We calculate lead scores in Salesforce to help us prioritize our inbound book of business. Put simply, the higher the score the higher value a potential contract with a customer should be. We use Clearbit to enhance our contact information as it is created and then compute a score out of 70 in Salesforce based on the following parameters:
- Employee count - larger companies are more likely to have a bigger customer base and more usage data to capture. They are also more likely to need an Enterprise plan.
- Ability to pay - indicates whether a company is likely to pay for a product like PostHog to solve their problems. This is computed from the estimated company revenue.
- Role - from experience we sell best to people in an engineering, product or leadership role.
- Country - from experience we know that certain countries have a higher inclination to pay for software so we weight those.
Note that we also calculate an ICP score in Salesforce. This is more marketing aligned and designed to show us whether we are capturing who we are building for as inbound leads.
Metric | Value | Score |
---|---|---|
Employee Count | 1-10 | 0 |
11-1000 | 10 | |
1000+ | 20 | |
Ability to pay | Estimated Revenue $0m-$1m | 0 |
Estimated Revenue $1m-$10m | 5 | |
Estimated Revenue $10m-$100m | 10 | |
Estimated Revenue $100m+ | 20 | |
Role | engineering | 10 |
product | 10 | |
leadership/founder | 10 | |
marketing | 5 | |
other | 0 | |
Sub-role | data_science_engineer | 10 |
project_engineer | 10 | |
software_engineer | 10 | |
web_engineer | 10 | |
founder/ceo | 10 | |
other | 0 | |
Country | Austria, Canada, France, Germany, Japan, Norway, Sweden, UK, USA | 10 |
Australia, Belgium, Estonia, Finland, Georgia, Guernsey, Netherlands, New Zealand, Poland, Portugal, Singapore | 5 | |
Other | 0 |