Ecommerce retailers are fighting harder than ever to deliver a shopping experience that will win customers and increase sales.
While text-based search has long dominated how retailers deliver that customer experience and execute their digital marketing strategies, feel this traditional tool has become inefficient at finding the right products online.
What if you could understand what your customers want from their browsing behaviour, affinities and preferences and then provide them with a completely personalised shopping experience? Well, this is exactly how Visii is transforming the customer and shopping experience for websites.
Visii’s predictive intent engine selects the most contextually-relevant personalised product recommendations for each customer based on their actions and browsing history. The result is increased click thrus, more products viewed, speedier journeys to checkout and 40% increased sales.
Quite simply, businesses that employ intelligent predictive product recommendations are winning over those that don’t.
Look at how Amazon, Netflix and Spotify have rewritten the rule books of their industries and are posting record revenues while their competitors struggle. The key to these businesses’ success is their single-minded focus on providing personalised customer experiences.
No two Netflix home pages are ever the same as they tailor each user’s interface based on their preferences and intent. Equally, Spotify and Amazon are masters at providing customers with highly relevant recommendations. In short, these businesses use data to understand what customers want and provide each one with a personalised experience.
Here are three easy-to-implement personalisation tools that will help transform your sales.
The tool enhances your curated groups of products by extending them with automatically generated recommendations that match a specific style, be it in a 'shop the look' feature, customers' favourites, or their wishlists.
By featuring items that are based on the detailed visual attributes of searched-for products, including patterns, shapes and colours, retailers can now show customers far more relevant and tailored items from their catalogues, enabling them to find the product they want 52 x more quickly.
This opens up increased cross-sell opportunities (for example, if a desired item is ‘out of stock’) and easy upsell capabilities by showcasing other products from a collection which are curated and not simply based on broader shopper behaviour.
Equally, where traditional search and tagging limits the choice of the products and designs that platforms show customers, uses deep learning AI to narrow down product results in real time, allowing shoppers to easily browse content they love from a far greater range of shoppable products.
Interestingly, shows that visitors who use visual search conduct 48% more product views than those who don’t.
By increasing shopper dwell time (and bringing down bounce rates), Visii’s clients are showing shoppers more products from their catalogues that might not have been otherwise discovered by traditional filters and keyword search. The overall result is that clients are seeing sales increase by more than 30%.
And what about usability for those customers who know what they’re interested in? Traditional search experiences often create ‘search fatigue’ as there’s typically a semantic disparity between how retailers describe products and how consumers search for them.
We live in a visual culture, so why not allow customers to start their search with an image? allows shoppers to simply drag and drop an image file to find the most similar available products, not only making the experience interactive and engaging, but also super-effective and quick. And what’s more, highly profitable, with ROIs of 33x.
For a fuller discussion on how True Recommendations increases online sales, please get in touch at firstname.lastname@example.org