Over the past few years, the worldwide retail industry was on the steady decline stage. Lots of retail markets reported shortages, sales drops and closing of the offline stores.
Among the most wide-spread reasons for that there are slow customer movement towards online shopping, increasing shopper consciousness and lack of engagement in physical retail stores.
Indeed, why would one go to a shopping center if almost anything can be bought online and delivered to the door tomorrow or even later today? Many customers, again thanks to the Internet, became more experienced in online shopping, able to easily search for better deals and prices.
To cope with that, retailers launch sales, and although they sell more items, the income is getting lower and lower. And how boring has it become to go shopping — everything you see is just a store with hangers and shelves, not that much to be excited about.
The good news is, software opens a door for a smart retail and introduces possibilities to make good old shopping exciting and engaging. Let’s have a look at some of the solutions.
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While it seems quite a new thing, it actually has been already in use for much longer than you could think. First applications of AR in retail date back to at least seven years ago. At the beginning, the AR needed much computational power so the appliances were pre-installed in physical stores.
For example, in Lego stores you’d be able to look at the finished model of your choice simply by putting the box before camera. Or, in Japanese Uniqlo stores, you could have walked into an improvised AR changing room with a large LCD displaying you wearing clothes of your choice.
What’s good, these days the needed computational power is always with you, so you can provide AR shopping mobile apps right to your customers’ phones. Anything is possible, from fitting your new shoes in Converse Shoe Sampler, to checking out how that couch will look like directly in your room with IKEA Catalog.
The most known way to increase sales in retail industry is selling lots of seasonal goods. Of course, anyone understands that most red Santa caps are sold before Christmas, and that customers buy new sunglasses just before summer comes.
These examples are obvious, but season-dependence is not the only thing about prediction of purchases. These days everything is much deeper.
There can be a strong interest in goods related to TV shows, political events and mass media in general, and these are really hard to predict.