As well as reducing overheads and offering greater convenience for their
customers, online retailers have an additional advantage over their
bricks-and-mortar competitors - data capture.
They can easily see enormous amounts of information on their customer
behaviour while browsing their online store, such as the most popular sections
of a site, the time spent on certain pages, where customers leave the store
without buying and much much more.
The ability to analyse such information and to accumulate and compute
‘big data’ - that which is not possible to process using traditional
information management processes - is now a standard part of a website’s
infrastructure, and additional free tools, such as Google Analytics, make the
job even easier. With such analytical power, the online retailer can enhance
every area of strength and reduce weaknesses - improving calls to action on
less productive pages, testing the conversion rates of different designs etc.
How can the high street compete with such consumer insights? Well,
technology is not limited to the online world. Consumer research specialists
are developing powerful tools of their own, and retailers are no longer limited
to just seeing which products have shipped the most come 5pm.
In-store analytics is helping to bring big data to the high street and
64% of retailers plan to invest in this area in 2014.
Why do they want this in the first place though? What can they gain? The
benefits of improving poorly performing web pages for example are clear, but
what are the physical equivalents?
Sales goals are the same:
- Increase customer loyalty
- Reduce returns
- Increase average sale value
- Increase sales volume
In-store, through a combination of video, wi-fi and Bluetooth it is possible
to gain aggregate data on how many people enter a store and when, where they
walk to, what they are looking at, what they buy and what they don’t buy. You
can measure the interactions of sales staff as a group or by role. You can
measure how other variables such as weather or ambient temperatures effects
these behaviours and interactions. These measurables may vary by the hour, by
the day and by the week. There are a number of companies, such as Blue Yonder Research based in Leeds, UK, who deliver such retail insight with technologies deployed in test environments or real life retail settings.
Thousands of data points can be collected on an individual customer’s
visit to a store on a single occasion, so multiply this by thousands of
customers, perhaps making multiple visits in a year, and across a retailers
chain of tens or hundreds of stores, and you can imagine how we end up in the
realm of ‘big data’ vs just ‘data’.
All this information can be collated and analysed to help a retailer
make informed decisions in areas such as staffing, merchandising and seasonal
promotions. The end goal being to maximise the return on investment (ROI) per
shopper visit. How do you convert as many visits as possible to a sale, how to
you maximise the value of that sale and how do you minimise the cost of
generating that sale?
This all may sound quite impersonal and even predatory - seeing each
customer with a dollar sign over their head. However, to maximise the use
of this data, retailers need to improve the experience of the customer to
signpost them to what they want, to help them make informed decisions, and this
is what will ultimately generate sales and loyalty. By using big data to
enhance customer experience and improve profitability, it can deliver a
win-win - and the high street looks set to benefit as much as any other area of
business.
