To wrap up our “Fake Analytics” series on e-commerce, we
interviewed Benoît Gaillat, an e-commerce expert who shares his experience and
gives us his vision of the use of Web analytics in an e-commerce context.
Find all the articles in the series:
Fake analytics: “I don’t have time for analytics”
Fake analytics: “I’m investing everything in traffic acquisition”
Fake analytics: “I do all my reports in Excel”
Hi Benoit, can you introduce yourself in a few words?
I am Benoît Gaillat, an e-commerce expert for more than 15 years, independent
e-commerce consultant and author of the info-ecommerce blog.
I mainly work as a freelance e-commerce director for companies and
e-commerce sites that need support in their e-commerce strategy.
The aim is to increase e-commerce revenue by developing sales, streamlining
marketing, automating processes and making them more reliable, etc.
In this context, data and analytics are two essential points I rely on to
improve my customers’ e-commerce sites.
What are the main data and analytics challenges for your e-commerce customers?
An e-commerce purchase generally consists of 4 phases: acquisition,
conversion, loyalty and logistics. Today more than ever, e-commerce is highly competitive,
and this leads to a surge in customer acquisition costs.
It is therefore quite logical as a merchant to turn to conversion and
loyalty to develop your business.
And so far, using data as a basis is the best way to do this. The real
challenge for my customers is to make the data more reliable, then to store it and
to use it as efficiently as possible.
Ensuring reliability is key because when the amount of data explodes, you
have to be sure that it will be collected.
Storing it in the right way has also become even more important with the GDPR.
And its exploitation is vital because collecting data is of little use if
it is not transformed into action.
Today, at most of the merchants where I work, these axes are in place, but
it is generally necessary to continue to automate, ensure reliability and
increase in power.
Many companies use free tools, including GA. What do you think about that?
Google Analytics is obviously a source of data, but what bothers me most is
that it is often “a default choice” or used “just because it’s
free”. I rarely have clients who have carried out an analysis of the tools
on the market to check which one was the most suitable.
This can result in a lack of data or simply problems of adaptation between
the company and its analytics tool.
There is a lack of information about the limits of GA and its role in the
Google world. Without painting too dark a picture, GA is a measurement tool
developed by Google engineers, to whom the merchant often spends a large amount
on Google Ads. I can’t see Google engineers making choices to default their main
source of income. The day Facebook Ads, Bing Ads, Criteo or others are
integrated natively into GA, I may change my point of view.
Are we sure we can get quality data with this kind of tool?
Overall, it is possible to work with any tool but again, if you do not
clearly define your needs and do the actions “by default” there is
little chance that the data will be reliable.
A well-configured and reliable analytical tool requires work, especially in
e-commerce. Placing the tag is only part of the job. To limit server costs, it
is also necessary to see that some analyses can be partial. Sampling can be
useful for displaying data quickly but can represent a discrepancy with actual
data. Since some merchants confuse web analytics with their CRM, sampling is
not always easy to explain. Generally, the biggest problem I see is that with
GA, merchants don’t spend enough time on their tagging plans, and they are
often false or very partial.
We are sometimes convinced about the ideal purchasing path. How can I be on
the safe side?
Being sure is “difficult” in web analytics. My philosophy is
rather to make assumptions, measure them, test and start over again.
To answer the question more precisely, the ideal purchasing experience for
me is when 100% of visitors convert!
In all honesty, today, between the different modes of consultation, mainly
mobile, desktop, and the splitting of purchasing paths, it is difficult to talk
about an ideal purchasing path.
This makes data analysis even more necessary. It’s important to get out of
the “I think so” and analyse factually where visitors are going. We should
also be interested in paths that do not convert.
Answering the question “Why people don’t go further by visiting this
page” can bring you as much money as answering the question “how to
optimise my purchasing experience”.
Do you think that the GDPR is a brake or an opportunity for digital
marketing actors?
Even if the GDPR is a step forward in terms of content, in terms of form,
for the moment it is more of a nuisance for customers, on the use of the sites.
What we are seeing is a massive circus: popups everywhere on the sites,
dark patterns to mislead the Internet user about whether or not to activate
data collection, access to the site denied if cookies are refused…
In short, there is still a lot of cleaning up and best practices to adopt.
Basically, this is obviously a good thing and will encourage a little more
respect for users’ privacy. This at least has the advantage of having made the
use of data a central subject in all digital media. I hope that more and more
solutions and sites will really be “privacy by design”. In my
opinion, this is the real meaning of the GDPR.
Anything to add?
Data has taken the lead in many e-commerce fields (fortunately!) but not
everyone is trained as a statistician. This sometimes leads to misunderstandings,
but it is quite difficult to explain this to a customer or e-commerce manager.
Recently, I heard an expression that I really liked:
“On average, if you put one hand in the freezer and one hand in the oven, everything is fine.”
This illustrates the fact that we must not rely solely on one data, but that we must put it in context – and that statistics, web or other, require a real approach to be actionable.
