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14 Reasons Prospecting Data Can Fail - ECI Software Solutions
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7. Unknown nuances – Every data source has its nuances due to the way data is generated, collected, enriched, and maintained. Ask the vendor to explain how these activities happen. For example, you might assume poor phone number validity, but upon asking the vendor, you may learn that phone numbers are freshly appended each month and are therefore trustworthy. In this scenario, unless you asked, you may have sworn off using the valuable phone numbers. “Each of these measurements should be audited and trended.” 9. Data mismatches – It’s rare to invest in data that is a total mismatch to the investor, but data will always have some areas in which it doesn’t meet your business needs. Be sure to understand where these areas are and explain them to the data users. For example, you might sell body sculpting machines using a list of businesses classified as health spas, but not all health spas offer a service requiring such a machine. A salesperson may get discouraged if they call too many spas that have no use for a sculpting machine.
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6. Skeletons in the closet – Employees at any level might have a few secrets that could be exposed by a new data set. These might include failure to call on key accounts, losing major customers, or misrepresenting the current situation of sales or marketing efforts. Be sure you ask enough questions of any salesperson who strongly resists your new initiative. “Every data source has its nuances due to the way data is generated, collected, enriched, and maintained.” 8. Not accounting for data quality – Every data source has imperfections. Ask about the three key quality measurements: 1) Freshness (how long ago the data was updated), 2) Completeness (how much of the subject matter the data covers), and 3) Accuracy (how well the data represents the subject it covers). Each of these measurements should be audited and trended.