eCommerce Search and Merchandising
Search and Merchandising
With any eCommerce website, increasing sales is the name of the game. Of course it is. But too often, retailers are doing the hard work in driving customers to their sites and falling down by failing to provide the customer experience that users demand.
Search and merchandising plays a key role in enhancing your customer experience and driving conversions. And with 30% of site visitors using an internal search box to look for products, it’s not something that you can ignore.
What is Search and Merchandising?
Search and merchandising when combined is the ability to tailor your eCommerce site search results to fit the criteria you define. You provide your users with the ability to search your site for specific products, then through your merchandising you ensure they see the best possible results for them. But also for your business.
This could include trending products, seasonal items, related products with higher margins for example. By tailoring your search results in this way, you cater to customer experience and business priorities.
You must provide the user experience consumers demand
If your SEO strategy is performing, your campaigns are tailored to your core demographics and your targeting is working, you’ll drive users to your website. But if you don’t provide the requisite user experience onsite, you’ll lose them. Up to 89% of customers will switch to a competitor because of a poor customer experience – you need to get it right.
It’s unforgivable for a modern eCommerce website not to provide tailored search results for users. Consumers expect personalisation and a smooth cross-channel experience. If they don’t get it on your website or in your app, you’ll lose them.
Do it well and you’ll boost your conversion rate
When done well, search and merchandising work in tandem. If combined correctly, they can serve both the users and your best interests.
In fact by providing site search, you’re tapping into an increased user intent – when your users search they have more intention to buy as opposed to simply browsing. By tapping into this, there’s a chance to increase your conversions by up to 5 to 6X. Get your merchandising strategy right and you’ll enjoy significant business benefits. And growth.
But too many websites are getting this wrong. Common mistakes include:
- Not supporting searching by product name or number
- Providing no useful search results when users get one character wrong in a product name
- Requiring users to search with the exact jargon used onsite
- Poor autocomplete suggestions
Mistakes are being made and poor user experience is the result. Get your search functionality optimised and your merchandising strategy on-point and you’ll find your competitive advantage.
Choosing the right search engine: Solr vs. Elasticsearch
Enhancing your search function requires the right choice of search engine. By combining AI and machine learning you can provide personalisation for your users and utilise customisable algorithms that are tailored to the needs of your business.
Here we’ll focus on Apache Solr and Elasticsearch.
Both Apache Solr and Elasticsearch are built on top of Apache Lucene and offer key benefits. The right choice depends on your business requirements and your specific use case.
Both technologies are simple to begin working with. Solr provides great functionalities in relation to information retrieval, while Elasticsearch is a better option to take into production and to scale. Below we’ve listed the key differences between the tools.
| Solr | Elasticsearch | |
| Installation / Configuration | Simple to get up and running. Supportive documentation. | Simple to get up and running with supportive documentation. You can choose between several packages depending on your eCommerce platform. |
| Searching / Indexing | Optimal for text search and enterprise applications close to the big data ecosystem | Useful for text search and an analytical engine. Powerful aggregation model. |
| Scalability and clustering | Cluster coordination dependant on support from Solr Cloud and Apache Zookeeper | Ideal for scalability. Its design is optimal for cloud deployments. |
| Community | Historically large ecosystem | Thriving ecosystem |
| Documentation | Slightly out of date | Well documented |
Other search and merchandising solutions you might be interested in
Klevu
Klevu is a leader in eCommerce search and merchandising, utilising advanced features such as natural language processing and machine learning. Personalised search results are driven by user behaviour, leading to increased conversion rates and customer satisfaction. Klevu’s seamless integration with major eCommerce platforms and scalable solutions cater to growing business needs.
Algolia
Algolia delivers powerful, fast, and customisable search results for various applications, not just eCommerce. Algolia will handle large data volumes and traffic, offers robust API support and comprehensive documentation, making it suitable for developers tailoring the search experience to meet specific business needs.
Crownpeak
Crownpeak’s AI-led and fully accessible Digital Experience Platform (incorporating Attraqt and Fredhopper) places content and commerce at the heart of the buyer’s journey. The platform delivers personalised content at scale, AI-driven commerce search, merchandising, and recommendations, to provide the best possible customer experience.
Voyado
Voyado provides powerful omnichannel marketing and personalisation features, leveraging in-depth customer insights to enhance search and merchandising efforts. The discovery engine uses AI to enhance e-commerce sites with a deep understanding of product knowledge and shopper intent.
Implementing the right strategy is to key to effective Search and Merchandising
The best approach is often to work alongside your search platform vendor and provide them with your merchandising strategy – together you can define which algorithms are right from a business standpoint. This should consider the likes of seasonality, trends and specific business requirements.
Custom algorithms should then be imported into your site search. Monitoring and adjusting results as you go is key. To help set your strategy, consider the following:
Define business priorities: Understanding key business goals will help align your search results with business performance.
Define merchandising factors: This plays into what results are shown when a specific search is conducted. Common data points to include into the algorithms include:
- Number of sales in a specific timeframe
- Product availability
- Click-through rate
- Seasonality
- Profit margin
- Product release date
- Stock levels
Implement algorithms: Once your factors are defined, it’s key that you work with your provider to integrate these into the system.
Monitor and iterate as you go: Once your functionality is up and running, test, measure and adapt.
Essential tips to optimise the search process
It’s essential for your search and merchandising approach to work in tandem. And with an optimised search process, you’ll give your users the best chance of finding the products you want them to see. Key steps to optimise the search process include: