Customer Data in Excel? You Need a Proper Database for Your CRM

21 Oct 2019

Creating an Excel list for your customer data may sound like a good idea. It's a program that many people are used to, and a basic CRM tool can be created in no time. However, as the number of records grows and many changes are made to the data, this solution quickly reaches its limits. Mapping interactional information or running analyses will cause your Excel list to burst at the seams. Using a proper database is therefore a much better and more profitable solution. Why is Excel no use as a CRM tool? We have 10 reasons why.

Have you read our article on planning marketing campaigns in Excel? In this article, our protagonist was tasked with creating a customer list in Excel and entering every interaction with customers and prospects in this list. Unsurprisingly, he failed. This article is a must-read. 

Let’s turn our attention back to the topic of CRM and Excel. Most companies use some form of tool or software. However, there are those that choose not to bother with this, and instead use Excel. Then there is the fact that data is often located in different silos with no interface between them. As a result, there is no flow of data. When Marketing or Sales teams retrieve information from different silos, it inevitably ends up in Excel, where it is in turn manually cleaned and prepared for campaigns. 

Those who absolutely must manage their customer data in Excel can still do so. There are countless templates available to download online. However, we advise against this, as it will be of no benefit in the long run. Quite the opposite, in fact. It prevents the flow of data between departments as well as the ability to make good decisions based on available data. 

There are a number of reasons for this.

1. Excel is not a database 

Excel has always been and still is a spreadsheet program, not a database. With a database, you can retrieve data using specific, precise SQL queries. Excel also offers a query function, but it cannot match SQL in this respect. Databases also precisely define what may and may not be input in a field. When something is defined as a decimal separator, only a number may appear after it – nothing else. This ensures a high level of data integrity. 

2. Deleting data (accidentally) 

It’s very easy to delete a record in Excel. Select – delete. All of the information and records linked with this entry, such as invoices and ordered spare parts, are also irretrievably lost. Databases don’t allow this to happen. They query the user’s action and inform them that this will lead to information being lost. 

3. Collaborative working 

Shared working in an Excel file makes about as much sense as having people vacuuming in pairs. It simply isn’t the most efficient way of doing things. 

4. All data is available to all users immediately 

When data is in a database, it can be made accessible to users through an interface. They see exactly the data that they need for their daily business. A database allows control not only of the access rights, but also the permissions for editing data. 

5. Complex queries 

Try entering a query such as “All customers who ordered spare part XY in the last year” in Excel. You won’t get very far. With databases and SQL, the process for handling queries is much better and faster. 

Do you need a new CRM? Take the test

Do you need a new CRM? Take the test

We’ve put together a questionnaire for you. Download it and take our free self-test.


6. Keeping data current 

Databases can be connected through interfaces. This is exactly what parcel service provider DPD did. The Salesforce CRM system is connected via API to the Dun & Bradstreet database, from which it retrieves the current data. Company relocations, new phone numbers, new management, etc. – all of this information flows directly into DPD’s CRM system through live updates. This ensures that the data is always up-to-date. 

7. Access to data 

Do you want to give all users unlimited access to all of your data? That’s what you’re doing when you manage customer data in Excel. It’s a question of when, not if someone accidentally deletes or messes something up. In databases you assign rights of use as you see fit. Everyone therefore only has access to the information that they need for their work. Every company has confidential data. Storing it in a publicly accessible Excel list is not a good idea. There may also be privacy issues. 

8. Data is not available live to sales representatives 

When a DPD sales representative visits a new or existing customer, they have access to all data available for this company in the CRM system. This includes risk information. When a sale is made, the sales representative checks the customer’s financial situation live. If the result is good, the sales representative is authorised to approve the deal there and then. If not, the deal is submitted to the Finance department for a detailed review. 

Excel does not support on-site customer registration. DPD has also solved this problem. We previously discussed the interface link to the CRM system. See 

9. Complete data 

In databases you can define mandatory fields. Incomplete entry of companies in the CRM system is thus not possible. This is extremely important. For effective marketing and sales you need a complete company profile. This makes it possible to identify the ideal customer. 

10. Smart Data Analytics 

Smart Analytics is a highly effective method for gaining intelligent insights from large volumes of data. Messe Frankfurt uses Smart Data Analytics to generate high-quality, qualified leads for its Sales team. As we said earlier, analyses require large volumes of data. Both internal and external data is involved. Merging and matching this data in Excel is not practicable. It works far better in a database. 

Your journey to perfect Master Data 

Do you manage your data in Excel? Do you have difficulty keeping data current and correct? Do you have duplicates in your data? 

Then we have the perfect whitepaper for you – our free guide “Modern Data Management: Three Steps to Perfect Master Data”. It describes the execution of a data management project in detail. 

Three steps to perfect Master Data

Three steps to perfect Master Data