When was the last time you did a proper "spring cleaning" of your CRM ? Was it a long time ago? Or are you conscientious and schedule regular CRM update tasks to be done? Even then, you will certainly not look forward to these deadlines with joy. Cleaning up CRM data is not one of the most popular tasks for good reason. Not only is there often a lack of clear responsibilities between departments regarding who should carry out updates - what makes matters worse is that in many cases the maintenance is even carried out manually .
In this article, we would like to break the habit of updating CRM data manually for all of our readers who feel addressed in the above paragraph. Because in 2021, such tasks should be a thing of the past and have been completely converted to automated processes. Today, we will show you what problems you expose your CRM to with manual updates and how you can initiate them better and more securely instead. So let's get started right away:
60 minutes of wasted working time
According to a 2016 HubSpot study, around 72% of lebanon whatsapp data salespeople spent a full hour or more entering data into their CRM. This includes not only adding new contact details, but also importing new or more current information from other systems. Even though five years have passed since then, this number is unlikely to be much lower today.
Not only is valuable time lost for actual sales activities, but at the same time, overall job satisfaction also decreases , but even worse, satisfaction with the quality of the CRM itself also suffers. Finally, continuous manual data entry and manual import from external databases also pose a risk to the quality, validity and integrity of the data as a whole.
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The most typical errors in manual data entry
But what are the immediate dangers of manually updating data between different systems? Broadly speaking, risks can be divided into two areas: human error and system error .
On the human error side, there is the unconscious or unintentional overwriting of important data in the old data set. Especially when importing larger data sets after a long period of time, there may be many differences in the data sets. These are difficult to resolve manually. In addition, versioning is not always available, so older data sets cannot be restored if they are overwritten. On the other hand , damage, accidental deletion and other forms of human error represent a significant but equally avoidable risk.