Vernacular Search Support: Why Business Owners Should Care About It

It’s safe to say that almost every Internet user probably uses some kind of search engine every single day. There are several different kinds of search engines, but below are the two most important ones.

• Web search engines, such as Google and Bing, which are used to find information from all over the World Wide Web.

• Site search engines, which are usually embedded in a website or online store, and only retrieve information (content, products, etc.) from that site or store

The most popular language on the Internet is English, and by a huge margin at that. It has been estimated that more than 60% of the top 10 million websites are in English. However, sizable proportions of Internet users are native speakers of languages other than English. The proportion of netizens who speak Chinese, Spanish, Arabic etc. is also relatively significant.

Thus, given the diverse backgrounds of netizens, it’s important for site search engines to support languages other than English as well (let’s refer to these languages collectively as ‘vernaculars’). Indeed, the demand for vernacular search support is rising, because people find it easier to look for things online in their mother tongue. 

When it comes to site search, catering to speakers of vernaculars is especially critical because doing so can actually translate into better business outcomes for website and online store owners. Modern site search engines, which make use of artificial intelligence (AI), machine learning (ML) and natural language processing (NLP), can provide vernacular language search (and even mixed language search) right out of the box.

Let’s now take a quick look at the importance of vernacular language search, and then look at the benefits that modern search engines offer for website and store owners. In what follows, we will focus specifically on site search and in-store search (i.e. site search on online stores).

The importance of vernacular language search

According to the CIA, only 4.9% of the world population natively speaks English, and only 13% of the world speaks non-native varieties of English; together, these two groups consist of 1.5 billion people. While that is undoubtedly a huge number, you should keep in mind that that is less than a fifth of the world’s population. It goes without saying that in general, people prefer looking for products or content in their local languages.

According to a report by Google, 90% of Internet users in India use their local vernaculars for searching and carrying out other online activities. Similarly, around the world as well, netizens are happy to carry out searches in their native tongue instead of in English, to the extent that search engines allow them to do so. 

Additionally, at such times when inputting search queries in the native language is easier than English, but 

• users can either not find the right search term in their language, or 
• the user found the item on the web described in another language, 

it becomes more convenient to use a combination of languages. At these times, an input in the combination (such as ‘Spanglish’, which has been claimed to be the “fastest growing hybrid language in the world”) will not give the right results unless a neural layer is added to the search engine. 

This is where coupling AI and NLP comes to play. This allows users to use multiple languages in the search query to lead them to their desired results.

Thus, by giving your potential customers the option of phrasing their search query in their mother tongue, or in a combination of languages, you can provide them with a better in-store experience. This in turn is likely to increase your conversion rate.

Traditional versus AI-based site search engines with vernacular support

A vernacular-enabled site search engine provides several benefits to website and online store owners that traditional search engines may not be able to. Four of these are stated below.

1. Multi-language support with minimal manual maintenance.
2. Mixed-language support.
3. Automatic improvement over time.
4. Customer satisfaction and loyalty.

1. Multi-language support with minimal manual maintenance

Suppose you operate an English-only website, but want your site search engine to support another language as well (say, Spanish). With a traditional search engine, this would require you to create a large database of strings in Spanish and their translated equivalents in English. This database would allow your search engine to convert Spanish queries into English, which would then be used to produce the final search results.

To reduce reliance on such a database, you might consider simply tagging your products or content with Spanish tags. However, this might then mean that you will regularly need to add more and more tags to products, as you learn what kinds of search queries people use when they’re trying to find them. This means that once again, such tags will need to be manually created and maintained.

And this is the case just for one language: imagine if you wanted your site search to support multiple languages! You’d need to maintain a separate string database and tagset for each language you wanted to support.

In contrast, an AI-based site search engine doesn’t require such manual tasks to be carried out. Instead, the underlying algorithms can automatically deduce correspondences between different languages, and deliver accurate results accordingly. This leads to lower costs, more time savings and better performance as compared to traditional search engines.

It is also important to note that supporting multilingual search is becoming increasingly vital for businesses: according to Google, more than 1.5 billion people started using the Internet between 2015 and 2020, and more than a billion people are slated to start using it by 2025. Moreover, most of the new users between 2015 and 2020 came from Asia, Latin America and Africa. Couple this with the fact that nearly 75% of Internet users in 2020 were non-English speakers, and it should be apparent why all online business owners should seriously think about providing multilingual site search.

2. Mixed-language support

As hinted at above, AI-based search engines are also capable of providing mixed-language support, which is relatively difficult and cumbersome to implement using traditional search engines, if not outright impossible. For instance, a user of Spanglish might type in a query such as ‘ropa para newborns’ (i.e. ‘clothes for newborns’), which might more accurately reflect how that person would spontaneously express themselves. 

While string-based search engines would struggle with such a query without large amounts of manual intervention, an AI-based engine would not have too much trouble with it. As you can imagine, this would lead to a much better customer experience, as they could minimize their cognitive load and still get highly relevant search results.

3. Automatic improvement over time

Search engines based on AI and ML require their underlying ML models to be “trained” using large amounts of structured bilingual data, so that they can create associations between words from two different languages. Several modern NLP-based search engines come pre-trained on massive amounts of data, and can also use real-time search data to improve their performance over time with minimal manual intervention.

4. Customer satisfaction and loyalty

The lack of vernacular search support adds to the cognitive burden for a proportion of your site/store visitors, who are not as well versed in English. Moreover, at some level, non-English speakers are also likely to look upon your site/store more favorably for supporting their language. Vernacular search support, thus, gives them a smoother and more enjoyable experience. Both these factors can increase the conversion rate, and can also help retain non-English-speaking customers by building trust.

Empower your customers with vernacular search support

Thus, in sum, site search engines that provide vernacular search support are important for attracting more visitors and retaining more customers. Given the relatively large proportion of netizens who prefer using languages other than English to explore content or products, providing vernacular search support is a smart business decision. 

Moreover, with NLP-based site search engines like Zevi, visitors on your website/store can now experience the freedom to phrase their queries as they see fit: Zevi will intelligently understand their intent and provide them with the most relevant search results. It can even handle multilingual queries: a single query can contain words from different languages! 

If you wish to empower your customers using the latest AI capabilities and generate more revenue for your business, simply integrate Zevi into your website/store. Start free trial here.

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