Track leads & customers from AI in Salesforce

Are you struggling to work out how many leads and customers you are actually getting from AI tools like ChatGPT?

It is a fast-growing problem. AI tracking tools will show you how many mentions and citations you get, and analytics tools will happily tell you that someone arrived from ChatGPT or Perplexity, but working out how many of those visitors turned into leads, how many went on to become paying customers, and how much revenue they brought in is much harder.

Fortunately, there is a solution.

In this article, we'll walk through how to use a tool called Attributer to capture AI referral data with each new lead in Salesforce. We'll also show you a set of reports you can run to see exactly what AI is delivering for your business.

If you use Attributer with Salesforce, then it's easy to see how many leads are coming from AI tools. Here's how it works:

Attributer passes through two types of information about each lead. There's how they got to your site (the channel) and what content brought them there (the landing page).

So if you were on the marketing team at a law firm and somebody asked ChatGPT to recommend a contract lawyer, then clicked through to your site and became a lead, you would get the following.

• Channel = AI Referral
• Channel Drilldown 1 = ChatGPT (Or whichever AI tool sent them)
• Channel Drilldown 2 = chatgpt.com (the domain they arrived from)
• Channel Drilldown 3 = None (there is no deeper level of detail to capture for an AI referral, so this comes through as None)

You would also get information on the page they landed on. Continuing that example, it might look like this.

• Landing Page = abbottslaw.com/blog/contract-lawyers-sydney
• Landing Page Group = /blog

That landing page data is what tells you which of your content AI tools are actually reading and citing, and therefore what is worth creating more of.

Over my 15-year career in marketing, I have built more reports than I can count trying to work out which channels were working for us and which ones weren't. Here are 4 reports that become possible once you are capturing AI referral data.

This report shows how many leads you get each month, broken down by the channel they came from (AI Referral, Organic Search, Paid Search, Paid Social and so on).

It gives you a good understanding of how much AI is actually contributing to your lead goals. If AI referrals are still a thin slice, that tells you there is room to grow. If they start rivalling organic search, then clearly you are doing something right!

The comparison is the valuable part. Finding out that AI is quietly delivering as many leads as a paid channel you spend heavily on tecan help you understand how to best allocate your marketing budget (and time).

This report shows how many new customers you get each month, broken down by the AI tool that sent them. It allows you to see how ChatGPT compares with Claude and Gemini for instance.

That distinction matters, because the tools do not behave the same way. One might surface your content far more often than the others, or send visitors who convert at a noticeably better rate.

Knowing which tools actually produce paying customers, rather than just traffic, tells you where to concentrate. If the bulk of your customers arrive via ChatGPT, that is where it is worth putting the effort to stay visible and well cited.

This report shows the rate at which leads turn into customers, broken down by the channel they came from.

It is often the most revealing report of the set, because lead volume on its own can mislead you. You might find that 35% of your leads from AI Referral go on to become customers, against 10% of those from Organic Search and 7% from Paid Search.

If that is the pattern in your data, a lead from an AI tool is worth several times one from paid search, which should change how you think about where the next dollar goes. It often works out this way because people arriving from an AI tool have already had their questions answered and come in better qualified.

This report shows how many customers, and how much revenue, each piece of content on your site has generated from AI referrals.

It makes it easy to see which content pieces (like which blog posts) AI tools are citing and sending actual buyers to, rather than just curious visitors.

That is a practical guide for what to write next. If a handful of posts are responsible for most of your AI-driven revenue, then producing more of that kind of content is a sensible bet.

If you have been trying to work out how many leads and customers AI tools are genuinely sending your way, using Attributer alongside Salesforce is a great way to do it.

Best of all, it is free to get started with Attributer and setup usually takes less than 10 minutes. So start your 14-day free trial today!