Magazine article CRM Magazine

Four Steps to Improve CRM Data Quality

Magazine article CRM Magazine

Four Steps to Improve CRM Data Quality

Article excerpt

Your CRM data is probably one of your company's most valuable assets. But, how good is your data really? The sobering truth is that at least 25 percent of most companies' data is probably inaccurate, according to industry analyst Gartner.

And, how much is all that bad data costing you? Consider the "1-10-100 Rule" which posits that it takes $1 to verify the accuracy of a record at point-of-entry, $10 to clean it in batch form, and $100 per record if nothing is done (which includes the ultimate costs associated with undeliverable shipments, low customer retention, and inefficient CRM initiatives). Simply put--it'll cost you more in the long run to not have a data quality solution in place to verify, cleanse, and guarantee you have valid customer contact information.

With this in mind, here are four steps to improve the quality of your CRM data.

1. CHECK DATA AS IT ENTERS THE SYSTEM

The first line of defense for improving CRM data and saving money is to employ a "data quality firewall" at the point-of-entry to immediately verify the accuracy of information as it comes in through shopping carts, Web forms, or calls into a call center. If a potential customer or your own data entry personnel submits invalid contact information, a real-time data verification solution can be applied to prevent bad data from entering your database in the first place.

"Garbage in, garbage out" may be a cliche, but that doesn't mean it is any less true. Verifying and correcting contact data at the point-of-entry will save you time and money, and those benefits can't be ignored. The end result is a cleaner, more accurate database of customers and prospects--one that will fuel better response rates, enhance analytics, and improve customer satisfaction.

2. FILL IN THE GAPS--ADD MISSING DATA

Even though most CRMs have validations to check for mandatory data fields, it's not always easy to ensure a value for every field at the time a record is generated. For instance, if your contact source is a tradeshow list of attendees with only contact names, job titles, and phone numbers, it has very little value if you plan an email campaign or direct mail follow up. These gaps in data can adversely affect lead generation and revenue potential--and prevent you from gaining a holistic view of your customer. A periodic data append effort can add missing information to your records including verified street addresses, email addresses, phone numbers, names, and other key demographics--helping make every record as complete as possible. …

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