Dog Fooding BuiltWith to find customers for Datasets

We recently launched BuiltWith Datasets - a new mega technology tool that really suites investment professionals and anyone in related spaces such as hedge funds and other users of Alternative Data.

We needed to find and reach out to relevant customers in this space - what better way to do that than use BuiltWith to find people on the tool that would be interested. We started off with a list of 96,000 websites, filtered that down using the BuiltWith Pro tool to 821 websites and then used LeadsEye to filter that down further to 130 solid leads.

Here's the steps we went through to do that -

Step 1: Get the source list of domains that have an account and push that into the system using the list upload feature (See KB Article)

Step 2: Filter this list down using the keyword filter to find sites that have relevant content on their homepage (See KB Article) because we are looking for investor type leads we created multiple filters like "ventures" "hedge fund" "investment" "private equity" "alternative data" "investor" -

Step 3: Filter the list down by relevant technologies - to find financial and large companies we tried the 'Investor Relations' technology as a filter as this is sites that are most likely listed on a stock exchange (See KB Article).

Step 4: See all of the reports you created. We could have actually created an 'Advanced Filter' and done all of these keyword filters in a single report (using the 'OR' switch) see KB Article on how to do that.

Step 5: Export all of the 'Meta Data' zip files from all of your variations

Step 6: Use Excel or another spreadsheet tool to create a mega list of all of the domains in your filtered reports and save a text file domain list.

Step 7: Upload that list into LeadsEye (it will remove the duplicates itself)

Step 8: Eyeball the homepages in LeadsEye to determine if they are a good fit for the Dataset product (View the Demo on how this works)

Step 9: Export the leads from LeadsEye and join them back up with the emails.

We don't ask for names of individuals when they signup but because my list has gone down from over 100,000 emails to around 130 I just used Google to search for the email address and domain to find their name. This is the most cost effective approach we found to finding people names with the highest success rate (around 90%).

Step 10: Use your CRM to create a lead list with the persons first name to and send a simple relevant personal email to them.

And that's it - a super powerful method or using BuiltWith tools to create a highly targeted lead list.


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