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 up to scratch, 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 a text search solution 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”)?
The phrase “One size fits all”, does NOT apply to search solutions.
Context matters. The same word being used in different contexts can mean two very different things.
Specifically when it comes to fashion, even the position of the word in a sentence can indicate a wholly different intent.
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.
“Plus size full slive men shirt under 40$”
Now, a typical search solution would provide you with shirts, and maybe, shirts with full sleeves, if the product had been enriched with relevant metadata and tags.
But 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.
And if it’s not asking too much, the search solution should be able to provide you suggestions, and complete your query for you
So for a search solution to work for the modern consumer, it 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.
Streamoid provides a “Tailored-to Search solution” which utilises NLP (natural language processing) to ensure a near perfect search experience. Find out more here.
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