Why Does Product Discovery Matter?

Product discovery is the process of helping customers find products they want or need in an online environment. It can involve several tools that use technology, human expertise, or both.

This process is crucial for ecommerce success because it connects the right customers with the right products at the right time and price. Effective product discovery increases engagement, builds trust, and reduces frustration. It simplifies purchasing decisions while giving brands a strong competitive advantage.

1. Navigation Menus and Categories

Using menus and categories to manually browse a website has been a standard practice since the early days of ecommerce. Products are typically organized into categories and subcategories accessible via a navigation menu.

In recent years, some companies have deprioritized these features or even considered removing them. This is a mistake for companies with more than a few SKUs. Properly designed menus and categories remain highly important and can be a major source of revenue.

Pros:

  • Easy for casual shoppers to explore.
  • Helps customers discover related products.

Cons:

  • Large catalogs can overwhelm shoppers.
  • Manual categorization requires consistent upkeep and maintenance.

2. Search Bars

Search bars are user-friendly tools that allow customers to find products quickly by typing keywords or phrases. They are ideal for customers with specific needs, especially when enhanced with features like autocomplete and filters.

Although a well-optimized search bar requires significant resources to develop, it improves the user experience, reduces browsing time, and boosts conversion rates.

Customers can search for specific brands or keywords (e.g., “Coffee Mug,” “YETI”) or even use complex queries (e.g., “How to keep my coffee hot”).

Pros:

  • Fast and efficient for users who know what they’re looking for.
  • Can be improved with autocomplete and filters for better results.

Cons:

  • Not as useful for customers who are unsure of what they want.
  • Poorly optimized search algorithms may show irrelevant results.

3. Personalized Recommendations

Personalized recommendations are suggestions tailored to individual customers based on their demographic information, behavior, preferences, browsing history, or purchase patterns. These recommendations use algorithms and AI to provide relevant suggestions.

Basic examples include “Customers also bought” sections and retargeting marketing emails. More advanced implementations involve sponsored influencer content on social media.

Pros:

  • Makes shopping more intuitive and faster for customers.
  • Creates a sense of personalization, which many shoppers enjoy.

Cons:

  • Poor-quality or insufficient data can lead to irrelevant suggestions.
  • Customers may worry about how their data is collected and used.

4. Guided Selling

Guided selling uses interactive tools like quizzes or questionnaires to ask users specific questions about their preferences. These tools recommend products based on the user’s responses.

For instance, a skincare brand might use a guided selling tool to ask about a customer’s lifestyle, skin type, or age and then recommend a tailored skincare routine. While popular in skincare, fashion, and tech, guided selling could expand to other industries in the near future.

Pros:

  • Provides relevant recommendations based on individual needs.
  • Simplifies shopping and reduces decision fatigue for customers.

Cons:

  • Customers may find answering multiple questions annoying or invasive.
  • May not work well for large, complex catalogs without constant updates.

5. Human-Curated Selections

Human-curated selections involve experts or staff manually creating collections of products based on trends, themes, or customer needs. Unlike AI-driven recommendations, these collections focus on a personal touch.

For example, a perfume expert might select and discuss their favorite fragrances for the holidays.

Pros:

  • Adds a personal, expert touch that some shoppers appreciate.
  • Highlights new products that algorithms or AI may overlook.

Cons:

  • Labor-intensive and time-consuming to update.
  • May not cater to individual customer preferences.

Final Words

These methods of product discovery are not exhaustive, and no single approach fits all customers. Successful ecommerce brands typically combine multiple techniques to deliver the best shopping experience and meet the needs of diverse customer segments.

By investing in these strategies, brands can improve customer satisfaction and loyalty while driving revenue growth.