5 Reasons to Integrate Big Data Analytics into Your CRM

Are you managing customer experiences from the outside-in? Customer experience may sound like a simple concept—how your customers perceive their interactions with your company. In a soon-to-be-published book called “Outside In,” Forrester Research argues that customer experience is a fundamental business driver.

Find Correlations in Data to Improve Customer Satisfaction

In fact, it’s the only source of competitive advantage in an age where customers and potential customers have unprecedented access to reams of data about your company and competitors. “Despite its economic power, customer experience remains the most misunderstood element of corporate strategy today,” argues Forrester analyst Kerry Bodine. “You must manage your business from the outside in—bringing the perspective of your customers to every decision you make—and you must do it in a systematic and repeatable way.

One of the best ways to bring the perspective of the customer to business decisions is by using data analysis and CRM analytics to find correlations, isolate patterns, and track trends to serve up the type of information to allow a company to tailor the customer experience for improved engagement and better profits, according to an article by Marianne Cotter at CRMSearch.

Five Reasons to Integrate Big Data Analytics to Your CRM

Better Customer Understanding: CRM analytics can integrate all customer data points including call center, the Internet, email, and social media to group customers according to their behaviors. This allows a company to identify the most profitable customers who should receive special offers or get preferential treatment to boost their lifetime values.

In-depth understanding of customer-facing operations: Analytics provides insight into new areas, like linking CRM with social media to better interact with the customer.

Decision support: After defining the value of customer-facing operations, changes can be made to drive operational investments. Companies can answer questions around building new call centers or outsourcing based on this analysis.

Predictive modeling: Predictive analytics allow a company to forecast how customers are going to respond in the future based on their past behaviors and their segmented demographics. For example, a telecommunications company could find out how likely a customer is to turn to another carrier when his/her wireless contract expires. Or, a consumer products company could predict how well a certain demographic will respond to a new marketing initiative based on past purchasing behavior.

Benchmarking: CRM analytics allows a company to track over time how well it’s performing related to a strategy or to competitors. Benchmarking analytics in areas like customer satisfaction, retention, cost-per-customer service call, and revenue-per-call will expose operational areas that are lagging behind, and those that are up or above company and industry standards.

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