Top 8 Ecommerce Personalization Examples to Boost Conversion Rates

Personalization tactics shouldn’t be overwhelming for your customers. There’s a fine line between being effective and being too salesy.

That being said, you simply can’t get away with no personalization in today’s ecommerce ecosystem. In fact, according to one report, 71% of consumers expect personalization and almost as many are frustrated when there is no personalization.

There are many options for personalization, and it doesn’t have to break your bank. It’s possible that you can enable some of them in your ecommerce platform without any additional cost. Others, for example natural language search that adapts to your customers’ queries, will take a sizable budget to implement.

In this article, we’ll explore:

• Product-detail page recommendations
• Virtual try-on
• Automated email and text messages
• Conversational shopping
• AR shopping
• Natural language search
• Personalized shopping guides
• Recently viewed products

Product-detail page recommendations

How it works: Recommend similar or complementary products to shoppers at almost any moment in the customer journey. When they’re browsing shirts, the recommendation system could show them fitting jackets or pants. If they’re browsing phones, it could show them bluetooth speakers and protective cases. For the best results, identify the places where your customers are most likely to add something to cart quickly - like a recommendation pop-up right before the check out.

Requirements:

• The easiest way to start using this tactic is to implement one of the many product recommendation tools, like Nosto, into your ecommerce platform.

Source: nosto.com

• A more difficult, but more customizable way is to develop a custom recommendation system.

Potential results:

• Home accessories brand Urbanara achieved a 94% increase in conversion and 123% increase in average order value.
• Fashion accessories brand Pura Vida achieved 24 million recommendations, an additional 1.6 million clicks, and 7.9% average recommendation conversion rate.

Virtual try-on

How it works: Whether it’s nail polish or jeans, virtual try-ons leverage 2D and 3D graphics, machine learning and AI, and computer vision to help shoppers visualize how their new clothes or accessories will look on them. For the best results, identify the products that are returned the most often, and build your virtual try-on MVP around it.

Requirements:

• The easiest way to start using this tactic is to implement a ready-made plugin like Auglio into your ecommerce platform.

Source: auglio.com

• You can also build a custom system, which might be more beneficial now that rapid progress in AI is enabling more sophisticated virtual try-ons than before.

Potential results:

• Virtual try-on used in Snapchat ads has generated a return of 6.2x for brands like Dior.
• 51% of customers in one of the richest countries in Asia, Singapore, stated that virtual try-ons influenced their buying decisions.

Netguru's example of the concept:

• Netguru's Virtual Dressing Room Concept achieves the main goal of reducing the likelihood of returns by allowing customers to visualize how products look on them before making a purchase. The user path was designed to allow users to learn how different pieces of clothing fit together, take advantage of mix-and-match recommendations, add complete stylings to their cart, and share their look on social media.

Automated email and text messages

How it works: Send your customers automated emails at the right times to nudge them towards buying more products, more often. These can range from something like “Happy Birthday, here’s a promo code!” all the way to emails that remind customers of abandoned carts, or simply “Thank you!” messages sent after the purchase is finalized. Automated and personalized communications like this increase brand loyalty and boost sales.

Requirements:

• The easiest way to start using this tactic is to use a platform like Mailchimp or Intercom or implement a plugin (like Shopify Email) in your ecommerce platform.

• If you operate at global scale and have a complex plan for automated messages, it might make sense to build a custom system.

Potential results:

• Text messages generate open rates up to 98%, and average click-through rates of 11%.
• Average conversion rates for automated emails range from 2.4% to 2.8%, whereas typical campaign emails generate only 0,10%.

Conversational shopping

How it works: The basic idea is that instead of clicking and browsing through pages and lists of products, customers can use AI assistants, chatbots, voice chat, or call a support agent. Conversational experiences can be applied to specific parts of the customer journey, like support questions or product search, or it can replace the traditional customer journey entirely.

Requirements:

• The easiest way to start using this tactic is to use a platform like Intercom to create a chatbot that will solve customers issues or provide product recommendations.

Source: intercom.com

• With the rapid development of AI, it might be beneficial for major brands to implement a system that combines different methods into one, powerful conversational experience.
• One new, but unproven avenue to try is building a plugin for ChatGPT, like Instacart did.

Potential results:

• Personalization and fast response times are key factors for shoppers in a hurry, and conversational shopping gives you an opportunity to significantly boost both of them.
• Rooftop vehicle tent brand, Cascadia Vehicle Tents, achieved a 27% conversion rate with a text-message based conversational experience, as well as a 45% increase in average order value.

AR shopping

How it works: Use augmented reality to help customers visualize how furniture would look in their office or home, like IKEA does with their IKEA Place app.

Requirements:

• This is a costly investment that requires building a custom system.

Potential results:

• AR furniture shopping results in increased conversion rates (in one case, the AR feature in a mobile app generated a conversion rateof up to 69%) and reduced returns, and it is slowly becoming an industry standard so customers want to have this feature.

Natural language search

How it works: Instead of forcing the customer to type in the exact name or type of the product, natural language search helps find the right thing by understanding the customer’s intent and performing a complex search.

Requirements:

• The easiest way to implement natural language search in your store can be using a system like Searchanise.

Source: searchanise.io

• To satisfy more complex requirements, you might need to develop a custom system that will meet your customer’s needs.

Potential results:

• Google’s data shows that 75% of U.S. online shoppers lose interest in buying after an unsuccessful search, and 85% of global consumers view a brand differently after a failed search, proving that it’s a critical area for improvement in ecommerce.
• Natural language search shortens the customer journey, improves conversion rates, reduces zero-results rates, and minimizes the chance of customers bouncing.

Netguru's example of the concept:

• We began testing the feasibility of NLS in our R&D department. We developed a fully functional NLS capability for fashion retailers, which enables online shoppers to search for shoes using long-tail, human-like queries. A distinctive feature of this capability is its ability to display highly relevant results without requiring search filters. Currently, we are advancing our R&D to create prototype apps for both web and mobile platforms.
  

Personalized shopping guides

How it works: You can implement a questionnaire to ask customers about their preferences and later recommend products that fit their needs. Boost this tactic even more by adding recommendations based on the browsing and purchasing history of the customer.

Requirements:

• The easiest way to implement a personalized shopping guide is to use a system like Dressipi.

• You can also try to add it within your ecommerce platform, either by turning on the right feature or looking for an appropriate plugin.

Potential results:

• Personalized shopping guides can result in 12% more revenue and 15% reduction of returns.

Recently viewed products

How it works: Help your customers remember what they were previously browsing by bringing it up when they revisit your store. It’s the same principle as streaming platforms, which have a “continue watching” feature. Customers don’t need to perform a search again; they can instantly revisit the products they already viewed, helping them make a buying decision quicker.

Requirements:

• The easiest way to start using this tactic is to enable it in your ecommerce platform or set it up using a recommendation plugin.

Potential results:

• By shortening the customer journey, you make it easier to find desired products which can positively influence conversion rates.

Summary

If you haven’t explored personalization in depth, chances are that you could boost conversion rates by simply adding a plugin or two or enabling an existing feature on your ecommerce site.

Remember, personalization won’t solve all problems. If your site has slow loading times and poor performance in Lighthouse reports, this should be your priority to fix before you start implementing sophisticated personalization tactics.