The market leaders in ride-hailing apps both took their stock public in the first half of this year, and both similarly suffered inauspicious first-day trading. Our analysts were not surprised by this because our data science team, using two types of alternative data, had confirmed their existing doubts about potential rising costs and potential declining sales growth.
On the costs side, from direct deposit information, we were able to identify Lyft and Uber drivers from our sample of bank account data. Through 2017 and 2018 that data showed a rising percentage of drivers working for both companies. That implied declining driver loyalty and increasing driver churn even as the absolute number of drivers was rising.
On the sales side, from credit and debit card transactions, we found clear evidence of rapidly declining new customer growth for all three of the leading ride-hailing firms, which suggests that future revenue growth will be ever more reliant on increasing use by existing customers.
Driver Preference – Lyft vs. Uber
New Customer Rate: Rideshare Rivals
Source: Second Measure, Neuberger Berman.
These findings were not decisive for all portfolio managers: some decided not to invest; others saw the findings as a counterpoint to a strongly held investment thesis. All would agree, however, that these cases show how alternative data can provide a unique window into the true performance of pre-IPO companies. This case also shows how there is more to bank account data than consumer spending insights (payments out of accounts). Payments into accounts (e.g., paychecks) are key to explore labor mix and labor costs for individual companies, sectors and the economy as a whole.