Customer analytics is the process by which data from customer behavior is used to guide key business decisions via market segmentation and predictive analytics. Businesses use this information for direct marketing, site selection and customer relationship management. Essentially, customer analytics tells you who your customers are, what they are doing, what they want, and how and when to reach them so that you can create customer experiences personalized, at the individual-level, to win more business and drive loyalty.
Customer analytics software helps organizations by:
- Targeting customers with highly relevant offers across all channels, including digital, mobile and social
- Segmenting customers into small groups and address individual customers on actual behaviors
- Maximizing customer lifetime value through personalized upsell and cross-sell offers
- Tracking customers and how they move among different segments over time, including customer lifecycle context and cohort analysis
- Engaging with customers through the right channel at the right time with the right message
- Predicting the future behavior of customers using predictive customer behavior modeling
- Understanding customers in the context of their individual relationships with your brand
- Predicting which customers are at risk of churning and why, and take actions to retain them
- Using advanced calculations to determine the customer lifetime value of every customer and base decision on it
- Measuring customer sentiment and identify emerging trends in social media and survey data
The challenge with some customer analytics software solutions is that they require enormous data integration efforts between heterogeneous databases and data warehouse systems. Often, there is little agreement on exactly which key metrics to use to profile customers for marketing and analytical applications. These data integration projects typically result in batch-heavy ETL solutions, for both consolidation and subsequent processing, with analytical and reporting applications that often only have access to resulting data on a weekly or even coarser basis.
The most powerful and results-oriented customer analytics solutions build individual customer profiles, in real-time, and solve data integration issues by providing a standard, customer-centric approach with thousands of pre-defined metrics that are centrally managed, continuously updated and available for application connectivity.
How does your organization use customer analytics solutions to drive the customer experience?
For further interest:
