How to improve product discovery for your BigCommerce store?

Why should brands and businesses around the world improve product discovery? In 2019, over 3.5 billion e-commerce searches resulted in $2.3 trillion in revenue for online stores, according to Shopify. Shoppers using search have a 1.8X higher conversion rate than an average visitor.

It goes without saying that merchandising choices play a key role in good search experiences. The problem often does not lie in the assortment but rather in the quality of product data. As a matter of fact, this article will show you how to improve product discovery for your BigCommerce store

Personalized Search Results

According to a Forrester study, 77% of shoppers have chosen, recommended, or paid more for a brand that provides personalized experiences. This means that product catalogs need to have product metadata that is detailed, accurate, and optimized for discovery. Vue.ai predicts product tags, available in a standard catalog allowing for standardized product data, enabling a dynamic personalization experience.

Reduce Null Result Pages

Ideally, the search engine should identify every poorly worded search and return a good set of results. With standardized product meta tags, it is possible to map common erroneous tags. Which ensures that any keyword search returns some related products or product suggestions. 

Automate Zero Result Page

If the shopper is looking for a product that is currently not in the catalog, it is important to boost products or categories that are closely related to the search terms used.  With high-quality product tags attributed to each product, retailers can understand how products across categories relate to each other and provide “related products” offerings, delivering improved alternate product recommendations to what the shopper is looking for.

Rank higher on Search Engine Results Page (SERP)

Studies suggest that over 60% shoppers start any product search on Google. Good product tags help improve product discovery on external search engines. With product data that takes into account every product’s attributes, optimize search for long-tail queries to ensure shoppers find products wherever they are, in any way they want to. Read more: Bigcommerce upsell

Manage Common Typing Errors with Intelligent Guesses

Spelling mistakes, use of broad terms, differences in how people describe the same product can make product search a struggle. A search as simple as one for a “Sheer” dress instead of a “Shear dress” can drive shoppers out of the website. Ensuring products are tagged with enough robust meta tags that enable them to be mapped with synonyms or close matches provides relevant results for every search term used. 

Improve Product Sorting and Filtering

Shoppers using site search have proven to have 21% higher average order value compared to customers that simply browse. Customizing search results can help shoppers narrow down results obtained for a query. 

Having product attributes as specific as outfit type, shape, style, length, and occasion in the form of search filters can make a huge impact on how well shoppers engage with the site. Creating and maintaining detailed meta tags with rich attributes power greater catalog coverage and better search experience.

Conclusion

Product recommendation is not at all an easy task, but if you find it too complicated, refer to BigCommerce Product Recommendation App. This is an application that creates & manages multiple rules. They can based on customer behavior and choose specific conditions to show recommendations: pages, cart items or values, and customer behaviors. In conclusion, this is a simple and flexible solution for upselling and cross-selling products.

 Atom8 for example, this is an automation app that helps to automate some websites tasks. This can also act as a product recommendation to suggest products for your consumer automatically based on their shopping behavior. So do not hesitate and check out the app right away. 


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