What is the future of search?
A brief history of search
Like anything else, search engines have evolved. In the beginning, the web directory acted as an index of websites. But as the number of websites increased, the need for an advanced solution to search through them was required. AltaVista and web crawlers were born to search through all these sites automatically. Then came Google and its PageRank algorithm, which counted the number of pages that linked back to a site and ranked it higher if it had more links. The PageRank algorithm quickly became one of the most important algorithms in computer science, and search engine optimization was born.
Search has been an integral part of the web since the beginning. It has advanced and grown from simple keyword search to advanced natural language processing.
Today, search is a blend of technology and art, where it tries to understand user intent and fulfill their needs. It is increasingly becoming a crucial component for every website. Not only does it help customers find what they are looking for, but it also provides valuable signals to website owners about their business.
Some use cases of search include:
- E-commerce: Search helps users find products and services on e-commerce websites and enables them to browse through catalogs efficiently
- Media & Entertainment: Search helps users discover new content and recommend similar content based on their previous actions/behavior
- Jobs & Classifieds: Search helps users find jobs and relevant information about jobs based on various filters such as location, type, etc.
What might the future of search be for products, documents, and eCommerce? What is needed?
We're living it right now.
- Autocomplete search suggestions
- Full-text search with semantic Ranking
- Personalized search result ranking
- Intent-driven Semantic Search
- Highlighting key portions of top-ranked documents to show relevancy
Get customers to products quickly
As information systems have progressed, so have search solutions. Initially, they focused on getting customers to a website or document that answered their query. Still, as online shopping grew, it became necessary that customers found the product they were looking for directly. This has made Semantic Search solutions popular among e-commerce companies today.
Search solutions should now focus on getting customers to the product or document they are looking for no matter what they search.
Search must be easy
Search is a fundamental part of the Web. We have come to expect that if we want to find something, we can use a search engine. The first result may not be correct, but it will point us in the right direction.
The future of search is about making things more convenient for the user. The search box on a website should be easily accessible and not hidden in a menu or buried at the bottom of the page. It should also be present on all pages of your site, not just on a designated search results page.
Autocomplete search suggestions should help with spelling mistakes and type-ahead suggestions of search terms and popular queries.
Rank results based on intent
Search engines are becoming more intelligent with their results based on user intent and behavior. If a user is not satisfied with their search results, they're likely to leave the site, often without making a purchase or completing another conversion event.
In the past, the ability to rank results based on simple keywords was all that mattered. But now, consumers are expecting more from search. Semantic Ranking is the ability to order full-text or keyword search results based on user intent and semantics. It is one of the most exciting developments in search technology over the past decade. It allows a website's search tool to find relevant content and understand its meaning and context and then deliver highly personalized results based on a user's intent.
Intent-based Ranking is the concept of ranking search results based on user intent. It considers what users are trying to find when they make a query, rather than just matching keywords.
There are four types of user intent:
- Informational: A user wants information about a topic (e.g., "What is the future of search?").
- Navigational: A user is looking for a specific website or page (e.g., "Google ranking factors").
- Transactional: A user wants to purchase or perform an action (e.g., "Buy Nike shoes online").
- Commercial investigation: A user explores products or services with no intention to buy immediately (e.g., "Best digital marketing blogs").
Intent-driven Semantic Search is a must to get the right results
The future of search is semantic. It's how we get from one place to another using the shortest route, it's how we find a suitable place to eat, and it's how we find information on the web.
Semantic Search is an approach to understanding natural language and intent based on the concept of meaning and context to provide more relevant results.
It relies on various mechanisms to analyze, understand, and extract knowledge from unstructured data (such as text) to produce meaningful results. This involves different technologies such as Natural Language Processing (NLP), Natural Language Understanding (NLU), and Ontology.
Intent-driven Semantic Search is a must to get the right results. It finds the semantic similarity between the search query and the results without considering the keywords.
For example, if you want to start a new business, you can type either of these phrases: "how to start my own business" or "what are some good entrepreneurial ideas."
The goal of Semantic Search is to present the best results that match your intent, whether you have used keywords or not.
Search solution does not have to be expensive
Search is a challenging problem. Every user query is different and thus requires another search engine for your specific use case.
The world of search has changed significantly over the last few years. As consumers have become more reliant on their phones and digital assistants, they have also begun to use their voices to ask questions and look for answers. At the same time, businesses are relying more heavily on search technologies to provide customer insights that help them drive revenue growth.
As a result, the demand for new search technologies has increased dramatically. Despite this demand, many companies — tiny businesses — struggle to best implement these new technologies.
Modern Search solutions allow you to do this. You can build a highly customized solution that meets the needs of your business and provides an excellent experience for your users. But there are costs associated with making these solutions, which can be prohibitive for many companies.
Cost considerations are essential. Building your solution is expensive. Modern solutions like Azure Cognitive Search, Algolia, Yext can be costly if the number of queries per month cannot support those costs.
Search is the answer to everything. And that's a big part of the reason why it's so crucial in today's technological world. Because search is the first destination people turn to when they want to find something online—a solution, a product, a piece of information—companies desperately need to search for remaining relevant.
The future of search is full-text search with Semantic Ranking, autocomplete search suggestions, and intent-driven Semantic Search. At least, that seems to be the case for now.
Looking for a low-cost search solution? Check out Seqwa!
Search solutions must deal with complex queries with the exponential growth of products, websites, and eCommerce. Modern search solutions should focus on getting customers to the product or document they are looking for, no matter what they search for in particular.
Seqwa provides enterprise search solutions for organizations that quickly and easily find information. The Seqwa search solution is designed to work with your existing systems, delivering relevant results across all content repositories in real-time. It's easy to use, and there's nothing to install or maintain.