What is Fashion optimized search and how does it impact your revenues?
Imagine, you need to buy a black shirt, you need it in a medium and it needs to be formal, with full sleeves.
You walk into a store, and you tell the nearest assistant your exact requirements, and you’re out of the store in a matter of minutes.
Now compare this to an alternate scenario
With the exact same requirements, you go to the store, and begin to browse for the right product. There are racks upon racks with the product name on top. You walk aimlessly through half the store, and finally find shirts, you see one that’s perfect, but it’s not available in your preferred size or colour. You speak to the nearest employee, and ask when it’s available next… it’s in 4 weeks. You walk out the store, probably empty-handed.
If you think about it, that’s exactly how e-commerce websites are designed. If the consumer knows exactly what they want, they can use the text search functionality. However, if the quality of your search isn’t good, the consumer will end up using browsing by product category.
“50% of users prefer using the internal search engine of the site rather than navigating on their own AND these shoppers are 2–3x more likely to convert!”
If in site search is so critical to bottom line, why is it that 31% of all search queries do not return any relevant products on most websites? Further, why are 84% of user queries not supported (eg: subjective qualifiers like“good quality” or “cheap”)?
Web developers certainly add site search as a key feature for the website but the phrase “One size fits all”, does NOT apply to search solutions. You need an advanced domain optimized search to maximise your sales revenues.
What is Fashion optimized search?
Fashion optimized search refers to the process of using specific algorithms and techniques to improve the search functionality on a fashion e-commerce website. This can include using natural language processing (NLP) to understand user queries, utilizing machine learning (ML) to improve search results, implementing filters and facets to help users narrow down their search results and offering relevant recommendations. Additionally, fashion optimized search can also involve using data on customer behavior and search history to personalize search results for individual users.
An advanced search feature on a website typically includes a range of options that allow users to narrow down their search results and find exactly what they are looking for. Here are some features that are included in an advanced search feature:
- Faceted search: Allows users to filter search results by specific attributes, such as brand, color, size, or price range. This can help users narrow down their search results and find products that meet their specific criteria.
- Boolean operators: Allows users to combine keywords using logical operators such as "and", "or", and "not" to create more complex queries.
- Wildcard search: Allows users to use a wildcard character, such as an asterisk, to match multiple variations of a word.
- Proximity search: Allows users to find words that are within a certain distance of each other in the text.
- Field-specific search: Allows users to search within specific fields, such as the title, price, latest etc.
- Search suggestions: Provides users with suggested search terms or phrases based on the letters or words they have typed in, which can help them refine their search.
- Search history: Allows users to see their previous searches and easily repeat them.
- Personalization: Allows users to save their preferences and search history to personalize their search results based on their needs and preferences.
- Synonyms and related terms: Allows users to find synonyms and related terms to their search query.
- Search in natural language: Allows users to search using natural language, allowing them to write a question or sentence to the search bar.
Overall, advanced search features can make it easier for users to find what they are looking for on a website by providing more options and flexibility in their search queries.
Key advantages of having a fashion optimized search:
- Improved user experience and engagement : Site search allows users to quickly find the information they are looking for, which can lead to higher satisfaction and engagement.
- Increased sales: By providing users with a more efficient way to find products or services, site search can lead to increased sales.
- Reduced Bounce rate: Site search with relevant results can help users find what they need more quickly, which can lead to reduced bounce rate.
- Increased retention: The ease of discovery leads to increased retention and repeat visits.
- Better insights: Site search data can provide valuable insights into what users are searching for, which can help retailers improve their content and navigation and can also provide insights for designing the next collection.
Retailers can track these benefits by keeping an eye on metrics such as conversion rates, bounce rates, and other user engagement metrics.
Computer Vision:
Visual search is a type of search that allows users to find information or products by using images or videos as the search query instead of text. This can be particularly useful in the fashion and eCommerce industry, where customers may have a hard time describing the product they are looking for in words.
Computer vision is the technology that powers visual search. Visual search optimized for fashion comes with pre-trained models that recognise the fashion products in the images and ignore the irrelevant background noise. Good visual search systems are able to go down to granular attribute level recognition of the garments and accessories and find similarity based on specific attributes like Style, colour pattern, Collar, length etc.
Some of the key benefits of visual search include:
- Improved accuracy: Visual search can be more accurate than text-based search, as it can match the exact product or item that the user is looking for, even if they don't know the name or exact description.
- Speed: Visual search can be faster than text-based search, as users can quickly find what they are looking for by simply pointing their device's camera at an object or item.
- Personalization: Visual search can be used to personalize search results based on the user's preferences and past searches, as well as their social media activity.
- Increased conversions: Visual search can help increase conversions by making it easier for users to find the products they want, thereby reducing the chances of them abandoning their shopping carts
- Increased engagement: Visual search can help increase engagement by providing an interactive and dynamic experience, which can help increase customer loyalty.
- Better understanding of customer's needs: Visual search can provide insights on customer's needs, such as the type of products they are interested in and their preferences, which can help in product development and marketing.
Overall, visual search is becoming increasingly important as it allows users to quickly and easily find the products they are looking for, and can help improve the overall user experience on a website, leading to increased customer satisfaction and sales.
Other Key factors that impact an advanced fashion Site search:
Taxonomy: Fashion in particular does not have a universal Taxonomy what is long sleeves for one is full sleeves for another. When it comes to colour the variables are almost infinite. So, a Search provider who has a well-developed taxonomy has an advantage of being able to recognise synonyms and offer results that are the closest in proximity to the intent detected. Most basic searches fall back to “category” but that is not an acceptable solution now.
Understanding of Fashion: Context matters. The same word being used in different contexts can mean two very different things. Especially when it comes to fashion, even the position of the word in a sentence can indicate a wholly different intent. Let’s take for example “ Dress shirts”. This could mean a womens dress shirt or a mens shirt for a formal occasion.
A cascade of small, but important, details affect the search experience on the website. Your search solution needs to be intelligent and customized to your industry. In today’s world, it’s not enough to just match the keywords in the search query, you must also understand the intent of the query and the fall-back options should be as relevant as possible and not come up with Zero results or wrong results.
What should a perfect fashion search solution look like?
Now let’s say the shopper is looking for “Plus size ful slive men Polo shirt under 40$ without checks” or “what can I wear for Brunch?”
The perfect search solution would be the one which understands your query, and enhances product discovery
- Search must understand what exactly the customer meant with each word, even if misspelt. At most eCommerce sites the customer needs to be a perfect speller to get relevant results “Full Sleeve -> full Sleeve”
- Search should also understand that different words, or different spellings of the same word may mean the same thing, for example: dress and dresses, or Kaftan and Caftan should give the same results.
- It should understand price and words like “Over”, Under” and “Without”
- Polo could mean the brand Polo or a T-shirt with collar
- It should provide suggestion to complete your query for you
- It should understand that is appropriate for an occasion like Bruch and suggest accordingly
- And it’s not too much to expect your advanced search to make recommendations based on similar trending products or complementary products to enhance discovery.
To sum up an advanced search solution for the modern consumer, needs to have three core capabilities:
1. Offer intent detection: Being able to understand the query, and work out exactly what is required
2. Offer entity recognition: Should be able to understand regular language usage of synonyms, stop words, and misspellings.
3. Offer smart suggestions: Provide suggestions based on the brand and some consumer personalisation.
According to Digital commerce 360 “Retailers inventing in advanced search capabilities see a 50% higher conversion rates”
Streamoid provides InSearch an advanced fashion search out of the box which utilises NLP (natural language processing) and Computer vision to ensure a near perfect search experience. Find out more here.
Importance of Product Taxonomy: Role of AI in Automating & Improving Taxonomies
