Hey, Ruchin here! Welcome back to Toplyne Labs - Edition #3
A weekly digest that covers unique insights on what makes PLG businesses tick, what signals make for the best PQLs, what sales teams get right, what they get wrong, and the meaning of life⦠Go figure š¤·š»āāļø
This week, we look at data from over 5M users to answer a question that all PLG companies ask themselves every now and then - especially as they look down their list of new sign-ups:
"WTH do we do with all these personal e-mail sign-ups?"
Disclaimer: While this analysis spans over 5.M users, it also captures a breadth of behaviour across various categories of PLG products. We encourage you to use these insights directionally and thematically.
Insight #1: Do you block Gmail logins? You might be turning away 30-80% of signups
If youāre a sales or demand generation team, personal email ids are your friend.
They can expand your top-of-funnel by 30-80% - irrespective of whether youāre a B2C or enterprise business.

Insight #2: But Gmail signups have 1-3x lower conversion rates
No doubt, Gmail IDs add noise to the funnel.
You donāt know which company they work at, how large the company is, how much theyāve raised, yada yada.
Traditional profiling and legacy third-party enrichment just donāt work.

But that sounds like a YOU PROBLEM š¬
Because boy, do these leads convert.
Depending on B2C/Enterprise, personal email id signups can account for 20-70% of total conversions.
Itās your job to find these users⦠vs. expecting these users to find you (?!) whutt š¤Ø

Insight #3: Gmail win rates can be a LOT better
The best PLG sales teams close personal and business domain leads at equal win rates 𤯠How?
Letās get real for a second. A large % of the Gmail signups you let through the door will never convert.
As a PLG company, itās your job to identify those who would. The carrot at the end of the stick - 20-70% of your potential conversions.
But traditional lead scoring fails in doing this. It relies too heavily on the BANT framework - a legacy qualification framework based on Budget, Authority, Need, and Timeline.
Traditional lead scoring indexes heavily on Budget and Authority. But with Gmail signups, you know a lot less about:
- Budget: You have no idea which company this person works for, how large they are, or how much theyāve raised?
- Authority: Is this signup in a CXO, VP-level position, or an entry-level role?
But as a PLG company, you have a lot of knowledge about the Need and Timeline your prospect is working with.
Hell, your potential customer is already a user of your product!
Tapping into product usage data is the need of the hour.
All you need to do is train an AI to scan through the millions of clicks within your product to spot users who have shown the highest proclivity to buy.
Hereās how you do it:
- The talent youāll need:
- A data engineer or two - a few $100k.
- Hire a data scientist or two - a few $100k.
- What these folks would need to do:
- Set up pipelines to sync and stitch together all your product usage and customer data in a warehouse - a few $10-100k.
- Train AI models to scan through the data on Snowflake and identify users most likely to convert based on historic patterns in conversions.
- Set up a live data sync into your CRMs with a rev-ETL tool.
- (OPTIONAL) Set up a performance tracking and A/B testing framework - no points for guessing, the more you iterate the better the results.
- The stack youāll need (representative) - Fivetran, Snowflake, AWS, dbt, MLflow, rev-ETL tools, etc, etc.
ORā¦..
You could just signup for Toplyne and weāll have this set up and ready in 7 days š¤·š»āāļø