Thinking of Switching Search Engines

The big gorillas of open-source search engines are Solr and Elasticsearch. Solr is the older of the two and has been managed as an Apache open-source project for as long as I can remember. Elasticsearch is younger and has distinguished itself for its data analytics support as well as search. Both search engines use the same underlying Lucene index for the core search capabilities, and in many ways, they have feature parity. Nonetheless, many organizations may be considering a switch from Solr to Elasticsearch, or from Elasticsearch to Solr. Factors such as team skills or platform consolidation play a role in these initiatives. But what should a project team expect when planning to make the switch? What’s the resource commitment for a business to change search engines?

Returning Related Results with Query Expansion

When working with non-search experts, I try to spend time explaining key search concepts so that we understand what’s possible with search and what trade-offs we can expect from different search strategies. One idea that most people seem to be familiar with is the use of synonyms for query terms. Query synonyms are examples of a more general techniqe called query expansion. A query is a list of one or more words.

Getting Started with Query Log Analysis

If you manage an ecommerce property and are responsible for site search performance, you may be wondering how get started measuring search. Site search has some unique characteristics but there are some simple ways to get started with measurable insights you can use to track performance as you make improvements to your search results. In this post, we’ll look at getting started with query log analysis.

Automate Search Relevance Testing

When it comes to search, traditional testing strategies should be adjusted to fit the unique conditions of relevance testing. If your dev team has invested in automated testing, it may seem fairly straightforward to use the same techniques to test search relevance. Sadly, this isn’t a successful strategy. I’ll explain why, but first let’s review traditional approaches to testing.

Site Search Analytics

To create a fully optimized e-commerce search experience – the kind that drives engagement and conversion – you need to know how your shoppers are using search. You will learn the top queries for your shoppers — actionable intelligence on your shoppers intentions and expectations. If you’re not already tracking the searches performed on your site, you need to start now. Even if you’re not ready to analyze the search activity, you can just turn on logging now and let it accumulate until you are ready.

Search Relevancy for Ecommerce

The defining difference between a great search experience that drives sales and a poor experience that loses sales is relevance. How relevant are the product results to your shopper’s intent? The more relevant your search results, the more engaged your customer is likely to be. Users reward highly relevant search results with more sales, and so it is very worth investing time and money into increasing the relevance of your search results.

Search Runs on Data

The defining difference between an excellent search experience and a substandard experience is relevance. How relevant are the product results to your shopper’s intent? The more relevant, the more engaged the customer is likely to be. The foundation of an engaging search experience is the quality of your product metadata. Without useful metadata you are reliant on undifferentiated text searches which do not perform nearly as well when it comes to returning relevant products.

Sorting, Paging & Filtering Search Results

Sorting and paging are search interactions that many e-commerce sites get wrong but are easy to fix. Sorting Sorting is a way of seeing the same results from different perspectives. It can help shoppers find products or get a sense of what’s available to buy. When you display results after a search, the default sort order should be by relevance. Many e-commerce sites make the mistake of sorting by popularity by default.