In my last post, I talked about how the Theory of Reasoned Action and the original Technology Acceptance Model tried to predict both intention and usage of new technologies. As a quick recap, let’s look again at Davis and Bagozzi’s original model.

In aiming for the simplest model possible, there was significant conflation applied to the front end of the model – with just one box representing external variables, which then led to two similarly conflated boxes: Perceived Usefulness and Perceived Ease of Use. While this simplification was admirable in the quest for parsimony, in real world situations it seemed like it went too far in this direction. There was a lot happening between the three boxes at the front of the model that demanded closer examination.

Davis indicated that there was an interesting relationship between Perceived Usefulness and Perceived Ease of Use. One of the mechanisms at play that has to be understood is self-efficacy. In understanding adoption of technology, self-efficacy is a key factor. Essential, it means that the easier a system is to use, the greater the user’s sense of efficacy. They believe they have control over what they are doing. And control, especially on a work context, is a strong motivational driver. There is an extensive body of work exploring the psychological importance of control. If we feel we’re in control, we also feel empowered to mitigate risk. The concept of self-efficacy helps to highlight the importance of the Perceived Ease of Use box. But what about the other box: Perceived Usefulness?

Davis, in his accompanying notes and research, indicated that Perceived Usefulness is a stronger indicator of intention than Perceived Ease of Use. In other words, we are willing to put up with some pain to learn a new technology if we feel it will offer a significant improvement in our ability to complete a task. This balancing equation requires two heuristic evaluations on the part of the user: the allocation of cognitive resources required to gain proficiency and the expected usefulness of the tool once proficiency is gained. This is exactly the same equation used in Charnov’s Marginal Value Theorem, applied in a different context. In optimal foraging, we (and all animals who forage) balance expenditure of resources required to reach a food patch against the expected food value to be derived from that patch. In technology adoption, we balance expenditure of resources required to master a new technology against the increased usefulness that technology offers.

In this heuristic evaluation, there are four key marketing lessons for anyone who’s business model relies on the adoption of new technology:

1)   Lessen the intimidation of the learning curve. Persuade the user (and this is a key point that I’ll return to in in point 4) that this is a reasonable investment of resources. Build a sense of perceived ease of use. Provide visible links to intuitive learning resources. Often, marketers overplay the feature benefits of their products to show how powerful they are. But, as they’re doing this, they fail to realize that this upsets the balance between perceived usefulness and perceived ease of use.

2)   Provide clear examples of perceived usefulness in terms that are immediately relevant. Remember, this is the key factor in the equation the prospect is trying to balance. The more salient you can make the perceived usefulness, the more likely the user is to adopt it, even if a learning curve is present. Ideally, get that usefulness across with very specific, industry relevant examples that allow the user to visualize usage of the technology.

3)   Remember that the user is balancing the two factors. Ease of use is great, but it can’t come at the expense of overall usefulness. In fact, in calculating the right balance (which should be done with extensive testing feedback from target customers) it should offer a significant gain in usefulness (as measured against any incumbent technologies) with a relatively manageable investment of resources.

4)   Remember that you’re talking to a user. When trying to strike the right balance, remember that you’ll probably be talking to different people as the decision progresses. For the user, the right balance between perceived usefulness and perceived ease of use must be struck. But at some point, you’ll be talking to a buyer, not a user, before the sale actually is closed. This would be one of those external variables that fall outside the scope of the Technology Adoption Model. This switching of roles from “doers” to “buyers” is dealt with extensively in my book, The BuyerSphere Project.

In the next post, I’ll talk about how the Technology Acceptance Model has been modified over the past 2 decades so it better reflects real world decision making.