Unlocking eCommerce Product Discovery: 5 Strategies To Boost Online Sales

In the vast world of eCommerce, product discovery plays a crucial role in driving sales and revenue. After all, customers can't purchase a product if they can't find what they're looking for. With the increasing number of online shoppers and the growing competition among eCommerce businesses, this means that it is important than ever to ensure that your products are easily discoverable by potential customers.

In this blog post, we will explore 5 important strategies enterprise-size retailers must use to enhance their eCommerce product discovery experience and boost sales. From leveraging the latest advancements in search technology to optimizing your product data and site design, these actionable insights will not only boost your bottom line, but set you up for future success in the eCommerce market.

To ensure that customers find what they're looking for, it's crucial to first understand what they're looking for. 79% of consumers say the search function on retail websites sometimes provides irrelevant results. This is often because legacy search engines, which run on keyword-matching technology, are not able to understand true user intent.

When you input a query such as "date night dress" a legacy engine searches the product catalog for "date" and "night" and "dress." It does not understand that the phrase "date night dress" refers to the classic "little black dress" rather than a dress with a date palm leaf pattern on it.

By understanding the intent behind your customers' queries, you can provide more accurate and relevant search results, thereby improving the customer's search experience. How do you understand user intent?

• Leverage the power of LLMs:
  Large Language Models (LLMs) are the same technology that powers ChatGPT, Bard and other Generative AI applications. However, LLMs have been used for years in search. Trained on large quantities of untagged text, LLMs are exceptionally good at parsing input and search queries -- especially long-tail queries and conversational queries. This allows LLMs to excel at understanding user intent.

This technology can also be used to power other features, like autocomplete and type-ahead suggestions when customers input their queries into the search bar. This provides a Google-like experience, which customers have become accustomed to over the years.

Read More: How to Excel at eCommerce Product Discovery: Key Insights and Strategies.

In eCommerce customer experience is everything. Every online retailer is currently competing with Google and Amazon -- the titans of the industry -- for the same customer base. As such, the experience you provide during their online shopping journey must live up to the standards these titans set.

• Start with page load speed:
  Optimize your website's performance by minimizing page load times. Shorter page load times have repeatedly been linked to increases in online shoppers' conversion rate, and 52% of online shoppers stated that quick page loading is important to their site loyalty.
• Streamline the customer journey:
  The eCommerce customer journey is a multi-step process with many possible drop off points and multiple calls to action (CTAs). Figuring out what the key CTAs for your site are, and then optimizing the customer experience for them, can help greatly improve conversions, reduce search abandonment and improve the overall customer experience on your site.
• Offer multiple delivery and fulfillment options:
  Customers today expect multiple delivery options, including next-day or same-day delivery, curbside pickup, buy-online-pick-up-in-store (BOPIS) and more. In fact, according to the Baymard Institute, shipping costs are one of the biggest contributors to search abandonment.
• Display inventory levels in real-time:
  Displaying inventory in real-time can be a challenge for retailers, especially when you've got multiple locations, but it pays off. One of the worst customer experiences is going to buy an item and discovering it's out of stock. That's only beaten by having an order canceled because the item you purchased was already out of stock -- but that wasn't displayed on the site. You can greatly improve the online shopping experience by displaying inventory in real-time, so your customers can purchase exactly what they want, and be assured their ideal products will be delivered.

Site search is the most critical component of eCommerce product discovery. Google found that 69% of customers use the search bar on eCommerce sites, making it the most common way customers discover products. Typing a query into the search bar not only allows customers to quickly find products within your website, it displays high purchase intent -- meaning these customers are more likely to convert.

To optimize site search functionality:

• Use a next-generation, AI-first search engine:
  As mentioned above, legacy search engines are built on keyword-matching technology that doesn't account for user intent. Next-generation AI-first search, however, is built entirely from AI. They learn on their own and adjust as user behavior changes. Legacy search engines require hundreds if not thousands of rules and a full team of merchandisers to even attempt personalization. AI-first search, on the other hand, can produce relevant, buyable search results that are personalized to each individual customer and are also optimized for revenue -- without any search rules. This not only drives sales, it frees up your merchandising team to work on more valuable business initiatives as well.

For retailers who have multiple sites or brands, next-generation Search and Product Discovery solutions running on an AI-first engine are also capable of filtering search and browse results and autocomplete suggestions by site. This is especially useful if two sites or brands have different target audiences.

Personalization is key to providing a seamless and engaging customer experience. However, true personalization goes beyond segmentation and delivers individualized recommendations and results. And it pays off: research shows that 80% of customers are more likely to purchase from a company that offers personalized experiences.

To deliver true 1-to-1 personalization you'll need to:

• Streamline the collection of customer data:
  eCommerce retailers today know how vital customer data is. However, collecting and analyzing that data for the necessary insights is a different task altogether. Data from different platforms needs to be curated and normalized before it can be analyzed together, and that's why setting up a data pipeline that unifies all of your customer data is a vital first step to delivering truly personalized online shopping experiences.
• Leverage an AI-first Search and Product Discovery Platform:
  as discussed above, AI-first search technology far exceeds the capabilities of legacy search technology. AI-first search, like Google Cloud's Retail Search engine, can take into account preferences of the individual consumer when displaying search results and will deliver a truly unique page of results. For example, if two different customers both search for blazers, based on their preferences, they could see different cuts, styles, colors and designers sent to the top of their search results. However, all of their results will be optimized for revenue as the AI automatically ranks and reorders items based on how likely they are to be purchased by that specific customer, for a truly profitable and individualized experience.
• Implement intelligent recommendations:
  Recommendations are like the personal shoppers of the eCommerce world. They need to make intelligent suggestions, recommending relevant products to customers based on past purchases, browsing history and customer preferences. The best product recommendations, however, utilize machine learning algorithms to go beyond presenting more of the same products. They deliver relevant suggestions for related items, like shoes and belts when a customer has been browsing for pants. This creates upsell and cross-sell opportunities for customers that did not exist before, boosting sales and revenue.

Read More: Mastering Omnichannel Retail: Strategies for Seamless Customer Experiences

Product data and product descriptions have long been an important part of the eCommerce experience. Browsing in an online store means customers cannot see or touch products, and so they rely on pictures and product descriptions to influence their purchasing decisions. T Optimizing product attributes and tags can significantly improve the discoverability of your products. When customers search for specific product features or characteristics, having detailed and accurate attributes can increase the chances of your products appearing in relevant search results.

• Provide comprehensive product descriptions:
  Include detailed and accurate product descriptions that highlight important attributes and features -- especially ones customers are likely to search for. This helps customers understand the product they're looking at, and if it's the right one for them.
• Increase the number of product attributes:
  Increasing the number of attributes associated with a single product leads to a more accurate search experience for your customers and higher revenues for you. By implementing product attribute terms that align directly with your shopper’s search intent, you can also increase product findability and critical conversion points along the online customer journey.
• Implement intelligent recommendations:
  Assigning relevant product tags will increase your products' discoverability within your online store, but doing this at scale can be very time-consuming. GroupBy's Enrich leverages sophisticated machine learning models and a global taxonomy to deliver complete, normalized product data without the manual labor.

You might have noticed that several suggestions above -- such as AI-first search, intelligent product recommendations, enriching your product data, and understanding user intent -- all tie back to leveraging AI and ML. This is because, for enterprise-level retailers, AI is the most effective way to manage their sites. Humans are simply not able to keep up with either the volume large sites require, or with how quickly shopping behavior changes online.

This is because AI is the future of eCommerce. Whether it's boosting conversion rates or lowering your total cost of ownership, leveraging AI has become essential for retailers to secure their place in the market and provide the online shopping experiences customers have come to expect. Every touchpoint has a role to play, and can negatively or positively impact customer satisfaction. In the ever-more-competitive world of eCommerce, AI-driven product discovery strategies are crucial for boosting sales and revenue.

GroupBy’s next-generation Search and Product Discovery Platform powered by Google Cloud Vertex AI Search for Retail runs on the only AI-first search engine built for eCommerce use cases – Google’s Retail Search Engine. Our one-stop-shop platform delivers all your vital product discovery needs – including Data Enrichment, Search and Browse, Recommendations, Merchandising, and Analytics and Reporting. Capable of delivering hyper-personalized digital shopping experiences, we support all fulfillment and delivery types, and customers regularly see revenue gains of 10+% when switching from legacy platforms.