Internal search is an important tool for quickly finding information on a website, especially on resources with large amounts of content such as online stores and news portals. Unlike menus, a site search provides instant results, saving users from having to scroll through pages.
Effective search improves UX by speeding up tasks like purchasing a product or reading an article, which directly increases conversion.
The advantages are clear:
➤ Fast access to content: visitors can quickly find the products, articles, or documents they need.
➤ Reduced bounce rates: an intuitive site search decreases the chances of users leaving due to poor navigation.
➤ Increased conversions: users who use the search feature are more likely to make purchases in online stores.
Where is internal search critically important? In some cases, the absence of an effective search can seriously harm the business:
A properly configured internal site search is not just a convenience but an essential tool for growing your web resource and increasing its competitiveness.
What types of internal search systems exist?
Imagine a large online store without a search function. A user needs to find a specific phone model — but instead of simply typing the device name into a search bar, they have to endlessly scroll through product pages. Most likely, this customer will close the site and go somewhere everything works perfectly.
That’s why a well-configured internal search becomes an essential element of any site with extensive content. Now, let’s explore how to add search to a website, what types of systems exist, and how they differ.
Simple search forms
This option suits small websites and blogs with a limited number of pages. A basic site search is implemented via an HTML form and JavaScript, working with direct character matching in static content.
➤ Advantages: easy setup and quick integration.
➤ Disadvantages: lack of indexing, filtering, and relevance.
Suitable for business card websites and personal blogs where handling complex queries is not required.
Database search
This method uses SQL queries to databases like MySQL, PostgreSQL, and other relational systems, offering filtering and sorting of content. Such search is ideal for medium-sized businesses, for example, online stores where users can filter products by price or color.
➤ Pros: support for complex filters and query logic, integration with the admin panel.
➤ Cons: slower query performance with large data volumes.
It can be improved using MySQL Full-Text search or the Solr engine to increase result accuracy.
Indexed search
For large platforms and marketplaces, high speed and search accuracy are critical, which is ensured by systems like Elasticsearch and Apache Solr with data indexing. This approach speeds up search by pre-organizing information, which is especially useful for sites with a large number of pages. Elasticsearch offers powerful APIs for query caching and result ranking.
➤ Pros: high performance, accuracy, and the ability to cluster data.
➤ Cons: complex setup and the need for powerful servers.
These solutions are ideal for news portals, marketplaces, and large SaaS platforms.
Search via third-party APIs
You can use ready-made search solutions for your site. Tools like Google Custom Search, Algolia, or OpenSearch integrate quickly via API but depend on external services.
➤ Pros: quick implementation, low development costs.
➤ Cons: limited customization options and the risk of functionality changes. Suitable for startups and temporary solutions.
Each system has its pros and cons. Simple forms fit small sites, while powerful engines suit large platforms. The choice depends on business goals and content volume, but quality search is key to successful user interaction.
How to add basic search with HTML + JavaScript
How to add search on a website using standard HTML tags and ? This approach assumes that the user enters a query in the search bar, and the site redirects them to a search results page.
Example of a basic HTML search form:
This code creates a form that sends the query to be processed by the server.Limitations of basic HTML search:
➤ Lack of content indexing — queries are passed without considering relevance.
➤ Search by headers and metadata — limited to <title> and meta tags.
➤ Lack of filtering and sorting — no filtering by categories.
➤ No autocomplete and suggestions — no prompts, which negatively affects UX.
How can basic search be improved? Adding JavaScript scripts can significantly expand its functionality. For example:
Although standard HTML search forms have their limitations, they can serve as a starting solution for small websites or blogs where advanced features are not yet necessary.
Internal search with MySQL and PHP
Integrating search with a database enables creating powerful and flexible features on websites. MySQL combined with PHP provides flexibility in managing queries and processing results, which is important for sites with large amounts of content, such as online stores, forums, and news portals.
How to create an SQL query for searching content?
For a simple search, you can use the LIKE operator, which allows finding partial string matches:
SELECT * FROM articles WHERE content LIKE '%пошук%';
This query will return all articles in which the word "search" appears in the text. However, this method of data processing is inefficient for large databases, as it requires scanning all rows and leads to a high load on the server.
Improving search with FULLTEXT index in MySQL
Using a FULLTEXT index significantly improves search performance and relevance, allowing searches over entire texts with consideration of word morphology and ranking of results.
Example of a query using FULLTEXT:
SELECT *
FROM articles
WHERE MATCH(title, content) AGAINST('поиск' IN NATURAL LANGUAGE MODE);
Advantages of FULLTEXT search:
➤ Higher query processing speed;
➤ Ability to rank results by relevance;
➤ Consideration of word proximity and frequency of use.
To enable FULLTEXT search, it is necessary to add an index:
ALTER TABLE articles ADD FULLTEXT(title, content);
Optimizing results with relevance ranking
FULLTEXT allows ranking results by the degree of relevance to the search query. This helps to provide more useful results to the user.
Using elasticsearch or apache solr
Using MySQL with PHP opens wide opportunities for effective site search. Proper indexing setup and query optimization significantly enhance the user experience.
Using elasticsearch or apache solr
These are powerful full-text search engines that allow processing large volumes of data and provide users with fast and relevant results. These tools are actively used on large platforms such as marketplaces, news portals, and corporate content management systems.
What is elasticsearch and how does it help index content?
Elasticsearch is a search engine based on Lucene with a distributed architecture that quickly indexes large volumes of data and performs complex queries. It creates indexes for textual, numeric, and geographic data and integrates with PHP through API integration, allowing customization of search functions.
Its main advantage is dynamic ranking of results, taking into account query popularity, synonyms, and personalization. It also supports filtering and sorting, which facilitates the search for products in stores or articles on news portals.
Advantages of solr for full-text search
Apache Solr is also based on Lucene and is ideally suited for tasks related to content management and enterprise systems. Its strengths include:
➤ High indexing and data processing speed.
➤ Support for complex search queries with lexical analysis.
➤ Advanced capabilities for working with multilingual content.
The Solr engine is especially valued for its clustering and scalability capabilities, making it an excellent choice for large platforms with high loads.
These technologies are important tools for creating efficient internal search systems capable of processing and analyzing large volumes of data at high speed.
Connecting google custom search engine (CSE)
This is a simple solution to add search functionality to a website, using Google’s algorithms. Setting up and integrating CSE takes little time and does not require deep technical knowledge.
How to set up free Google search?
To start working with CSE, you first need to register your site in Google Search Console, which allows proper tracking of page indexing. Then:
➤ Go to the Google Programmable Search Engine platform and create a new search by specifying your website’s domain.
➤ Configure the settings — you can limit the search to your site only or include multiple domains.
➤ After creation, you’ll receive a unique HTML code that needs to be inserted into your page’s markup.
Installing site search is simple: copy the code and insert it into your site's HTML markup. For flexible customization, use Google Tag Manager, which allows managing the code without direct access.
Limitations of Google CSE
Despite its convenience, Google CSE has some drawbacks:
➤ Dependence on Google indexing. If a page on your website hasn’t been indexed by the search engine yet, it won’t appear in the search results, even if it exists on the site.
➤ Ads in the free version. The free version of CSE includes ad blocks that may distract users. To remove ads, you need to switch to the paid version of the service.
Using Google Custom Search Engine is a great solution for those who want to quickly add search functionality to their site and are ready to accept certain compromises.
Tools to improve search
Modern technologies significantly enhance the effectiveness of internal site search, improving its accuracy and user-friendliness. Let's look at the key tools:
➤ Autocomplete: speeds up the search process by suggesting query options as the user types, which is especially important for e-commerce websites. Implemented using JavaScript autocomplete, jQuery, and AJAX search.
➤ Filtering and sorting: refines queries by categories, price, and other parameters, and sorts results by relevance.
➤ Synonym support and typo correction: corrects spelling errors and offers synonyms to improve accuracy using NLP (Natural Language Processing).
➤ Search query logging: helps identify popular topics, improve search results, and enhance website content.
These tools make search faster, more precise, and more convenient for users, enhancing interaction with the website.
How to track the effectiveness of internal search
Tracking the effectiveness of your site’s internal search can be organized through Google Analytics by using the internal search report. This report shows which queries users enter and how often they lead to successful results. It helps identify popular search terms and pages that need improvement. By analyzing this data, you can enhance the site structure and increase the accuracy of the search engine.
Setting up tracking via Google Tag Manager allows flexible collection of query data, including those that yield no results. This signals the need to add relevant content, which improves user experience and boosts conversions.
Errors in search setup
Such errors can significantly reduce the effectiveness of search and worsen the user experience, including:
➤ Lack of proper content indexing, leading to missing or outdated search results;
➤ Low relevance of search results when the engine fails to accurately match the user's query;
➤ Ignoring UX research and insufficient query processing, reducing search usability;
➤ SQL injection vulnerabilities due to improper data handling.
It is important to consider all these factors to create a high-quality and secure search system on the website.
Conclusion
You can create a search engine on your website in various ways — from simple HTML forms to powerful solutions like Elasticsearch. The choice of the right option depends on the site structure, indexing requirements, and budget constraints. Implementing an effective internal search improves SEO promotion, enhances user experience, and increases conversions. It is important to regularly analyze search query logs, test ranking algorithms, and consider UX optimization.
