Personalization Opportunities for E-shops
In our previous customer analytics article, we introduced you to the world of e-commerce personalization and personification. We summarized the main differences between the two approaches, suggested suitability for businesses of each size, and informed you about customer data platforms (CDPs). If you are still unsure about the main differences, we highly recommend catching up on that blog first.
Personalization is currently perceived as one of the most important aspects of e-commerce marketing for engaging shoppers, turning them into long-term customers, and increasing their customer lifetime value (CLTV). It is kind of an e-commerce holy grail that all e-shops are trying to attain but, as it is not a trivial task, they can struggle along the way. For some marketers, it has become an ungraspable buzzword. Nevertheless, the benefits of personalization tactics speak loud and clear as confirmed by, for example, Epsilon research: 80% of consumers are more likely to make a purchase when brands offer a personalized experience, or Accenture research: 91% of consumers are more likely to shop with brands who recognize, remember, and provide relevant offers and recommendations. Personalization can create a seamless and unique experience for a customer, which will reward your business with more conversions, higher average order value, increased customer trust, and a lower churn rate. Although implementing personalization on your e-shop can be a tricky endeavor, these should all be good enough reasons to stop treating each customer in the same, general way, and to try and treat each customer uniquely.
Before getting into examples of what parts of an e-shop can be personalized, we need to clarify what data are crucial for delivering the most effective recommendations. First of all, the better the quality and larger the quantity of your real-time customer data, the better the personalization engine will work. This is crucial. If your e-shop is just starting out with a few customers and a handful of orders a week, you do not have to rush into creating a personalized shopping experience, as they would not work very well on such a small scale. If your e-shop is already scaled up, but your data quality is poor, there are various ways how we can help you improve the quality, as well as the personalization engine performance. When it comes to the data needed for creating personalized experiences the most important categories are:
Behavioral and transactional data – such as past actions, browsing history, visitor frequency, and purchase history.
Demographic data – such as gender, city, country, and age.
Contextual data – such as device and browser used and shopper’s location.
Once you can provide the required data in a large enough quantity, the biggest blocker is removed. Another potential blocker can be the data latency at the front-end which needs to be minimized in order to provide a real-time personalized experience. Once these issues are fixed, we can proceed to tangible examples of personalized experiences.
In the e-shop context, content personalization refers to adjusting the content elements on the website such as hero images, various banners, CTA buttons, or other in-page modules to the taste of each customer. Content personalization might be overlooked by some marketers as it usually does not provide tangible results as quickly as product recommendations might. Nevertheless, if you are interested in improving the user experience and long-term results, such as customer lifetime value (CLTV), content personalization is one of your most effective tools. It will make customers more interested in your e-shop, they will spend more time browsing your site, and it will increase their overall engagement and loyalty. On the other hand, if you decide not to personalize the content on your website, you risk losing some of your shoppers because 74% of customers feel frustrated when the website content is not personalized to them.
Tip: You cannot personalize content for new prospects who are visiting your site for the first time but you could, for instance, create an interactive quiz to help them find the most suitable product. In return, you will receive plenty of relevant information to help you personalize the content.
A special category of content personalization is website messaging which encompasses most of the text on the website such as descriptions, reviews, or titles. Based on the available data these texts can be either ranked in a specific order e.g., reviews or personalized and A/B tested against each other e.g., titles, CTA buttons, in order to determine the best performing text version for each customer or segment.
Product recommendations in e-commerce are a very broad area. However, its goal is quite simple – to offer the right products, to the right customers at the right time, and in the right phase of their customer journey, based on user behavior. Product recommendation banners can be placed in various places on your e-shop.
The homepage is the gateway to your e-shop where the shopping journey for most customers starts. Therefore, you want to grab their attention with personalized content as well as with products of their interest so that they continue browsing the website and eventually purchase. Successful homepage recommendation boxes can be based on very simple logic such as “user’s recently viewed products” or “seasonal and discounted products”. Other recommenders can be more elaborated and predict what products could be interesting for a customer even though they have not made a purchase on the e-shop yet.
Category page recommendations
Category pages usually contain so many products that it becomes difficult for a customer to navigate them and select the products they like. Personalization can simplify the selection process for the customer. There are two major ways to achieve this:
First, we can rank all the products on a category page for each customer differently, based on the customer’s probability of liking and purchasing each product. In case there are too many products on the category page, a threshold can be set and all products with a very low probability of being purchased by a customer can be hidden.
Secondly, we can create a specific recommendation banner (or page), where each customer would see some products based using the logic “probability of liking and purchasing a product”. The rest of the products on the category page would be ranked based on a different logic or left un-personalized.
Product detail page recommendations
Once a user selects and clicks on a product they arrive on a product page to view the product details. At this point, we have an idea of what the customer is looking for and we can recommend them a slightly different product. The goal here is to provide a better deal to customers via upselling. Therefore, we can recommend, for example, a bigger pack of the same product or a similar, but a more luxurious product.
Shopping cart recommendations
Once customers reach the shopping cart and are about to finalize their purchase, we do not want them to rethink their choice, but we still have a possibility to offer them additional and complementary products. By conducting a market basket analysis we can find out which products are most frequently bought together and use this knowledge for shopping cart cross-sell recommendations.
When it comes to the shopping cart we can encounter one additional problem – cart abandonment. The average cart abandonment rate across all industries is just under 70%. This is an enormous challenge for e-commerce businesses that can be tackled via advanced predictive analytics and personalized campaigns.
Many e-commerce sites contain too much information and too many products which can overload users. The search query model helps customers to narrow their shopping choices. Albeit to just let your customer search your site does not go far enough. Nowadays, users require that the search performance is very fast and accurate otherwise they can easily get annoyed and opt for a different e-shop one click away. The challenge for e-commerce companies is to make the search work even better and luckily, there are a few ways that the search can be improved and personalized:
Personalized search suggestions enable your organization to predict how a customer’s search query will be entered and provides them with suggestions in a dropdown menu.
Personalized autocomplete works in a similar way as “search suggestions” but this way the engine attempts to complete the search query with just one, most probable option, directly in the search entry text field.
Personalized results enable your organization to sort the results (usually products in the e-commerce world) in a specific, personalized way. There are two approaches toward results personalization. You can either opt for providing a more relevant set of search results and hide the non-relevant results, or you can rank the most relevant results higher while also keeping the less relevant results lower on the page. This tactic is very similar to category page recommendations. You can also give more power to your customers by introducing a filtering feature, to have them tailor the search results even further. Filters can narrow the results by price range, color, or various product parameters.
The menu, or navigation bar, on the e-shop is an important tool for customers to orient themselves on the website. Once we have enough behavioral data about a customer we can rearrange the order of buttons based on each visitor’s preferences and conduct A/B tests to confirm the best performing order. Although this sounds like a small change, each simplification can play an important role in keeping customers, increasing their spend, and, for example, decreasing the bounce rate by 10% or more.
Apart from personalizing the on-site customer experience you also have the power to personalize other marketing channels which are fully in your control. One of those channels is email, and since email marketing is still a very important source of repeated sales, personalizing the email experience should be on your radar.
Usually, the same attributes that are personalized on the website can be personalized in email. Therefore, we can personalize the content e.g., the hero banner, images, or CTA buttons, recommended products e.g., show the customer their recently viewed items or cross-sell recommendations, or the messaging. Moreover, there is one more crucial part of email marketing to be personalized – the subject line. According to this study, personalized and customized subject lines are 26% more likely to be opened.
There are many ways in which personalization can be applied to your e-shop. The extent of personalization possibilities might seem daunting after reading this article. Nonetheless, you should think about e-shop personalization as a process. You can start relatively simple with a “recently viewed items” recommendation bar on the homepage, measure its impact on your sales, and continue with the next personalization steps once you are fully convinced the investment pays off.
However, one thing is for sure, if your e-shop is not personalized, and if you are not planning to personalize it, you will continue lagging behind your competitors. In our experience, personalized e-shops see up to a 60% improvement in conversions over non-personalized e-shops. We offer a special service of a 4-hour free consultation by one of our expert customer analytics consultants to discuss the personalization challenges in your company, whether you are just getting started or need to fine-tune current implementations. Get in touch with us now to secure this offer.