The 3-Part Marketing Attribution Framework All PLG Companies Need
If you’re like most product-led growth founders, you’re probably using product analytics tools to track key acquisition metrics. We’re talking numbers like sign-ups, conversion rate to activation, conversion rate to customer, and more.
But if you aren’t sending marketing attribution data into these tools (i.e., tracking if users come from Google Ads, Facebook Ads, or SEO), then how do you know what’s actually driving these sign-ups? And how do you know if your ad campaigns are actually generating customers and revenue?
Fortunately, adding comprehensive marketing attribution information info into your PLG analytics tools is not impossible. And after all, it helps to know exactly how your various marketing initiatives are performing.
In this article, we’ll introduce you to a three-part attribution framework leading PLG companies use and show you how you can implement it in your own tools.
Why do you need marketing attribution? A case study
In late 2021, my company Simul Docs (a version control tool for Microsoft Word documents) lost 40% of its sign-ups out of the blue. This was a huge issue for our business and if we couldn’t fix it, we were going to miss our already aggressive revenue targets by a long shot.
We started investigating the problem by looking at the number of sign-ups we got per month, broken down by the lead source. For Simul Docs, it’s our website or our Office extension.
Looking at this, we saw that the drop had come from website sign-ups, as sign-ups via the Office extension had remained stable.
To learn more, we filtered out any sign-ups from the Office plug-in. It left us only looking at website sign-ups. We then broke that down by channel:
It became clear that the drop in sign-ups had come from organic search. All our other channels (paid search, paid social, and direct traffic) had remained relatively stable while sign-ups from organic search had plummeted.
This was a great step forward, but we still needed to know more. Why had our traffic from organic search dropped so much?
Putting a microscope to marketing channel data
Next, we looked only at sign-ups through the website from organic search and broke them down by landing page group. This chart gave us further insight as to where the drop came from. It was our template library.
We learned that the drop came from fewer people signing up via our website after landing on our document template library from organic search. But what strategies could we develop to address it?
We worked on creating additional, unique content for each page and started an ongoing link-building campaign to try to grow domain authority. Over the course of the year, we restored and even grew the number of sign-ups we get through our templates.
If it hadn’t been for the fact we had a solid marketing attribution system in place, we never would have been able to work out what happened. In fact, we would have very likely missed our revenue growth targets by a wide margin.
The 3-part attribution framework you need to be using
When most people think of marketing attribution, they think of attributing customers to channels like organic search or paid search. But there are actually three key questions you need to answer with marketing attribution:
- How did they arrive at my site?
- What attracted them to my site?
- What converted them?
1. How did they arrive at my site?
The first question you want to be able to answer from your analytics is, how did these users get to my site?
It’s important that you capture both the high-level information (like the fact a sign-up came from paid search, organic search, or organic social) as well as the finer details (like the campaign, ad group, and ad they came from).
A good way to do this is to establish a hierarchy of properties that can be sent to your analytics tool, such as:
2. What attracted them to my site?
Beyond just capturing the channel that someone arrived at your site through, you also want to be able to track what attracted them there.
Most PLG companies produce a lot of content each month, including blogs, white papers, webinars, templates, and free tools. It’s just as important to understand how these contribute to sign-ups and customers, as well as how your Google Ads contribute.
To do that, you want to be capturing two pieces of information:
- Landing Page: This is the first page on your website a visitor sees.
- Landing Page Group: This is a grouping of the first page the visitor sees. So if the landing page was slack.com/blog/best-chat-app then you’d want to be capturing “/blog”
These two fields allow you to see how many sign-ups and customers you generate from certain types of content on your site. They also help you drill down into how each individual page or post is performing.
3. What converted them?
The final part of the attribution framework is capturing information on what converted the visitor into a lead. Did they sign up through your website or via your iOS or Android app? Or did they come through your Chrome Extension or Microsoft Office plug-in?
It’s important to have this information as these different paths tend to attract people with very different levels of intent and product knowledge, and can have a big impact on activation and conversion rates.
For example, UTM.io is a tool that helps organizations standardize their use of UTM parameters. When I worked for them, I saw data showing people who signed up from the website converted at much higher rates than those that came through the Chrome Extension.
But what was the reason? People who came through the website were much more educated on the product’s features, thanks to featured case studies on the site. As a result, the cognitive load of learning about the product lessened because they understood how it works. They were also more interested in setting it up because they knew the product could solve their problem.
To properly capture information on what converted a visitor, again, it’s best to use a hierarchy of fields:
How to get these 3 attribution elements in your analytics tools
The good news is that you don’t need to completely overhaul your existing analytics setup to implement the framework. You simply need to send through some additional information on each user that signs up for your product.
Here are some examples:
How did they arrive at my site?
Additional information you need to track: Marketing channel.
Simply put, you want to track the marketing channel where your visitors have come through, in particular by using tracking codes on your website. The code helps you understand where visitors have come from, enabling you to pass that through to your analytics tool when they sign up for an account. Tools like Attributer.io are purposely built for doing exactly this.
What attracted them to my site?
Additional information you need to track: Landing page.
You need to be tracking the first page they visited on your website. Send that through to your existing analytics tools. Dedicated marketing attribution tools can also help with this.
What converted them?
Additional information you need to track: Lead source.
Tag visitors as they sign up for an account in your product or complete a demo request form. This could mean adding extra information on account creation, or it could mean adding some hidden fields to your demo request form so you know that’s how they became a lead.
So, what can you capture and report on with this framework?
Now that you understand how the framework functions and have got it all set up, here are a few interesting reports you can run:
Activation rate by channel
This can be a useful way to segment activation reports, as users from higher-intent channels like organic search can have higher activation rates than lower-intent, paid sources like Facebook Ads or display ads. I’ve even seen users from organic search convert 10% higher than users from Google Ads, even though they both searched for the same thing.
Customer conversion rate by landing page group
During my time at SafetyCulture, we generated a huge volume of sign-ups through our template library, leading people to sign up for the product to use the checklist. Unfortunately, people converted to paying customers at significantly lower rates than people who came through the homepage.
Fundamentally, these people weren’t looking for a new checklist app. They just wanted a checklist template in a PDF or Doc format. Being able to see your customer conversion rate by landing page group can help you see how different content initiatives like templates, blogging, and webinars are performing.
Retention rate by lead source
This helps you to see the retention rate of users who sign up via your web application apart from those who sign up via your mobile application. The retention rate report, when shown as blended data, may be hiding opportunities for improvement.