According to a report, 43% of eCommerce visitors use on-site search, and among them 2-3x users are more likely to convert. Yet, several online stores experience drastic sales losses. You know why? It’s because their search engines fail to comprehend what exactly a shopper wants.

That’s where Natural Language Processing(NLP) can play a significant role. NLP solutions use AI and ML-based algorithms that help eCommerce platforms interpret search intent, even predict queries, and then offer hyper-personalized outcomes.

However, you need to hire a leading NLP development services provider that can suggest ways to reduce bounce rates, increase click-throughs, and ultimately boost search conversions.

This blog will discuss four powerful NLP strategies to facilitate eCommerce search and convert browsers into buyers.

Top 4 Methods to Enhance Search Conversions using NLP in eCommerce

Natural language processing can significantly enhance search predictions, thereby displaying the most relevant products to the right customers. Let’s see the top four ways NLP solutions are helping retailers.

1.     Smart Autocorrect and Query Suggestions

Old-school or traditional search bars only match the exact keywords. This leads to confusion and sometimes frustration when users mistype or use vague terms. Therefore, you end up with product suggestions that are not relevant to you.

An NLP-assisted intelligent autocorrect system can check your spelling by:

• Correcting any typos, for example, “runing shoes” → “running shoes.”
• NLP-integrated search bar can also suggest synonyms, for example, “sneakers” for athletic shoes.”
• The best aspect is that they can even predict intent based on trending searches. For example, an iPhone 16 search can be clubbed with iPhone 16 cases.

How does it boost conversions?

Well, faster product discovery can lead to less search abandonment. Moreover, the website gets a higher click-through rate (CTR) because users click on relevant recommendations.

What can you do?

Consult with an NLP development services provider to add this modern tech. They can use BERT or GPT-based models to ensure accurate context. Additionally, they can monitor 24/7 and even update suggestions based on user behavior.

2.     Semantic Search for Better Results

Keyword matching is outdated. In fact, traditional search often fails when you enter complex queries, such as “best budget wireless headphones for workouts.”

However, NLP solutions use semantic search to understand difficult queries. So, let’s take the above search query and bifurcate it:

• In that, the context is “budget,” which means “affordable”.
• The synonyms for “workout” can be “gym” and “running”.
• And finally, the user intent (wants to buy sweat-resistant headphones)

How does it impact sales, though?

It accesses a vast library of databases to come up with zero-result pages that lead to more engagement. Additionally, the conversion rates are higher due to precise results.

How to implement it?

You can take the assistance of an NLP development company. They may leverage vector search engines like Elasticsearch with NLP plugins. Apart from that, they use various LLMs fine-tuning techniques to train models on industry-specific terms.

3.     Voice Search Optimization

According to Comscore, more than 50% of searches will be voice-based by 2025. NLP helps voice assistants, chatbots, or AI agents to interpret natural language. For example,

• Show me red dresses under $50
• Where can I buy organic dog food?

Why voice commerce drives conversions?

First, voice shoppers generally have higher purchasing intent. Furthermore, if you optimize search for long-tail and conversational queries, it can capture a wider target audience.

What strategies can you follow?

Ask your NPL development agency to train models that can answer FAQs precisely. Additionally, you can optimize answers for local intent, for example, “near me” searches.

4.     Personalized Recommendations

Natural language processing accesses user behavior, location, and past buying experiences to provide custom results. For example, showing “winter coats” to a shopper in Canada instead of generic “jackets”.

NPL for eCommerce also recommends “frequently bought together” products like phone cases and screen protectors to drive more sales.

What are the conversion benefits?

With intelligent cross-selling techniques, you increase your AOV (Average Order Value). Apart from that, lower bounce rates will improve category product ranking.

How to implement it?

Ask your chosen NPL development services provider to use the collaborative filtering option with NLP, for example, customers like you bought, or something similar. Moreover, as an eCommerce business owner, you must update recommendations per click with real-time personalization.

Final Thoughts

NPL in eCommerce has the potential to reinvent workflows and become a catalyst for change. It can transform the search guessing game into a precision tool. By utilizing the four ways mentioned above, you can dramatically improve search conversions and outperform your competitors. You can start by teaming up with an NPL consulting company that can audit your IT systems to suggest a better NPL implementation roadmap.