Wall Street is now selling more data like social media sentiment and geospatial mapping, and less analysis as only ~21% of research emails are opened
Research units take different tack to refine information for clients; geospatial mapping for mall trips and Googling interest in ‘Luke Cage’ Tweets: @briantimoney and @charlesraaii Tweets: Brian Timoney / @briantimoney : Wall Street discovers the wonder of the drive-time polygons to replace their radius-buffers to say profound things about mall preferences. Wait till they hear about Amazon Prime. http://www.wsj.com/... http://twitter.com/... Charles Rotblut / @charlesraaii : More proof that individual investors have lost the technology battle. Your trading app can't do this. https://www.wsj.com/... via @WSJ
Context & Ripple Effects
This 2018 report sits mid-arc in Wall Street's long renegotiation with data. Two years earlier, banks were fighting fintechs like Mint and Betterment over who pays for access to customer financial data — the industry already treating information as a priced asset rather than a free byproduct. What changed here is the product itself: with only ~21% of research emails opened, sell-side shops stopped leading with analyst prose and started packaging feeds — drive-time polygons around malls, 'Luke Cage' tweet volume — as the deliverable.
The pivot proved durable rather than episodic. Within a year, satellite data startups like Orbital Insight and SpaceKnow were institutionalizing the same model for hedge funds, selling imagery-derived signals instead of reports. By 2021, after GameStop, institutions had come full circle — hiring teams to scrape Reddit, Twitter, and Discord for the very retail chatter this article first monetized.
First-order effects
- Buy-side clients receive raw or lightly refined data products — geospatial trip counts, social sentiment scores — in place of analyst write-ups, whose ~21% open rate has made the traditional email deliverable commercially dead weight.
- Analysts' value proposition shifts from judgment to curation: their firms now compete on the freshness and exclusivity of licensed signals, exemplified by the drive-time polygon work Brian Timoney flagged replacing crude radius-buffers.
Second-order effects
- Alternative-data suppliers gain a direct sales channel into banks and hedge funds, turning satellite operators and social-data vendors into upstream vendors whose pricing power grows as the sell-side becomes a reseller of their feeds.
- Charles Rotblut's observation that retail trading apps can't replicate these datasets points to a widening tooling gap: individual investors are structurally locked out of the same information their own social activity generates.
Third-order effects
- If the pattern holds, sell-side research consolidates around platform economics — whoever aggregates and licenses the widest signal set wins — echoing how the same institutions later built desks to monitor retail forums directly, closing the loop between the data sellers and its sources.
- The structural endpoint is a two-tier market: institutions trade on proprietary feeds while retail investors act on public sentiment, a split that regulators and platform operators become the de facto arbiters of.
The trend: Sell-side research is recomposing from analyst judgment into licensed data products, with competitive edge defined by signal latency and exclusivity rather than written analysis.