Understanding The Complexity Of Mobile Ad Attribution
In this complex and fragmented marketing landscape where a consumer’s purchasing journey moves from desktop to mobile to offline channels, measuring the contribution of all these touch points is exceedingly complicated. Recently, one of these media has become increasingly challenging: mobile. While consumer usage of mobile devices is ballooning, mobile ad spend is still lagging […]
In this complex and fragmented marketing landscape where a consumer’s purchasing journey moves from desktop to mobile to offline channels, measuring the contribution of all these touch points is exceedingly complicated. Recently, one of these media has become increasingly challenging: mobile.
While consumer usage of mobile devices is ballooning, mobile ad spend is still lagging behind. Marketers know that consumers are on their smartphones and tablets 24/7 and that this usage will only continue to grow, but a lot of uncertainty remains around attribution and how to accurately measure mobile campaigns.
There are multiple devices that people use to engage with brands, and without a universal method to track campaigns across all of these devices, the efficacy of mobile campaigns can be underreported or devalued. While “closed loop” point of sale technology (mobile payments, coupons, etc.) may seem like a sure bet to measure mobile campaigns, many of these methods are still in their nascent stages with no clear standards.
Therefore, there are challenges in delivering measurement at scale, especially when brands are trying to address the “upper funnel” audience where mobile is seeing high amounts of dollars.
Currently, if an advertiser uses a pixel like a Google Floodlight to track conversions, the measurement is going to be flawed and lacking. The current cookie cannot track across device or within mobile environments (mobile web to app). That means if a user saw the ad on a smartphone and then converted on a tablet or desktop, the pixel will not give credit where credit is due.
However, moves like Google’s acquisition of Adometry means that there are companies that are working towards advancing its pixel to track cross-device.
Beyond online and mobile tracking challenges, it’s also difficult for marketers to track the digital influence of offline purchases. A customer could have seen an ad for a sale on their mobile device and walked into the store to convert, but the credit will not be given to the influencer unless there was a tracking mechanism in place that can tie the two together.
While innovation in mobile attribution is still in its early stages, there are a few best practices that marketers should keep in mind to determine how to measure the impact that mobile has on the overall media mix.
Adopt A Cross-Device Attribution Model
The industry is working to solve for attribution challenges by deploying cross-device targeting solutions into attribution measurement. Before the rise of mobile usage, attribution was focused on spreading credit beyond last touch. With the rise of mobile devices, there is an inherent need to move beyond just last touch measurement and incorporate all devices — and touch points — into your attribution model.
While there are still shortcomings with scale and device matching using first-party login data, and matching algorithms may only be based on probabilistic scores without login data, marketers should still adopt a cross-device model to get the most accurate information about their customers’ purchase patterns.
Review The Effectiveness Of Your Brand Messaging
Looking at the efficacy of your brand messaging will help you measure engagement with mobile ads. Building engagements within the mobile creative will help marketers measure the efficacy of their campaign.
Deploy Mobile Payments, Coupons Or QR Codes
Mobile payments, coupons or QR codes can be tracked more efficiently, which helps if your campaign objective is more ROI-driven. By integrating these tactics in your mobile marketing platform, you can generate more success from your marketing spend.
Use Location-Based Data
Using location-based data analysis to determine the mobile marketing impact on offline and in-store purchases is another effective tactic. Companies like Ninth Decimal and PlaceIQ are doing this by aggregating all of the mobile devices that were reached during a campaign and analyzing the number of those same devices that were later seen within a specific location or place footprint.
The high demand for mobile attribution is only going to spread as mobile payments and other forms of in-store engagements increase and as more ad dollars are spent on mobile devices. This in turn compels attribution companies to further advance their technologies to measure cross-device effectively.
At this point, there is no one-size-fits-all approach for achieving measurement at scale, but by continually testing methods and developing new technologies we will get closer to an effective solution.
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