Data quality is necessary for success in the digital era of marketing and sales. Your data quality plays a tremendous role in your ability to target and attract the right business leads.
The following is a look at the importance of data quality for your sales pipeline and your overarching strategy.
Data and Artificial Intelligence
Salesforce and other top sales prospecting software programs rely on quality, accurate data for delivering useful analytics reports. Analytics and artificial intelligence are only as powerful as the quality of the data inputs they rely on.
The best predictor of prospecting success is a data-driven view of your most profitable current customers. Analytics paint the picture of the demographic, geographic, firmographic, and behavioral traits that help you win opportunities and achieve long-term profits.
If you have incomplete or inaccurate data, it is difficult for your reporting tools to offer accurate outputs. You might, for instance, get misleading characteristics about your ideal customers.
Clarity or Cloudiness
Generally, the more data you collect, the better. However, you must ask whether your data quality contributes to clarity or causes cloudiness in assessing targeting and communication strategies.
There are numerous causes of poor data quality, including incomplete profiles, inaccuracies, and duplication. As you build your buyer personas, data quality helps you present a more clear picture of the target. This clarity assists sales reps in understanding the needs and concerns of prospects in order to optimize messaging. In contrast, cloudy data makes it more difficult to really communicate in a way that drives conversions.
Efficient Communication
Data quality is important to communication efficiency as well. You can’t communicate with the right person if you have incorrect profile data. Imagine calling “Jon” and asking for “Jan.” Even if Jon stays on the phone long enough to realize he is the actual target of the call, you’ve lost credibility as far as suggesting you have his interests in mind.
Similarly, inaccurate or missing addresses, emails, or phone numbers get in the way of effective communication. Nothing frustrates sales reps more than calling on disconnected or incorrect phone numbers. Bad email addresses clog your database and contribute to undeliverable emails. At the extreme, bad emails could result in the setting of spam detectors with an email provider and potentially losing your delivery privileges.
Fiscal Management
There are costs involved with database management. Over time, it is more expensive to capture and hold bad data than it is to maintain clean data. This point is especially true if you don’t have preventative measures in place, and instead rely on expensive clean-up processes when your database is plagued with massive problems.
Conclusion
These are some of the most compelling examples of why data quality matters for your sales organization. Given its importance, it makes sense to do everything you can to capture and use accurate and complete data.
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