3 Tips for The Ultimate Fashion Search Engine

From obvious to ingenuous, find out how to make the search bar the most powerful tool on your website!

Introduction Customers now expect personalized experiences rather than be flooded with a slew of products. They want their favourite brands and websites to know them as well as they know the latest products released by brands and sold on the websites. Brands and websites are now expected to tailor experiences taking into account each person’s individual style preferences.

59% of web visitors frequently use the internal search engine to navigate on a website. - Neil Patel

Search engines users are high intent users and represent a crucial segment of any e-commerce site. Fashion websites and brands need to use search engines that are made with their needs in mind because today, a general search engine won’t take any important attributes like colors, brands and sizes into account while doing a broad match search.

Here are the 3 must-haves for the ultimate fashion search engine.

  1. The Relevance of Search Results

The key priority for any brand or e-commerce site is to ensure that all products are easily discoverable and need to think of what people will be looking for. The results of a search on a website need to capture the intent of that search, and show products that match the search term as closely as possible. This is possible only if the products themselves are cataloged clearly with the right titles, attributes and descriptions.

67% of consumers say they research products online before shopping for them in brick-and-mortar stores. - Retail Dive

Search results need to be ordered in a way where the first ones are exact matches of the search terms and as the shopper goes lower, the results are broader but still relevant. Here is where a lot of fashion brand websites surprisingly ignore style preferences while rendering search results. For example, it is very common that a customer searching for a ‘red party shirt’ will be put off by results that show red party dresses instead. This is because their site search has parsed the search query and returned results matching the term ’red’. However, an image recognition powered site search enables the recommendation engine to understand the visual style preference of the customer, in this case, a ‘red party shirt’ and thus return results which are all primarily red party shirts of various types and then list shades of red in the next level of results and so on and so forth. It is critical that retailers are cognizant of the need for relevant search results since, at the end of the day, the idea of site search is to enable the shopper to find for they are looking for and not have the browse through pages of results, which can lead to disengagement and dropoffs.

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Google searches are listed sequentially, but the click-through rate (CTR) is exponential as you get closer to the top. There is a 67% difference in CTR between the No.1 and No.2 result on Google search - Forbes

Accurate and SEO-ready tags, titles and descriptions for products can boost product discoverability on search engines like Google considerably. They enrich the metadata of the catalog, boosting the quality of information available on each product. This information is also indexed into all the search terms and in turn boosts the SERP of the product. Combined with customer ratings and reviews, these factors can take a product to the very top of search results which automatically gives an instant boost to the sales of the product.

In the image above, the dress has an SEO-ready title & descriptive tags. This makes the dress easily discoverable.

2. Personalized style based results for each user to boost customer retention

Fashion brands and websites spend a lot on customer acquisition today. While growing the customer base is good, retaining customers is a lot more important. Repeat customers tend to trust the brand more and consequently, will be ready to spend more money on the website. Repeat customers are also a lot more likely to recommend the site and its products.

The probability of selling to an existing customer is 60–70% while the probability of selling to a new prospect is 5–20% Invesp 2017

Brands that are customer focused, need to know the shopper as much as the shopper knows them. They need to understand the visual preferences and style of each shopper to design offers and trending items specific to them. Style is a combination of visual and non visual preferences like colors, patterns, sleeve length, brand, neck type, etc. A customer has a much higher chance of buying if the results are close to their personal visual style. No two people look at a product for the same reason. Each of them has their own unique style that is bound to influence their decision to choose a preferred website to shop on. It is possible to learn the style of each shopper from their purchase history. For a fashion search engine, it is not enough for a product to match the search criteria but it must also be in sync with the rest of their wardrobe for a truly personalized experience.

Acquiring a new customer is anywhere from five to 25 times more expensive than retaining an existing one. - Harvard Business Review

For example, given the search term below “Wine Ralph Lauren Off Shoulder Evening Dress”, it is important to make a distinction in the results for Becky and Lisa, given that the former has a greater affinity towards the brand versus Lisa that prefers having dresses that are closer to her color preference. As seen below, AI can help tailor the search results, by boosting specific affinities for each shopper. Each click can be used to learn about the shopper’s preferences and converge to a hyper relevant search bar that understands the customer.

Algorithms which can understand color, pattern, shape, style and more can capture various aspects of the shopper’s style preferences and shape their journey accordingly. This impacts conversion and moreover, the overall site experience, which in turn can have a bearing on the customer’s lifetime value.

3. Flexible Search Options

By 2021, early adopter brands that redesign their websites to support visual and voice search will increase digital commerce revenue by 30% Gartner

Most people see a dress worn by a friend or a celebrity and try to find something similar. This opens up a whole new market when websites have visual search options. This gives brands with image search a huge boost as shoppers can view a dress they like, click a pic of it, quickly upload it into the site search and find visually similar products. Convenience is key when it comes to online shopping and features like image search have a direct bearing on product discovery, leading to brand loyalty as well as building brand recall.

In the image below, an AI powered visual search engine detects the clothes worn by Jon Hamm and allows the shopper to purchase them right there.

Most brands today look at visual search as a peripheral feature. But today, it is becoming a mainstream feature that is expected of all fashion search engines. It is not just Google, eBay and Amazon that have started using visual search. Brands like Macy’s, Target and Asos have already implemented it to great effect. In a couple of years, it will be hard to find apparel brands without a visual search feature. With mood boards becoming more and more popular by the day, visual search seems to be the key to cracking the millennials.

Source : Business Insider

Other than visual search, a search engine that can understand natural language, work past spelling mistakes, complete the search and offer suggestions are now more a norm than a novelty.


Fashion search engines today are expected to do a lot more than just search exact keywords. They are the window through which customers find not just new products, but whole new styles, trends and looks. Today, buying a good search engine is simply not enough.

Similar to a well-oiled supply chain, clean catalogs are needed. Descriptive product titles and attributes are really the first step towards improving the search experience of shoppers. Then comes personalization of search results where data on purchase history & style preference is used to show relevant results. Features like image search can help further enhance the experience and provide flexible options to your customers.

Technology has come a long way from simple searching algorithms. Artificial Intelligence (AI) can take a simple search bar and transform it into one of the most powerful tools in your website that completes the search with personalized words, understands shopper behaviour, recognizes styles, identifies attributes of outfits from images and shows results that distinctly connect with the shopper not only as an extension of their own style but also suggests new ones to try.

With the advent of AI-powered search engines, building customer loyalty begins right from the humble search bar.


AI Powered Chatbots for E-commerce

Shyam Ravishankar

Written by

Digital Marketing at Vue.ai


AI Powered Chatbots for E-commerce