With the “Back to School” season many retailers take the challenge of adapting their online stores and catalogue to fit the common customers’ needs of this time of the year.

We have checked the searches made in one of our bookstore customers, and we have seen how searches by reference number, in this case ISBN (International Standard Book Number), have been heavily increasing during July in Spain. The number of queries this month has been multiplied by 25 compared to June, which confirms that the textbooks demand is shaped right after the end of the school year and these purchases are made with enough anticipation so that customers avoid out-of-stock issues with the school books for their kids.

In such important periods and search scenarios for retailers offering the best search experience becomes critical. Our site search should guarantee that our customers are locating any product in the catalogue, and this goes beyond having users typing the right keywords. Here is where search technology takes over by providing multiple ways for assisting users within search and discovery processes. What is more, the search technology should not only assist but even anticipate the user’s needs by instantly detecting queries types.

In this way, the world of searches by SKU, ISBN or reference number can be transformed into an evoking experience where the search box automatically offers suggestions of items starting by the reference typed. Similarly, if a product with the indicated reference is out of stock, the search engine can offer similar suggestions under the same family or category of products based on the attributes of the original SKU.


When talking about “Back to school” purchases not everything is about textbooks. It also has to do with school clothing and other school supplies. And here is where the search engine should appeal to the Discovery element; especially for marketplaces and department stores with multiple categories. There are many ways of making the most of Search, and the own search features can act as assistants for filling up the shopping cart, similar to a smart list creator.

One of these features is Next Queries. The collective analysis of millions of search journeys allows predicting what the next query of a user journey could be, thus anticipating search demand. Although this feature can be implemented in multiple ways, let’s focus on a simple use case for ‘back to school’:

Users perform a search for “notebooks”, add a notebook to their basket. They go back to the search box and, before they start typing, a list of recommended and “contextual” queries is displayed (e.g. pencils, backpacks, or even school shoes). Users then add shoes to their basket and the search box follows up by suggesting school uniforms, track-suits, etc., next.

In the same way, Search Suggestions can be displayed within the search box to guide the search journey and display a set of popular queries or even products related to the query already typed. That would help to make users know how broad our catalogue is and what other school supplies or clothes could meet customers’ needs. This kind of suggestions are proven to increase the average order value and, most importantly, to enhance the search experience becoming a discovery journey.


Search Suggestions and SKU searches are two of the scenarios where search experience can be completely revamped: from the tedious work of finding the right textbooks and clothes for the back to school season to a new way of search and discovery; more intuitive, meaningful and definitely human. If Search is capable of opening the door to evoke those feelings combining expression and design with its core functioning, then our customers will be firstly surprised and amazed; secondly, appreciated and relieved; and, finally,loyal and devoted to our brand.

If you want to know more about these search features to get the most of your site search, download our Search Use Cases review.