3 rules by which to measure mobile creative
April 21, 2014
Brian d’Alessandro is vice president of data science at Dstillery
Mobile advertising is the new kid on the digital advertising block. The mobile fanfare has been blasting for years, but only recently has mobile become a viable advertising option.
While the talk is loud and the technology is available, adoption by marketers is still in its early stages. Their hesitation is understandable. No digital marketing solution can achieve real scale until the measurement problem has been solved.
Total advertising spending in standard display has finally surpassed that of broadcast television. There is little doubt that innovations in attribution, viewability and fraud detection have helped bring display over this long-awaited hump. Mobile advertising is next, but to have this debutante of a channel attract the attention of the potential suitors out there, we need to master the measurement piece.
When it comes to mobile measurement here are three rules to live by:
1. Do not engage in child's play
Clicks are cheap and easy to evaluate, so it is no surprise that many mobile marketers have adopted the click-through rate (CTR) as their default metric.
The most important variable for predicting clicks is the inventory itself, and, tellingly, there is little variation across brands or creatives on any given inventory source.
The most clicked-on inventory tends to be gaming applications and, in particular, game that are targeted to children.
Many marketers invest a lot of time developing good creative, only to optimize toward an audience that cannot even read. True value creation can happen with mobile advertising, but only if we can move beyond the cheap and easy.
2. Do not forget to explore
Mobile data streams offer many endemic data points that can be used to measure advertising effectiveness. The most obvious one is location data.
Many marketers have branded physical locations, and visits to these locations can be a great measure of advertising success.
But the opportunity goes beyond location.
The mobile data stream also contains Internet service providers, wireless carriers and device model. With a bit of creative thinking, these can help define effective and measurable outcomes.
Recent case in point: a leading cable provider measured the degree to which users change ISPs after being exposed to ads for Internet service. When compared to a control group of users who were not exposed, the group that saw at least one mobile ad switched ISPs 20 percent more often.
Given the value of acquiring a new customer for high-speed Internet service, this effect delivered a significant positive ROI.
3. Do not be single (channel) minded
Mobile devices are without a doubt a huge step forward in convenience and, of course, mobility. But some activities are still easier using a browser on an old-fashioned computer.
So we should not expect all of the impact of a mobile ad to be observed on the mobile device.
With access to device-matching technology, one can measure the extent to which mobile ads drive desktop behavior.
Let us return to the cable provider to review the extent to which users who saw the brand’s ad on a mobile device visited the brand’s Web site on their desktop.
Like the measurement of ISP switching, users exposed to ads on mobile phones were 25 percent more likely to visit the company’s site on a desktop than the control group. This effect was even stronger for tablet ads, which drove a lift of 40 percent.
Even more, users that were targeted as in-market for cable and Internet services were 250 percent more likely to visit after seeing an ad.
This last point really illustrates the importance of audience targeting on top of channel targeting and, of course, this point can only be discovered with the right measurement in place.
THE DATA IS for truly innovative mobile and cross-channel measurement.
What these methods need are for brands to be willing to commit to them.
The data shows that mobile ads are effective at driving various brand-related outcomes.
With more minds focusing on analyzing causal impact, those outcomes become a matter of common sense and the budgets will be committed accordingly.
Brian d’Alessandro is vice president of data science at Dstillery, New York. Reach him at .
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