Uptake by people of a product can, slightly artificially, be seen from two perspectives; that of the people, and that of the product. This article looks at three theories, loosely along those lines, from two American professors in the 1960s.
Bass Diffusion Model
This was published in 1969 by Professor Frank Bass of Purdue University, and is one of the most used models in marketing. The version presented below uses the same equation but has rearranged it slightly- there is an entire website devoted to it if you want to use the original. The main difference is that the original presents the result as a probability of uptake, whereas in the below version both sides have been multiplied by total addressable market size to give number of new adopters as the output.
The model aims to tell you how many new customers you will get in a given time period in a given country.
It makes the assumption that there are two types of homogenous potential buyers, innovators and imitators. Innovators will buy a new product regardless of who else has bought it, so the number of new innovator customers you will get is simply a function of the number of innovators in the target market who have not yet made a purchase.
Imitators will only buy based on a more complicated function of how many other people have bought the product, as well as of how many non-customer imitators there are left in the market.
Let
- i = target country
- t = time period
- S = size of population (number of people)
- C = adoption ceiling- the maximum proportion of S that could feasibly be customers (fraction)
- CS = size of the target market (number of people)
- N = number of previous cumulative adopters (number of people)
- CS – N = untapped potential (number of people)
- N/CS = penetration of target market (fraction)
- n = number of new adopters
- a = coefficient of innovation (“the advertising effect”)
- b = coefficient of imitation (“the word of mouth effect”)
With these components we can build the model piece by piece. The first thing to note regards inputs. S is demographic data. C is economic data. Only CS is business data, so any modelling you see based on demographic or economic data is going to be inaccurate.
Sometimes “M” is used for CS, as Market, but here it is left as CS because that tells you where to look to find the data inputs you need. If your product costs £100 per year, then only people in your target country with £100 in disposable income (not GDP/capita) are feasible customers.
We can start with the innovators. Each time period t, a number of innovators will adopt your product. This is the coefficient of innovator uptake, a, multiplied by the remaining untapped market size, CS – N. So new innovators = a x (CS – N).
Imitators have their own coefficient of uptake, b, but before it is multiplied by the untapped market size, CS – N, another factor must be considered. Imitators, by definition, adopt based on the number of other existing adopters, N, relative to the total market size, CS. So we must multiply b by the penetration fraction, N/CS. Thus, our number of new imitators each year are b(N/CS) x (CS – N).
We can add our new innovators and new imitators together, for a time period t in country i, to get our total number of new adopters, n; in other words, our uptake.
Calculating a and b is difficult early on. Use estimations based on proxies at the start, and then use regression once you have enough data. Each will vary by product but generally a ranges from 0.01 (consumer durables, like a toaster) to 0.05 (free subscriptions). b ranges from 0.35 for consumer durables to 0.9 and more many tech products.
The cumulative uptake curve is an S-curve, and the steepness of the curve will depend on the ratio of b:a. The larger that ratio, the steeper the curve will be. Even if the numbers are not available to calculate the maths, this still provides a useful insight into your own uptake forecasts in relation to your marketing plan.
Slow sales which then hit an inflection point and rapidly grow mean an assumption that your coefficient of imitation is very high relative to your coefficient of innovation; word of mouth will drive uptake once you get enough mouths on board. So you may reasonably ask for investment to purchase those early innovators at a loss.
A smoother curve means advertising and innovators will play a larger role. That means your customer acquisition costs will always be higher, but that you should be able to see returns on marketing spend fairly early on.
A linear curve means your product will be different from 50 years of accepted marketing wisdom- as always, that’s possible, but you’ll need a lot of data to convince an investor of it.
Rogers Diffusion of Innovations
Professor Everett Rogers published a book, “The Diffusion of Innovations”, in 1962. The next two theories are both from him.
Under the Rogers diffusion model, the participants in uptake were broken down into more than just innovators and imitators. He modelled uptake on a normal distribution (bell curve), and then divided the customers behind that uptake into groups by z-score.
The blue line shows the number of new adopters at any time. Rogers labelled the five groups as shown, and assumes a smooth transition from group to group. The yellow line shows the cumulative uptake, or S-curve.
For each group, the idea is to determine the key characteristics, so that you can work out which of your potential customers fit into which group. This gives you more realistic targets as you move (or fail to move) through the groups and grow your cumulative adoption. The below characteristics are very general but are food for thought in both B2B and B2C situations.
- Innovators (2.5%). High risk tolerance, and the ability to absorb failure of the new product (often through having a better financial position).
- Early Adopters (13.5%). Focus is on opinion leadership, so they are more discriminating in what they adopt, and are driven by a desire to maintain a central communication role from dispersing knowledge.
- Early Majority (34%). Slower uptake, and have contact with opinion leaders without being ones themselves.
- Late Majority (34%). Sceptical of innovation and have little contact with opinion leaders.
- Laggards (16%). Have a preference for tradition or routine, and are apprehensive of change.
If high risk tolerance and a strong financial position doesn’t describe your local hospital trust, then they may not be the ideal innovator and first customer for your new medical product!
Rogers Five Factors
Another theory taken from Rogers moves across from the people-focused view to the product-focused view. It looks at five aspects of the product itself to determine what blockers and drivers there will be behind its uptake. Note, however, that all five factors are perceptions, not absolute facts, and so an understanding of the user journey is still necessary.
- Relative Advantage. This is the degree to which people perceive the product to be better than the existing product it is replacing. Value might be a question of price, servicing, prestige, or anything else.
- Compatibility. The perception of how well the new product fits with their values, experiences, needs, and so on. This can have a negative requirement- for example, in high fashion, people might want the new product to have nothing to do with other offerings.
- Complexity. The perception of how difficult to use the new product will be, often an externality of differentiation.
- Trialability. The perception of how much someone can test it before committing to it. This can be demonstration, like make-up booths in large shops, or free samples, like movie trailers.
- Observability. The perception of how much use of the product, and any impact from its use, are observable to others. Ferraris and weight-loss pills score highly, spatulas less so.