Predictive analytics for marketers
Marketing is all about capturing interest: getting customers and clients excited about the product you are selling, the service you are offering, and the company image you are conveying. As such, an understanding of customer behavior and preferences is crucial. In order to attract customers’ interest and better address their needs, you have to know what makes them tick, and that’s where marketing analytics platforms come in. Learn how predictive analytics can help effectively segment customers, build better workflows, optimize ads and campaigns, and build brand strategically.
Marketing analytics use cases
FINANCE & OPERATIONS
Put the customer first with predictive insights
Cater to different customers
Not all customers are the same. By creating customer segments using clustering techniques, learn about the different qualities and behavior that make up your customer base.
Segmentation can also help adopt a more personalized approach in terms of messaging. Create targeted messages and campaigns that are tailored to your customers’ needs.
Monitor customer feedback
Understand your customers by listening to them. Make sense of social media feedback, emails, customer service interactions, and any other messages through text analytics and natural language processing.
Reduce customer churn
Get visibility into why customers are no longer purchasing your products or signing up for your services. Leverage predictive modelling to identify the factors that contribute the most to churn.
Proactively address needs
Using predictive analytics, anticipate customers’ needs. Proactively design campaigns or experiences around these needs in order to sustain customer interest and create a higher level of engagement.
Improve product positioning
Perform a market basket analysis to provide better and more personalized product recommendations in real time. Increase the likelihood of purchase with strategic cross-selling and upselling.