6 Unique Ways Cognitive Search Powers Frictionless B2B E-Commerce Experience

1. Bridges the Gap Between Specific Product Queries and Search Results

Imagine a B2B buyer, Ron, who is looking for an online vendor to restock ‘milk frother’ for their chain of stores. He starts his search by typing ‘H422 Stainless Steel Electric Milk Frother’ on the website of a potential supplier. The search returns no results. He thinks maybe the query is too specific and alters it to ‘Stainless Steel Milk Frother.’ Still no result. He quits. Turns out the site did have milk frothers, but labeled as ‘Dual-Speed Power Frother.’

Rudimentary search engines bite the dust when paired with long-tail queries. A cognitive search engine, on the other hand, makes it a breeze to return relevant products by indexing the entire product inventory & product descriptions. Backed by AI and ML, it eliminates the ‘no results’ page and keeps visitors coming back.

2. Delivers Contextual Results by Understanding Your Customer’s Intent

To err is human. When B2B customers search on your e-commerce site, they often end up messing up spellings, spaces, and abbreviations. They expect your site’s search engine to take care of these silly mistakes itself.

E-tailers can breathe a sigh of relief because a cognitive engine comes with NLP. It can easily understand what customers are looking for even if they frame the silliest queries laden with typos. An array of features such as autosuggest, spellcheck, and synonym recognition meets ever-evolving buyer needs and populates the best products every time.

3. Takes the Personalization Game to the Next Level

Richard Isaac, CEO of RealDecoy, says personalization in B2B maybe even more important than B2C. In B2B purchases, a lot of people are involved. When a specific user logs in your e-commerce site, a cognitive engine provides personalized dynamic product recommendations.

These are based on the user profile, history of transactions, clicks, and views, making repeat purchases a lot easier. This is especially useful for creating a great merchandising strategy. In addition to creating a seamless user experience, this drives customer loyalty and average order value (AOV).

4. Provides Intuitive UI Powered by Dynamic Filters and Facets

McKinsey reports that 86% of B2B executives prefer using self-service tools for reordering, rather than talking to a sales representative. The same report also states that lack of speed in interactions with their suppliers emerged as the number-one “pain point,” mentioned twice as often as price.

A cognitive search engine takes care of all the above things. It comes with dynamic facets that reduce customer efforts and propel self-service. Users can tweak results on the fly based on price, specific features, brand, and whatnot. Guided navigation on your website helps users cut through the clutter and get to relevant products faster.

5. Offers Better Omnichannel and Product Discovery Experience

In this age of social media and multiple channels, creating a consistent customer experience is as important as having an online presence. If a client is not getting the same brand messaging across different channels, you WILL eventually lose their trust. For instance, if a buyer sees a deal on your Facebook page and lands on your website only to find out a different price, they won’t bother coming back.

Advanced cognitive engines ensure a unified customer experience. It integrates different digital properties so that users get relevant information. If a buyer has previously checked your blog post on ‘5 Best Dishwashers of 2020’ and then landed on your e-store, the search engine is smart enough to display dishwashers page with facets for an easy and quick transaction.

6. Improves Conversion Rates With Search Analytics

Happy Friendship day! Search analytics is going to be the next best friend of your marketers and merchandisers. It empowers them to easily spot products that appeal to certain buyers at the click of a button.

Gartner coined the term insights engine for cognitive search because it offers rich insights such as top products, keywords used, product clicks and views, cart abandonment rates, etc. Based on that, you can develop a strategy to upsell and cross-sell items, making the most of your e-store.