By Matt Rhys-Davies
It is undeniable that web technologies have advanced over the recent years, to the point where we now deal with technologies every day which would have been a mere twinkle in a software engineer’s eye only ten years back. Take for example personalised merchandising tools, that enable ecommerce sites to tailor product selections based on browsing behaviour, incoming channel and any numbers of additional metrics.
It is advancements in all areas of web technology such as the above, that has lowered the barrier to entry for online commerce to essentially everyone with internet access. The days of requiring advanced technical knowledge, expensive servers and mind-blowingly complex platforms have gone (well, they can still exist if you wish to use them), and have been replaced by incredibly user friendly SaaS (Software as a Service) platform such as Shopify.
Taking Shopify as an example – because it’s one of the better known platforms – a retailer, with absolutely no knowledge of front or backend code, payment gateways or APIs, can, in less than an hour, have a slick store front up and running with a secure method of taking payments, automated stock management, and sending order confirmation emails, all with minimal financial commitment and zero technical investment.
Lowering the retailer’s barrier to entry has predictably increased the number of merchants who now jostle for a place in the global marketplace. More competition of course brings with it the need for retailers to set themselves apart from their competitors. In the case of online retail, the foundation to getting ahead is data. Data, data, data.
In the world of online retail almost everything is measurable and quantifiable. Not only can a merchant see where their best converting traffic enters the site from, but they can drill into more niche data. Such as the originating channel of traffic that spends the highest time on site and the journeys they take; what landing pages entice the user to progress further into the site, and what landing pages bounce the hardest, and the most important metrics of all: the view of the conversion funnel.
The funnel is all too frequently overlooked by retailers large and small, yet it provides the merchant with the most insights into their site’s goal: converting users, selling product & making money.
The funnel should ideally be defined as starting when a user adds an item to their basket, and then each subsequent page they are required to visit in order to get to the confirmation page. A typical ecommerce funnel will be: add to basket > cart > checkout (login / register) > checkout 2 (billing & shipping address) > checkout 3 (payment details) > checkout 4 (order confirmation) – although this is dependent upon platform.
Once set up, the analytics package will provide vital information in the form of customer drop off in terms of absolute numbers, percentage figures and visual diagrams; all of which serve to highlight any issues your (potential) customers experience in their effort to become actual customers.
If there’s one concrete tip I can give to get ahead of your competition, it is to assess your funnel. Look at where users drop off, split test elements to see what keeps (potential) customers from travelling down the funnel. It may well be something basic such as the colours of the calls to action or the copy used; or it may well uncover something more intrinsically wrong with your conversion journey e.g. not telling the (potential) customer how long delivery will take. By perpetually assessing your site’s funnel you are working to make the process smoother and easier for the customer.
Data is a gift. Use it. That is how you will get ahead, and stay ahead of your competitors.
About the author
Matt Rhys-Davies is a Freelance Ecommerce Analyst working primarily in UK & European markets, with experience in development, marketing and analysis.