E-Commerce Category Merchandising - What It Is and How It Can Improve Your Sales and AOV

Today, shopping has moved online — most younger people, 60 percent to be precise, shop online. But the e-commerce space is crowded, and customers have infinite options. To stand out online, retailers must have their basics right.

In a physical store, shoppers spend more time browsing items, and there is an increased likelihood of making a purchase. But in online shopping, it is easy for customers to click off. E-commerce businesses need to capture and maintain customer attention. And one way to do that is with optimal merchandising.

Merchandising plays a pivotal part in the retail experience, which remains true for e-commerce businesses. E-commerce merchandising involves displaying products strategically on a website to increase conversions and sales and it creates a visual connection between a brand and its customer.

With today's fierce competition and the need to keep up with evolving consumer behavior, brands need to bank on effective digital merchandising strategies to stand out. These strategies include product recommendations, upselling and cross-selling, featured products, and more. 

In this article, we will tackle one such important merchandising strategy - e-commerce category merchandising.

What is e-commerce category merchandising?

Ecommerce category merchandising is the art of arranging and presenting products within specific categories on your online store. It's like organizing a physical store's shelves, but done virtually.

Online retailers use e-commerce category merchandising to optimize product categories on their websites. It helps create a cohesive and engaging customer shopping experience by grouping and highlighting products that complement each other. 

Category merchandising can also involve changing how products in a category are featured on the homepage or other category pages and how products are filtered or sorted. This type of merchandising helps build an online shopping experience that helps customers find the products they are looking for more quickly and easily.

Many online retailers use smart merchandising. Smart merchandising utilizes cutting-edge technology like artificial intelligence (AI) to inform product display decisions. Using data and analytics, brands can inform decisions, such as which products to showcase or recommend to customers. This approach has become increasingly popular as it allows retailers to understand customer preferences better and cater to them more effectively.

AI is helping businesses drive their merchandising efforts and stay competitive in new markets. It can glean insights from data to drive decisions beyond product merchandising, like pricing, promotions, and personalizing the shopping experience by recommending the right products to match customer needs. AI forecasting models can also better anticipate consumer demand and plan for future merchandising strategies.

The importance of category merchandising - How it can drive your eCommerce sales and AOV

A startling study states that up to 70% of online sales originate from category pages, but less than 50% of category page traffic advances to a product page.

This means that most online businesses are not leveraging effective category merchandising strategies and are losing out on sales. How can online retailers create a winning category page that translates to a higher average order value (AOV)?

To achieve this goal, retailers need to improve the shopping experience on their websites using appropriate merchandising techniques.

Category merchandising can create a personalized experience for shoppers that displays products that align with their interests, preferences, and prior purchases. This, in turn, will drive engagement and encourage customers to purchase more items. 

Category merchandising can allow companies to understand their target audience better, giving them valuable insight that can help them develop more effective marketing strategies and better products. This will help retailers generate more revenue and establish a strong presence in the digital marketplace.

6 tips to optimize category merchandising for your eCommerce store

The six key tips to optimize merchandising for eCommerce store are listed below.

1. Advanced personalization (from autosuggest to product ranking).
2. Build a robust search experience - Search results re-ranking and autocomplete.
3. Dynamic boosting of products.
4. Incorporate visual merchandising.
5. Leverage customer data and past behaviour. 
6. Real-time user segmentation.

Let's dive deep into them.

1. Advanced personalization (from autosuggest to product ranking)

Personalization can be a very powerful tool in an online retailer's toolbox. It can increase conversions and customer satisfaction. In a poll, 44% of customers said they would become repeat shoppers if their shopping experience was personalized.

While personalization techniques like showing relevant products are becoming increasingly common, advanced personalization can take an online store to the next level. Advanced personalization techniques can include capabilities such as autosuggest and product ranking.

Autosuggest is a tool that helps users find what they are looking for faster by providing suggestions as they type in the search box. Knowing the customer's preferences beforehand allows the website to populate the products for a customer automatically as they head to the search bar. Similarly, with product ranking, the website's product page display changes depending on the customer. The products they are more likely to purchase appear at the top, while the products they usually show little interest in are out of sight at the bottom.

Customer preferences can be based on factors like past purchases, past reviews and ratings, interactions on social media, and a host of other considerations. AI and machine learning (ML) algorithms are used extensively to accomplish advanced personalization easily and quickly. 

2. Build a robust search experience - Search results re-ranking and autocomplete

Most customers head straight to the search bar when they visit an online store. A slow or ineffective search experience can frustrate shoppers and ruin their online shopping experience. It may lead to lost sales or even lost customers. Hence, a robust and effective search experience is crucial.

An ideal search experience should allow customers to sort and filter products to get what they want easily. The following search capability factors should be kept in mind when designing an ideal search experience.

Search results today should be based on natural language processing (NLP). NLP is more human-like than its predecessors and relies on natural and conversational language to understand its customers. Instead of searching exactly for what is typed, NLP tries to understand the user's intent when searching.

Synonym detection is an NLP technique that detects words and phrases with similar meanings. Examples include finding synonyms for words like "car" (automobile, vehicle, etc.) or phrases like "cold weather" (frigid temperatures, icy conditions, etc.) Typo tolerance is another NLP feature that makes it possible to search for words and phrases that have been misspelled or incorrectly formatted. For example, a search for "brkfast" would still produce results related to "breakfast," even though it was misspelled.

Another technique to improve search results is re-ranking. Taking into account the customer's previous purchases, re-ranking can adjust the order of search results and provide a more relevant set of products. Similarly, autocomplete suggests a list of suitable products before the customer is even done typing their query. It is also based on the customer's previous search behavior and helps to save time that would be wasted typing out long searches.

3. Dynamic boosting of products

Dynamic product suggestion involves using AI to analyze user behavior and provide tailored product recommendations. AI can study the shopper's preferences and suggest products that match their interests. AI-driven product suggestion algorithms can also learn from past purchases and interactions with the website, allowing them to dynamically adjust product recommendations as the user's behavior changes.

Real-time adjustments in product suggestions can leverage the last-minute cart additions that provide online businesses with a crucial revenue bump.

4. Incorporate visual merchandising

When a shopper visits an online store and finds what they are looking for within seconds, their experience goes from satisfactory to delightful. In order to improve user experience (UX) on their website, e-commerce brands must focus on creating outstanding visual merchandising. 

Shoppers visiting an online store should be able to seamlessly navigate from category pages to product pages to the shopping cart. They should spend less time searching for what they want and more time looking at products that appeal to them. 

Brands need to pay special attention to UX design to make their product pages inviting and compelling so that shoppers want to keep coming back and spending more time browsing.

5. Leverage customer data and past behaviour 

To give customers the personal and seamless experience they want, companies will have to utilize customer data on their past behavior extensively. 

AI and ML algorithms need this data to make informed decisions about which products to display or what kinds of discounts to offer each customer. By understanding customer behavior, companies can create more personalized campaigns, target specific customer segments, and discover new ideas for product offerings. They can also use customer data to uncover trends and develop more effective loyalty programs. 

Companies can better understand customer needs and create more compelling experiences by using customer data to inform decisions.

6. Real-time user segmentation

User segmentation is the process of separating customers into groups based on shared characteristics. This segmentation might be based on age, language, geography, or other factors. Effective segmentation helps companies design personalized experiences for each segment.

A step further than user segmentation is real-time segmentation. When the segmentation is real-time, it updates automatically based on how a user behaves on the website. This can not only tweak the website to offer the shopper a more effective and personalized shopping experience, but it can be a highly effective way to boost sales.

An example of real-time segmentation is offering a discount to a first-time visitor or changing the homepage products depending on the shopper's age or gender. 

Adding more relevance to a customer's journey through the website will increase customer loyalty and retention.

Conclusion

A well-executed merchandising strategy can be of tremendous value for elevating search and shopping experiences. With emerging technologies such as AI, digital merchandising is taking massive strides towards delivering a hyper-personalized user experience. 

This manifests as AI-powered product recommendations and focused marketing tailored to each customer's needs. Advanced ML algorithms also take the search relevancy and accuracy to the next level. 

Deliver a better user experience with Zevi's AI-powered smart merchandising. With Zevi, you can rank search results based on product performance, boost relevant products to match customer preferences, deliver a smooth and consistent experience to your customers, and much more!

Try Zevi's powerful solutions to get the most out of your business. Book a demo today.