With conversion on mobile much lower then desktop, improving it is a priority for retailers.
How does your mobile conversion measure up?
Finding out how your mobile conversion rates compare with the market average, and with a range of retailers, is the first step towards focused optimisation.
It’s no secret that conversion rates amongst customers using mobile devices is a real issue for retailers. The fact that mobile delivers roughly half the conversion rate of desktop is worry enough - but add shoppers’ growing preference for the mobile channel and it’s little wonder so many retailers now see mobile optimisation as a priority.
But where to start? That’s been the first question for almost all the retailers with whom we’ve worked on mobile optimisation over the last few months. They’ve known it’s a problem, but not how big a problem or where to begin tackling it.
The first step has to be to understand the scale of the problem - to look at mobile conversion not in isolation, but in the kind of meaningful context that provides an answer the question:“How big a problem is mobile conversion for this retailer?”
The work we’ve done in this area at Biglight has generated a huge amount of data around customer behaviour on mobile - and, as a result, we can benchmark performance in aggregate and in micro-conversions from arrival on the site through to checkout.
In this post, I want to look at the top level - the aggregate view. We call it the Mobile Benchmark. It’s a simple, quadrant-style graph that visualises mobile performance, when compared with other retailers and an overall average.
It looks like this (below), the two gold lines marking the average positions on each axis - 50% for the mobile traffic mix, and just over 45% for mobile conversion rate, as a percentage of desktop conversion rate:
This is real data, based on the UK performance of 15 leading retailers of apparel, footwear, homewares and accessories in March and April this year, but the method can be applied to almost any type of retailer. Just follow this simple formula and then plot the results on the same X and Y axes:
- Work out the Mobile Traffic Mix % (the X axis) - Mobile (smartphone) traffic divided by total traffic, multiplied by 100
- Then work out the Relative Conversion Rate % for mobile (the Y axis) - Mobile Conversion % divided by Desktop Conversion %, multiplied by 100.
By looking at relative conversion performance, we eliminate the variation in conversion between retailers for other reasons (such as overall proposition, availability etc), allowing us to focus on the performance of mobile in a relatively comparable context.
In essence, this instantly highlights how big any retailer’s mobile optimisation opportunity is, and how urgently the process should begin.
For instance, a retailer that plots in the top left quadrant is in a relatively strong position - that position denotes a relatively low mobile mix, and a relatively high mobile conversion rate. That means, mobile users are a lower proportion of traffic than average and that those who visit the site using mobile deliver a better than average conversion rate, relative to desktop.
On the other hand, those that plot in the bottom right quadrant have a serious, and urgent problem (or the biggest potential opportunity). The combination of a high mobile mix with a low relative mobile conversion rate is not good news - lots of people are visiting by mobile, but they are not simply not converting.
Of course, those are the extremes. As the example above demonstrates though, most plot somewhere between the two, which shows that, for the vast majority of retailers, there remains a significant opportunity to improve mobile revenue performance.
We’ve noted over time that all data points tend to shift to the right (as mobile continues to displace both desktop and tablet as the users’ device of choice), but there is no evidence of any increase in relative conversion performance as this happens. In short, there is no correlation between an increase in the Mobile Traffic Mix and Relative Conversion Rate over time.
Where the Mobile Benchmark has proven most useful for our clients is in offering visual, empirical evidence of the issue, benchmarked against the market - the ability to share that across the business has proven very handy when scaling the opportunity (relative to both the average and maximum performance) and securing budget to get the mobile optimisation process going.
The next step is to understand precisely where the issues are - which aspects of the mobile journey are simply not working and why.
That, again, starts with a benchmarking process; one that breaks the journey down into stages. We look at ‘Browse to Basket’ and ‘Basket to Conversion’ as two broad steps in the journey - then in more detail at micro-conversions (for instance the product detail page to product listing page micro-conversion), to identify the specific parts of the journey that present the biggest optimisation opportunities.
We then complete structured usability testing, focusing on those parts of the journey, along with other behavioural research, to identify the_why_behind the opportunities the data has revealed. That discipline, along with prototyping major changes, A/B testing and rapid deployment, are the final steps towards delivering a step-change in mobile revenue performance.
I’ll cover those steps in the process in more detail in my next post. In the meantime, why not take the challenge?
Plot your own mobile performance on the Mobile Benchmark and let us know how you get on.