Why TickerTrends Is Built to Outperform Legacy Equity Research Firms & KPI Forecasting Businesses
Why Software-First Architecture Changes the Economics of Alternative Data
Most alternative data and research firms today are not really software companies. They are research organizations that use software.
It shows up everywhere in how these businesses scale.
Firms like Yipit and M Science do good work. They employ large teams of analysts and have spent years building coverage. But their model is fundamentally human-driven. Each new company they cover requires analyst time, custom work, and ongoing maintenance. As a result, their coverage scales more or less linearly with headcount.
You can see this in the numbers:
Yipit covers on the order of ~170 companies and brands.
M Science’s core research coverage is ~254 companies.
TickerTrends already has 337 tickers with deep coverage.
And we didn’t get there by hiring hundreds of analysts.
Software First vs Research First
TickerTrends was built as a software company from day one. The core of the business is not analysts writing reports. It’s infrastructure:
Data ingestion pipelines
Normalization and cleaning systems
Automated mappings
KPI extraction and time series generation
When we add a new data source, it doesn’t just improve one company. It improves coverage across the entire system.
That’s the key difference.
In a research-first model, adding one company is a project.
In a software-first model, adding one data source or improving a system upgrades everything.
Why This Scales and the Old Model Doesn’t
For legacy firms:
More coverage = more analysts
More analysts = more coordination, more cost, more overhead
Every new company increases ongoing maintenance work
For us:
More coverage = more pipelines and better mappings
The marginal cost of adding the 400th or 1,000th company keeps going down, not up
That’s why we can already support:
337 companies with deep KPI-level coverage
Tracking for thousands of public businesses
Data for tens of thousands of businesses, private and public
And that’s also why this gap will keep widening.
Coverage Is a Byproduct, Not the Goal
We don’t decide coverage one company at a time.
We build systems that ingest large data sets, and coverage falls out of that automatically.
That’s a very different way of working:
We don’t ask “should we add this company?”
We ask “what data do we need so that all relevant companies are covered by default?”
This is also why our coverage is more consistent and more comparable across companies. It’s coming from the same underlying machinery, not from 300 slightly different analyst processes.
What This Means Long Term
The legacy research model will always exist. There will always be a place for human judgment and bespoke work.
But it will never be the best way to build or maintain coverage across hundreds or thousands of companies.
That’s a software problem.
And software scales very differently than organizations.
TickerTrends already covers more companies deeply than these firms. But more importantly, the way we’re built means that number can go from 337 to 1,000+ in a matter of months.
Not bigger teams.
Better systems.
For more information about access or the TickerTrends KPI Forecasting suite, please contact your TickerTrends representative admin@tickertrends.io