The psychology of buying new tech

Sandra Pretorius

Sandra Pretorius

Marketing Director at Reapit

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Understanding what’s driving our decisions to try a new category and a new product or service.

A few months ago, I was delivering a presentation on the psychology of buying, and one of the questions, designed to gauge our innate aversion to trying ‘new’ tech, was asking who bought their groceries online and who didn’t. The result was surprising, to say the least. And especially interesting against the backdrop of the current lockdown. 

Asking the question, I assumed that most of the attendees would be in favour of buying online due to the sheer convenience of it all. It turns out that less than half of the people in the room shared my enthusiasm for the virtual trolley. Reasons cited for still going into the actual store boiled down to not being sure they’d get the best product, or the right product, and having an overall lack of trust in the process.

It was a classic example of the phenomenon that Kahneman and Tversky coined “loss aversion”. Every new purchasing decision we make is underscored by a very powerful driver: the need to avoid a loss – and it’s worth remembering that loss is not always financial by nature but could mean loss of time, loss of convenience, loss of control etc. In their Nobel-prize winning research, Kahneman and Tversky found that ‘losses loom larger than gains’, and as a result what we have is often valued higher than what we might have (even if that is a completely irrational evaluation). It goes a long way to explain why a consumer might decline using a new product or service, when it actually seems perfectly rational to purchase it. The same goes for the way we do things, for example online buying. 

And then the plot thickens. When it comes to choosing a new technology, be that a new phone or new CRM software, there’s another layer of decision making that flows from our innermost need to avoid loss, and it’s best described by the Unified Theory of Acceptance and Use of Technology (UTAUT) by Venkatesh et al., built on the original Technology Acceptance Model (TAM), one of the most widely used frameworks for explaining why a consumer will accept(try) and continue using a new technology. The framework suggests that there are four driving factors that lead to a person’s acceptance of a new technology: 

·      Performance Expectancy (or Perceived Usefulness in TAM) – will this new piece of tech deliver a real gain to me?

·      Effort Expectancy (or Perceived Ease of Use in TAM) – is this easy enough to use? 

·      Social Influence – are others using it and are they expecting me to do the same? 

·      Facilitating Conditions – is there enough technical support for me when I use this system?

In summary, collective research tells us that we will only choose and accept a new technology if the wins are significantly more than the expected losses (Kahneman puts this at approximately 2,5 times higher than the perceived loss) and if we see it as both useful and easy to use. Added drivers will be social pressure and the assurance that there is enough support facilitating the new choice. 

Back to my online grocery example in the context of a worldwide pandemic: in the span of a few days our behaviour and choices have shifted dramatically at the start of lockdown, with online shopping sites like Ocado experiencing unprecedented demand, leading to the crashing of their website and app, as well as a current queueing system on their website.  And that’s got everything to do with how we calculate loss. When comparing the loss of a bruised aubergine to the loss of possibly contracting the virus by going into a store, the win/lose calculation was dead easy to make. Suddenly, those who had no idea where to even start with online shopping, were clamouring for the privilege to add to cart. 

So let’s for a moment, stop and consider the decision making set for an online shopper, against the decision making frameworks I just mentioned: 

Win/Loss Calculation: either you buy online, or you risk your health going into a store. Right there is a win that far outweighs any losses you may have, either in time as you try to learn how to use a new platform or in satisfaction when you receive peas instead of the ordered sweetcorn. The losses in this case pales in comparison to the possible loss of life. 

Supplier Benefits Calculation: after deciding to try the category, the consumer’s actual choice of an online grocer was probably more closely influenced by the UTAUT framework, including the ease of use, how many other people are using it and the degree to which the buyer thought there would be support if anything went wrong. 

In summary, when it comes to adopting a new technology, consumers are often choosing both a category and a brand in the category. When they choose the category, the decision is probably being made at a win or loss level. When they choose their supplier in that category, it is more than likely based on the UTAUT framework – and that’s where the marketing function in your organisation plays a pivotal role. 

One of the greatest mistakes we can make is to impose our own inner-company mindset on the prospect, assuming they perfectly understand that our product or service is the superior choice in the market – and that the only discussion to be had is whether they want the standard or premium version of our product. But to the prospect, we’re just part of a line-up of products in a category they may still be considering to start off with. 

It’s your marketing team’s responsibility to understand what the aversions to loss are for their specific target market (through qualitative and quantitative research primarily) and to then market the wins against the perceived losses, all the while making sure the usefulness, ease of use, popularity and social necessity, as well as available support for your product is being sufficiently and consistently communicated at all levels in the marketing funnel. P.S. If this article sparked your interest, you will definitely appreciate this Harvard Business Review article by John Gourville, diving deeper into Kahneman and Tversky’s research.

This article was originally published on LinkedIn.