How to Apply Big Data and Artificial Intelligence to Your Marketing Strategy


The marketing industry is rapidly evolving. It’s at a new phase where Big Data and AI (Artificial Intelligence) are driving strategy development and decision making. Because conventional analytics scale at a gradual pace, marketers are beginning to utilise AI to analyse the large volume of unstructured data to improve marketing research, forecasting accuracy and campaign experiences.

A research of CMOs from the US, UK, and China from companies with more than $500 million in revenue revealed that around two thirds of these think Artificial Intelligence will play a significant role in their future marketing operations. But only a third claimed to have good knowledge of how it is actually implemented.

Another study of B2B marketers at managerial or higher level positions at organisations with 250+ employees revealed the main benefits of AI implementation were in marketing.

Benefits of Artificial Intelligence for marketing

Today, AI tracks and records every interaction a consumer has with a website, email, or social media platform, while machine learning can gather the incoming data in real time, and deliver personalised experiences to each person in immediately.

Here’s a breakdown of how this process works (courtesy of Genii Analytics):

Artificial Intelligence process

What you see is a simplified chain that makes sense of Big Data when several independent agents interact with one another. The AI-powered funnel doesn’t work in a vacuum; it responds to the feedback received in its environment from both AI agents and humans.

With greater insight into socio-economic data, geographic patterns, and customer demographics, marketers will be able to develop proactive campaigns that optimise output. And the good news is that you don’t have to learn about AI and machine learning; off-the-shelf algorithms are available for companies to use.

Range of AI & Big Data Possibilities for Marketers

Several companies are already leveraging Artificial Intelligence and Big Data to improve campaign reach. The aggregated information is already being used in the following scenarios:

  1. Customer Service

The key application of Artificial Intelligence and Big Data is combining the technologies of natural language processing and machine learning to build chatbots (intelligent assistants). These are interactive customer service reps that communicate with customers naturally and assist them in solving problems and accessing specific information. An example is IBM’s Virtual Agent Watson. It allows marketers to engage with customers by tackling usual questions and interacting in a personal manner when responding to requests on any channel. It’s programmed to learn about a company and its customers.

  1. Consumers’ Feelings

As user-generated content and social media platforms started producing their own Big Data, marketers began to analyse these vast data set for insights but they faced a new challenge – knowing if people are talking about you is less useful than knowing their sentiment towards you. That’s where semantic analysis comes into the picture. It provides context to certain behaviors and actions, enabling you to cluster data elements.

For instance, an AI tool will know that:

  • “Banana” and “organic” are semantically related.
  • “Banana” and “yellow” are more closely related than “banana” and “organic”.
  • “Banana” is frequently capitalised.
  • “Organic” can refer to vegetables too.

And make a connection that the yellow banana is a sign of organic goodness.



AI and semantic analysis helps uncover information such as how exactly people feel about your offering or product. It’s about making sense of things using data by considering proximity, frequency, and many other factors to make a cognitive leap. Big Data cannot be utilised on its own, but with the right analytics it can be a powerful tool.

  1. Product Recommendations (Up-sell & Cross-sell)

Marketers that utilise Big Data and AI leverage the fact that such technologies understand people’s buying intent, which enables them to suggest possible product recommendations to aid the customer’s shopping experience. Two examples are Netflix and Amazon’s recommendations of TV-shows and products; machine learning systems and algorithms learn from new data such as viewing history and past purchases to make automated decisions – no manual intervention needed. Cognitive computing tech will keep giving companies the opportunity to up-sell and cross-sell.

In a nutshell, marketers can trust and act on AI’s wisdom to gain a competitive edge. 

AI Is Also Relevant To Influencer Marketing

Content related to the rise of Artificial Intelligence in Influencer Marketing is appearing on the web for a reason. AI-enabled Influencer Marketing platforms allow the creation of scalable campaigns with measurable results. Buzzoole’s Artificial Intelligence allows in-depth analysis of the Influencers online presence to find the perfect match with a Brand. For instance in order to evaluate an Influencer’s affinity, Buzzoole’s technology also takes into account other factors such as contextual relevance, demographic target, etc.

Also, semantic analysis, that we deliver thanks to our collaboration with ExpertSystem, analyses our Influencers text on their social profiles and blogs and is able to really understand what their topic of interest is, and their sentiment towards the Brand. This way we can identify the Influencers who have great affinity with the Brand and create solid and authentic relationships.


When using Big Data and AI for marketing, the possibilities are endless. AI technologies can be used to help marketers improve how they connect with Influencers and carry out campaigns. By activating the right campaigns by leveraging the ideal experts, Brands will make their activities scalable, thus increasing marketing ROI, which is paramount in today’s competitive industry. 

This post is also available in: Italian

gennaro varriale

Gennaro is Buzzoole’s CTO and co-founder. He started developing at the age of 8 and since then has never stopped exploring the world of programming. In 2013 he developed (now in just 6 hours. The app went viral in no time and quickly appeared on popular review sites. Gennaro is not only passionate about Data Science, Machine Learning, and Big Data, he also loves photography and creative copywriting. Get in touch with him on Twitter or Facebook.

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