Natural Language Search Solution

NLP Main Banner

Why Natural Language Search?

Site search is a crucial interaction point for customers and can make or break a shopping experience. Customers who cannot find the information which they are looking for leave the site unsatisfied.

Automatically understand customer intent & bring relevant search results
Detect & distinguish products from their attributes
Product Tagging
Natural Language Search

Our Solution

Royal Cyber’s Natural Language Search solution takes advantage of Natural Language Processing (NLP) to provide a deep understanding of the customer’s intent. Natural Language Processing (NLP) is an arm of Artificial Intelligence (AI) that helps computers understand, interpret and manipulate human language.


How Does It Work?

How Does It Work

So basically, our Natural Language Search solution breaks down the language into shorter pieces, attempts to understand relationships between the pieces and investigates how the pieces work together to create meaning, as shown in the above diagram.

Product Features

Keyword Search

The Long-Tail Keyword Search

Understanding customer search text means understanding not only the words but also the concepts and how they’re linked together to create meaning and automatically provide the relevant results. For example, if the user is searching with “show me UVA protected glasses under 200$”, the NLP search will show the UVA protected sunglass less than $200.

Prioritization of Products

Contextual Filtering for Easier Prioritization of Products

Give the user power over their search experience, allowing them to modify numerous attributes such as amount range, color, size and so on, to reduce to the perfect search results with laser-like focus. For example, when a user looks for a gaming laptop, filters are contextual to this particular search query. When a user explores for a fridge, filters are now different, again based on this specific search query.

Spellcheck & Autocomplete

Spellcheck & Autocomplete

More advanced features for spell correction and autosuggestion can be achieved by training machine learning models to help the user get the relevant results.

Negation Recognition

Negation Recognition

A user can search a product by excluding any category or product feature and get the exact relevant results. For instance, a user wants to search for “show me the XL size red shirt not half-sleeves”.

Unit of Measure Conversion

Unit of Measure Conversion

Automatically change units of measure for valid search results. e.g., a search for “20-quart paint pail” will also display 5-gallon paint buckets, turning quarts to gallons behind the scenes and identifying the relevant match.

Automatic Insights

Automatic Insights

Derive meanings from the unstructured text by automatically identifying different product attributes, color, category and other parameters.

Talk To Our Experts

Contact us to find out how Royal Cyber can give you a Competitive edge