As marketing becomes more data-driven, marketers are planning to leverage predictive engagement analytics for strategies beyond customer acquisition and retention

In the last decade, enterprises have invested heavily in data analytics to understand and predict customer behavior. Companies now are taking a step further to use these insights from predictive analytics and build what is being called as ‘predictive engagement’.

According to experts, predictive analytics lets enterprises see the ‘early signs’ and helps forecast the preceding events where marketers can intervene before market incidents happen. Though the strong data analytics capabilities help to overcome internal choke points, predictive engagement now looks like the next natural consequence of these investments in analytics capabilities and technologies.

Taking a step ahead in the tech, prescriptive analytics is allowing marketers to create rules for when predictions are met, thereby automating business processes. According to Gartner, the predictive engagement software market is expected to reach $1.88 billion by 2022. By next year, predictive and prescriptive analytics is expected to attract 40% of enterprises’ new investment in business intelligence and analytics.

Experts suggest using predictive analytics from the first day of digital strategy, to enable the ability to maximize ROI within the current technology stack.

Predictive models can help businesses identify, focus on and grow their most profitable customers. Sales teams of enterprises can identify the best accounts using predictive analysis for different lead nurturing methods. Predictive Analytics helps ensure that right sales resources are used at the correct time to pursue the prospects which help in narrowing down the process. The technology also makes sense of the distinct data to build more robust, holistic ‘personas’ and segments.

This technology can also unearth actionable insights to reduce ‘lost’ sales. According to a report from CSO Insights, 54% of all forecasted deals by sellers don’t actually make it to the finish line. Since predictive algorithms use internal data including that from CRM or Marketing Automation data and external data sources it can help sales teams understand the next target, the lead for it, the way for communication and also if they should attempt to cross and upsell. Predictive analytics is being leveraged to understand further engagement with clients.

Marketers can also plan to increase their clients’ base using predictive analytics with more fruitful campaigns as it can determine future client responses and purchases based on past behavior. However, experts also warn about balancing predictive analytics with human common sense. As machine learning algorithms don’t always know the “intent”, it may predictively optimize a campaign leading to unintended results.

In the times of data-driven everything, adding predictive analytics proves to be a smart layer that can give your business the ‘complete’ package.