Page 54 - Decoding Decisions ~ Making sense of the messy middle

54 CHAPTER 4 INFLUENCING THE MESSY MIDDLE

We wanted participants who were familiar with online shopping, so to
control for this we selected people who said they had shopped at the UK’s
largest online retailer. Likewise, we wanted shoppers who were familiar
with searching for products online, so we selected people who had used
the UK’s most popular search engine for that purpose. Together, these two
characteristics provided a broad, qualified sample of participants familiar
with the parameters and conventions of online shopping. 18

The final and most important qualification was that every participant had

to be in-market for the product featured in their simulation, and intend to
purchase it within a timeframe appropriate for that category (in other words,
for car shoppers the applicable window would be longer than for someone
buying shampoo). We also excluded anyone who said they had already made
their mind up about exactly which product they were going to buy, to exclude
the possibility that participants might have already exhausted their capacity
for exploration and evaluation.

To ensure a robust sample size for each product, we recruited 1,000
shoppers in every category. This equated to several thousand shoppers per
sector, and a total sample of 31,000 in-market shoppers for macro-level,
cross-category analysis. Participation was remote, with each shopper
completing 10 purchase simulations within a given category, giving a total
of 310,000 purchase scenarios within which to analyse our six cognitive
biases. Because of the prejudicial effect of measuring the presence of a bias

against the absence of the same bias, we paired different levels of execution
ranging from strong to weak (for instance next-day versus seven-day
delivery, or five-star versus three-star reviews).

We believe that our tests amply – and with statistical validity – demonstrate
the fluidity of preference between trigger and purchase. However, the results
of a simulation can only ever be indicative, and as such we don’t suggest that
anyone should treat our results or recommendations as a substitute for their
own rigorous, in-market testing.

So, with caveats and methodology taken care of, on to the experiments.

18 Respondents who never use Google Search or never use Amazon (2% of category buyers aged 18–65) were screened out before participating in the research.