Data Analysis to Connect Marketing, Customer Service

Reading Time: 2 minutes

Historically, enterprise marketing and customer service departments have gathered and maintained customer data separate from one another.

Creating these data silos prevents each department from developing a deeper understanding of customers – information that can be used to identify new products or services that customers share in their contact center interactions along with additional insights that can be provided to agents to deliver more personalized and knowledgeable support.

For instance, a customer who reaches out to a retail bank to inquire about an auto loan may also be in the market for auto insurance.

An agent or branch manager who fields a customer inquiry about an auto loan could gauge the client’s interest in the bank’s auto insurance offerings, including how rates could be lowered by pairing auto insurance with homeowners’ or renters’ insurance.

There’s a wealth of information available online, through the use of search engines, in social communities, etc., that is empowering consumers to make more informed decisions about the products and services they decide to purchase.

But there’s also a gold mine of data now available to marketers and contact center leaders about customers – including sentiments shared about their preferences, needs, attitudes, and interests through their contact center and social media interactions – that marketers and contact center leaders can analyze to craft relevant experiences, support, and offers.

Because the contact center typically represents the first – and often the most personal – interaction that a customer has with a company, this may help explain why customer service is gaining an upper hand in shepherding the customer experience.

For example, corporate executives most frequently cite marketing as the leading function responsible for customer experience marketing, according to a 2012 report from Aberdeen Group.

However, more recent research from Aberdeen reveals that customer service has claimed the leadership role and is now more regularly cited than all other departments.

Regardless of who pulls the strings on customer experience management, it’s clear that both marketing and customer service can benefit immensely from sharing customer data with one another.

For example, customers who are repeatedly calling the contact center trying to resolve recurring issues are at high risk of defecting to another company that can offer better support.

Marketers and contact center leaders can apply predictive analytics against this information to identify the customers who are at risk of churning and evaluate the most appropriate responses to retain their business.

Depending on their purchase histories and lifecycle statuses, some customers may be interested in receiving attractive discounts for certain products.

Others may be swayed by having customer service managers or account managers contact them personally to better understand the nature of the problems they’re experiencing and offer help to resolve the issues once and for all.

Deeper data analysis may reveal that customers with similar characteristics whose issues have been resolved and who have received certain types of offers are more likely to remain loyal to the company and extend their business with that firm.

Next Steps:

  • Subscribe to our blog to stay up to date on the latest insights and trends in data analysis, predictive analytics, marketing, and customer service.