Quick answer
The technology adoption curve models how a new technology spreads through a population, dividing adopters into innovators (2.5%), early adopters (13.5%), early majority (34%), late majority (34%) and laggards (16%). Cumulative adoption follows an S-shaped curve.
Formula: F(t) = (1 − e^(−(p+q)t)) ÷ (1 + (q/p)e^(−(p+q)t))
What is the technology adoption curve?
The technology adoption curve describes how a new technology or product spreads through a population over time. Plotted as the number of new adopters per period it is a bell curve; plotted cumulatively it is an S-curve: slow at first, then rapid, then leveling off as most potential users have adopted.
The model comes from Everett Rogers' Diffusion of Innovations (1962), which split adopters into five groups by when they adopt.
The five adopter groups
| Group | Share of adopters | Typical traits | What they need |
|---|---|---|---|
| Innovators | 2.5% | Enthusiasts, tolerate bugs, love novelty | Access and something genuinely new |
| Early adopters | 13.5% | Visionaries, opinion leaders | A big advantage, even if incomplete |
| Early majority | 34% | Pragmatists | Proof it works, references, a complete solution |
| Late majority | 34% | Skeptics, adopt when it is standard | Low risk, low effort, peer pressure |
| Laggards | 16% | Traditionalists | Adopt only when the old option disappears |
Rogers derived the shares from a normal distribution of adoption time: the boundaries sit at one and two standard deviations from the mean.
Crossing the chasm
Geoffrey Moore's Crossing the Chasm (1991) argued that for disruptive technology products the hardest step is between early adopters and the early majority. Early adopters buy a vision; pragmatists buy a proven, complete product with references from people like them. Many products stall in that gap: plenty of enthusiastic early users, then flat growth.
Modeling the curve: the Bass diffusion model
The Bass model (1969) explains the S-curve with two forces: innovation p (people adopting on their own, from marketing) and imitation q (people adopting because others have). Cumulative adoption share is:
F(t) = (1 − e^(−(p+q)t)) ÷ (1 + (q/p) × e^(−(p+q)t))With p = 0.03, q = 0.38 and a market of 10,000 potential users (sample values):
| Year | Cumulative adopters | Share of market |
|---|---|---|
| 1 | 358 | 3.6% |
| 2 | 851 | 8.5% |
| 3 | 1,505 | 15.1% |
| 5 | 3,312 | 33.1% |
| 6 | 4,392 | 43.9% |
| 8 | 6,517 | 65.2% |
| 10 | 8,128 | 81.3% |
New adoptions peak around year 6.2, when word of mouth is strongest. The first three years reach only the innovators and early adopters (about 16%), which is why early growth can look disappointing even for a product on track.
Applying it to product features
The same pattern appears inside a product when you launch a feature. Track feature adoption as the share of active users who have used the feature at least once, by week since launch:
- A steep early rise that flattens at 10–15% often means only power users found it: an "early adopter plateau". Better discovery or onboarding may be needed.
- A slow, steady S-curve that keeps climbing usually means word of mouth or team invites are working.
- Compare adoption by segment: new accounts versus old, small versus large teams. Different segments sit at different points on the curve.
See feature adoption and measure product adoption.
Limits of the model
- The 2.5 / 13.5 / 34 / 34 / 16 split is an idealization; real markets are lumpy.
- Not every product reaches the late majority, and the ceiling (market size) is often overestimated.
- It describes adoption, not retention: people can adopt and then abandon.
In TapCub
To see where a feature or product sits on its curve, track a "first used" event, then chart cumulative adopters as a share of active users over time, and break it down by segment or account. Retention by cohort shows whether adopters stay. See activation rate and aha moment for the moments that turn trial into adoption.
Sources
- Rogers, E. M. (2003). Diffusion of Innovations, 5th ed. Free Press.
- Moore, G. A. (1991). Crossing the Chasm. HarperBusiness.
- Bass, F. M. (1969). A new product growth for model consumer durables. Management Science, 15(5).
- Wikipedia. Technology adoption life cycle.
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Product Adoption Consultant
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