We’ve made it pretty clear in the past that Google Analytics is not affiliate tracking software, but that doesn’t mean your web analytics can’t improve your affiliate marketing channel. By combining affiliate tracking data and web analytics, you can more effectively isolate potential affiliate performance issues and properly attribute non-conversion behaviors to your affiliate channel. This matters whether affiliates are being compensated or not.
Here are a few key ways you can use web analytics to help affiliates succeed (and improve your bottom line).
Going Beyond the Conversion
It’s easy to shower top tier affiliates with attention, especially when they are driving the majority of your affiliate conversions. What about affiliates who are sending clicks but aren’t converting? Do you write them off as noise in your data stream? Or are you digging deeper to find out why those clicks don’t convert to sales?
If you’re ignoring affiliates who are sending clicks without conversions, you’re costing your company money. Either the affiliate is sending you garbage traffic (and possibly hurting your brand reputation in the process) or something about the offer flow is falling down for that affiliate.
One of my biggest frustrations as an affiliate is knowing I’ve sent a bunch of clicks to an offer and seeing zero conversions. I typically assume that means the tracking is broken or the landing page is a dud and I quickly move on to focusing my attention on something else.
What I’d really love to know is what happens after the click? This is a big opportunity for affiliate managers to improve the conversion funnel by offering deeper analysis than just clicks and conversions. Affiliate managers should have access to far more data than affiliates.
From an affiliate perspective, most of the data is binary. Either a conversion happens or it doesn’t. A simple buy or no buy doesn’t tell the complete picture. Web analytics software can tell you what happens to those clicks.
Some percentage of users who click an offer link are taking additional actions. They may be signing up for a newsletter, or clicking a Facebook Like button, or tweeting about the company. Affiliates can’t see these non-conversion events.
While the jury is still out on whether these non-sale actions are worthy of payment, if you aren’t attributing them properly to the affiliate sales funnel you may be losing valuable data.
Compare Affiliate Traffic to Other Channels
Are affiliates delivering visitors who behave like everyone else or are affiliate-generated visitors different in some way? Your web analytics software will show you whether affiliate-generated visitors have a different bounce rate; you can see how many pages they visit; you can also see if affiliate traffic converts at a rate higher or lower than in-house PPC and display channels.
If affiliates are outperforming, that’s outstanding! It also means your in-house channels need some attention.
When affiliates are underperforming compared to other channels, use web analytics to help discover why. Is the affiliate creative different? Are the affiliate landing pages congruent with the offer? What path on your site do visitors follow when starting from an affiliate link?
Watch for Trends in Your Affiliate Traffic
Affiliates typically see marketing opportunities early. Pinterest is the most recent example of this, but it’s just one of many. By looking at both your affiliate tracking software and your analytics data, you can get a better idea of where your traffic is coming from. If a significant percentage of traffic is coming from someplace new, like Pinterest, take a look at how you can capitalize on that more effectively. Do visitors from Pinterest need a different kind of landing page than those coming from other sites? Do visitors from this new site engage with your brand differently? Are the visitors people you want your affiliates referring?
Find Out Who Clicked
One of the more interesting metrics you can determine from web analytics is the number of repeat visits you get from affiliates. This may need to be mapped back to your CRM as well, but knowing which affiliates deliver new leads, as opposed to the affiliates who are likely sending you repeat customers provides a broader marketing pictures.
If an affiliate is routinely sending you repeat purchasers, it might say something about your in-house marketing to existing customers. Why are the purchasers buying after visiting the affiliate instead of buying when you send repeat-purchase marketing materials. Is the affiliate always catching the buyer at the right point in the purchase cycle?
When an affiliate is generally sending you new buyers, that means they are connecting people with your product who may otherwise never purchase. If you find an affiliate who routinely delivers new visitors, that’s probably an affiliate who warrants more attention.
Using Analytics for Recruiting
Another area where web analytics provides insight is in the area of recruitment. If there are sites that are currently sending traffic, but aren’t part of your affiliate program, investigate how they are sending traffic. It’s possible the site should be in your affiliate program and will generate even more revenue once they are motivated to promote your products.
Communicating with Affiliates
Web analytics provide a great opportunity to share data with affiliates. As an affiliate, most of my interaction with affiliate managers happens when new offers are sent out. The best affiliate managers I work with provide me with information and advice that helps me optimize what I’m already doing. By offering data affiliates can’t get without your help, you make your affiliate program more valuable to the affiliate, which in turn should translate to more dollars generated through your affiliate channel.
Are you using web analytics to support your affiliate marketing efforts? What do you find most beneficial in looking at web analytics data?
Jake Ludington has over a decade of experience building content publishing teams, coupled with more years as an affiliate marketer than he cares to admit. Follow Jake on Twitter.