The game of marketing is becoming more complex, personalized and you should use all the things at your disposal in order to get ahead. Wasting money can be annoying especially if it can be prevented.

A very simple way of becoming better at your marketing is simply by using your existing data and making meaningful small or big changes in the way you do marketing. For achieving optimal results, you need to rely on data quality.

1) Check Your Data

The most elementary step in getting clean data is to validate the data manually or systemically according to simple business rules. For mailing or email lists at least run it through a scrubbing program which will catch obvious errors (such as “srteet” for “street”). You may want to consider using a data validation service for the checking. Many companies such as Dun & Bradstreet, WinPure and Trillium offer both software and services and can advise you on which best suits your needs.

2) Set Data Standards

Increased data structure and decreased variation results in much higher data quality. Set standards (such as “St” for street) and create internal process reviews to enforce them. Companies should establish rules for how company names are entered to a system. For instance, is IBM entered as “IBM” or “International Business Machines”? Is Microsoft entered as “Microsoft” or “Microsoft Corp” or “Microsoft Corporation”? The way your CRM system collects data can also help keep it clean. For example, numeric fields should be checked for the reasonableness of the entries (possibly using number ranges) and not permit alpha characters. Also instead of having the user enter fields with a limited number of values, consider using drop down menus or radio buttons in order to improve data consistency.

3) Get Correct Email Addresses at the Source

These are easy to capture from emails and other sources. Pay special attention to email addresses entered on forms by the prospect. It's often a good idea to ask for the email address twice.

4) Periodically Cross-Check Entries Looking for Duplicates

Duplicate contact records will usually possess more than a single field of duplicate data. Use the search function on your database to find entries which match in most or all but one field and subject them to manual scrutiny. Certain fields, such as email address, can be used to quickly identify duplicate records and then consolidate the records or discard one of the entries.

5) Monitor Returned Mail and Bounced Emails

Failures such as bounced emails and returned mail usually mean a failure to sufficiently clean your database. Monitor the number of returns or bounces and use that as a metric to understand how effective your data cleaning procedures are. Also be sure to correct the information in your database as timely as possible. That can include removing it completely if you can’t fix the error.

Thanks to crmsearch.com