Predictive analytics: The Big data tool digital marketers cannot afford to ignore

The ability to correctly predict consumer behavior gives digital marketing experts a vantage point from where they can better plan their strategies to suit the consumer’s need.  If you can correctly gauge the preferences of your consumer based on the history of his/her browsing and spending pattern, you will not only be able to service the consumer better but also devise marketing strategies that fit into their behavioral needs.

This ability to analyze is fast becoming the bedrock of digital marketing strategies. The rise of artificial intelligence and big data has empowered marketers, equipping them with powerful analytical tools. Insights into customer behavior backed by hard data can be used to boost marketing efforts at all stages of the sales funnel, and Predictive analytics is one of the most effective tactics to do it.

What exactly is predictive marketing?

Before we get into what Predictive analytics is, let us try to understand Big Data. More than 2 quintillion bytes of data are created every day. It is estimated that by the year 2020, over 1.5 MB of data will be created in a second for every human being on earth. Using that data for planning and executing a marketing campaign will guarantee better results.

Predictive analytics is a branch of analytics that leverages the power of big data to predict future results or events. It integrates techniques from statistics, data mining, machine learning, modeling, and artificial intelligence to scan and analyze data sets and develop predictions.

You define the business outcome, collect data, analyze it, test it using statistical methods, create predictions about customer behavior, use the data to design and implement marketing strategies, and track the effectiveness of the campaign using models. Let us take a look in some of the ways it can be used to boost marketing:

• Better lead scoring – Lead scoring refers to the process of ranking the business leads based on their position in the sales funnel. It lets the sales and marketing teams to collaborate more meaningfully. Prescriptive analytics makes it possible to score the leads based on their readiness to make a purchase. This helps market better to a prospective lead based on their buying habits.

• Better lead segmentation – Nurturing the lead requires a lot of planning. Using behavioral and demographic data, Predictive analytics can be deployed to grow your business by grouping the leads by segment and creating tailor-made campaigns to move the lead forward in the sales funnel.

• Targeted content marketing – Predictive analytics can help you understand what type of content works better for your lead. Once you are able to understand the type of content that works with your target audience, and have a clear idea on which channel you have the best chances to reach out to them, you can customize your content curation and distribution better. If customers receive more focused communication from a business, the chances of sales conversion are higher.

• Predicting lifetime value – Customer lifetime value is a metric that lets you know the worth of a customer throughout their relationship with you. Predictive analytics allows you to take the customer’s historical data and use it to forecast the future of your relationship, and how much revenue it can bring in. Such estimates help you allocate the right budgets for customer acquisition, and give you a more accurate picture of your ROI.

• Predicting churn rate – Churn rate is basically the attrition rate, the percentage of users who end their subscription to your service in a given time period.  For optimal growth, your business’ growth rate should be higher than its churn rate. Predictive analytics can help you identify if you are going to lose a customer, allowing you to nurture the relationship and make timely follow-ups before it is too late.

• Readiness to upsell and cross-sell – Analyzing the customer buying patterns can help you upsell and cross-sell better to increase your profits. For instance, if you know that 40% of customers who buy product X buy product Y within five months, you can market product Y soon after they buy product X. This will help you speed up the process and capture customers who wouldn’t have considered buying product Y otherwise.

Predictive analytics holds the key to building an effective marketing campaign. By integrating the correlation between metrics and business results using advanced strategies, it helps create a stronger impact across the customer life cycle. But, as with anything else, it does not guarantee success, but merely increase its chances.

Author: Tuhin Banik, Founder Thatware LLP

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