How to Build Effective Search Services for Your Company: A Guide to Choosing the Right Search Solution
Have you ever thought about how powerful search can transform your business? As an e-commerce platform, an internal tool, or even a content-driven site, how your users interact with search can make or break their experience. Having worked with search systems across various projects, I’ve seen firsthand how a well-implemented search engine can improve user engagement and boost conversions. But when it comes to picking the right search solution for your company, it can get overwhelming — especially if you don’t know where to start.
The background
Why Should You Care About Search? My Personal Experience
My friend and I were debating how search functionality should work. I suggested using debouncing or adding a time delay before each request, while he argued that we should handle each request individually by calling the API, discarding old responses, or caching them for future use.
It’s easy to overlook search when building a website or app, but trust me, search is often the silent hero that drives users to the right products or services.
In this blog, I’ll share personal insights from testing different search solutions (yes, even Amazon’s , Google) and provide recommendations to help you choose the search system that works best for your project, whether you’re a startup, mid-sized company, or enterprise. So, let’s dive into it!
This blog covers the Working and Search part of System, whole there interesting another part Suggestion will cover in next blog :)
Types of Search: Which One is Right for You?
When it comes to search, there’s no one-size-fits-all solution. Different types of search systems serve different needs. Here’s a breakdown of the most common types of search functionalities:
1. Basic Search (Keyword Matching)
The simplest form of search, matching the words a user types with product titles, descriptions, or metadata. Great for small catalogs with fewer products.
2. Faceted Search
Think filters — size, color, price, and more. It’s what you see on Amazon when you narrow down your results to only the “red” shirts under $50. If you have a growing catalog, this is a must.
3. Autocomplete Search
As the user types, suggestions pop up. This not only saves time but also guides users to the right products faster. Super effective for large catalogs!
4. Personalized Search
This goes beyond keywords. It’s powered by algorithms that suggest products based on past searches or purchases. Amazon does this beautifully — imagine you’re buying a phone case, and it suggests related accessories.
5. Voice and NLP Search
The future is here! Voice search and Natural Language Processing (NLP) allow users to search in a conversational manner. Want to find “blue sneakers under $50”? NLP understands that and gives you the best options.
How Amazon and Google Search Work: Behind the Scenes
Let’s take a look at two giants — Amazon and Google — to understand how search works on a large scale.
1. Amazon Search:
This image outlines the architecture for an e-commerce search system with integrated Recommendation Engine, Personalization Engine, and Filtered Search Results. Let’s break down the components:
- User Search Request Flow
- Normal User Data / Personalization data passed with User Query - Search Service Layer: The core part of the system where most of the processing happens. It is responsible for query parsing, tokenization, spelling corrections, synonym expansion, and query rewriting. These steps help in better understanding and transforming the user input into a form that the system can process effectively.
- Search Index & Ranking
- Search Index: A large, optimized index of products that helps to quickly match and retrieve search results.
- Search Results Ranking: Once search results are retrieved, they are ranked based on relevance. This could involve relevance scoring or more complex algorithms like Learning-to-Rank (LTR).
- Cache Layer: Frequently accessed search results are cached to reduce the need for repeated searches, improving response times.
If you need detailed explanation on each part drop a Comment I’ll post a blog explaining each component.
2. Google Search:
As you can see in the above diagram, there are numerous services and algorithms tailored for their specific needs.
You may start to wonder, “Do I need to write these kinds of services for my own search?” The simple answer is no. Their business needs are different from yours and mine.
What works for Google is optimized for their scale, infrastructure, and specific goals. For your project, it’s essential to identify the right fit for your needs and find solutions that align with your goals. We don’t need to replicate complex systems but rather focus on creating efficient, targeted solutions that serve our unique requirements.
How to Choose the Right Search for Your Project or Business
Picking the right search system isn’t about what’s popular — it’s about what works best for your specific needs. Here’s how to make the right choice:
1. Consider the Size of Your Catalog
— Small Catalogs: If you have a limited number of products, a simple keyword search might do the trick.
— Large Catalogs: Faceted search(Elasticsearch , Apache Solr ,MeiliSearch) Autocomplete (algolia , Backend Auto suggestion System), and Personalization (PredictionIO , Custom Recommender Systems (RS)) are essential for larger platforms.
2. User Experience Is Key
User experience is everything. A smooth search system doesn’t just return results; it guides the user. Features like autocomplete, filtering, and real-time suggestions can significantly improve engagement.
3. Budget Considerations
If you’re a startup or a small business, you’ll want to consider cost-effective solutions. Fortunately, there are great open-source search engines like Meilisearch and Typesense that don’t break the bank.
4. Scalability for Growth
Make sure your search engine can scale as your business grows. As traffic increases, you’ll want a solution that can handle the load, like Elasticsearch or Algolia.
5. Search Type Requirement
Do you need basic search functionality, or are you looking for advanced features like NLP or personalized results? Choose a solution that matches the complexity of your needs.
Open-Source Search Engines You Can Use
If you’re on a budget or just want more control, open-source tools are a fantastic choice. Here are some of the best options:
1. Elasticsearch
Powerful and scalable, Elasticsearch is great for businesses that need advanced search capabilities and plan to grow.
2. Meilisearch
Fast, lightweight, and easy to integrate. Ideal for smaller businesses or projects that prioritize speed over complex features.
3. Solr
Built on Apache Lucene, Solr is an enterprise-grade solution that offers flexibility and supports complex search features like faceting and filtering.
4. Typesense
A modern, user-friendly search engine that’s fast and scalable — great for small to medium-sized companies.
5. Apache Lucene
If you’re a tech-savvy developer and want complete control, Lucene is the foundation for many search engines. It allows you to build a custom solution from the ground up.
Final Thoughts: Choose Wisely for Your Business
Search is a critical part of any digital experience, whether it’s on your website, app, or e-commerce platform. The right search system not only helps users find what they’re looking for but also drives conversions, engagement, and satisfaction. So, take the time to understand your business needs — be it a small, mid-sized, or large company — and choose the search solution that fits.
Remember: It’s not just about the technology — it’s about creating an experience that feels seamless and effortless for your users. Whether you go with an open-source option or an enterprise-grade solution, getting search right can change the way your customers interact with your business.
