How can you avoid CRM failure due to poor data quality?

1 What went wrong?

The case study involves a large insurance company that implemented a CRM system to improve its customer service and sales performance. However, the system soon became a source of problems, as the data was inaccurate, incomplete, and inconsistent. For example, some customers had multiple records with different contact details, some had outdated information, and some had no records at all. This resulted in poor communication, missed appointments, and lost sales.

2 What were the consequences?

The CRM failure had a negative impact on the company's reputation, revenue, and customer loyalty. The company received many complaints from customers who felt ignored, misled, or harassed by the CRM system. Some customers switched to competitors, while others reduced their purchases or canceled their policies. The company also lost potential customers who were turned off by the poor data quality and service. The CRM failure cost the company millions of dollars in lost revenue and customer retention.

3 What was the root cause?

The root cause of the CRM failure was the lack of data governance and quality management. The company did not have a clear strategy, policy, or process for collecting, storing, updating, and using customer data. The data was entered manually by different staff members, without any validation, standardization, or verification. The data was also stored in multiple systems, without any integration or synchronization. The data quality was never monitored, measured, or improved.

4 How can you prevent it?

To prevent CRM failure due to poor data quality, you need to implement a data governance framework that defines the roles, responsibilities, and rules for managing customer data. You also need to establish a data quality management system that ensures the data is accurate, complete, consistent, and relevant. This involves using data quality tools and techniques, such as data cleansing, deduplication, enrichment, and validation. You also need to integrate and synchronize your data sources, so that you have a single view of the customer.

5 How can you fix it?

If you already have a CRM system that suffers from poor data quality, you need to take action to fix it as soon as possible. You need to audit your data and identify the sources, types, and extent of the errors. You need to prioritize the data issues and address the most critical ones first. You need to clean, update, and enrich your data, using data quality tools and services. You need to implement data quality controls and checks, to prevent new errors from entering the system. You need to monitor and measure your data quality, and track the improvements and benefits.

6 How can you benefit from it?

By improving your data quality, you can benefit from a more effective and efficient CRM system that helps you achieve your business goals. You can improve your customer service and satisfaction, by communicating with your customers in a timely, relevant, and personalized way. You can increase your sales and revenue, by identifying and targeting the most profitable and loyal customers. You can reduce your costs and risks, by avoiding errors, duplicates, and fraud. You can gain a competitive edge, by leveraging your data as a strategic asset.