CRM Analytics Defined
Customer Relationship Management Analytics or “CRM Analytics” is all of the activity that falls within the analysis of data for customer marketing. This also includes facilitating and streamlining business decisions.
This is a massive spectrum from database management and data mining on one end to highly personalized audience segmentation and omnichannel marketing campaign execution on the other.
The process involves the use of tools that help in measuring the effectiveness of customer-related processes and eventually provide customer categorization. These include event monitoring, profitability analysis, predictive modeling and often, what-if scenarios.
These days, companies continue to add newer and faster ways of interacting with customers. As such, the need to transform customer-related data into valuable information has become more and more essential.
Companies use CRM analytics to separate customers for marketing campaigns and even train call center workers with current information regarding callers.
How Businesses Currently Use CRM Analytics Today
It provides insights into understanding and using the mined data. Organizations use CRM analytics in the following ways:
- This involves learning which customers are ultimately responsible for the highest profits. It requires knowing the amount that is spent by the customer and the amounts of marketing resources that should be dedicated to getting them to return in the future.
- Customer Audience Segments
- Separating customers into groups by their propensity
- those who have browsed certain products
- those who have not browsed certain products
- those interested in categories of products
- those uninterested in categories of products
- those who have purchased a product and likely to buy again
- those who have purchased a product and unlikely to buy again, etc.
- This involves the capacity to personally market to customers based on collected data. This calls for gaining a 360-degree customer view
- Measuring and Keeping Track of Escalation
- This involves the capacity to measure the frequency of problems with a product or service and formulate ways to eliminate the issue and swiftly attain customer satisfaction.
- Predictive Modeling
- This involves comparing different product development strategies to determine likely future success. This uses customer shares to measure the levels of customer engagement.
The collection and analysis of data are viewed as an iterative and continuing process. Over time, important decisions about your business are distinguished based on feedback from previous analyses and resulting decisions.
The Future of CRM Analytics
The future of CRM analytics will be an assembly of real-time connectedness that allows smart marketers to recognize, target, convert and develop their customers via business intelligence, artificial intelligence, and machine learning.
Not only will demographic or psycho-graphic data be processed, but the behavior of customers across a largely digital landscape will be processed as well. Buyers will concentrate on the addition of developing technologies that allow for more effective customer experiences.
The Many Developing and Advancing Use Cases
CRM analytical tools assist in a number of areas and these include:
- Evaluation of customer service and customer satisfaction
- Verification of user data
- Enabling better pricing policies or more aggressive pricing
- Enhancement of supply chain management
In-demand Services in the Area of CRM Analytics
Some of the core functions of CRM analytics are highlighted below:
- Data Warehousing (Data Integration and Management)
- Customer Segmentation and Analysis of Customer Behavior
- Analytics and Data mining (Marketing Campaign Analysis)
- Predictive Data Mining (Personalization and reference models for niche marketing, service applications and sales)
How is the Field of CRM Analytics Changing?
CRM analytics constantly discovers new ways of influencing or completely changing customer service, marketing spends, product research and development and sales effectiveness.
As data storage becomes more and more commoditized, there will be a reduction in the cost of cloud-based analytics and ETL tools will become easier to use. This will start to penetrate the marketplace of subject-matter-experts, and even more, the opportunity will be realized.
Top 10 most Important CRM Metrics to Track
- Customer Acquisition Cost (CAC)
- This reveals the price per lead and allows you to measure the average spend for lead generation efforts.
- Customer Lifetime Revenue (CLR)
- Also referred to as Customer Lifetime Value, this is the total projected amount of money a customer will spend during the course of their relationship with your business.
- First Response Time
- This measures the length of time it takes to respond after a customer gets in touch with your business the first time.
- Length of Sales Cycle
- This is the average period of time between when you create a prospect in your CRM platform and when that opportunity is closed.
- Percentage of Customers Who Result From Marketing
- This reveals the percentage of new business that was generated from new marketing and is an especially helpful metric for CRM analytics.
- This data can be used to determine the overall impact of your promotional efforts.
- Retention Rate
- This analyzes the percentage of customers that remain with you and the fraction that also leaves over a particular period of time.
- Return on Advertising Spending (ROAS)
- This calculates the return on your advertising budget. We do the math by dividing the generated sales by the advertising spend.
- Net Promoter Score
- Recouping the Cost of Customer Acquisition
- This indicates the length of time taken to repay the cost of customer acquisition.
- This number greatly differs by pricing model and industry.
- There are many ways to calculate margin; however, your revenue must typically exceed your operating expenses and cost of goods sold.
Benefits, Challenges, and Summary
CRM analytics can result in vastly improved and more productive customer relationships. We do this by analyzing customer service, evaluating customers and validating your user data. However, it can also result in the development of supply chain management like speedier delivery and a lower inventory burden. This will create the opportunity for more competitive pricing and lower overall costs.
Among the biggest advantages of CRM analytics, however, are its capacity to use customer analytics to produce highly effective and targeted marketing campaigns with radically high conversion rates. However, CRM analytics can be challenging and complicated. As such, to get the most out of CRM analytics, you should consider working with an experienced team of professionals with deep experience in both CRM Insights and Analytics.
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