Enhancing the customer experience is one of the main goals of most every business today. A customer who experiences a positive interaction with a company is more likely to conduct business with the company a second time, a third time, and any number of times, leading to a longer and more profitable relationship.
To improve the experiences of their customers, many companies have invested heavily in customer relationship management (CRM) software so they can collect, store and act on customer data. But is the data being used correctly? Is it possible to glean a deeper understanding of the customer from the data? Is there a way organizations can reap additional benefits from their CRM systems?
The problem is CRM systems fall short when it comes to delivering quality analytics. Traditional CRM systems are mostly designed to capture and store transitional data including point-of-sale data and contact information. They focus on operational data and rarely provide advanced data analytical capabilities.
Related customer data points, including benchmarking, campaign analysis, predictive analysis, customer segmentation, and lifetime value analysis, to name a few, are generally excluded from CRM systems. Thus, it becomes imperative that organizations develop advanced analytical approaches to understanding customer preferences, expectations, and churn.
An advanced analytical approach allows organizations to develop or enhance strategies that increase cross-sell opportunities, upsell opportunities, and customer retention.
In this article, Marianne Cotter makes the point that there are “power reasons” to integrate analytics into a CRM system.
First, she suggests that embedded analytics will lead to better customer understanding. The data generated by call centers, emails, social media and other customer data points allows you to develop groups based on their behaviors and other identifying information, if available. In other words, segmentation analysis and target marketing is enhanced.
Next, Cotter says analytics can also help justify the cost of investing in a CRM system. Operations related to customers can be analyzed and returns on investments (ROI) can be calculated. Reports and analyses are then shared with the executives and the CFO. The analyst can establish ROI and use it to justify additional investments.
Analytics can also help execs make the best operational decisions by enabling them to ask and answer questions that help promote the business, Cotter says. Analyzing customer data can support your decisions and lead you to solutions to enhance the customer experience. The development of forecasting and predictive models helps an organization anticipate how a customer will react to strategies under consideration.
Finally, embedded analysis allows for benchmarking and a period-over-period comparative analysis.
Embedding an analytical system into a CRM system can help an organization manage total cost of ownership and provide additional analytics that can be used to further the development and understanding of customers and generate more business.
- Check out this post, “The Role of Advanced Analytics in CRM,” and learn more about the relationship between advanced analytics and CRM.
- Download this complimentary ”5-Minute Guide to CRM Analytics,” and learn how agile analytics technology can deliver critical value to executives and front-line marketers.