How do you detect a spam prospect?
A prospect walks in the virtual door with a personal email and a weird website. Are they a good risk? It depends. Read more: "Everything Starts Out Looking Like a Toy" #220
Hi, I’m Greg 👋! I write weekly product essays, including system “handshakes”, the expectations for workflow, and the jobs to be done for data. What is Data Operations? was the first post in the series.
This week’s toy: an aspiring newspaper publisher prints a personal news page using a dot-matrix printer. We need more of this retro-cool, combining the ability to get custom-made information with a form factor that’s decidedly analog and prevents infinite scrolling. Edition 220 of this newsletter is here - it’s October 14, 2024.
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The Big Idea
A short long-form essay about data things
⚙️ How do you detect a spam prospect?
In your GTM machine for B2B Saas Software, one of the best defenses against spam emails is to ask for a business email in your lead form. By having this initial barrier, you make it harder for prospects to use free personal email addresses to clog your funnel. You’ll need to screen for disposable domains, but finding a real prospect is much easier.
But what happens when you can’t use that filter as an initial sort or when your ideal customer uses a personal email to identify themselves? Finding a spammer then becomes a combination of detecting behavior and validating other information you get during the lead flow.
Visualize the ideal customer
To find a spammer, consider the ideal customer, then invert the behavior.
For example, a logical progression for a typical prospect might be to start a trial and make progress through that trial over a few days. When a prospect immediately becomes a customer with no prior contact in that setup, you might feel a little suspicious. However, if your GTM involves customers purchasing software on the first visit, this behavior isn’t spammy at all.
When you expect to call a prospect on their phone number because your clients typically run a business, it’s odd if the phone number they gave you doesn’t get answered. If that same prospect has an odd-sounding email and shares a phone number that’s a VOIP number rather than a wireless or business phone, your fraud radar might increase.
If your prospect is flagged by your credit card processor as a high-risk card, you have another data point toward your answer.
Does that mean that every prospect with an email of gamerguy123@freeemail.com is automatically a spam prospect? It depends how much that prospect resembles the kind of prospect who would be a good customer, multiplied by the other signals you observe.
Start by looking at the facts and guess whether it ends up being spammy. Over time, your detection and prediction will get better, tuned for your company’s GTM.
Build the data factory of tests
Your “guess” must be objective, and the rule or rules to mark something as “potentially spammy” must be as easy to determine as possible. It’s better to have a easy choice instead of a vague description of what makes spam.
Here are a few examples of behavior that suggests a spam prospect:
use of a “disposable domain” email address, typically with a developer tool like mailinator.com - this hides the real email address
submitting a website URL that is not related to your company for the purpose of passing through a form
use of a temporary or “burner” phone number connected to a VOIP service
These items can all be tested to be true or false, and the outcome of these simple tests is a scale from 0 (doesn’t trigger any of these tests) to 3 (triggers all of the tests). Is every prospect marked a 3 on this scale a spam prospect? Probably not, but a 3 on this scale is a lot more likely to be spammy than a 0.
Use data to refine your tests
The best way to measure your tests? Compare them after the fact to the actual results. In this (very) simple scenario, if a spam score of 3 ends up being a spam account 90% of the time, you might choose to remove those leads from your lead flow entirely, or qualify them differently to create a better mix of leads for your sales team.
Tests don’t tell you the whole story. A middling prospect with low activity in your application might look like any other middling prospect, so the critical path here is to contact the prospect and have a conversation.
What’s the takeaway? Product-led growth sometimes attracts customers that look like spam. The best defense? Contact them like any other prospect and find out what they’re up to. Adding spam signals to share with your sales team will help them know more.
Links for Reading and Sharing
These are links that caught my 👀
1/ Read more, scroll less - 46% of Americans didn’t read a book last year. There are so many ways to consume books these days, so grab an e-reader, a paperback, or a library card and find something great to read.
2/ Measure blood pressure from your app - The next generation of health wearables are going to be able to tell you in the moment whether you’re having a high blood pressure episode.
3/ 6 degrees of Kevin Bacon - If you’ve wondered if Kevin Bacon is the most well-connected actor in Hollywood (as measured by the ability to connect him through movies he’s appeared in), that’s not quite true. But it’s still a fun game to play and explains the concept of connected networks quite well.
What to do next
Hit reply if you’ve got links to share, data stories, or want to say hello.
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The next big thing always starts out being dismissed as a “toy.” - Chris Dixon