Dirty Data: The Bane of the CRM Database
Companies have opted to use e-CRM because of its efficiency and accuracy. By using a CRM software business owners are promised excellent results and a boost in sales, but what happens when the opposite of what is expected occurs? What if you end up with a bunk of dirty data in your company’s database?
A software like Infusionsoft CRM is as accurate as the data it gathers, and the problem lies there. CRM depends on its data, the data you as business owner gathers from prospective leads and loyal customers. Data acquired by companies is ideally accurate and precise but in the real world, this kind of scenario is too good to be true. The U.S economy alone suffered a whopping 3.1 trillion dollars loss due to bad and inaccurate data. And inaccurate and invalid data has caused companies like Takata to file for bankruptcy due to tampered airbag test results which ended up in a massive recall.
What is Dirty Data?
Dirty Data, is as what the world wide web calls it, is erroneous, invalid, inaccurate and obsolete information that is entered into a company’s database. For CRM system this equates to wrong customer information such as incorrect emails and contact details of customers, incorrect spelling of names, and so on. These can all have negative impacts on the productivity of the CRM system as well the of sales of the marketing team.
Identifying Dirty Data
Here are examples of Dirty Data that can snake its way into a company’s database:
- False data – these are data intentionally entered by either humans or internet bots to damage/ undermine a business’s performance and competitiveness.
- Incorrect or Invalid data – these are information of customers entered in the wrong fields. This wrong information causes your CRM system to crash or be unable to process the data due to the incompatible formatting. Examples of these can be wrong email addresses, wrong contact information, and even wrong physical address.
- Duplicated Data – these are duplicated information about clients logged in using different names in unaffiliated websites with different accounts. These types of data can be debilitating to your CRM system because it causes confusion and can disrupt the sales funnel for prospective leads.
- Un-updated Data – these are contact information provided by customers which are no longer in use or customers who are unresponsive to your campaigns. These not only cause a waste of time in marketing strategies but it can also lead to spam reports.
- Incomplete Data – the lack of data for relevant fields in a customer’s information detail can be crippling for some campaigns since these data can be stepping stones for important marketing strategies.
How can Dirty Data impact your enterprise’s productivity?
- Dirty data leads to a higher cost of research usage and maintenance costs.
- Lowers the metrics for customer satisfaction as well as the possibility of retaining customers.
- Leads to more spam reports, wrong email deliveries and higher possibility of prospective leads opting out of purchase.
- Prolongs and the sales cycle and increases related costs for selling a product or service.
- Muddles up the distribution channel and sales of products.
- Damages the sales performance metrics as well as creates issues concerning data inaccuracy.
- Lowers the overall cost-efficiency and productivity of a business.
- Results in penalties due to the business’s inability to comply with highly regulated standards in the different industries.
- Tarnish a business’s reputation.
- Hamper revenue growth.
- Leads to bad reports, bad product designs and overall bad decisions.
The presence of dirty data in your CRM database, even just one, can have a negative impact on your business’s productivity. All the more the accumulation of dirty data in your system can result in not just monetary losses but also in loss of customer trust and your business’s reputation. So the utmost attention and care should be taken when extracting information from your customers. After all, business data can either make or unmake an enterprise.