Using Predictive Analytics to Engage and Retain Your Best Customers

In a tight economy, customer retention is absolutely critical, Analytics-led research shows that it costs six to seven times as much to replace a dissatisfied or unhappy customer as it does to retain a satisfied customer. Yet few companies devote the resources and energy available to retain good customers.

Satisfied Customers Using Predictive Analytics to Engage and Retain Your Best Customers Instead, they allow perfectly retainable customers to walk out the door because they fail to pay adequate attention to their needs or preferences. Or companies simply allow their customers to become dissatisfied as they devote greater attention (and capital) to adding new customers.

The problem with this kind of logic is that it’s like allowing water (in this case profits and revenue) to slip through the holes of a leaky bucket. In many cases, customer attrition is preventable and analytics can help plug up these holes.

For instance, companies can use predictive analytics to identify the known triggers for customer defection (e.g., reduced transaction volumes, increases in the number of complaints to the contact center) and act on these issues before a customer leaves for a competitor. Simply demonstrating to customers that the company is paying attention to them and wants to make them happier can go a long way toward improving customer satisfaction and customer retention.

Another effective way for companies to tackle customer defection and strengthen relationships with their top customers is through the use of customer engagement analytics. These tools can be used to determine how both retail consumers and B2B customers are using a company’s products and what their level of engagement is, notes Paul Ressler.

Customer engagement analytics can help companies better understand whether certain products or product features are being underutilized and the reasons behind this. Discovering this type of information can help guide executives as to possible weaknesses or perceived problems with products that can be corrected or improved to help boost customers’ usage and satisfaction.

Think Apple. Apple has an incredibly devoted customer base. A big part of the reason for this is that Apple’s products are relatively simple to use and they’re designed from a customer-experience standpoint.

Companies can also use analytics to determine the most effective ways to engage with specific customer groups. Doing so can help decision makers strengthen business outcomes.

Bain & Company, which has conducted research on this topic, finds that customers who engage with companies using social media are spending up to 40% more with these companies than other customers.

Companies can also use engagement analytics to determine the types of channels groups of customers prefer to use for specific interactions (e.g., interactive voice response for rote support, chat tools to interact with agents to resolve more complex issues) and to identify relevant topics that customers are interested in discussing.

These techniques can demonstrate to customers that a company is paying attention to their interests. This can open the dialogue for deeper engagement and stronger, more beneficial customer-company relationships. Our deep-set commitment to our customers defines how we do business, and our years of experience working across industries underpin the vast array of services we offer. As per our understanding of industry, combined with insights from Center of Excellence, allow us to more efficiently equip our business with proven solutions that incorporate industry best practices.

With engagement models that match the size and scale of our operations, we can support your business goals and offer partnership opportunities based on gain-share and risk-share models, as appropriate. Whatever your business needs or aspirations, we have the in-depth knowledge, world-class processes and standards, and relationship-based approach to put the right solution in place.

Customers that have already learned what it means to experience certainty hail from a wide range of industries:

Banking & Financial Services Energy, Resources & Utilities Government Life Sciences & Healthcare High Tech Insurance Manufacturing Media & Information Services Retail & Consumer Products Telecom Travel, Transportation & Hospitality

Cell Profitability/Network Optimization

L – Low H- High Above is the graph showing the clusters of the cell according to their per user

volume usage in each cell. To calculate that which cell is falling in which Cluster we need to do the below

cumulative frequency for Unique user and Volume Usage to the frequency of their appearance in the cell.