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The four pillars of omnichannel retail


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1. OPTIMISED CONSISTENCY It’s a delicate balance to fi nd, but retailers must ensure that every channel has a consistent feel, while maintaining full effi ciency. Each and every one of your channels should


be simple to use and intuitive. The design should work perfectly on all screen sizes, and no consumer should ever have to switch devices because your website is easier to use on another type. If that happens, I’m afraid you’ve fallen at the fi rst hurdle. Everything from your brand’s look and feel


to the payment options available should be consistent. Consumers shouldn’t have to think about using the site. It should just happen at their fi ngertips. However, that said, each and every channel


should be optimised based on the user trends you see. So if your app is used mostly for browsing because your audience do it on their commute to work, the menu and search function should be the easiest thing to fi nd when a user loads the app. And if you know that your audience generally checks store availability on the desktop version as


they’re sipping their Saturday morning coffee, planning their day, then your desktop web design should be tailored to that. It’s a case of helping your customers do what


they want to do on each channel, rather than forcing them to do different things on different channels through unintuitive design.


2. DATA UTILISATION Another contradiction in terms, you need to fi nd a way to personalise the big data. It’s crucial that you are constantly collecting


data on your customers and looking at the bigger trends, but another challenge for omnichannel retailers is not losing that personal touch. And we’re not just talking about knowing their name and vital statistics. Use the big data you’ve collected to power


the little things that mean the most. For example, if you know that people replace their best pair of jeans every two years, use customer data to start showing them new jeans when that period is coming to an end. Or if you see from your big data that your sofas tend to last eight years before your customers replace


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