Imagine going to a shop to buy a pair of casual shoes and asking the salesman to show a few pairs of the same. Now, imagine the salesman showing you loafers that other customers have bought and liked. Would that make you frustrated and leave the store? This is exactly what happens on E-commerce sites that keep showing you product recommendations based on other customers’ shopping patterns.
What is Personalization in Ecommerce ?
Personalization is the customization of a customer’s buying journey on a Ecommerce website according to his preferences and choices to ensure purchase and repeat visit. Personalization can be done in a number of ways like Homepage Personalization, Personalized recommendations, user specific discounts & offers, notifications etc. Amongst this list, personalized recommendations is the most difficult to implement as it varies from category to category. For example, for Electronics category, personalized best sellers type of recommendations work better whereas on fashion or furniture categories, visually similar recommendations always show better results lead to better click-through rates. Let us understand just how Visually similar recommendations help in personalization.
How Visually Similar Recommendations help in improving Personalization?
Salesman Like Experience: Like an in-store shopping representative asking about your preferences before showing you each set of products to choose that perfect product from, visually similar recommendations are your online personal shopping assistants, where recommendations are provided based on your current browsing product.
Popularity agnostic and user preference focussed recommendations : Visually similar recommendations are popularity agnostic and work only on visual similarity. This means that when a customer is searching for a particular type of pants, only those pants that are similar in colour, shape, pattern and other aesthetic elements would be displayed as suggestions. This also ensures that each set of recommendations is unique and makes sure the same products do not keep getting recommended to different set of customers.
45% of customers are more likely to shop on a site that offers personalized recommendations
Personalized Out of Stock Alternatives: Products going out of stock create dead leads and drive customers to competitors. With so much competition in the online space, losing a definite customer is the worst thing for an e-commerce platform.The best way to retain those customers is to show them similar alternatives to their selected product. Visually similar recommendations provide exact alternatives from the catalogue and save customers from leaving.
How Visually Similar Recommendation help in accelerating Conversion Rates?
Now, although a huge array of product categories and a similar array of products listed in each category make an e-commerce portal popular in the sense that it may offer what the customer is looking for, it may not necessarily be profitable for business in terms of conversion rates. Getting a customer to the checkout page and onto the payment tab is a herculean task. As of June 2018, industry reports suggest that the shopping sessions that lead to products in the cart are around 14-15% and the business conversion rates, even then, amount to only 3-4% of the total website visits.
This number suggests that because the conversion rate is very low, e-commerce portals have to work to the best of their abilities to lead each transaction to the checkout page. The mantra, therefore, is that conversion rates are inversely proportional to the time spent on the portal. The faster the process of selecting the product, the faster will be the checkout. The more time the customer spends on the portal often shows that they have not yet discovered the product they are looking for.
When used correctly, product recommendations increase the average number of items in the cart by 68.14% and increase conversion rates by an incredible 320%.
By using personalized visually similar recommendation, with the almost similar recommendations the multiple query steps are eliminated as the customer is quickly led to the required product. This results in a faster decision-making process and leads the customer to checkout. In the case of a product going out of stock after leaving it in the cart for a good amount of time, visual recommendation will immediately study and analyze the product and offer very similar looking products to the customer instead.
Both Fashion and Furniture are of individual taste and choice as they largely depend on aesthetics and looks. No two people are going to make identical choices while buying them. And hence, showing them “Customers who bought this also bought” or “Best sellers” may not perform well. Customers today have ample number of choices to shop from and hence less patience to stick to one store either online or offline. The onus of making customers stick around and take faster decisions is in the hands of the retailers. Offline retailers have appealing aesthetics and salesmen and hence online retailers need to include all possible techniques like personalized recommendations amongst others to stay in the market.
“Turing Analytics is a machine learning company that delivers intelligent solutions to Retailers helping them improve product discovery, customer engagement and boost conversion rates. They expertise in building Visual Search & recommendation solutions, which enable retailers to recommend visually similar products to their customers and search products by uploading a picture.”