Curtailing Dirty Data
Today, 67 percent of businesses rely on CRM data to segment and target customers and 64.8 percent of sales reps’ time is spent on non-revenue generated activities.
Another recent survey found that 40 percent of sales reps are looking for somebody to call and 24 percent of sales managers cited lead quantity and quality are one of the greater challenges in prospecting clients.
Yet, dirty data is still an obstacle for sales teams as inaccurate data costs 546 hours a year per full-time sales rep, 27.3 percent of sales reps’ time.
Dirty Data can Arise From Many Areas:
Duplicates of customer profiles or leads can hurt a company’s reputation and cause potential customers to ask off lists. It’s estimated that duplicate data alone can add up to $20-$100 per record.
Inflated data storage fees. When there are duplicate names and addresses, when old names aren’t removed, when lists contain errors, they can become inflated making companies pay ever-increasing storage fees.
Salespeople waste time contacting worthless “leads” that are on dirty lists. This is time that could be spent contacting hot leads.
IT personnel waste man hours. IT personnel can spend hours and weeks trying to clean up dirty lists. Since most IT people don’t specialize in list generation and maintenance, the wasted hours can quickly add up.
False statistics. Companies live and die by statistics such as number of hot leads, number of mailings to their customer list, number of emails sent weekly, etc. These stats and more tell executives if they are having an impact on their public and help predict future sales. Dirty lists skew statistical results, throwing confusion into a company.
Incorrect market research. A survey done on “customers” or “leads” generated by a dirty list may yield inaccurate information.
False records for investors. When companies are invested in or acquired, company lists play a vital role. If contact records of leads, sales, customers, and employees are not accurate, these paint a false picture which can, in turn, scare investors off or invite legal problems.
The bottom line is it doesn’t matter how creative or aggressive your B2B sales campaigns are if they aren’t built on quality, clean lists, then they won’t perform.
It is recommended that a company’s CRM be scrubbed with basic internal processes on a weekly basis to assure all leads, customer info and sales data is accurate. Just as people use a doctor to help fix a health problem, it is smart to use a data specialist to fix a company’s lists. Normally, in-house professionals do not have the expertise, tools, and data assets at their disposal that a reputable third-party data intelligence company has.
Thus, B2B companies should still be careful when searching for a third-party data intelligence company as they won’t be able to clean businesses’ data if their house isn’t in order.
Top 3 Questions to Ask a Data Company to Determine if They Have Clean Data:
1. How many U.S contacts do you have in your database?
a. Many data companies will tell you they have 100 million-plus records. This is a bad sign with 150 million people employed in the US as no data company will have two-thirds of all U.S workers.
b. A list of this size is only possible if many of their records are duplicates or outdated dirty data.
2. Can you exclude contacts or companies that we already have?
a. If they can’t do this, they aren’t a real data company and will have poor quality data.
3. Can you send me a sample?
a. Check the sample for accuracy.
