Data science

A 6-step process for applying ‘test and learn’, including defining KPIs, creating test criteria, achieving statistical significance and turning insights into action.

Examples of how intelligent automation is solving big problems for marketers, including advanced lead scoring and turning predictive analytics into action.

Key search marketing trends marketers need to know, including intelligent automation, augmented reality, micro-influencers and content consumption.

Some great ways AI changed the world in 2019 including finding human trafficking victims, tracking great white sharks and writing the new Harry Potter book!

Five key data science tips for travel companies including hyper-personalisation, real-time insights and predictive analytics.

There are several reasons why you might be seeing (not set) in Google Analytics – here are some examples and what you should do about them.

Data science is key to helping retail marketers get the edge through personalised pricing, data-driven attribution, intelligent up-sells and customer lifetime value modelling.

Data-driven attribution accounts for the importance of every touchpoint a prospect goes through before converting, and can significantly increase your marketing ROI. In this article, we explain how it works and how you can develop your own.

In this short blog, we explain what data science is in the simplest of terms, plus list some practical examples of how it can help marketers supercharge their marketing efforts.

It’s no longer enough to rely on standard SEO techniques. If you want to get the edge, you need to use advanced data science techniques to unearth hidden opportunities. In this article, we explain a four-step framework to help you do this.

A quick and simple explanation of what machine learning is with working examples of how marketers can use this technology to improve their marketing.

Many marketers might think AI is beyond their reach but this isn’t the case, as we showcase in these four examples of how companies are using it right now.

Data science is playing a growing role in every aspect of our lives. So it’s only natural that interest is increasing. In this FAQ, we answer the most common questions asked about data science.

What are predictive and prescriptive analytics in marketing? In this third chapter, we explain what you can achieve with a mature big data analytics setup.

This article moves us on to the more thrilling part – learning how to ask the right questions (using data science) and receive the best answers (using data analytics).

You know that data science is your strongest bet for remaining competitive. But where do you begin when that data of yours is well… big? Our team is here with some answers.

Identifying important social media cues, trends and signals now requires extensive analytics capabilities. So how do you stop the incoming data flood and transform it into a steady stream of distilled insights?  By applying science to the most pressing problems at hand.

To reach the ‘sceptic’ consumers, brands should be raising the quality of content they are producing and sharing. Data-backed content is now in high demand.  And data science should become your tool to elevate your brand’s authority and credibility.

Data science –  it’s the talk of the town for certain. Do you need to invest in data science Here are five signs indicating that it may be time to do so.

Data has always been crucial to marketing, but our ability to make the most of it has always been limited to the technology we have available. These limitations have almost disappeared thanks to machine learning and automation, which make big data accessible to businesses of all sizes.