Searching is the primary way through which we interact on the internet. It's how we find what we're looking for, who we’re looking for, or the type of result we are looking for. And it isn't just about finding words; it's about understanding intent.
Google sees over 8.5 billion searches every day, which says a lot about how important search is to our society. We've become so reliant on search engines that we often don't even think about how they work. We just type in what we're looking for and hit enter.
But have you ever wondered how those search engines understand what you're looking for? How does a computer understand everyday language? It's actually pretty simple.
It’s called Natural Language Search (NLS). Natural language search is a search carried out in everyday language. Instead of messing around with keyword combinations users can simply phrase questions as they would if they were talking to a human. NLS uses techniques such as Natural Language Processing (NLP) to break down human language into a way computers can understand.
A brief history & evolution of search
The late 1990s saw the introduction of search engine technology that used keywords and Boolean searches to interpret user queries.
Search engines started to use NLP in the early 2000s, though it was far from a perfect solution. It was at this time when Google made its debut on the scene with a revolutionary algorithm that was able to interpret user queries better than any other search engine. Natural language processing capabilities have come on leaps and bounds since then, as have machine learning technologies.
What is Natural Language Search
Natural language search is a type of search which answers query typed into a search bar in everyday language. Machine learning algorithms break down the query into its individual elements and try to get an understanding of what the user is asking. Natural language search also looks at words in context, as to understand a piece of text better than just looking at individual words alone. This means that it can take into account how certain phrases are used in different contexts.
In addition to understanding user queries, natural language search also takes into account the relevance of a page and its content to better understand what the user is looking for. For example, if you type "macaroni and cheese near me" into Google, it will only show you results for restaurants that serve macaroni and cheese in your area.
The Benefits of Natural Language Search
Natural language search is incredibly useful as it's intuitive, easy to use, and can understand complex queries better than keyword-based searches. With natural language search, the user only needs to know what they want, and your search engine will find it.
For online businesses, natural language search offers a powerful tool to make your users’ lives easier. Why do you NEED NLS? Let’s take a look at what NLS brings to your business.
- A better experience for your users – Natural language search gives users a better experience as they can quickly find what they're looking for. Natural language searches will allow them to quickly find what they’re looking for within seconds – as opposed to taking minutes or hours of sifting.
- Your users are used to the Google experience – They expect a sophisticated search that understands their intent and can find what they're looking for quickly.
- Generates useful data for analysis – Natural language searches generate data on everything from user intent to popular terms and phrases. This data can be used to improve search engine optimization (SEO) and inform content strategies.
Implementing neural search for your website
Neural search is a powerful tool that can help your website provide more accurate and relevant results to users. It uses deep neural networks (a DNN is a kind of machine learning algorithm that is used to analyze data and learn from it) for natural language processing and understanding (NLP and NLU) to understand user queries better than traditional keyword-based searches. Implementing neural search on your website can help you provide a better user experience and generate useful data for analysis.
To implement neural search on your website, you will need to use an NLP library such as spaCy or NLTK. These libraries allow you to create custom models that are tailored to the specific needs of your website. You will also need to create a database of relevant terms and phrases that the search engine can use to understand user queries better.
Once you have set up your neural search system, you should test it thoroughly before launching it on your website. This will help ensure that the results are accurate and relevant. You should also monitor the performance of your neural search system to ensure that it is providing the best possible results for users.
Finally, you should consider integrating other features such as auto-complete or voice recognition into your neural search system to make it even more user friendly.
Where next for NLS?
- The advancement of Voice Search – According to Juniper Research, voice commerce will grow to reach more than $80 billion per year by 2023. Voice search has the potential to revolutionize natural language searches by allowing users to ask complex questions just as if they were talking to a person.
- The rise of Virtual Assistants – Virtual Assistants are becoming increasingly powerful and can be used to answer natural language queries. For example, Siri on iPhone or Alexa on Amazon Echo can understand complex questions and help users find what they’re looking for.
- The growing use of deep neural networks – DNNs can be trained to understand natural language, allowing them to better interpret user queries.
- The growth of AI-powered Search – AI-powered search is becoming increasingly powerful and can be used to improve and refine natural language searches. AI-powered search engines are able to better understand user intent, helping them find the most relevant results for a query quickly.
- Chatbots – Chatbots are an easy and effective way to provide natural language search capabilities. As more businesses adopt chatbots, Natural Language Search will become increasingly important for them
Natural language search is the future – with the advancement of voice search, virtual assistants, and AI-powered search, we are moving towards a more intuitive and human way of interacting with technology. This will revolutionize the way your users interact with your website.
We've gone from keyword-based searches to machine learning algorithms that can understand user queries in everyday language. Natural Language Search is a powerful tool that will help your business drive engagement and conversions by offering an intuitive experience for your users while also generating insightful data about user behavior.
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Zevi utilizes the power of AI to deliver instantaneous and precise results. Try a demo today and see how Zevi can revolutionize the way your users interact with your website and drive growth.