E-commerce Search Trends and the Perks of AI and Analytics

E-commerce search is no longer just a functional tool. It’s a strategic growth engine that directly impacts conversion rates, revenue, and customer experience.

E-commerce search trends reveal what shoppers are actively looking for. Often, before sales data reflects that demand. On their own, these trends are useful signals. When combined with AI and analytics, they become a practical way to improve relevance, guide merchandising decisions, and remove friction from product discovery.

In this article, we look at how e-commerce search trends work, what they reveal about customer intent, and why AI-powered search and analytics are essential for turning raw query data into measurable business impact.

Why e-commerce search trends matter

Every search query reveals intent. Every autocomplete interaction signals demand. Every no results found page presents an opportunity. The brands that win in today’s digital commerce landscape are those that turn search behavior into actionable insight using AI and analytics to improve product discovery, increase engagement, and drive measurable revenue growth.

Search is one of the strongest indicators of intent in an online store. Shoppers who use search often know what they want or are close to making a decision. Its usage, however, varies by product category or industry, as the intent differs.

Tracking which queries rise, fall, or repeat over time helps teams understand changing demand, gaps in results, reflect shopping behavior, and moments of uncertainty in the buying journey.

Search trends reveal shifts in demand, content gaps, relevance issues, and moments of shopper uncertainty. Rising query volume may indicate growing interest, while repeated or refined searches often signal friction with results or navigation.

If customers search for products that are in stock, but don’t appear in results, the issue is rarely demand. It’s a discoverability issue. Understanding how e-commerce search works is key to correctly interpreting these signals.

Where do search trends appear across the shopping journey?

Search behavior isn’t limited to a single interaction. Search trends surface differently depending on how shoppers engage with your site.

On desktops, users often type more detailed queries. On mobile, searches tend to be shorter and less precise, with heavier reliance on suggestions. Reviewing trends alongside mobile search UI insights ensures search performs well across devices and contexts.

Autocomplete trends, for example, can reveal whether users struggle to finish queries or frequently change direction mid-search, signals that relevance or guidance needs improvement.

How AI and Analytics change the value of search trends

Traditional search reports typically show volume and clicks. AI-driven analytics go further with the behaviour and outcome analysis.

AI interprets intent. Analytics measures performance. Together, they transform search from a utility into a growth channel.

Instead of asking “What’s popular?”, teams can ask:

• Which trending queries actually convert?
• Where do users refine or repeat searches?
• Which suggestions help users move forward—and which cause drop-offs?

Features like search-as-you-type and thoughtful search bar design play an important role here, helping users express intent earlier and more clearly. AI models learn from this behavior to improve relevance over time.

Unlike generic analytics tools that operate separately from search engines, Luigi’s Box integrates AI search and analytics into one system. That means insights immediately translate into product ranking adjustments, boosting rules, and measurable improvements.

Let’s look at how this works in practice inside Luigi’s Box.

What can I learn from the Trending searches in Luigi’s Box?

Trending searches

Luigi’s Box Trending Searches helps you identify what customers want right now and whether your search results are actually delivering it.

Clicking on a phrase in the table will display the products that appeared most frequently in the selected time period after users searched for that phrase.

Next to the table, in the phrase details, there is a Clicks Heatmap. It visually shows the clickability of individual results. The brighter the position on the heatmap, the more desired the product is.

Ideally, the most frequently clicked results are displayed among the first ones. So that potential buyers are not forced to spend a long time looking for the most popular products.

You can click on each result to see which phrases customers are typing in the search bar to find those products.

If you see the “_” at the end of the phrase in the report, it just means that the customer typed the term with a space.

In the beginning, make sure to choose whether you are interested in search results, autocomplete, or both. Use the switch above the table to set it up.

For each phrase, product, category, or article, we see the phrase popularity (development), clickthrough rate (CTR), and the number of unique visitors (profiles) who searched for it. The CTR is also displayed visually – it is represented by the area in each row highlighted in yellow.

Trending Items

After clicking on the result in the table, the phrases that resulted in clicks most frequently will be displayed.

Clicking on any search query in the table will display an overview of the results that are displayed for that query.

How to use this information to improve e-shop conversions?

Product ranking

You can determine whether a high CTR product is in the right position among the results. If it is too low, correct its position with the Product Boosting feature. You can also choose the opposite approach and boost the products that sell less.

In these cases, it is important to keep in mind that a high CTR may not equal a high purchase rate, and, therefore, search performance may be achieved, but the customer will not eventually reach the purchase goal. In this case, it would be better to strengthen the products that meet both of these attributes.

To support less-searched products in your search results, you need to keep track of your statistics on an ongoing basis so you can stop prioritizing a product when there is no increase in clicks on it in the search results. This way, you can easily prevent inefficient products from “taking up” places in the results.

Perhaps it is not possible to get more clicks for particular products, because the audience that might be interested in them is limited in terms of quantity.

SEO optimization

If a product is frequently searched for but does not perform well in sales, it may be missing information or pictures, have a poor structure, metadata, blank data, bad wording, or descriptions, etc. The more organized and transparent the product information is, the better the search experience.

These errors can be easily corrected, although reindexing it to get back to the desired position can take a long time.

However, despite the accuracy of the information provided, customers may expect different features, dimensions, or prices for the product. So it’s not a description error, but different customers’ expectations.

Since the algorithms usually support what users are looking for, you may need to monitor your customer journeys more closely.

Remember to optimize for mobile devices, as our data shows that search usage is just slightly lower than desktop usage for most product categories.

PPC campaigns

By regularly monitoring trends, you can also determine which products to include in PPC campaigns. You have several options:

• Start ads
• Boost ads
• Reduce ads
• Stop ads
• Don’t change ads

Which option is the right one? It depends on several factors. There are 2 options to consider:

1. Promote products that perform well – if they perform well and you still support them, their interest and the performance will be even higher.
2. Promote products that do not perform so well – underperforming products can get a boost from campaigns designed to put them in front of their optimal audience.

Further questions you should ask yourself:

• Do we have a sufficient number of specific products in stock/for delivery?
• Do we have a sufficient margin on these specific products?
• Aren’t these products off-season now?
• What is the value of a PPC product click compared to the product price and margin?

Cross-sell

You can see which customers are buying together, along with specific products, and use this information to cross-sell.

If a few customers purchase non-typical product combinations, the proposed products may seem unrelated to other customers. Especially if the products are not bought often or are new.

The great thing is that cross-sell data can be used not only on the web. They can also be transmitted via API to other systems and channels, such as PPC. You can even use them in digital marketing.

That way, you can target not only specific users but also groups with similar interests and thought processes, increasing conversion rates from these channels.

Use the Description Analysis tab to find out what queries customers use to access any product, not just the most popular ones.

Conclusion

E-commerce search trends become truly valuable when paired with AI and analytics. Without AI and analytics, search trends are just numbers. By analyzing search data, e-commerce businesses can gain valuable insights into the effectiveness of their search engine and digital strategy, as well as their target audience’s shopping habits and preferences. Trending searches can help e-commerce platforms make informed decisions about search volume and key trends, drive more traffic and customer engagement to their sites, and deliver the ultimate customer experience.

Ready to turn search data into a measurable growth strategy? Explore how Luigi’s Box Analytics helps you monitor trends, optimize relevance, and increase conversions in real time.

Frequently asked questions