1/ So I use to run a competitive intel team and spent a god awful amount of time sourcing data.

If you aren't familiar with Second Measure they effectively aggregate online sales data (ie credit cards) which they then sell to co's as market share data https://www.bloomberg.com/company/press/second-measure/

2/ In the old offline world, retailers such as Walmart, Target, etc. would sell their sales data to someone like Nielsen. Nielsen packages this up with consulting services and resells it back to manufacturers (ie P&G, Colgate, etc.) or other co's such as investment firms

3/ This structure has not replicated itself in the online world. Amazon, DoorDash, Netflix, etc. aren't sharing their data with anyone.

4/ If you wanted to procure online market share in a particular category you have a some options.

1. Consumer panels and surveys
2. Banks / credit cards
3. Apps that skim your receipt emails
4. Apps that can see your transactions (ie Honey - not sure if they actually do this)

5/ Aggregating all this data in a way that is accurate is hard. You need huge unbiased samples with sophisticated data science models. Even if your off by a 2-3% that would be unacceptable to most clients since they're making >$100M decisions based on this stuff

6/ And each source has its own issues. Ie credit card data doesn't allow you to drill down to the city or neighbourhood which is important for someone like DoorDash. Apps that skip your email are biased towards certain users and can have sampling issues

7/ This data can be particularly helpful for making investments. Ie VCs might use to determine which start-up to invest in for a particular category. Sell-side would use this to inform their models.

8/ Second Measure is one of the industry leaders. So, Bloomberg already has a captive customer base and salesforce. Similar to $SFDC or $ORCL, their plan would be heavily cross sell this at a premium. Lower CAC and higher prices = profit