Sounds complicated? No worries, in this article you may find a lot of examples. But if something remains unclear, you have more sophisticated business requirements, or just need advice – simply contact our team and we will help.
Generally, every product in a store has these basic pieces of information:
- Product name
- ID – unique identifier
In some stores, there are way more Data Fields, like vendor code, brand, model, parameters, tags, SKU’s.
Often there are more things, like categories or collections, that need to be included in the product info. For example, the category name ‘corner sofas’ describes the product very well and it is definitely a good thing to include to the description.
Another example of a Data Field is color. Kea Labs extracts colors directly from photos. So when your customers will search for a ‘Red dress’ , they will receive highly relevant results.
However, making every available Data Field searchable is often a bad idea. We will tell you why a bit later in this article.
Website Search Priorities
It’s natural that of the Data Fields describe product better and have higher importance. But other needs to be used as additional information, or, even be ignored by default.
Kea Labs allows to specify the priority for each Data Field, you can easily choose which one needs to be boosted, ignored, or be scanned with a normal priority. We also have the ability to tweak priority more precisely – just ask our team to help.
Fuzzy Search, Spelling correction and Autocomplete
This is another important concept is for which Data Fields you want to have spelling correction, or autocomplete enabled. This has a big impact on the level of noise – how many undesired results the website search brings.
Imagine what may happen when to autocomplete with a spelling correction is enabled for a 1000-symbols long description: search may even suggest almost every product when you type something simple and popular, like ‘dress’. If you have ‘these shoes go with evening dresses’ in the description – you will get some relevant shoes in the search results. That’s definitely not the desired item for User.
On the other hand, it might be very useful to have autocomplete enabled for the vendor code. It’s pretty often used by a store staff, especially when you have thousands of products. It allows to quickly and easily find needed items.
Well, enough of boring theory, let’s switch to practice:
Naturally, it’s one of the most important information about the product. Add it with a top priority, spell check and autocomplete enabled – pretty much in every store it’s the most often searchable information.
Product Description Prioritizing
Be accurate and pay extra attention to this Data Field. Some of the descriptions contain only facts and necessary information about products, on other stores descriptions might include even user feedback, instructions, and YouTube videos.
Try not to prioritize the descriptions – it may bring a lot of undesired items.
We do not recommend enabling autocomplete or spell check here too – it’ll bring you tons of surprising items in results.
The rule is simple: if you have informative descriptions, assign them a low priority. Otherwise, it’s better to ignore it.
You can also disable search in description (and other low priority Data Fields) by default. After this users will be able to tick ‘Search in description’ checkbox when these Data Fields need to be searched.
Brand, Vendor, Model
For most of the stores, we recommend to have brands searchable with a top priority, with spell check and autocomplete enabled. Shoes, clothes, electronics, food – pretty much everywhere brands are popular in website search phases such as ‘Samsung phone’, ‘Levi’s sneakers’, ‘perfume Chanel’.
Vendor code, Product ID
We recommend to have vendor code to be scanned with a high priority with autocomplete – it’s useful for the store staff and allows quick navigation. You may also consider having fuzzy search enabled on this Data Field.
If you have complicated vendor codes and would like to have other notations searchable – let us know. i.e we can have pretty much any transformations of vendor code – i.e. remove trailing zeros, search by parts, etc.
On some Stores, product ids are useful for website search as well.
If your users may see product id, consider adding this into search as well. For example, a customer may call to your support and ask ‘do you have shoes in a brown color available?‘. You may ask them to tell a product id from the page URL, or other places, and then quickly find it and check. Tiny feature, but it saves your time and shoes your proficiency.
Kea Labs Smart Search Context
This is the place where the power of Machine Learning gets applied.
Pretty often products don’t have enough Data Fields describing it, or useful information is spread on the low-important content. In order to solve this, Kea Labs Smart Search analyzes all the products and enriches it with additional information, such as:
- Product type – evening dress, corner sofas, laptop for gamers
- Adjectives, describing the product – cozy, bright, convenient, etc.
- The most important attributes for this type of products – i.e. screen size or material
- Attributes helping to differentiate product within similar products
- Pricing segment which adjusts further website search results for User
We recommend keeping this information searchable with, at least, a normal priority.