Unlocking eCommerce Success: Why Smarter Search Is the Key to Higher Conversions
The days of static product listings and basic search bars are over. Today’s eCommerce shoppers demand seamless, personalised experiences that help them discover the right products quickly and effortlessly. But how can businesses meet these expectations while also driving sales performance?
Enter AI-powered search platforms. By combining semantic search, vector search, and sales data insights, these platforms allow businesses to create dynamic product discovery experiences that deliver results for both customers and companies. In this article, we’ll uncover the technologies and strategies powering modern search systems and show you how to use them to unlock higher conversions and long-term eCommerce success.
The Role of Search in Modern eCommerce
Search is no longer just about finding products—it’s about creating an intuitive, personalised shopping experience that aligns with user intent and drives sales. Modern search platforms enable eCommerce websites to provide powerful product discovery tools that integrate seamlessly with business strategies.
These platforms address two primary use cases:
- Helping Users Find Products: Customers use queries to search for products, often expecting fast, accurate, and contextually relevant results.
- Generating Product Listing Pages (PLPs): AI-powered platforms dynamically generate and optimise PLPs using a combination of filtering, faceting, sorting, and pagination, ensuring that customers are presented with the most relevant and engaging products.
Additionally, advanced platforms can combine sales strategies—like boosting best-sellers and burying underperforming items—with manual configuration options to create dynamic shopping experiences tailored to both customers and business goals.
Key Technologies Powering Search and AI in eCommerce
Modern search platforms leverage cutting-edge technologies to enhance product discovery and create tailored experiences for customers. Here are the core components that make these platforms so effective:
1. Semantic Search
Semantic search goes beyond keyword matching to understand the meaning and intent behind a query. For example, if a user searches for “lightweight waterproof hiking boots,” a semantic search engine will surface relevant results, even if the exact phrase doesn’t appear in the product descriptions.
Benefits for eCommerce:
- Reduces irrelevant search results.
- Enhances the customer experience by providing more accurate matches.
- Increases conversion rates by aligning search results with user intent.
2. Vector Search
Vector search uses numerical representations (vectors) to compare the similarities between queries and product attributes. This technology allows search systems to find relevant results, even when queries are imprecise or unconventional.
Example in Action: A customer searching for “fruit-shaped candles” could find products described as “orange-themed wax decor” thanks to vector search’s ability to match contextual meaning rather than exact terms.
3. Filtering, Faceting, and Sorting
These classic eCommerce features are essential to improving the usability of search and product listing pages:
- Filtering: Allows users to narrow results by attributes like price, colour, or brand.
- Faceting: Provides dynamic categorisation, helping users explore relevant subsets of products.
- Sorting: Enables users to reorder results based on criteria like price, popularity, or relevance.
When paired with AI, these features can dynamically adjust based on user preferences or historical sales data.
4. Boosting and Burying with Sales Data
Search platforms can use AI to optimise product ranking by factoring in real-time sales performance and business priorities:
- Boosting Best-Sellers: Popular items or top performers are elevated to the top of search results and product listing pages, driving higher conversions.
- Burying Underperformers: Low-performing or less relevant products are deprioritised to improve the overall shopping experience.
Manual Adjustments: In certain cases, businesses can manually configure product orders for specific categories, ensuring that strategic items are prioritised.
Business Benefits of Modern eCommerce Search Platforms
Modern search platforms are more than technical tools—they are key drivers of business performance. Here are some of the ways they deliver value:
1. Improved Customer Experience
By delivering accurate and contextually relevant search results, eCommerce platforms can dramatically improve the customer journey. Faster, more intuitive search experiences keep users engaged and reduce frustration, increasing the likelihood of a purchase.
2. Increased Sales and Conversions
Search platforms that integrate sales data into product ranking can surface high-performing products at the right time. Features like boosting best-sellers and personalising PLPs help match customers with items they are more likely to buy.
3. Optimised Product Discovery
With advanced filtering, faceting, and sorting, customers can explore products more efficiently. These features not only enhance usability but also increase the chances of customers discovering complementary or higher-value products.
4. Operational Efficiency
By automating tasks like generating PLPs or ranking products based on performance, search platforms reduce the manual effort required from eCommerce teams, allowing them to focus on more strategic priorities.
Challenges and Considerations
While modern search platforms deliver transformative benefits, implementing them successfully requires addressing certain challenges:
1. Data Quality and Organisation
Search platforms rely on structured, accurate data to deliver meaningful results. Poorly organised or incomplete product data can undermine their effectiveness.
Solution: Invest in data cleansing and enrichment to ensure product attributes are complete, consistent, and descriptive.
2. Balancing Manual and Automated Adjustments
While automation improves efficiency, certain categories may require manual input to align with business strategies, such as prioritising new product launches or seasonal promotions.
Solution: Choose platforms that offer both automated and manual control for optimal flexibility.
3. Integration with Legacy Systems
Integrating modern search platforms with existing eCommerce infrastructure can be complex, especially if legacy systems lack APIs or compatibility.
Solution: Work with platforms that provide robust integration capabilities and pre-built connectors to streamline the process.
How to Get Started with Search and AI in eCommerce
For eCommerce businesses considering modern search platforms, here’s a step-by-step approach:
- Define Your Goals: Identify the specific challenges you want to solve, such as improving search relevance, optimising PLPs, or increasing sales.
- Evaluate Platforms: Compare solutions like Elastic, Google Vertex AI Search, and others based on scalability, ease of use, and integration options.
- Prepare Your Data: Ensure your product catalog is clean, organised, and rich with metadata to maximise search performance.
- Start Small: Launch a pilot project with a specific use case, such as improving search queries or generating a dynamic PLP for a key category.
- Measure and Iterate: Use analytics to track the impact of your search platform and refine your approach over time.
Conclusion: The Power of Search and AI in eCommerce
Search and AI platforms are redefining the eCommerce landscape by enhancing product discovery, boosting customer satisfaction, and driving revenue growth. From improving search relevance to dynamically generating product listing pages, these tools allow businesses to create seamless shopping experiences that align with both customer intent and business goals.
By investing in modern search technologies, eCommerce businesses can not only keep pace with customer expectations but also gain a competitive edge in an increasingly crowded market. Whether you’re new to search platforms or looking to upgrade your current system, now is the time to unlock the full potential of search and AI.