Why the man who invented eCommerce didn’t bet on data

Inventor of eCommerce

Inventor of eCommerce (photo credit: Michael Aldrich Archive)

Michael Aldrich invented online shopping in 1979 – and geriatric grandmother, Mrs Jane Snowball, was one of the first people he ran user experience (UX) tests on.

Yep… in 1979 – disco wasn’t quite dead and the Internet wasn’t quite born. But Michael Aldrich successfully got people to shop online because he wasn’t a slave to existing data.

He rose above the limitations of quantitative data and went in search of qualitative data. When he got the idea for online shopping, this was one of the first things he said:

“There was no market, no demand and no infrastructure. Perhaps it was all nuts. We had to get a reality check. Talk to real people. Get some feedback. Get some reaction.

There’s an amazing writer called Scott Berkun – I follow him on Twitter and you should too – who wrote an article about the dangers of faith in data.

His article inspired me to write this one, specifically for eCommerce professionals (which I am too). Here are 3 reasons an over-reliance on analytics and quantitative data is dangerous.

1. None of us are *actual* data scientists – not even the people with “data” in their titles

Prominent experts argue that “data science” is an unregulated, made-up thing statistics is perceived as the appropriate scientific field.

Why does this matter? There’s a sobering list of cognitive and research biases that can taint the way we collect, analyse and apply data. The scientists who use data to draw high-risk conclusions have to learn these biases (and many other corollaries), so they can be mitigated.

eCommerce professionals don’t have to do the same – understandably so (our job is demanding enough, in its own right).

Let’s not even get into the problems with the technology that collects data – e.g. Google Analytics and the ways it can skew your numbers.

eCommerce inventor UX testing

Mrs Jane Snowball during a UX test (photo credit: BBC)

2. Data can’t “say” or “drive” anything – data needs to be interpreted

Mock human reasoning all you want (I certainly have), but you can’t escape it. All data still needs to be processed by a human mind before it can become useful.

The data isn’t driving you, you’re driving it. As Tom Lloyd, our head of marketing, says: 

“Don’t be data-driven, be data-informed.” 

I also want to draw a distinction between reasoning and guessing. Reasoning is the application of our senses and faculties to come to a conclusion – guessing is the abandonment of our senses and faculties, then pulling a conclusion out of our arses.

To effectively apply data, you still need the human touch.

3. Relying on only one type of data is like begging to be lied to

Data, like a flashlight, is only as useful as the person wielding it… To get good information you want multiple sources so you can triangulate information and compensate for the inherent biases each kind of data has.” Scott Berkun

Don’t rely solely on analytics and A/B tests… or, indeed, only on UX testing and qualitative data. Combine quantitative with qualitative data and UX testing – just like the inventor of eCommerce did – to achieve unprecedented growth.

Check out the microsite: UX and eCommerce – Separated at Birth

Michael Aldrich’s story, and the successes of our clients with UX testing, inspired me and the team to create a microsite for helping eCommerce professionals increase online sales.

It explains how UX and eCommerce were separated at birth – and how bringing them back together will blast the revenue from your eCommerce site through the roof.

UX eCommerce Optimisation

Eco (eCommerce) and Uxley (UX) – the stars of our microsite

Reunite UX and eCommerce

Timi is a London-based copywriter and full-time marketing sceptic – there are now more unvalidated opinions out there than ever.

He became a UX testing enthusiast after seeing its power while working at TUI – the world’s largest travel, leisure and tourism company. He then joined WhatUsersDo to sharpen his UX knowledge and work side-by-side with the field’s best and brightest.

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