Maximize your CRM potential with first-class data expertise

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The prosperity of the 20th century was based on natural resources. In the digital age, data treasures have taken their place. The ability to structure, analyze and use data is becoming a decisive competitive advantage – from the service sector to production.

The technical term for this is data literacy. Find out here which aspects data literacy covers, how you can promote data literacy in your company and how the CRM system ensures data quality.

Expert:
Philip Enders, Area Sales Manager
GEDYS IntraWare GmbH

Data culture and data competence: two success factors for your company

The basis for creating value from data is the data culture anchored in the company. It is crucial to achieve a common understanding of the importance of data . All departments – from sales and marketing to management – should have the same high standards of data quality. Otherwise, the weakest link in the chain determines how efficiently and successfully other departments can work with the data.

A concrete example: the more accurately and conscientiously customer service maintains the data, the more valuable information is available to sales – for example, for acquiring new customers. You can find out which data quality requirements are important and how to use the CRM accordingly below.

A data strategy follows from the data culture: the corporate objective of how data should be used to achieve business goals. The data strategy in turn requires a correspondingly high level of data expertise among employees, and not just in positions with a specific connection to data management such as data scientists. On the contrary, data literacy is important in all departments if data is to be used profitably throughout the company.

Core competencies are:

• Identification of relevant data sources
• Correct data acquisition
• Ability to read data
• Targeted data use and data interpretation

Data strategy compact

How do you create a sustainably successful data strategy? These four steps will give you a good orientation.

Step 1: Goal setting

First define the goals you are pursuing with your data. Specific targets could include improving customer satisfaction or increasing productivity in the departments.

Step 2: Identify relevant data

Next, determine which data is relevant to your goals. From this you derive which data should be collected in customer contact and which data from the departments must be included.

Step 3: Use ERP and CRM system

Both systems manage large volumes of data that you can use and evaluate for yourself. If you have not yet integrated a CRM system, choose a technically powerful solution such as the GEDYS IntraWare CRM software.

Step 4: Ensure data quality

Once you have implemented all the steps, all that remains is to maintain the data regularly – you will find specific tips on this in the following sections. They help you to improve data quality and make optimum use of your CRM system.

What are the benefits of data competence in the departments?

In addition to the general benefits, high data quality in CRM and data literacy have specific positive effects in the individual specialist departments of your company.

• Marketing:
  The CRM contains specific information on contact persons and their areas of expertise so that personalized campaigns are possible. Your letters reach the right contact immediately.
• Distribution:
  Via the CRM system, the sales department has access to all important information about the customer and can, for example, prioritize contacts, find ideal offer prices or identify possible upsell potential.
• Customer service:
  Tailor-made customer service is expected today. In the CRM, you can immediately see the entire history of a customer, including which products have been purchased and which tickets have been set. This makes it easier for service employees to respond to the individual needs of a customer.
• Management:
  The well-maintained database in CRM allows advanced analyses to position the company for the future and identify lucrative business areas.

In the next chapter, you will learn how to achieve high data quality in CRM.

Data quality through CRM use right from the start

The use of a CRM system alone generates a valuable treasure trove of data, because it is the place where all your customer data comes together. A logical structure helps you to improve data quality in CRM. The following best practices will make your data easier to use.

Establish guidelines

Standardized guidelines support your departments in achieving and maintaining high data quality. Don’t just take internal standards into account, but also ensure that legal requirements are met (keyword: GDPR).

Clarify responsibilities

In general, it makes sense for all departments to have the necessary data expertise to operate the CRM. At the same time, it is advisable to assign fixed responsibilities. This ensures efficient and seamless data management.

Standardized data entry

The basis for smooth cross-departmental work is a uniform standard for data collection in CRM. Consistent data also helps you to automate processes or compare them over longer periods of time.

Regular care

Your customers’ contacts change, product requirements are subject to constant adjustments. It is advisable to maintain data regularly and establish routines so that changed data is updated immediately. To this end, it is helpful to equip all relevant departments with the necessary expertise to take over data maintenance in CRM.

There’s always room for improvement: 4 tips for optimizing data quality

Data validation

It is advisable to introduce mechanisms for data validation. An efficient solution is automatic data validation tools such as SNP Validate, which you can use to compare the existing data with (publicly accessible) data sources such as business registers, digital business directories, LinkedIN profiles and company pages or Google Places API.

Data cleansing

Incorrect and outdated data can paralyze your internal processes. Therefore, encourage departments to regularly delete outdated data or replace it with new data

Automation

Modern AI tools in particular make it possible to automate many of the steps involved in data maintenance – for example validation, conformity checks and structuring. Please note, however, that you must comply with the applicable data protection regulations.

Feedback

Encourage your employees to report quality problems. Last but not least, feedback from third parties, such as suppliers, partners or customers, can also help to continuously improve data quality in CRM.

Conclusion: High data competence and data quality can be achieved with the help of training and the right CRM strategy

Whether marketing, sales or management: it is clear that data competence and high data quality are an advantage everywhere. With a CRM system like GEDYS IntraWare, you create the best conditions for this. Regular training, intelligent data management, standardized procedures and automated processes with AI support help you to continuously improve data quality. This way, you and your teams get the most out of your tech stack. This means that you benefit from decisive competitive advantages in the long term.

FAQ – Frequently asked questions

What is Data Literacy?

Data literacy stands for data competence – the ability to manage, analyze and interpret data. In general, the
Data competence in companies must be high in order to be able to use data efficiently.

Why is Data Literacy important?

Data literacy is important because (customer) data is one of a company’s greatest assets in the digital age. A high level of data competence ensures that high-quality data is available in the company and can be used as required – for example for personalized offers in sales.

How to achive Data Litercay?

By providing internal and external training for employees and by appointing persons responsible for ensuring compliance with guidelines and standards for data collection within a company.