Customer analytics allows to gain a deep understanding of your customers, predict their next move, and create personalized experiences in order to timely provide them with awaited and relevant offers, thus increasing retention rate. Currently, customer analysis became vital for, practically, all marketing activities including predictive modeling, data visualization, information management and segmentation.
What Customer Analytics Include
- customer experience analytics
- customer segmentation
- customer support automation
- personalization
- dynamic pricing solutions
- demand forecasting
What You Can Do With Customer Analytics
- Decrease marketing campaign costs by approaching only those customers who are most likely to be interested and respond
- Timely provide proper messages or offers to customers that are really expecting them and are willing to perform consecutive actions (read, visit, purchase, etc.)
- Increase customer response rates, engagement and loyalty by communicating only to the right customers
- Increasing retention rate by identifying customers that are about to leave and proactively designing activities to retain them
- Decrease response time by automating customer support activities
- Increase revenue by establishing dynamic pricing solutions according to customer segmentation insights
- Optimize logistic activities by accurately forecasting demand of your customers
