# Tailoring Autocomplete for Zoot Brought a Fashionable Conversion Rate Increase of 2.5%
> Zoot and Bibloo, part of the Czech fashion giant Digital People, offer over 1 million products across 11 European countries.
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E-Commerce
## Tailoring Autocomplete for Zoot Brought a Fashionable Conversion Rate Increase of 2.5%
Zoot is an online fashion store and a part of the biggest Czech fashion house, Digital People. Along with its sub-brand, Bibloo it is present in 11 European countries, offering more than 1 million products from 300 fashion brands.
- Based Global
- Platform Custom
- Segment Fashion
- Products
- Analytics
- Search
Although Zoot’s 2 million monthly visits (+Bibloo’s 2.5 mil monthly visits) are impressive, more importantly, the brand itself managed to gain the “love-brand” status in the fashion community.
So, when the client decided to take its site search to a new level, it made this project a big challenge and committed us to improving the precision of the search results and enhancing the user experience.
#### The results quickly showed Luigi's Box's superior robustness
We A/B tested Luigi's Box against our own and other tools. The results quickly showed Luigi's Box's superior robustness, and further A/B tests didn't find a better alternative.
David Šandera Chief product and technical officer, Zoot (digital people)
### The main challenges:
- Increase the overall search results accuracy
- Manage to provide relevant autocomplete search suggestions for a huge number of products (1 million) while maintaining a fast load time.
- Facilitate the product discovery process with customized autocomplete showcase and dynamic faceted filters.
### Analyzing the user behavior
Data showed us that Zoot’s visitors are three times more likely to convert when using search. With around 10-11% search usage, it’s been more than clear that it would be a missed opportunity to only provide the technology without adapting it to the specifics of the fashion industry.
That’s why our first step aimed to understand how users interact with the website and the search itself. To do this, we implemented [Luigi’s Box Analytics](/products/analytics/), which helps us understand how users are searching for different types of products by analyzing:
- The most important product attributes (e.g., colors, gender, style/cut, brand, etc.)
- Usual synonyms and typos (jeans, denim, blue pants, etc.)
- The most common reasons for the no-result searches
### Fine-tuning the search
Afterward, we started to **fine-tune our search** to reflect the data in the search results relevancy and product rankings.
One of the main targets was to improve the accuracy of **color-related search terms** (e.g., blue jeans, white cardigan, etc.).
#### Identifying the most common [synonyms](/features/synonyms-management/), slang words, and [misspellings](/features/typo-tolerance/) was crucial to decrease the number of no-search results and increase accuracy.
Last but not least, we cooperated intensively with the client to improve the product feeds to get the most out of our search by providing full and accurate product data based on our findings and requirements.
### Design and usability
The design of autocomplete, search results, and faceted filters aims to adapt to website design based on the client’s brief.
As the client thought of the search as the fashion showcase, we created the full-width [autocomplete](/features/autocomplete/) bar design with a focus on a compelling visual presentation of the products.
[Autocomplete showcase](/features/autocomplete-showcase/) also contains recommended categories, top brands, and similar queries related to the search terms.
Since data showed us that the **most important filter attribute in search results is the brand**, we prepared a **quick visual filter (logos)** of the most popular brands matching the particular search term along with the regular faceted filter.
We also added recommended categories to the search results page since a lot of the search terms (e.g., “white top”) are often relevant to several product categories.
### A/B test and the results
Since Zoot was using a competitive solution at the time, they decided to launch an A/B test with the 50:50 split.
The A/B test started on August 17th and was evaluated after one month, but even after the first weeks, the results started to show an improvement in favor of Luigi’s Box.
After several prolongations, the test was stopped after three months. The results revealed that Luigi’s Box Search and Autocomplete:
#### +9.14%
Increased add-to-cart conversion rate
#### +2.57%
Increased purchase conversion rate
This case study showed us how important it is to choose an individual, data-driven approach to get the most out of the technology’s potential.
How our clients benefit from Luigi's Box
- [Lucide: 8% B2B Conversion Rate Uplift](/case-study/lucide/) · Lucide chose Luigi’s Box and achieved an 8% B2B conversion rate uplift and other improvements. Find out more in our case study.
- [Barron: 18% Product Listing Conversion Rate](/case-study/barron/) · Barron is a custom merchandise seller that chose Luigi’s Box and received a Product Listing conversion rate of almost 18% and other important improvements.
- [Pancernik: 175% Uplift in Search Usage](/case-study/pancernik/) · Switching to a new search paid off and brought a 175% increase in search usage, and positive results for search conversions, clicks, and other important areas.
- [GAP Achieved a 28% Recommender Conversion Rate](/case-study/gap/) · GAP chose Luigi’s Box and improved their website with new search functionality that brings results across multiple domains.
- [Chicco Chose Luigi’s Box Search and Improved the Shopping Experience](/case-study/chicco/) · Chicco's switch to Luigi's Box brought them numerous improvements, including Autocomplete CTR and Search usage increases.
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