E-Commerce Search Analysis | Search Rapid Test

Get your potential analysis to increase your online sales.

Use our e-commerce search analysis to find out how powerful your search is, how well it supports your company’s customer experience and where you can leverage the sales potential of your search.

With the help of our Search Rapid Test, we evaluate the performance of your search solution using 14 criteria in 5 categories. You receive a ranking, a summary suitable for management buzzers and a table with our e-commerce search analysis and the formulated potentials. The SRT is usually free of charge for you and can be implemented quickly and easily in B2C. In B2B, we either require access or arrange an appointment to go through the analysis with you.

Why a good e-commerce search is so crucial…

The e-commerce search is the central tool for your customers when it comes to finding products quickly and easily. 43% of all visitors to your website use the search immediately and without any detours. And this trend is on the rise. A good search is therefore essential. It increases the probability of purchase, effectively enhances the shopping experience (CX) and increases customer loyalty. Loyal customers with a positive shopping experience like to return more often, which increases sales. For this reason, e-commerce businesses usually invest in specialized search solutions that use modern, increasingly AI-based algorithms to deliver the most relevant results based on the search query.

Furthermore, good search solutions also offer tools and functions beyond pure search to improve the shopping experience and increase sales. These include, for example, product boosting, customization of facets, context-based recommondations in various places, etc.

Why should you use our search function evaluation?

E-Commerce Such-Analyse

Identify optimization potential

Use our e-commerce search analysis to discover which aspects of your search technology can be improved to maximize the user experience on your website and increase conversion rates.

E-Commerce Such-Analyse


Use a comprehensive e-commerce search analysis scoring system to find out how your search performance is performing and what specific measures you can take to optimize your search function.

E-Commerce Such-Analyse

Free service

We carry out the comprehensive e-commerce search analysis or Search Rapid Test as a service free of charge for you and thus offer you a valuable external insight into the performance of your search function without any obligation to pay.

E-Commerce Such-Analyse

Industry comparison

We sort your score within your industry and give you an indication of how your business compares to your competitors. Our e-commerce search analysis enables you to understand your company’s current position within your industry.

How our Search Rapid Test works:

  1. Register: Register with us to start the SRT. Your data will of course be treated confidentially and will not be passed on to third parties.
  2. Carrying out the analysis: Our experienced experts will then analyze your current search. Based on the classification in a points system, you will receive a meaningful result with an overall score as well as at category level.
  3. Summary of results: Once the analysis is complete, you will receive a summary as well as a table with the evaluation of the results
  4. Meeting: We will discuss your results in detail in a personal meeting. During this meeting, we will explain the individual points and provide information on the potential that you are currently missing.
Business Sumerary from Search Rapid Test for a German drugstore chain

Business Sumerary from Search Rapid Test for a German drugstore chain

A closer look at five categories…

The analysis of social proofing looks at how the development of trust is supported and how effectively purchasing decisions are influenced. This is achieved by displaying different types of social behavior. These include customer and product reviews, user group behavior (user social proof, e.g. X number of purchases in a certain period) or the use of well-known brand logos to increase credibility. Or the endorsement of celebrities or experts as Celebrity Endorsement /Expert Social Proof, as well as the use of personalized product badges.

Content discovery analysis examines how effectively content such as how-to guides, advice links and additional information is presented to customers to satisfy their information needs. This offers numerous benefits for the user and helps to develop trust. For example, through FAQs or tips, the shopping experience is enriched and the customer benefits from the comprehensive range of information, making decision-making easier and positively influencing the user experience. AI- and ML-powered content recommendation systems use advanced algorithms and data analytics to deliver personalized suggestions based on website interactions, search history and preferences.

The analysis of product recommendations examines how effectively product recommendations are played out, ideally dynamically based on various criteria such as the current context, the user profile and the characteristics of the product in question. This includes, for example, the presentation of trend products, bestsellers and products based on individual customer behavior. Personalized and context-based recommendations are also checked.

The analysis of query suggestions examines how potential search results are continuously calculated and suggested while a search query is being typed. Query suggestions are therefore also known as “search-as-you-type”. User behavior and context should be taken into account in order to achieve a higher click-through rate. In order to display the most relevant recommendations, search results are prioritized according to various factors. These include the placement of relevant products with frequent search queries and the adaptation of search results according to historical user behavior.

The analysis of search results is the most important analysis point and includes an evaluation of the effectiveness and efficiency of the search results displayed. It takes into account personalized aspects such as customization of search suggestions based on previous searches, the current shopping cart and other contextual information. In this context, AI can be used to prioritize search results based on different categories such as user preferences or search histories. Furthermore, points such as error tolerance or predictive search (“Did you mean…”), product boosting and the adaptation of facets are analyzed.

Geschäftsführer Ingo Ax

Ingo Ax – Managing Director codeitlabs GmbH

Are you ready to optimize your search?

Get in touch now and we will start your Search Rapid Test! You will get a valuable insight that will drive your online business forward. Optimize your search to increase customer satisfaction, expand your market share and boost your sales figures.

Arrange a meeting

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