Social Ads Continue to Be Exceptionally Good at Delivering High-Quality Users

May 8, 2013

This article is included in these additional categories:

Analytics, Automated & MarTech | Data-driven | Digital | Social Media

AggregateKnowledge-Media-Spend-Efficiency-Comparison-in-Q1-May2013In Q1, social vastly outperformed portals, networks, and exchanges in user quality index ”“ a measure that refers to a channel’s ability to reach a user that can be marketed to consistently ”“ according to the latest “Global Media Intelligence Report” [download page] from Aggregate Knowledge. The study, which analyzed more than 27 billion impressions across Q1, found that social performed 65% better than the industry overall in delivering such quality users, and 33% better than the next-best channel, portals. In a turnaround from Q4, though, portals emerged as the best option for reach efficiency, which tracks the ability to reach exclusive users at the lowest cost. Social was close behind in reach efficiency, still performing 45% better than the industry average.

Portals also turned out to be the most cost-effective option in Q1, at 2.5 times below the industry average. In Q4, that distinction belonged to exchanges, which continued to be cost effective in Q1 (1.5 times below the industry average), just not to the same extent.

The study also demonstrates that the value of social continues to be underestimated when using a pure last-touch attribution model, which is the most commonly used model. (Adobe also recently made the same point with regards to social media marketing.) In other words, when using a multi-touch attribution model instead of a last-click model, social sees its value increase the most, while exchanges lose a great deal of worth given that they are predominantly in the lower funnel.

About the Data: For this quarterly report, Aggregate Knowledge (AK) compiled data from a representative sample of its customer base. This includes 872 campaigns, accounting for 80% of AK’s total impression volume and 79% of conversions across approximately 130 billion ad events.

The methodology for data collection, analysis, and reporting consisted of multiple steps. Data was collected through the AK “pixel” (or “tag”), which was then ingested by the AK Media Intelligence Platform (MIP) using AK’s proprietary Summarizer technology. AK’s team of data scientists then worked with the platform, querying the MIP for channel-based performance and cost data, as well as target ability, overlap, and exclusive reach metrics. AK also looked over the raw event data for converting users to see whether or not those users had seen an ad on a particular channel (or combination of channels) further upstream, providing additional insight beyond that exposed by last-touch attribution.

Data represented covered over 600 different inventory providers across key vertical industries such as telecommunications, finance, retail, automotive, and consumer packaged goods.

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