What are they and how to differentiate them?

Are you looking for information or the information is looking for you?

When we refer to the “search” term we refer to the action of doing anything to find someone or something, in this case in the search context of the internet or in an online store, it’s the action that is carried out in an engine (search engine) in order to find files or documents, products, references or more, hosted on web servers.



On the Internet, a search is the action carried out in an engine (called a search engine), with the aim of finding certain files or documents that are hosted on web servers.


But what is discovery? Basically it is finding something that was ignored or hidden.

Why is discovery better than search?

One of the reasons is data overload, because, in order for this data to be processed requires a large amount of effort, space and time. 

Searching for something (either through Google or an online store search engine) examines large amounts of data, including non-relevant data. 

This is because a large amount of information is required for a search engine to know exactly what you are looking for.

On the other hand, “proactively” generated discovery, where a system generates a context of what it is doing or looking for, can be the next big leap in data management.

The combination of these elements (traditional search + Context) generates the discovery and because of this, we can save a lot of time and resources when we want to discover (for example a product or an offer).

This context is generated by several elements, such as: the information that the system is receiving (location, device, history, etc.), recommendations, similar purchases by similar users or machine learning, in such a way that the more we use it, more and better patterns are generated, the system manages to learn more and the results are increasingly accurate, resulting in less use of resources and the knowledge of what the user might need.

Therefore, when we mention a “proactive” system, we mean that the mechanisms of the discovery engine are activated not when the user requests it (passive), instead, the discovery tool provides the desired information when it is needed. That is the power of discovery, and that is what the search should eventually evolve into.

What do we need to do to achieve that evolution?

To “discover”, a system must be able to understand what we are looking for and how it will be applied, providing relevant information when asked to do so, or even automatically.

For a system to be able to understand and analyze the context, it needs a data repository, classified, organized and ordered in such a way that its processing is simple, fast and relevant information can be obtained.

This is the importance of having the appropriate recommendation or discovery system, which is capable of:

  • Attract online traffic where we want it.
  • Offer suitable product suggestions while storing data.
  • Involve consumers while making individual item recommendations.
  • Dig even deeper into a product catalog without having to search one after another.
  • Transform or convert users into customers.
  • Increase the average ticket value and the number of items per order.

In today’s era where data is everything, finding and classifying it becomes a greater challenge than ever, so information must be updated and presented in a renewed way, where users do not have to search, but to discover.