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10 Hacks to Improve Product Recommendations for a Next-gen Customer Experience

By
Gokul
• 
5 min
eCommerce product recommendations

Did you know that 91% of customers are more likely to purchase from brands that provide relevant recommendations and offers? E-retailers should remember that 67% of online shoppers are informed millennials, and the secret to converting them is creating a customized shopping experience. 

That’s why for any eCommerce retail strategy, personalized product recommendation has to be a top priority. This is largely because each customer has their own purchasing journey and they expect eCommerce brands to indulge them with recommendations aligned with that journey. Did you know that Lotte Mart has experienced up to 40% sales boost with Amazon’s personalized recommendation engine?  

These days almost all eCommerce stores display product recommendations on their home page, checkout page, or through emails. But the question is, how many of those recommendations are relevant?

Through our research, we found that there’s a critical gap in displaying personalized product recommendations. Even though the eCommerce stores try their best, they often fail to make a mark in users’ minds with personalized recommendations. So we thought we’d cover some cool product recommendation hacks that can help create a next-gen customer experience. 

Let’s get started.  

1. Look into the browsing history of customers 

One of the most common hacks is to display product recommendations inspired by customers’ browsing history. You can place a widget on the shopping cart page of your eCommerce website with the title “Products you have recently viewed”. The idea is to give the customers a nudge to buy previously browsed items. In fact, adding a similar widget to your transaction emails can also do the trick. 

Note how e-retail giant Amazon masters this hack: 

product recommendations from browsing history
Source: The New York Times 

 

See how Amazon reminds its customers of their past browsing history. So, why does this personalized recommendation strategy work? 

It reminds the users about the items they previously viewed. It nudges them to go back to those items and complete their purchase. It can help eCommerce stores to generate some instant sales.

2. Display product ratings within the recommendations 

Ratings can do wonders for online shoppers. Reviews and ratings work like social proof for brands. They instill a thought in customers’ minds that, “if others are finding this product useful, maybe I should give it a shot too.” An average customer reads at least 10 online reviews before making a purchase decision. So, why not leverage these ratings and reviews? 

If you have received high ratings from your customers, flaunt them along with your product recommendations.  Again, look how Amazon does it: 


Product ratings in product recommendation
Source: Channeladvisor 


Notice how Amazon displays ratings of each product in its expert product recommendation list.

This strategy helps to build trust. It makes users realize that the brand values its customers and stays honest about its recommendations. It also establishes transparency. You can see in the above image that Amazon has recommended a product with a 3-star rating as well. That proves Amazon’s loyalty  to its customers. 

This strategy to personalize product recommendations can help a brand create credibility. And higher credibility means higher conversion. 

3. Add the “Frequently bought together” widget 

This works on the principle of  FOMO (Fear of Missing Out). Suppose a customer purchases a pair of trousers from your eCommerce store. You can add the “Frequently bought together” widget to display which shirts, tee shirts, or shoes would go well with that trouser. In most cases, e-retailers place this widget on the product page to grab customers’ attention. 

Let’s see how GoPro champions this tactic: 


Frequently bought together product recommendation
Source: StoreApps 

 

See how this brand offers recommendations to camera kit and camera battery when the customer has added a GoPro camera to their cart. Here’s why this strategy can help you create an exclusive customer experience: 

Customers think “if others are buying these products with my selected item, maybe I should do too”.  

eCommerce brands also apply this technique to highlight their latest offers for the customers. 

This strategy often drives more sales as the shoppers can find some interesting products that match their needs that they may not have thought of themselves, and often end up buying them all. Conversion improvement!

4. Projecting the “New Arrivals” 

This may not exactly be a personalized product recommendation. However, sometimes displaying the latest arrivals can also drive sales. The idea is to notify your customers about the latest products. If properly planned, this tactic can boost your sales in the very first week of a product’s launch. 

Let’s take a look at Ulta’s strategy to get an idea: 


New arrivals product recommendations
Source: ConvertFlow 

 

Ulta, a popular eCommerce beauty store, informs its customers about the latest arrivals regularly. See how they have provided the “free gifts on purchase” offer on two of their newest arrivals to drive an immediate sale. 

With this strategy, you don’t have to wait for customers to find a product organically. Improve their digital experience by keeping them notified about the latest arrivals. 

This strategy creates users’ awareness and encourages them to explore new products. This could mean higher CTR and better chances of sales.  

5. Leverage the power of an AI-based personalized product recommendation engine 

A product recommendation engine focuses on the combined approaches of past purchases and predictive technology. With the past purchase approach, a product recommendation engine develops an idea about a user’s purchase pattern. The predictive technology algorithm suggests what the users are most likely to buy next. 

Suppose you’re using an AI-based product recommendation engine on your eCommerce website. Say, one of your customers has purchased a laptop from your store. With the predictive technology of the recommendation engine: 

You can suggest relevant products like personalized laptop covers, backpacks, keypad cover, and other relevant laptop accessories with autonomous machine learning You can segment your customers based on their choices and preferences and pitch them the most suitable products for faster sales 

A recommendation engine that masters the art of personalized product recommendations with predictive technology is Argoid

6. Craft crisp product recommendation copy 

Crafting your product recommendation copy is also a big deal! The way you pitch a product recommendation to the customers can make or break the sales potential. Try to write crisp and direct product recommendation copy that grabs the users’ attention and persuades them to click on the widget. 

In fact, simply writing “Recommended for you” may sound stereotypical. How about “Handpicked products for you” or “Our selection for you”? This sounds more appealing and conversational.  

7. Past purchase history can improve product recommendation 

Predictive analytics is what businesses are using to forecast the upcoming actions of a customer. It uses core statistical analysis along with data mining and machine learning technologies. Does that sound a bit too technical? Let us break it down for you. 

Every eCommerce store owner maintains a record of past purchases for its customers. How about using a recommendation engine that makes use of these datasets? A recommendation engine analyzes all these datasets with its in-built predictive technology tools. Based on these inputs, it suggests effective product recommendations that are very likely to impact customers’ buying decisions. 

Recommendation engines can track a customers’ browsing history, past purchases, wish-listed items, and other relevant factors to set certain motivators or triggering factors. eCommerce store owners can use these motivators to prepare customized product recommendation lists. 

Don’t forget that every customer has a unique journey and approach to browse across an eCommerce store. The easiest way to create an adaptive product recommendation list for the customers is with an AI-driven product recommendation engine

8. Display product recommendations within the cart drawer 

Adding your product recommendation widget to the cart drawer can also go in your favor. This means users won’t have to go back to the product page or homepage to see the recommendations. This opens room for new cross-selling opportunities. 

See how Dame strategically adds the product recommendations in the cart drawer: 


Product recommendation in cart drawer
Source: Niceverynice


This type of recommendation can engage the users instantly. Since they find it while completing a purchase, they may end up adding one of these products to the cart before moving forward to checkout. This is a cool hack to increase your AOV instantly. 

9. Add product recommendations to your exit-intent-popups 

eCommerce websites tend to show a popup message to their customers before they leave the store. The purpose of this message is to convince them to continue shopping. This message is popularly known as an exit-intent-popup. Generally, we get to see discounts, special offers, newsletter subscription messages, etc. in these pop-ups. 

How about adding product recommendations in your exit-intent-popup? That could be a unique way to send them back to the store. A properly-timed exit-intent-popup easily grabs your users’ attention. 

Here’s an example: 


Exit-intent-popup product recommendation
 Source: OptiMonk


Notice how this e-retailer personalizes its exit-intent-popup. The brand nudges the users with some personalized smartphone recommendations that could bring the user back to the portal. You can also add some special discounts in your exit-intent-popup message to engage the users further. 

10. Get customer feedback and stay informed 

Don’t underestimate the power of customers’ feedback. No matter how personalized your product recommendations are, you still need to know if they are aligned with your customers’ requirements. So, once in a while, try to collect customer feedback on the accuracy of the product recommendations. 

Here are a few ways to approach customers for feedback:

  • Conduct customer surveys over email and/or through social media 
  • New eCommerce stores with limited customers can practice 1:1 customer outreach to get an in-depth understanding of their requirements 
  • Add feedback boxes to your websites to get instant reviews 
  • Monitor customers’ behavior on social media to find out their likes and dislikes 

Final Words 

We hope you found this guide helpful. Start applying these tricks to your eCommerce store to create amazing customer experiences. Also, don’t forget to monitor how these strategies are working for you. All tricks may not work for all stores. So, experiment a little, run some trials, and you’ll soon hit your stride with product recommendations. 

Instead of doing it yourself, you can also use an AI-driven product recommendation engine to get faster results. Such an engine will offer all kinds of tailor-made recommendations that your customers cannot miss. Argoid can be your best buddy on this journey. 

Schedule a demo now! 

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