Smart Search Online Store

    Search in the online store has always been part of the overall package for creating an online store. And only recently it began to be offered as a separate product, for example, the findologoc service or as plugins for cms searchanise.com. This is not to say that customers immediately rushed at them, but a start has been made. And the emergence of such services is inevitable for one reason. A year ago, one retailer of digital technology (Kay), before creating his new front-end site in order to increase usability, conducted a focus group to identify the most important elements of product search.

    Oddly enough, in the first place was neither a catalog, nor filters, nor an online consultant, and not blocks with special offers, but a search string. A deeper interview revealed that the reason for such attention to the line is simple - it is a transfer of experience from search engines. People are more and more used to looking for everything you need directly from the search bar. I’m not sure that this will lead to the disappearance of the catalog in the online store, as it disappeared in the search engines (many still remember that all search engines began including as directories of Internet resources). The catalog is needed as a navigation map for the buyer (“what do you have here?”). But the value of the search string in the online store is clearly increasing.

    In principle, it seems more convenient and faster to write “Asus laptop 15 inches” directly in the search bar instead of looking first for Asus laptops in the catalog, then choosing inches in the filters. Especially for “blondes” and “locksmiths”.

    That is, it is an opportunity directly from the search bar to search by categories, characteristics and their values, which seems to be what visitors want. But existing solutions cannot handle such a request. The only one who can handle such results is the Utinet online store. But they made it only for themselves, that is, they cannot offer such a solution to anyone else.

    Usually, a search is built as a full-text index, for example in Sphinx, for certain fields of the product database. Most often it’s just a search by product name. But some extend it to search by categories (tags) and even by characteristics. And there is a problem. If you search all the fields of the “card” of the product, then the search results may contain a lot of garbage that the visitor will not like. Let me remind you that usually the words from the request are subjected to stamping, otherwise the problem is insoluble, for example, many others. and units numbers in the visitor’s request. But if I write a laptop with a terabyte hard drive, then this search will return both laptops and hard drives. In fact, it’s even worse, since there will be a lot of other “garbage”, for example, covers for hard drives, charging for laptops, etc. You can rank, of course, by assigning “priority” categories,

    Search by exact name - everyone knows how, only by one category, for example, telly (by synonym) - have learned. But something more complicated (category plus features) is no longer there. The fact is that one single word from such a request separately will certainly be found somewhere completely not where it is needed. And all products with such a word somewhere in the description will fall out to the visitor. He will not like it. Therefore, as I know (and if something is unknown, I will be glad to comment), everyone is trying to find a compromise option and select some separate fields for searching from the string. Like searchanise, searches by name, and by brand. All. A request like “telly up to 30,000 rubles” will no longer work. But you can also find by such a request. If you conjure with a query, and not with search fields and labels for ranking. More precisely, this requires parsing such a query. And one more thing. I won’t describe the details, so as not to clog the brain (we are still not on the Habré, but on the Megamind). Moreover, those who do not want to think long and do half a year can immediately contact us.

    But the question is different - how much such a search is needed, or what search does a visitor of an online store need? This article is an attempt to gather opinions on the pros and cons . Perhaps someone himself had experience with Utinet, or with Yulmart and Kay (we put such a search to them), maybe someone has their own statistics. I will be glad to opinions.

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