Customer Relationship Management (CRM) data reporting and analytics provide insights into customer behaviour, preferences, and needs, helping businesses better interact with customers. This makes CRM an essential tool for tracking customer interactions.
In one study from Resco, 74% reported that CRM improved their access to customer data, while 64% said it enhanced their ability to manage customer relationships.
Let’s discuss how CRM reporting and analytics can help businesses to extract insights for decision-making.
Benefits of CRM Reporting and Analytics
One of the key benefits of CRM Reporting and Analytics is helping businesses better understand their customers. This is important for tailoring products and services to meet customer needs.
A survey from Grand View Research found that 91% of businesses with 10 or more employees use CRM software because it provides many benefits to them.
Benefits of CRM Reporting and Analytics, include:
1. Identify Customer Behaviour Patterns
Analysing customer data can provide businesses with valuable customer insights into customer preferences, purchasing habits, and trends. This information can be used to improve marketing strategies and customer engagement.
CRM reporting and analytics can help businesses monitor sales and marketing success, track customer satisfaction, and identify areas for improvement.
2. Analyse Product Performance
Businesses can use CRM data to analyse product performance. This includes sales data, customer satisfaction, and feedback.
Analysing metrics helps businesses make informed decisions about which products to keep, discontinue, or improve.
Data-driven approaches can increase sales and improve customer satisfaction and loyalty.
3. Identify Profitable Customers
Companies can use CRM data to identify high- and low-revenue customers, then create targeted marketing campaigns to retain high-revenue customers and encourage low-revenue ones to spend more.
This helps build strong relationships with all customers, increasing customer loyalty and revenue over time.
Steps by Step to Extract Insight from CRM Data
To extract CRM reports and analytics for decision-making, businesses should follow these steps:
1. Define Business Objectives
Defining business objectives is crucial before extracting any data.
First, businesses should identify their goals, such as increasing sales, reducing customer churn, or improving customer satisfaction.
Next, they should determine what data is needed to achieve these objectives, such as customer demographics, purchase history, or customer complaints.
Prioritising data analysis efforts based on relevance to goals can avoid wasting resources, and ensure actionable insights that can inform decisions.
2. Identify Data Sources
Once the business objectives have been defined, companies should identify the data sources that contain the required information.
This may include CRM systems, customer databases, and other data sources. It is important to consider the quality of the data sources and the reliability of the data they provide.
3. Extract Data
After the data sources are identified, extract the data using tools such as CRM tools, SQL queries or reporting tools.
Verify and cross-check data sources to ensure accuracy. Ensure both data quality and completeness. Address any missing data or outliers that could impact analysis.
Document the data extraction process, including tools and methods used, for replication and future reference.
4. Clean and Transform Data
Cleaning and transforming data is an important step in preparing for analysis. Extracted data may contain errors or inconsistencies that need to be addressed in order to draw accurate conclusions.
One way to clean data is by using data cleaning and transformation tools, which can automate the process of identifying and correcting errors. These tools can help with tasks such as filling in missing values, eliminating duplicates, and transforming variables to make them more suitable for analysis.
By taking the time to properly clean and transform data, analysts can ensure that the results of their analysis are reliable and precise.
5. Analyse the data
During data analysis, carefully examine the data to understand its structure, format, and content.
Use analytical tools, such as data visualisation tools, predictive analytics tools, and other analytical tools to gain further insight into the data.
Look for patterns, trends, and insights that can inform decision-making. This can include identifying correlations, outliers, and anomalies, and exploring statistical models.
This step is crucial as it allows users to gain a deeper understanding of the data and make informed decisions based on data-driven decision-making.
6. Present the insights
When presenting insights gained from analysis, it is important to communicate in a way that is easily understandable.
One way to achieve this is by using data visualisation tools or other reporting tools that are tailored to the audience’s needs. When selecting the appropriate tool, it is important to consider the data being presented.
Use a line chart to show trends over time and a scatter plot to display the relationship between two variables.
Choose a tool that is user-friendly and easy to understand to present insights effectively and clearly.
Wrapping Up
CRM Reporting and Analytics provide important information about customer behaviour, preferences, and needs.
The data is essential for making informed decisions about customer interactions, identifying patterns of behaviour, and predicting future trends.
Using CRM Reporting and Analytics helps businesses to make better decisions, which ultimately enables them to serve their customers more effectively.
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