Elasticsearch, while versatile, demands resource-intensive management and technical expertise. We identified a few critical issues: software maintenance, scaling difficulty, and complex query language knowledge.
Why Elasticsearch is costly to maintain over time and how SaaS search tools deliver strong results without the technical burden.
The open-source appeal of Elasticsearch is obvious. It’s free, it’s flexible, and many online stores run on it. However, many e-commerce teams learn the hard way that “powerful” doesn’t mean “ready for shoppers.”
In this article, we’ll break down the expense of going all-in on Elasticsearch, and show how Luigi’s Box delivers pre-built features without the constant maintenance.
Elasticsearch is a fantastic foundation. But you need to build everything that makes e-commerce search good on top of it.
Features modern shoppers expect don’t come out of the box. You need to build them before your search begins to meet their expectations.
And once you’ve built it, you have to maintain it. Tuning search for one query can break results for others. Without a dedicated team watching it, relevance suffers, and customers leave without telling you why.
According to our data, no-result searches make up 13% of all queries, and 30% of customers abandon an online store after an unsuccessful search. Most of those failures come down to gaps that Elasticsearch alone doesn’t cover.
Luigi’s Box is built on Elasticsearch. We didn’t choose it reluctantly. It’s a fantastic foundation. That’s exactly why we know where it stops being enough.
Luigi’s Box grew out of serious academic research. What we built is everything that comes after Elasticsearch: the ranking logic, the NLP, the variant handling, the catalog analysis, the A/B testing infrastructure.
The parts that take years to get right, and that most e-commerce teams don’t have the time or headcount to build themselves. Our team is full of engineers, designers, product experts, and data analysts who work on search exclusively.
And we’re not done. We continuously improve the platform, with a clear vision for the AI era, which means you’re not just buying what we’ve built so far. You’re investing in a solution that keeps getting better.
Here’s what you get from day one, without writing a line of custom code:
Our product ranking system evaluates match quality across multiple parameters like clicks, sales, seasonality, margin, not just text score. A perfect match in the product name is ideal, but our ranking algorithm model considers what’s good for your business too.
We recognize when multiple results are really just variants of the same product and diversify results accordingly. Instead of showing the same backpack ten times in different sizes or colors, the system groups those product variants and offers a wider range of relevant products.
Misspellings shouldn’t derail the search experience. We automatically correct typos and retrieve relevant results even when the queries are inaccuarate.
For example, a shopper types “iphine” and immediately sees the correct iPhone products despite making a spelling error.
Our autocomplete surface results from the first character a shopper types.
Phrase suggestions appear as they type, matches are highlighted in the results, and recommended products show up the moment they click the search bar.
Basic autocomplete is possible with Elasticsearch, but getting it to this level requires significant custom development.
Myriad of filters overwhelm shoppers. Especially if they’re not relevant. Dynamic Filters show filtering options based on categories and product types.
A shopper looking at camping tents sees filters like capacity, weight, and season rating, not gender or size.
Easticsearch’s native non-English language processing is limited and often produces inaccurate results.
We have dedicated engineers who understand languages, and built our system in a way that accurately interprets queries across different languages.
We handle complex grammar and word forms, ensuring shoppers get relevant results no matter how they phrase their queries.
Search performance stays fast and reliable because Luigi’s Box runs independently of your servers. Even during peak events like Black Friday, traffic on your side doesn’t affect search performance.
Elasticsearch, while versatile, demands resource-intensive management and technical expertise. We identified a few critical issues: software maintenance, scaling difficulty, and complex query language knowledge.
Elasticsearch does offer you much more performance optimization potential, but maintaining it requires dedicated engineering resources that most e-commerce operations just can’t justify for their size.
Try out our build vs. buy calculator to compare the cost of your e-commerce search with in-house and third-party solutions.
Customizing Elasticsearch for e-commerce isn’t impossible. But the engineering hours, the ongoing tuning, and the features you still need to build yourself add up faster than most teams expect.
For companies with a dedicated search engineering team and a long runway, it can work. For everyone else, a purpose-built solution is the faster, cheaper, and more reliable path to great search.
Luigi’s Box is built on Elasticsearch, so we know exactly what it takes to get great performance out of it. We’ve already done the heavy lifting. You just get the results.
Elasticsearch is a backend search engine, not a full-featured e-commerce solution. It lacks personalization, analytics, and semantic understanding. It requires multiple custom-built components to match what purpose-built SaaS platforms deliver out of the box.
Without continuous tuning and a dedicated team, search performance declines over time. Fixing issues later becomes costly. Luigi’s Box eliminates this with automatic updates and expert-tuned relevance models our team continuously maintains.
Luigi’s Box has real-time personalization built in.It doesn’t require external data pipelines, custom ranking logic, or behavioral tracking infrastructure. You get immediate relevance improvements from day one.
Yes. Luigi’s Box leverages aggregated data from hundreds of e-commerce sites, giving it a level of optimization that’s hard for any single team to replicate. Even strong engineering teams rarely have the data volume or dedicated search expertise needed to match that scale.
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Filip Kubelka heads product marketing at Luigi’s Box. His background is in translation and it shapes how he thinks about search: precision matters, and the words you use to describe a problem usually reveal whether you understand it. He writes about what e-commerce teams are really struggling with when it comes to search and discovery.
More blog posts from this authorPreview AI Search on your website for free.
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