Effective customer retention is critical to maintaining a strong and growing business: retaining existing customers is much cheaper than acquiring new ones. In this article, we discuss how we use advanced analytics to tackle churn and create proactive retention strategies.
Our Strategic Analytics approach handles churn reduction end-to-end by first helping our clients understand why customers are churning, and then we use those insights to develop and implement strategies that proactively increase customer retention.
The importance of data-driven proactive customer retention
We start by blending data using our proprietary churn model to build a comprehensive fact base. Combining information on customers, product usage, service issues, billing, pricing, and competition, we correlate different patterns with churn risk, and then identify the most relevant churn drivers.
Through this process, our churn analytics solution helps our clients quickly focus attention on the biggest opportunities, answering a number of critical questions. Examples include:
Are sales, marketing, or other acquisition practices driving early customer churn?
Do some services result in poor customer experiences and below-average retention?
Which customer segments are most likely to churn after promotional pricing expires?
How much do service outages or poor customer service experiences increase churn risk?
Are there regional retention issues that can be targeted for quick resolution?
Which competitors are most effectively stealing customers?
Once the most actionable opportunities are identified and quantified, we then work closely with key stakeholders to prioritize and implement initiatives to increase retention and reduce churn. These can span the customer lifecycle, and can include a combination of technology-based churn analytics solutions as well as strategic support.
By following the process of blending data, correlating patterns, identifying opportunities, and prioritizing outcomes, we help our clients implement solutions that achieve their objectives.
Examples of our work include:
Developing predictive churn propensity models to proactively identify customers who are most “at-risk” of churning
Deploying web-based churn dashboards that provide up-to-date analytics on churn trends and drivers to key stakeholders
Optimizing sales and marketing processes to increase retention though better alignment of products and services with customer needs
Building and implementing customer retention and loyalty programs