Maximize your CRM potential with first-class data expertise
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.
Table of contents
Data culture and data literacy: 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. This means that all departments - from sales and marketing to management - should have the same high standards when it comes to data quality. Otherwise, the weakest link in the chain will determine 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 below which data quality requirements are important and how you can use CRM accordingly.
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
Data strategy compact
How do you create a sustainably successful data strategy? These four steps will give you a good orientation.
Step 1: Objectives
First, define the goals you are pursuing with your data. Specific objectives could be 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, derive which data should be collected in customer contact and which data from the departments must be incorporated.
Step 3: Use the ERP and CRM system
Both systems manage large amounts 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 Gedys CRM software.
Step 4: Ensure data quality
Once you have implemented all the steps, it remains to maintain the data regularly - you will find specific tips on this in the following sections. They will help you to improve data quality and get the most out of your CRM system.
Advantages of sound data literacy
How does a high level of data literacy benefit your company? In short: a lot. The potential data literacy benefits range from efficiency gains to increased sales. Here are some specific examples:
- Efficiency through accuracy:
Precise and well-maintained data can be used in departments quickly and in a targeted manner. - Security in decision-making:
Robust data puts you in a position to make data-based decisions. Keyword: data focus instead of gut feeling. - Customer satisfaction through the use of customer data:
By specifically addressing the needs of your customers as determined from the data, you generate greater customer satisfaction. - Competitive advantages by predicting market trends:
High-quality data can not only be used to derive actual states, but also to create data-driven forecasts.
What are the benefits of data expertise in the departments?
In addition to the general benefits, high data quality in CRM and data literacy have specificpositive effects inthe individual specialist departments of your company.
- Marketing:
The CRM contains specific information on contact persons and their specialist areas, so that personalized campaigns are possible. Your correspondence reaches the right contact immediately. - Sales:
Via the CRM system, the sales department has insight into all important information about the customer and can thus, for example, prioritize contacts, find ideal offer prices or identify possible upsell potential. - Customer service:
Tailor-made customer service is expected today. In CRM, you can immediately see the entire history of a customer, including which products have been purchased and which tickets have been submitted. This makes it easier for service employees to respond to the individual needs of a customer. - Management:
The well-maintained database in the CRM allows advanced analyses to position the company for the future and find lucrative lines of business.
In the next chapter, you will learn how to achieve high data quality inCRM.
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 the data about your customers 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
Uniform guidelines help your departments to achieve and maintain 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 will ensure efficient and seamless data management.
Standardized data entry
The basis for smooth cross-departmental work is a uniform standard for data entry in the CRM. Consistent data also helps you to automate processes or compare them over longer periods of time.
Regular maintenance
Your customers' contact persons change and 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 do this, it is helpful to equip all relevant departments with the necessary expertise to take over data maintenance in the 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 company registers, digital business directories, LinkedIN profiles and company pages or Google Places API.
Data cleansing
Incorrect and outdated data can paralyze your internal processes. 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, such as validation, compliance checks and structuring. Please note, however, that you must comply with 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.
Advantages of CRM and AI in customer service for companies
Why are more and more companies turning to automated support solutions? The benefits range from financial aspects to productivity gains and improved customer loyalty. The most important arguments for the introduction of AI in customer service are
- Faster problem resolution without waiting time for customers thanks to chatbots
- Cost reduction through automation
- More efficient use of existing data
- Stronger customer loyalty through personalized service
- More recommendations thanks to delighted customers
- Higher sales through AI-supported upselling
Good to know: The benefits result from the individually selected AI strategy for your company.
Conclusion: Highdata 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 such as 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. In this way, you and your teams get the most out of your tech stack. This means you benefit from decisive competitive advantages in the long term.
