ellipsis flag icon-blogicon-check icon-comments icon-email icon-error icon-facebook icon-follow-comment icon-googleicon-hamburger icon-imedia-blog icon-imediaicon-instagramicon-left-arrow icon-linked-in icon-linked icon-linkedin icon-multi-page-view icon-person icon-print icon-right-arrow icon-save icon-searchicon-share-arrow icon-single-page-view icon-tag icon-twitter icon-unfollow icon-upload icon-valid icon-video-play icon-views icon-website icon-youtubelogo-imedia-white logo-imedia logo-mediaWhite review-star thumbs_down thumbs_up

4 tips for moving beyond last-touch attribution

4 tips for moving beyond last-touch attribution Jarvis Mak

In the real world, someone might see an ad on Google search, Facebook, an affiliate site, as a display ad, and in an email. And yet sole credit is given to the last ad medium the person saw before clicking and buying. It's difficult to measure the impact of multiple touch points before a person converts -- a process called fractional attribution -- because it's so complex. As a result, brand marketers rely on last-touch metrics as a sub-par proxy to measure campaign success.


What can brand marketers do to start down the path of accurate attribution to every touch point in their digital marketing programs? Here are four simple steps.


Credit views, not just clicks
As previously discussed, many ad views that don't inspire clicks can still lead to sales down the road. Focus on measuring "view-through" exposure instead of click-through so you can accurately attribute value to ad views that later lead to conversions. Use a marketing analytics platform that favors view-based attribution. Companies such as ClearSaleing, Visual IQ, Adometry, and C3 Metrics are working to solve the attribution challenges of digital marketing.


Even if you don't have sophisticated marketing-analytics tools, you can measure view-through via simple A-B tests. Split your audience into two discrete cells of users and track the revenue each generates. First, test numerous creative units, rotating them equally to generate a good base of data. Measure which ads generate the most revenue upon click-through, and which pay higher dividends down the road -- a process known as post-impression revenue. Subsequently, expose Group A to ads associated with the most revenue upon click-through, and show Group B ads optimized for highest post-impression revenue. Then, compare both post-click and post-view revenue for A and B. This practice will give you a clear understanding that there's a positive view-through impact from online display advertising, suggesting that we shouldn't focus only on clicks. After all, people can't click on billboards, print ads, or TV ads as well but we know that each makes an impact.


Quantify lift from display ads
Some marketers are skeptical that online display ads can help them achieve brand goals. However, with the right methodology, not only will brand goals be realized but you may also predict and model the impact display ads have on revenue, even if consumers don't always click on the banners.


To get an idea of how views of display ads effect conversion, analyze the time window between an ad impression and a purchase. The best way to do this is to conduct another simple A-B test. Both groups, A and B, should be randomly generated yet statistically equal, thereby having equal exposure to all other media and to your other digital channels. Have your agency or a single-publisher partner show your ads to Group A, and display a set of public service announcements to Group B. Then, determine which group converts more, which will give you a high-level view of whether your display ads are having any type of impact on conversion.


Conduct a multi-touch analysis
Consumers are constantly jumping between marketing channels -- display, search, video, social, mobile, offline, and back again -- so they will see many different ads before they convert. To assign credit to each of the digital touches that influence a final action, you must collect user data across channels. To do this, work with a single technology platform that can measure and analyze all touch points for each user on the path to conversion. Your ad-technology partner can help you follow this simple mantra: "Put a pixel everywhere." Pixels help you track who saw what ad and where they went from there. Make sure paid search landing pages and all email communications are pixeled. In addition, provide a different pixel for organic searches than for paid searches, and supply different pixels for each ad targeting or retargeting partner. Lastly, provide different pixels for social marketing initiatives.


By collecting these data, marketers can hone in on several key types of analysis:



  • How much your digital channels complement one another

  • Identify partners that are undervalued as first-touch originators for conversions but are extremely valuable for filling the top of the funnel

  • Identify partners involved as influencers for those "high value" conversions vs. "average value" conversions

  • Whether some partners seem to specialize as influencers, especially when they're not credited with the last-touch prior to the conversion

  • Revenue associated with different influencer partners

  • Typical paths to conversion and number of touch points per conversion

  • Characteristics of conversion paths for higher value orders

Optimize campaigns based on findings
It's one thing to collect and analyze data on all touch points, but another to actually make better decisions from the data to optimize campaigns. To get there, you must gather more data. You'll want to comprehensively track actual conversion data, note how much revenue comes in and from where, and differentiate between return customers and new customers.


To build the most accurate attribution framework, ascribe value to all stages in the funnel, assign partners' campaign touch points according to those funnel stages, update campaigns with in-flight data, and experiment iteratively with the mix of partners, channels, and attribution allocation for a few different campaigns. It's likely that the same bottom-line results can be more efficiently achieved with fewer partners and fewer touch points. The key is determining the correct partners and touch points.


Lastly, it is important to work with media-buying partners that can incorporate real-time feedback into every ad-buying decision. At Rocket Fuel, we gather real-time feedback on ads through single-question, in-banner surveys to achieve a clear real-time reading on brand sentiment. Ultimately, you want to measure campaign impact across the full funnel -- from initial touch-through brand awareness to final sale.


Jarvis Mak is VP of analytics for Rocket Fuel.


On Twitter? Follow iMedia Connection at @iMediaTweet.

Jarvis Mak runs the Customer Success group for Rocket Fuel, responsible for ensuring successful campaigns and delighting customers. He originally joined Rocket Fuel in 2009 as VP of Analytics. Previously, Mak was with Havas Digital as a senior vice...

View full biography

Comments

to leave comments.

Commenter: Dieter Van Roekel

2012, February 07

Actually not bad article. Well done, reading stuff like this: http://www.imediaconnection.com/content/29694.asp a few months back makes me weep for the future of the industry. Good to see some people are actually awake. Keep it up!

Commenter: Bill Muller

2012, January 04

Great article Jarvis! At Visual IQ we see first-hand the extent to which display impressions (view-throughs) contribute to eventual conversions (or brand lift) via the display channel, or via other channels further down the funnel. This is universally true across virtually all of our clients. So marketers who are failing to measure the impact of every display touchpoint are -- in effect -- not measuring the performance of their display campaigns accurately. Some of the specialist companies you mentioned do this by -- in effect – automating A/B tests between every variables within the clients' marketing performance data to quantify the impact of every "touch." This can also be systematically done by marketers themselves, though can be very time consuming and labor intensive. The good news for the industry is that it's becoming recognized exactly how flawed the "last-click” or "last act” measurement model truly is.