5 Psychological Product Recommendation Strategies To Increase Ecommerce Sales
Researches have shown that cost isn’t always the most substantial factor, emotions play a significant role in purchase decisions. While making a choice, there is a high probability that most people will stick with their original decision even though it could possibly be wrong. It is due to a psychological bias known as the Overconfidence Effect.
Then why you should promote recommendations when you could use that space to do a whole lot of other things? Statistically speaking, the people who tend to switch from their original decision could only be 4.25% of your total customers. So how significant would 4.25% of your customers spending an extra $20, $50 or $100 be for your bottom line? If single product averages 100 customers/month that means you’d be adding an extra $86 – $430 to sales every month. By the end of the year, that’s an additional $1032 – $5160 for a single product. So what If you have more than one product with more than 100 customers a month. Now you do the math J it’s not just about money recommendations have helped merchants in increasing customer loyalty and trust in their e-commerce platform.
A visual of Oorjit‘s recommendation engine
Since now you have understood the importance of recommendations how do you exercise it effectively
Always present customers with the most closely related products as possible which will substantially improve the performance or add value to the original product. It can even be an upgrade of the product which the customer has already chosen. This can be executed well, only if merchants could evaluating previous purchase patterns and motivation factor of their targeted customer segment. Great way to add relevance is to tailor recommendations based on whether the customer is new or returning. For example, a new visitor who is looking for a pair of running shoes should see recommendations for the “best-selling” or “most popular” sneakers. For returning visitors – where you already have information about the specific brands they’ve previously browsed or purchased – highlight new products added since their last visit.
Illustration of an ideal relevant recommendation model followed by leading Multi-vendor e-commerce marketplace Amazon
As they say “too much of anything is bad”. The e-commerce merchants tend to recommend too many products in too many places in their e-commerce platform (like listing page, detail page, checkout page etc.). It is always recommended to minimise the number to 3-5 and also look for upsell opportunities when customers add an item to their carts by recommending the top one or two items that truly complement the main item they intend to purchase.
Researches prove that when two or more products/items are bundled together and sold as one, it increases the perceived value as well as the Average Order Value (AOV) of the main product. Merchants should leverage this opportunity by smartly bundling products and its accessories and offer at a price less than when they are purchased individually.
Illustration of an ideal bundle recommendation model followed by leading Multi-vendor e-commerce marketplace Amazon
Every customer wants to be treated specially. In major of the cases, the merchants offer same recommendations to all their customers. Instead, merchants should try to offer exclusively personalised recommendations based on customers abandoned cart history, previously purchased products etc. It is considered that personalised recommendations not only have a higher chance of buying but also helps in increasing customer experience and retention rates. The merchants should ideally group customers based on their behaviour and recommend products accordingly.
A visual of Oorjit‘s user group management engine
Every customer has a tendency to buy products that a number of people have tried and tested. It is because of this reason in many sites you could see recommendations in the name “Most popular products or people also bought”. Amazon takes this a step further by adding customer rating along with this recommended products (See image under relevance). The ratings increase the customer trust towards the recommended product and also acts as a certificate of guarantee to go ahead with the purchase.
Please feel free to let us know if there are some other interesting physiological product recommendation strategies that can be used. We would love to hear from you 🙂