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Natural Language Processing for Search Data Analysis and Market Trends

Emiliano Sammassimo

Google is the world’s biggest confessional – what people search says a lot about their lives, and the way people search has changed a lot over the last years.

Voice searches, IOT, geo-localized and “near me” searches: we got used to communicating with machines, smartphones, smartwatches, virtual assistants.

This has revolutionized the language we use in the searches, which is no longer a mechanical sequence of keywords, but instead a colloquial dialogue, more and more human-like.

Today more than ever, marketers need to understand these deep transformations regarding the users’ searches and their intent, as well as being able to anticipate the main online market trends.

However, how can you manage to process an increasingly massive amount of data, decrypting colloquial phrases and natural language? Artificial Intelligence and Machine Learning come to the aid.

NLP, what is Natural Language Processing

Natural Language Processing, often abbreviated to NLP, is one of the most popular AI applications in recent years.

It includes all those artificial intelligence algorithms that analyze and understand human natural language. In fact, the dialogue between man and machine is quite complex, since it involves phonetics, morphology, syntax, semantics, jargon and context: all these elements turn a simple sequence of words into a meaningful sentence.

Computational linguistics is the science that studies how human language works, in order to develop programs executed by machines that can mimic the same functioning.

NLP breaks down messages into words as primary units, to analyze their context and the sentiment expressed, in order to make the machines provide increasingly precise answers to users: a true interpretation of their query.

Search data analysis and market trends

As a matter of fact, analyzing user searches and online trends is increasingly complex: not only do you need to understand what people are looking for – in terms of seasonality, trends, peaks and troughs – but also how searches are carried out.

Mapping a large amount of raw data – which is even more impenetrable because it is based on natural language -definitely requires the activation of Artificial Intelligence.

For example, thanks to AI, you can  collect and analyze emerging trends on Google in the travel industry, to find out what and how Italians are getting information when they book their summer holidays.

Once you identify the most popular destinations you can: 

  • make ore strategic decisions
  • optimize the management of search campaigns
  • dynamically set up your editorial strategy

Our Trend AI platform let you monitor a relevant list of destinations, along with a series of variations (eg “flights to {placename}”, “hotel in {placename}”), with a dashboard that updates you every morning and gives you an alerting when growth thresholds are exceeded.

The advantages are mainly two:

  • you drastically reduce the search times needed with a classic approach on Google Trends
  • you can now identify previously inaccessible research trends, thanks to a much wider field of analysis.

NLP helps to aggregate searches by not focusing on the single query but rather considering the intent or the search category, identifying trends more precisely, taking the context into account as well.