketing, including social media ads.

Our data points to as much as 50%^[2] of sales driven by Meta platforms being misattributed to search results, undervaluing the role played by Meta platforms in driving sales.

As a result, the ROI of social channels is shown to be understated by as much as 44%, compared to when measured and assessed through MMM analysis. Mix Modelling analysis also showcases how performance figures relating to other channels such as Search and Display are overestimated by 336% and 364% respectively, resulting in an overinvestment that marketers could utilise across social ads and video content.

This all becomes an issue when brands and agencies make marketing investment decisions based on attribution models despite their blind spots, biases, and data gaps.

Flawed attribution leads to budget wastage

Attribution metrics can lead to missed opportunities, as the data shows they aren’t able to provide a complete view of all impressions, customers’ activities, and their impact on consumers - leading to bottom line wastage.

According to Analytic Partners’ research, 35 cents of every dollar^[3] spent on an attribution model is lost on average, showcasing the importance of investing across the right channels and diversifying ad spend to get the best return.

Given MMM, attribution, and experimentation all have different strengths and factors to be considered, a triangulation or calibration between these allows marketers to have a complete picture of marketing campaigns’ performance.  This includes running experiments such as lift studies, to calibrate attribution models to show the true value of your investments and provide a more accurate and holistic view of the campaign’s effectiveness.

Embracing a multi-faceted approach can bridge the data gaps, leading to better-informed decisions and optimised marketing strategies.

At Meta, we have built curated measurement content to be able to bring this to life. One of our product offerings includes Meta Align, a series of measurement modules that have been designed to overview key aspects from brand to MMM and attribution.

By adopting a more sophisticated analytical approach, marketers will be able to enhance their understanding of channel performance, divert some of the current investment into better performing channels including paid social ads and ultimately drive greater results.