Want More Sales? You Need to Nail Product Discovery

In ecommerce, product discovery is crucial. Whether you’re a retailer selling consumer goods or a manufacturer providing parts to businesses, helping customers find the right products quickly is essential. According to McKinsey & Company, 35% of purchases on Amazon are influenced by product recommendations powered by sophisticated algorithms. This applies equally to B2B and B2C, where personalization and recommendation engines play a pivotal role in shaping modern product discovery strategies.

Why Product Discovery Matters in Ecommerce

For both B2B and B2C businesses, the ability to guide customers toward the right products can make or break sales. Imagine a manufacturer with thousands of SKUs – if customers can’t efficiently navigate through the product catalog to find the right part, it could result in frustration and lost business.

In the B2C space, product discovery is about surfacing items that spark consumer interest, turning casual browsing into a purchase. But in B2B commerce, product discovery is often about precision. For example, a B2B buyer in the manufacturing industry might be sourcing specific machine parts. They need a search experience that quickly narrows down to the exact product based on part numbers, specifications, or even past purchasing data. This not only increases conversion rates but also fosters trust, as the buyer knows they can rely on your platform to meet their unique needs.

The Role of Personalization in Product Discovery

Personalization plays a central role in guiding customers to the products they need. By analyzing customer data – such as previous purchases, search behavior, and business requirements – ecommerce platforms can create tailored experiences. This makes it easier for users to find the right products without having to sift through irrelevant options.

In B2B, personalization might look different than it does in consumer retail. Rather than recommending trending items, a B2B platform might suggest items based on a company’s procurement history or offer contract-specific pricing. A manufacturer’s procurement team might frequently order certain parts in bulk; personalization can ensure that when they log in, those parts are prominently displayed, streamlining the reorder process.

AI-Powered Recommendation Engines: Driving Sales for B2B and B2C

AI-driven recommendation engines are the cornerstone of modern product discovery. They work by analyzing customer data and using machine learning algorithms to suggest products based on individual preferences, behaviors, and needs.

• Collaborative filtering recommends products based on the behavior of similar users. In B2B, this might mean suggesting tools or materials that other companies in the same industry have purchased.
• Content-based filtering focuses on the characteristics of the products themselves. For example, in a B2B scenario, if a company frequently purchases machine bearings, content-based filtering can suggest other bearings or related components based on technical specifications.
• Hybrid systems combine both methods to deliver highly accurate recommendations. For example, a B2B buyer searching for industrial motors might be shown motors with similar features and what other buyers in their industry have chosen.

These engines are invaluable for businesses of all types. In B2C, they improve the shopping experience by showing customers items they’re likely to buy. In B2B, they help businesses find the exact products they need without wasting time on irrelevant results.

How to Implement Effective Product Discovery Strategies in Ecommerce

Improving product discovery involves using customer data effectively and leveraging the right technology. Here’s how both B2C and B2B businesses can implement these strategies:

1. Collect Relevant Data:
   • User Data: For B2B, this includes business size, industry, procurement patterns, and contract terms. For B2C, it may involve demographic information and browsing behavior.
   • Purchase History: Knowing what a B2B buyer has ordered in the past helps create personalized reorder experiences, just like tracking a consumer’s previous purchases can inform personalized recommendations.
   • Behavioral Data: In B2B, this could be the specific technical documents a buyer downloads, while in B2C it may involve time spent on product pages or items added to the cart.
2. Leverage the Right Tools:
   • Recommendation Engines: Use tools like Lucidworks to power your product discovery. In B2B, these engines can suggest parts based on purchase patterns and technical needs. In B2C, they drive upselling by recommending related or complementary products.
   • CRM Systems: Platforms like Salesforce or HubSpot help businesses in both B2B and B2C manage customer interactions and tailor the product discovery experience based on detailed customer profiles.
3. Test and Optimize Continuously:
   • A/B Testing: In both B2B and B2C, testing different product discovery layouts, filters, and recommendation algorithms helps identify what works best for your audience.
   • Monitor Performance: Regularly analyze metrics like conversion rates and average order value to ensure your product discovery strategy is driving results.

How Lucidworks Enhances B2B and B2C Product Discovery

At Lucidworks, we’re not just talking the talk; we’re walking the walk. We’ve helped countless B2B and B2C businesses transform their product discovery strategies and achieve incredible results.

But don’t just take our word for it. See what the experts at Gartner have to say! In their latest report, Gartner explores the critical role of AI in modern commerce and highlights Lucidworks as a key player in the field.

Ready to unlock the secrets to product discovery success? Download the Gartner report today and discover how Lucidworks can help you:

• Boost customer engagement and satisfaction
• Drive conversions and increase revenue
• Create a truly personalized shopping experience
• Outperform your competitors

DOWNLOAD THE GARTNER REPORT