Data Hygiene & Your Business: How Clean Data Improves the Bottom Line
What drives your decision-making?
If you work in the foodservice industry, you understand the difficulty in keeping up with such a dynamic landscape. If your organization relies on gut feelings or guesswork to make important strategic decisions, it’s likely that your operating costs and the bottom line are being negatively affected. So, what’s the secret to creating superior sales and marketing campaigns?
Clean, accurate data.
If your business is like many others, you probably have gaps, inaccuracies, duplicates, and outdated information within your internal data. Unfortunately, this “dirty data” reaches beyond just your database – it has an impact on your marketing campaigns, sales initiatives, corporate strategies, ROI measurement, and more.
Data hygiene is essential for ensuring that your organization is leveraging only the most accurate and up-to-date information. Here are just a few of the benefits of clean data:
- Improved operational efficiencies.
- Increased sales revenue.
- Greater bottom-line profitability.
- More accurate competitive analysis reports.
- Quickly determine market penetration.
- Track turnover.
- Better segmentation and source management.
While big data is commonly recognized as an important component of market intelligence, with significant industry changes taking place every day, today’s foodservice providers and operators struggle to manage and clean their data, which can make it difficult to successfully target prospects and calculate market share.
Data cleansing tools are often used to fix and improve internal and transactional data.
For example, CHD Expert’s FINDsweeper corrects a multitude of data issues, such as human error, duplications, out-of-date records, and duplications, among other inaccuracies. FINDsweeper turns your dirty data into an organizational asset by making it more consistent, accurate, current, and actionable. In addition to cleansing your data, CHD Expert will also match it against our comprehensive foodservice database and fill in information gaps.
When organizations have accurate operator-level data, they are able to examine the overall foodservice landscape or drill down into specific segments. They are also better positioned to define their market, target operators that aren’t currently buying, and perform strategic restaurant foot printing.
Are you interested in learning more about the business challenges of bad data, or are you curious about what you’re missing out on when you rely on dirty data? Click below to view our latest infographic, “What are the Challenges of Bad Data?”
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