Building an in-house search for e-commerce

Building an in-house search for e-commerce


An e-commerce store without a good search is like a grocery store without labels, you'd be left wandering down the aisles of the store with the hope of locating what you are "searching" for by chance. As the store owner, this is bad business as some customers might get jaded before finding their "search", and the outcome of this means no or little business. This can also be applicable to an e-commerce store but replacing the attendants with the search widget or site search option, this illustration's outcome has made the need for a search widget unquestionable.

The efficiency of this widget has surpassed the need for navigation on the website by users but has also become a great tool for the store owner such that, if properly optimized and wielded rightly, it drives sales and increases traffic. The tech surrounding the functionality of the search widget is beyond the generic search present on most websites as this only gives results based exclusively on the search keyword, for example, if the word "shirt" is typed into the search bar, the search results are not expected to go beyond the word "shirt" and we could say this type of search is based strictly on the search keyword and not influenced by the user experience and all other factors.

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The need to rightly optimize the search, as the effectiveness of the generic search has been questioned. Currently, there are two main options which we will try to describe at a high level. For most CTOs this sounds like "build vs buy" and in many cases, the decision depends not only on what is better but what kind of company you are in: are you a tech-first company or your business first company.

Building an in-house search for e-commerce

Building e-commerce search yourself involves you employing the use one of search engines like Elasticsearch, ManticoreSearch or Solr but there are a handful of search features to consider and scope when building e-commerce search, like search types, autosuggest, typo tolerance and many other built in features require a cross-functional team and tools.

These search solutions provide a very flexible search platform. Setting it up can take a month at most, and this relies upon certain factors like the number of products and so on. The need to structure and optimize data for search cannot be left out as it is crucial to the functionality of the solution. The data should be prepared for search: which includes normalizing attribute values, the configuration of basic and advanced features that would improve user experience follows structuring and optimization of data then the ranking of search results based on their relevancies which can be carried out by developing custom ranking algorithms and also specific search functionality based on the specificity of the e-commerce store has to be developed, search functions like autosuggest, search voice assistant likes. And all these have to be pulled together by a team that will dedicate close to 12-15 months for the completion of this search tech.

Pros and cons of using self-hosted search

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Adopting 3rd party vendor

SaaS companies specialize in specific niches and always optimize their products to get excellent results based on the niche the product specializes in. They have focused on creating an excellent site search that possesses features like text auto-complete, spell checker, natural language processing (NLP), advanced stemming, and more.

Pros and cons of using SaaS


Where to start?

If you are wondering where you should start while doing your research on how to improve search on your site there are a few questions to answer first. Do you know what problem you are solving or what goal you have? If so - great. If not, you have to start from there. If you have an answer to this question here are a few basic metrics you should track to understand how your search performs and affects sales.

Conversion Rate

Conversion rate is arguably the most important metric, it has a significant impact on your site's profitability. When your website search function as well as it should, it becomes a salesman between users and their desired destination pages. That translates to an opportunity for engaging and converting a potential customer.

Bounce Rate

The bounce rate is the rate at which new visitors visit your site and immediately click away without doing anything, and you will want to minimize this especially if the bounce rate after the search is high. A high bounce rate can mean several things and common problems include poor design, low usability, or high search time. This is where your potential for improvement indicator is.

Search Page Speed

Page Speed is the amount of time that it takes for a web page to load. A page's loading speed is determined by several different factors which include a site's server among others and this issue can be solved by site search providers or the in-house developing team.

How Deep Search Users Go

This is as simple as it sounds and just entails how deep search page users will go. A lot of users get jaded after searching the first and second pages, so it's up to the search provider to optimize the search tool to bring results relevant to the keywords up in the search page. Key things you need to keep in mind while working on improving your search.

Relevancy Ranking

The task of ensuring that the best-matched results show up first becomes more difficult, ad data grows and negligence of this factor can result in bad search user experience which is not a good thing for your e-commerce store. Constantly improving your data tagging, assessing site search performance, and tweaking your relevance algorithms will be key to search relevancy.

A/B Testing

This is an important tool that involves a performance comparison between two versions of a software (a search results page, in this case). A/B testing can be used to determine which search changes to launch after monitoring certain metrics like the ones listed above, then your A/B testing approach will have significant implications for what kinds of changes you need to create, test, and then launch.

Team Cooperation

Last but not least building an in-house search for e-commerce definitely starts from a team. Talented engineers, data analysts, and marketers are required to work in an across-functional team together. Good chemistry between team members will ultimately mean the team can move fast toward achieving results.

In conclusion, the pros and cons of both options have to be considered in terms of how it fits the e-commerce store and the budget, among other factors.

Choosing how to develop your e-commerce search, shouldn't be a decision to jump into. Teams have to define what goals they want to achieve by working on search and evaluate all options carefully before making any decision.

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