Data Science in Marketing

Modern marketing is part art, part science. Digital marketing now means that brands can collect huge amounts of data on their audience. And as any good marketer knows, knowledge can be vital in attracting and converting customers. 

But collecting data for the sake of it is meaningless if you don’t do anything with it. That is where data science comes in. 

Data science in marketing takes this data and identifies behavioral insights and turns it into actionable information. What’s more, this can be done at a scale that would be impossible for marketing teams to achieve manually. 

However, data isn’t the be-all and end-all. Marketers need to know how to interpret this data and make decisions based on this. 

How can data science help marketers?

Data can be used to optimize every stage of the marketing funnel. The most common uses include: 

Optimizing marketing channels

Granular data can be much more accurate in determining an accurate picture of the ideal customer, how they think and what they want. Data science track the pathway of a user and flag up any potential opportunities on social media channels or your website. 

Enhanced segmentation

Effective marketing targets the wants, needs, and pain points of customers. Machine learning can segment based on their historical behavior, purchases and visits determine the best way to appeal to them.

Lead scoring

Every potential lead can be scored based upon the data and the behavior of similar leads in the past. This can allow you to reach out to the right customers and at the right time with the right products. 

Sentiment analysis

Tracking your brand reputation online is important. Data science can compile all mentions of your brand and assign them positive or negative sentiments automatically. 

Key points

Data science in marketing is changing the field as we know it and putting the power back in the hands of the marketers who know how to analyze and interpret this data to improve their marketing strategy. 


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