Offline & online stores: Parallels in optimisation?

In some ways online stores have much in common with bricks and mortar stores. The online home page is the offline storefront, online categories represent the sections you would find in an offline store, and the page names represent the section signs. Similarly, ads and email marketing act like display windows, while the landing page is the first section you visit near your chosen entrance is how you move from section to section in the store, and the search box is when you give up, and approach the counter to ask for help. The shopping cart is an obvious grocery store reference and the product details page is a poor replacement for actually holding the item in your hands.

But despite those parallels, with the offline store, optimisation is completely different online. That said, web site optimisation has borrowed some ideas from bricks and mortar store optimisation - which has a long history.

Offline store optimisation: How did it start?


The grand piece of literature regarding offline store
optimisation is
Why we buy: The science of shopping by Paco Underhill, who started the field of offline store optimisation in the late 70s. He was a psychology graduate student who was working in a building complex in Manhattan. His job was to examine if it was possible to expand a gift shop store in the building without congesting the pedestrian walkway nearby - and, as part of that assessment his team installed video cameras that monitored the pedestrian pathway 24 seven.

The birth of optimisation

While examining the long hours of film, Underhill couldn’t help noticing the action taking place inside the gift shop.

For instance, he noticed that the way customers were handled at the counter could be improved using his knowledge of anthropology. That was the starting point of the science of store optimisation - and Underhill started a company that helped retail businesses to optimise their stores.

The idea was to have people monitor the stores and the customers in it. They kept notes on customer attributes, e.g. age, gender, and also any action the person made. They calculated throughput of customers in the store, the conversion rate and they experimented with sign placement and product placements, always measuring effects of their changes.

If this type of undertaking looks familiar, that’s because it is exactly what website optimisation is about. It is just that website optimisation is the science of optimising a store online.

In the book, Underhill explains a crucial difference between online optimisation and offline optimisation. In offline optimisation, he points out, store spies can follow people around, carefully taking notes.

Even though these observations are few, they are thorough and detailed. A human being can experience the situation and use his or her entire knowledge - learned from living for 20-40 years - together with the retail training combined with a mix of commerce theory and anthropology.

Online store optimisation: Are there similarities?

Online, machines crunch the numbers, and although we can analyse even big data, it is much harder to come to definite conclusions, since it is hard to teach machines the lifelong knowledge a person has acquired.

Also we cannot directly transfer knowledge from the offline setting to online, since the obstacles are different. In a bricks and mortar store, an issue with the store design can be that the signs are invisible at specific locations in the store. But, while we can observe similar issues online around how we receive and interpret information presented to us - the problem is not directly comparable.

Another offline problem that Underhill discovered is the butt-brush effect. The observation is that people do not like to kneel down to grab products near the floor level, because by this move we expose our rear end and risk bumping into other customers. Thus, we spend less time examining products below our knee-level. This cause and effect reasoning clearly doesn’t transfer to online.

There are probably other similar situations to watch out for online, but we cannot observe them with our own eyes - in order to identify the underlying problem requires more sessions than offline.

Online optimisation and testing

Online store optimisation is a subfield of web site optimisation. The main tools used for optimising sites are A/B-testing or multivariate testing. Let us say that we, for some reason, want to test different versions of a page, because we believe that the current version can be improved.


In A/B-testing we create a set of different variants
of the page, then we partition the site traffic into equal sized groups, one group per page variation. Then we assign one variation per group and let the customers in the groups be exposed to their assigned variant. The result is collected and is measured according to a chosen KPI. The best variation is selected as the new default strategy. Once a test is finished, a new test can be issued.

We can also test several different variations at the same time. These variations may have to be tested simultaneously, since they can be interdependent. In such situations we need to fall back to multivariate testing, in which we need to create a much larger set of variations, one for each combination. Needless to say, we cannot test too many variations in this way, since the number of variants needed in testing will explode with the number of test items chosen.  

Even though store designers have A/B-testing tools at their disposal, store anatomy has not changed much since the first online stores were launched.

Is this proof that we have found the perfect design pattern or evidence of our inability to find new ways to communicate?

In the following posts we’ll revisit each page type again, and describe what to expect of the page, what each section on the page contains, and why it is there.