Average Order Value (AOV) is an e-commerce parameter to calculate the average dollar amount spent when an order is placed from the e-commerce website or app. This is an important metric as it gives insights regarding customer behavior to the companies. A low AOV reflects that the customers prefer to make only small purchases from the website.
Also, AOV helps companies in making business decisions that include marketing and product costs. Being dynamic, an e-commerce company should calculate the AOV on a weekly or daily basis. It should focus on maximizing the AOV to boost profit.
What are personalized ecommerrce product recommendations?
Personalized product recommendation is when an e-commerce brand tracks your buying history. This feature is based on a machine learning algorithm.
Below are a few ideas to make you more familiar with the personalized product description.
Product recommendation as per buyer’s purchase history: Companies like Amazon are doing a great job in product recommendation. The company understands the search history of each buyer and recommends products based on that. Please check the below image to understand this feature more.
Such recommendations help buyers to have a look at similar products they are looking for and take the buying decision accordingly.
Product affinities for recommendation: Many companies understand the personalised choice of the users and recommend them accordingly. Such details on the product page can help buyers in the next step of their journey.
Here in the below image, I was looking for some story books for children and added some of them in my cart. The Amazon e-commerce portal suggested to me some other types of books in which I may have interest.
Although I was looking for some books in English, apart from English books, Amazon also recommended some Hindi books in which I may have interest.
Such types of relevant suggestions can increase the AOV, as after all I ended up purchasing both English and Hindi books.
Well! If such suggestions insist that I buy some more books for my child, then it can happen with other customers too!
Such features play a pivotal role in increasing AOV, as all such recommendations are relevant to the search of buyers.
How to create effective product recommendations
Let’s take a look at some product recommendation strategies that really work!
1. Show your best sellers.
This is the simplest way to recommend your product. You must track your most popular products and highlight those items repeatedly among buyers.
You must be clever while placing the ‘best seller’ tag on products. These labels work as social proof and win the trust of customers. Check the below example on J. Crew’s website. It is a leading American e-commerce brand for apparel and other accessories.
2. Recommendations based on browsing history
This section you might have noticed under the section ‘you may also like’ while looking for any product online. This is done through collaborative filtering. This is a way to keep track of user preferences and make a note of the products that you view in conjunction with one another.
Let me share one of my personal experiences with you. I was searching for shoes on Flipkart, but their recommendation engine also suggested ankle socks which can go along with the shoes.
This collaborative filtering is very effective in increasing sales. A study done by Mckinsey shows that it increases sales by 20%.
3. Recommendation as per purchasing order
What customers are buying is more powerful than what they are actually viewing. Amazon is doing pretty well in collection of all such data.
Their product recommendation filter gathers all the data regarding what your peers are buying. Their ‘frequently bought together’ section is a benchmark in this regard.
But Amazon doesn’t stop here.
This platform will continue to suggest more items, even if you put some products in your cart based on their recommendation. As they know that a person who is in the right frame to purchase has the greatest possibility of adding a few more items in his cart before checkout.
Where to include personalization in the ecommerce portal
1. Product detail page recommendation
You can mention the similar or complementary products on the product description page. Take advantage of dynamic upselling by suggesting products to the customer which are higher in price, but similar in style or by brand.
Through cross-selling on product pages you can display complementary items and inspire customers to add more items in their cart.
Here, let’s check Myntra, a leading Indian multinational brand for all clothing and other accessories. I was looking for men’s shirts on this portal and while adding some in the cart, I started getting some other men’s products like wallets, footwear etc.
Such marketing is completely based on psychology and can invoke a higher purchase. All such recommendations may compel customers to add more products in their cart, if they are interested in other recommended products.
2. Show continuous shopping for returning customers
This is a powerful tactic on an ecommece portal. The best way to increase your AOV is to remember the last shopping behaviour of your customers and remind them of the same when they login again to your e-commerce portal.
Let’s take the example of Flipkart as this brand is doing well in this aspect.
This brand reminds the customers about their recently viewed products in a separate section which they can check immediately after login. This will allow customers to pick right from where they left off. Thus making it easier for the customers to buy the product readily instead of searching the products again.
How to boost AOV with personalization (Live Examples)
Here it is worth mentioning the example of Boden, a leading brand in the UK for all types of apparels. With the implementation of personalisation on their e-commerce portal, the company experienced an increase of 12% AOV.
The company decided to enhance the customer digital experience, and this has made them implement a data-driven personalization strategy on their portal.
The brand started including fit and size recommendations as per the user’s personal preferences. This allowed customers to check the size of the cloth which can fit them the most.
Also, on the product page (as shown in green box above), you will get the option as ‘ which size fits me’. You can click on that option to enter your height, weight, and age. As per your input, the portal will suggest the best size of the cloth.
Such a great level of personalization has increased the AOV of Boden and there is no wonder why customers have started loving this brand.
After Boden now let’s take one more example of a leading e-commece brand which is Amazon
The transformation journey of this brand started in 2010 when it added personalization on the portal through the ‘customer who bought’ widget.
Such personalization gave a huge leap to the brand in terms of sales and AOV and the brand is still doing wonders through its personalized suggestions to customers. 57% of Amazon customers have accepted that the brand offers them more product information, quality and features that have enhanced their overall shopping experience.
Conclusion
Today buyers prefer personal recommendations as it gives them a feeling of being taken care of. Such an approach will retain your e-commerce customers and will encourage them to make more purchases. This will improve your AOV.
Need help building a brand new ecommerce website? Contact GyanDevign Tech Services, we are a professional ecommerce development company in India, to get an unbiased advice on starting an online store.
For further information, read our blog on ecommerce website cost for better understanding.
