TomTom GO subscribers were 3.6× as likely to buy premium software
Subscriber purchase rate divided by the active-panel rate in 2024–2025; 1.0× indicates parity
Multiple of active-panel purchase rate
Source: YipitData U.S. e-receipt panel. TomTom GO subscribers n=1,790; active-panel benchmark n=2.75 million. App-store identification can favor more observable inboxes.
Chart data
| Series | Multiple of active-panel purchase rate |
|---|---|
| Premium software with a free alternative | 3.6× |
| Commodity retail and fast food | 1.9× |
What were the underlying purchase rates?
Premium software appeared for 26.2% of TomTom GO subscribers versus 7.2% of active panelists, producing the 3.6× difference. Commodity brands appeared for 51.7% of subscribers versus 27.4% of the panel, a smaller 1.9× difference.
Which individual services had the largest gaps?
The purchase rate was ~8.8 times the active-panel rate for 1Password, ~8.1 times for Garmin, ~6.7 times for Perplexity, and ~6.1 times for ExpressVPN. Each service-level result was based on roughly 40–60 TomTom GO subscribers, so those individual multiples are directional; the composite software basket is the more reliable result.
Does this reveal whether TomTom GO subscribers also use free navigation apps?
No. Google Maps, Waze, and Apple Maps do not generate purchase receipts, so the panel cannot observe their free use. The comparison identifies a broader tendency to pay for premium software; it does not measure navigation substitution, TomTom GO retention, or response to a new price or bundle.
Assumptions & Methodologies
We identified 1,790 U.S. e-receipt panelists with a TomTom GO Navigation receipt from January 2023–June 2025 after excluding unrelated Tom Tom text matches. Purchases were measured in 2024–2025. The premium basket covered paid security, AI, productivity, finance, and storage services with prominent free alternatives; the control covered commodity retail and fast-food brands. Each multiple divides the cohort purchase share by the 2.75-million-user active-panel share. The cohort ends before a later receipt-template break. App-store capture, panel composition, and residual purchase-observability differences can affect the comparison, and co-purchase does not establish causality.