Challenge with CRM Contacts Quality
People often talk how badly customer data quality is taken care of in CRM systems. This is an issue that raises daily discussions in marketing, sales and customer support. However, hardly anyone takes this as a challenge to actually improve data quality. Sales is responsible simply for their own key accounts and they know their own customers very well. Most of the time sales is in the driver´s seat when it comes to customer data, so if they don´t feel the need to improve data quality, nothing will happen.
If you have a database around 100,000 customers, it is likely that over 20% of the customers will change their position or company within the year. This is already more than 20 000 contacts that should be updated to the database in one year. So, how to keep up with the customer data?
GDPR brings another set of challenges to customer data quality management. Canada started with the tighter legislations in data protection few years back and now the European Union legislation GDPR is following. No doubt this is getting the attention of companies as you might get up to 4% penalty of the world wide turnover, if you do not comply with the law. Many companies are still baffled about what to do. What kind of privacy measures they need to take in order to keep data secure, how to acquire opt-in from the consumers etc. etc.? Many companies have to still tackle even the more simple issues such as sending newsletters to an existing database.
AI, machine learning and data analytics are enabling more sophisticated analysis of the customer base, creation of new offerings and the enriching of data. Without having a good basic processes of data governance and data quality in place, it will be impossible to move from pure manual data processes to more sophisticated and intelligent ways to utilize data.
Systematic customer data management processes are still new or immature in many companies. Data is often just left alone to rotten. Good governance is missing and it is not clear who is owns and what part of the data, , what are the minimum data requirements or what data should be cleaned from the systems. Or, what processes are automated and what are manual or how to enrich data. Often, data is just collected without a clear idea of what to do with it.
Data ownership is a major issue as full customer information is often a collection of pieces of information including customer interests, sales opportunities, influencers connected to the customers etc. It is hard to find a single owner or a team to take full responsibility for the data.
- Quality department is usually not interested in the customer data quality. It is not part of their job description. Furthermore, they are too far away from the customer activities.
- MasterData teams have long taken care of the billing addresses and VAT codes, but not individual contacts.
- Marketing organization would like to have good data quality as it builds up the basis for all digital marketing activities but they usually lack the sufficient mandate to do this.
- In B2B, account owners have clear responsibility for named customers. However, most of the time companies have much wide influencer group that sales is not actively managing.
In the past, marketing organizations have been able to manage marketing campaigns and emailings through various excel sheets or simple databases. Nowadays when targeted marketing and personalization is becoming a daily routine, it is hard to manage them with outdated tools. Integrations of the web content management and CRM systems also often gets too complicated. Marketing automation is providing several means to enrich and improve data quality. At the same time it is hard to start marketing automation, if the basis of the database is scattered and of bad quality.
Managing customer level information is challenging, as one person might have several email addresses, contacts might include various spelling mistakes and people change their roles more frequently than they used to do five years ago.
Treatment for Bad Data Quality in CRM
- First, the top management should realize that managing customer data systematically will bring more cash flow than its maintenance will cost. Support from top down is crucial in order to make necessary process changes and to allocate necessary resources to manage data. In order to see and understand benefits of the good data quality it is good that management have some objectives what should be achieved by improved data quality.
- There should be one person owning the process and with sufficient mandate to set up good processes and governance. This person could be for example cross divisional sales head, Chief Digital Officer or Chief Data Officer. This role needs to be clear in the organization.
- Responsibility for the data quality needs to go down to each sales person, marketing, customer support etc. Everybody needs to know what is expected from them as relates to the customer data quality. Additionally, MasterData team needs further expertise and focus on CRM data and processes.
- Then it is all about setting up maintenance processes. For example, who has full administrative rights to handle data, what are minimum data requirements and mandatory data fields, how data quality and security is monitored, how search results will appear to different user groups.
- After data is relatively in good shape and clear processes are establish, then it is possible to move forward with data enrichment. Possibilities for enriching data are endless as it is constantly easier to merge various databases. Furthermore machine learning and AI will provide various ways to enrich and analyze data in the future.
Have you experienced similar challenges? Improving data quality is about building up digital culture and love towards data. Each of us, should feel passionate about our customers. Let´s make our future business better and give a treatment to the bad data quality disease. You can read more about the digital culture from my blog post.