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Millions lost: Juno Results Prove that eCommerce Must Optimize Mobile

Earlier this month, Internet Retailer reported that top retailers in Q4 missed growth expectations by a significant margin. While analysts put the Q4 YoY growth for top retailers at 14-15%, the group included in the index grew only 9%.

The article concluded that lackluster mobile experiences were a primary reason. While online traffic is quickly shifting away from desktops toward mobile, growth in purchases on mobile devices is growing more slowly for all but a few standout retailers. In a report from IBM, mobile counted for 45% of all traffic to retail web apps over the holidays, while only accounting for 22.5% of sales. Basically, when retailers see traffic to desktop applications decline or go flat, many don’t see that loss compensated for on the mobile side. Mobile traffic and sales may be going up and to the right, but not fast enough to maintain the rapid pace of growth e-retailers are accustomed to.

How does this tie into Juno, the winter storm battering the northeast?

Because eCommerce companies lost $35 million in sales while it happened. As reported by Internet Retailer, it seems that so many shoppers still do their ordering at work that when they’re away from their desks for a day or two en masse, that’s enough to put a chill on sales.

It doesn’t have to be this way.

While all those employees were kicking around at home, they were probably browsing the web on their mobile devices. If they were provided with a great shopping experience, there is no reason they wouldn’t be making purchases at an equal or greater rate than if they were at their desks.

Just ask UsTrendy, a retailer interviewed for the above article, who bucked the trend and saw a major uptick in sales on those days. While we don’t know what percentage of their sales were mobile, it was not likely a limitation: UsTrendy has an intuitive and attractive responsive web design site that was clearly built to cater to mobile shoppers, with buttons and pulldowns that are easy to see, click, and use with a touchscreen.

On top of that, its highly performant: its category and product pages fully display in just around 7 seconds on a 4G connection with an iPhone 5, easily beating the online retail average of 11.6 seconds for that profile . (Click here and here to see the tests). Mobile users are impatient — and they have the gall to expect mobile websites to load about as fast as desktop ones, despite the clear limitations imposed by slow cell networks and lower-powered devices. UsTrendy shows that they can hold their own with performance, and their users clearly have responded.


How to avoid losing out in the mobile shift

Most retailers have already seen the writing on the wall, and are optimizing experiences for mobile. But dismal results like these show they have a long way to go before every retailer provides the experience of an UsTrendy.

What can you do?

1 – Take the dive and go mobile-first. It’s a big decision to totally revamp a retailer’s entire web experience to go to RWD; it’s even bigger to do RWD with a mobile-first methodology. But it’s simply the best way to make sure that your application is prepared for mobile audiences. There may be high short-term costs, but with mobile browsing set to eclipse desktop for retailers in 2015, it will pay off.

1.5 – If you can’t go RWD and instead have a mobile “” site, do not let redirects drag you down. A recent analysis shows that redirects impose a 2-3 second “tax” on performance on average; many sites force the user to wait through 3 or more redirects before sending him or her on the way to the mobile site.

2 – Use the best mobile optimization techniques and tools available. The mobile web is a horse of a different color when it comes to optimizing delivery and presentation. Old tactics, like using a major content delivery network for edge caching, are a desktop solution to a desktop problem. Instead, you have to think about the mobile context and take steps to ensure that your site is optimized in a way that addresses slow cell network connections, tiny processors, and impatient users. That means leveraging new techniques like sequencing, delay/lazy loading, and lossy image compression.
Taxi image courtesy of Anthony Quintano on Flickr

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