4 Tips to Optimize Your Internal Search Engine in e-Commerce

The behavioral analysis of Internet users, during a session on an e-commerce site, for example, shows a significant use of the search engine top seo agency
On average 40% of Internet users use the search bar during their navigation. The tendency is accentuated as soon as the site proposes a catalog rich in references. In the era of commercial sites with a r éférencement happening more and more complex, not counting those that combine marketplace , it becomes difficult to navigate to the desired product without exceeding the rule of 3 clicks.

The internal engine becomes a must for all Internet users, and a priority for e-commerce sites . Well optimized, it can be a sales accelerator, and thus improve the ROI of your traffic acquisition channels (SEO, AdWords, emailing …) via the increase of the conversion rate . Conversely, if it is not efficient, it may be a vanishing point for your shop and increase your bounce rateWe will see in this article the 4 points to analyze to improve your search engine , and positively impact the performance of your e-commerce.

Audit the relevance of the results of the top 100 keywords

Before deeply modifying your internal search engine, it is important to analyze the existing, ensuring the relevance of the results. For that, it will be enough to extract the key words the most plebiscites by your Internet users, in order to analyze them individually top seo agency
If you use an internal search engine solution, you can easily find these queries in your back office. In case you use the native engine of your e-commerce solution, it is possible to go back to the requests of the users thanks to the tools of web analytics or via your back-office e-commerce.

The objective is to find out if the answers provided really correspond to the will of your company: Does the request show enough results? Are these results relevant? High margin products or promotions better than others?

To perform an audit , here is a typical action plan:

list the 100 most searched keywords (on an Excel file for example)

individually test each request and give it an overall score. You must take into account the criteria that interest you: relevance, number of results, exclusion of products out of stock …

count the number of satisfactory requests on the total

If you have at least 20% of your top queries with a low score, that is, below average, you are currently losing sales. It is therefore necessary to thoroughly review the operation of your internal engine.

Define a keyword optimization process

The first step to optimize an internal e-commerce engine is to improve the relevance of the results. There are two main types of internal engines in e-merchants:

  • the native search engine (Magento, Prestashop, WooCommerce, Shopify …)
  • the use of an external search engine solution (open source, SaaS …)

In the case of a native engine, it will be necessary to modify the product sheets to add keywords, to highlight them on the queries. If this is not enough, it will also provide for the creation of additional fields, and modify the operation of the engine so that it takes into account these new fields. This process can be tedious and does not guarantee top seo agency relevant sorting of results. In the case of an outsourced engine, all these features already exist, and there is nothing to develop: you can however optimize the display of results, keyword by keyword, focusing on top searches. This work may seem time consuming but it will optimize to the nearest millimeter the most wanted terms. For your information,algorithm developed by the solution will also allow you to act on the other keywords, which constitute the “long tail”. You can for example cross additional criteria (data from your ERP in particular) or create synonym lexical fields very quickly, to make the results more relevant automatically.

Implement searchandising: the gondola head e-commerce version

As a consumer, we are all faced daily with the rules of merchandising supermarkets: gondola heads, promotional offers, new products positioned at the entrance of the shelves, etc. This lever is a strong sales generator, and can multiply sales by a factor ranging from 3 to 5 depending on the attractiveness of the offer.

Searchandising uses the same process. This is to display products, not only taking into account the entry of the user, but also using other criteria (margin rate, stock available, deal negotiated with the supplier, product rotation, etc. .)

Take the example of an e-commerce site specialized in computer hardware. For the “500 GB hard disk” request, the semantic query will only display products with this storage capacity. However, we may want to position at the head of the results a selection of 1to and 2to hard drives benefiting from a commercial discount, to promote the sale of these references and suggest to consumers more advantageous offers. If the A brand 1to hard drive is a few euros at the same price as the B brand 500GB hard drive, the consumer will be tempted to take the A brand model.

It is therefore essential to establish a strategy of searchandising. How? After you have completed your keyword audit, you will need to define display rules based on business criteria. For this there are two options: the development of a searchandising module, or the use of a search engine technology including searchandising.

The home-made solution can be expensive in terms of project management and development time. It will also have to be maintained by your teams, especially during updates on your e-commerce heart. Opting for an already developed internal engine technology, such as SaaS for example, offers the advantage of not having to worry about the technology (server loading time, development costs, updating of the solution, etc.). : everything is managed by your solution. In addition, this will allow you to customize the display of products by crossing many additional criteria, in order to increase the relevance, and assign an individual scoring to your products that will condition the display compared to other references.

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