Personalisation is an essential tool in converting visitors to your website into customers and sales – Amazon report that personalisation is the driver of 35% of their sales, and there are powerful statistics of the benefits:
When you think about the customer journey on your website, it is clear how your visitors’ experience depends on what they see and how the website can guide them. If they look at a product and it is not appealing enough to purchase, what do they do next? The most likely next step will be to click on another product displayed on the screen. So, making those alternative product recommendations personalised to the customer’s tastes is essential.
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The technology behind personalisation is rapidly evolving. While your website may show recommendations, how good are they? Here are three questions to ask:
Is every visitor getting the same recommendation? Less advanced platforms use simple sets of rules – “if customer is viewing a t-shirt, display hoodie in same range”. Check what your pages show – are they likely to make you buy the products as alternatives, or in addition? Is the website introducing a wider range, and in relevant styles and colours? Displaying a narrow, related range does not show the full choice of products that may appeal to this customer. Advanced personalisation software will automatically identify and manage a very extensive list of product characteristics, going far beyond obvious features like style, colour, material, price, pattern, and theme. AI and machine learning can derive what are called vectors of over 200 variables, to calculate the most relevant products linked to the customer’s taste. Additional algorithms then select from these relevant products, the ones that are most likely to convert.
Are the product recommendations dynamic? For example, can they consider the trends of what people are buying or viewing? Are recommendations adjusted if, for example, there is no stock, or the last review has been a poor one? If your website does not react to the latest information from all customer interactions, it may recommend inappropriate products. For example, recommending a product which is out of stock risks the customer delaying a purchase, or even searching for a preferred product on a competitor’s website.
Are search results also personalised and dynamic? A functional search window may handle misspellings and alternative product names, but is it personalised and dynamic? Personalised means that search results are tailored to the customer, recognising their tastes and preferences from data including browsing history. Dynamic means that results are modified based on recent events – so a product which is selling well would be high on the list of results, whereas a product which has just gone out of stock could be pushed down the list. The aim of the customer searching on your website is usually to find a product they want to buy, so the search engine should maximise the probability to convert.
If your current e-commerce platform does not tick the box on all these questions, it doesn’t mean you need a new platform. There are some powerful bolt-on software solutions which can integrate with your e-com platform, to give you the most sophisticated personalisation. Implementation is remarkably quick, as integration may be pre-built with major platforms like Shopify and Magento.
If you are interested to talk to us at CartUp AI, we would be delighted to hear from you. If not, we hope this guide helps you get improved results from your existing tech providers.
— Arvind Rapaka, Founder & co-CEO