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Are You Missing Data Hidden in Plain Sight?

By August 10, 2020 No Comments

Finding relevant data and effectively putting it to work within your company can feel like a massive challenge. Data sources, however, are abundant in many organizations. It’s important to get creative, however, in thinking about potential sources. Let’s look at where you can find valuable business data hiding in plain sight.

Looking at What Customers Have Said

Customers are a nearly endless source of useful data. You can use the people who buy your goods and services to source key data from:

  • Customer service inquiries
  • Sales data
  • Social media feeds
  • Website traffic logs

What’s great about customer-centric data is that it often can be used to draw a line from one bit of information to another. For example, using tracking cookies on your website can enable you to follow the progress a visitor makes through the sales funnel. You can watch how someone engages with a share on your Twitter feed to visit the website. That visit can then point to when they sign up for a newsletter, make a purchase, or download educational resources.

Publicly Available Data

Your tax dollars, in particular, pay to produce an ample amount of data. It’s available from sources such as the World Health OrganizationBureau of Economic Analysis, and European Space Agency. Yes, you’ll need to do some picking through the pile to find data sets that match your needs, but you also won’t be stuck dealing with licensing and usage restrictions.

There are also plenty of interesting publicly available data sources from private entities. Anyone who doesn’t have a Kaggle account, for example, needs to stop reading now and sign up. You’ll also find data in some odd places, such as the code-centric repository GitHub. Don’t be afraid to Google a topic as well.

Internal Data

Just about everything a company does generates bits of data. Suppose, for example, you want to figure out why personnel retention is problematic at your business. You should already have a database that includes data from the hiring and exit processes. There might be a trend developing in the forms filled out during exit interviews that shows employees leave because they lack opportunities for advancement. You can then formulate strategies for mitigating these concerns.

Notably, it’s important to start converting this sort of information into data. Don’t just let it languish on shelves at the off chance you’ll need it to defend against a lawsuit someday. Develop a process for converting entrance and exit information immediately into data upon receipt.

Required Reports

Reporting requirements, especially for publicly traded securities, have caused the generation of a massive amount of data. You can find a lot of numerical data at sites like Financial Modeling Prep and Quandl. It’s also possible to start looking at linguistic patterns in the written reports that are available from sources like the SEC.

Metadata

The data about your data is a source in its own right. Don’t be afraid to look past the simple numbers in the columns and dig into the descriptive elements of the data. If you’re going through your firm’s customer service data, you can look at relationships that arise from things like:

  • Time sequences
  • Person-to-person networks
  • Geography
  • Demographics

Metrics Produced from Your Data

Another approach is to use data to build new data. Suppose you have customer survey data available for each salesperson within your company. It ought to be possible to weight the different factors that drive success and profit. This information can then be used to create an index. Once each salesperson’s collection of data is compiled, you can then quantify their performance through a simple index that rates their work. Rather than sorting through 20 different data points, you can go straight to the index to start the assessment process.

Conclusion

Plenty of data is hiding in plain sight. It’s important to think about the different ways that data can be acquired and produced using these less obvious methods. With a commitment to finding data sources, you’ll be able to develop insights by working with information you might have previously overlooked.

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Scottie Todd

Scottie Todd

Digital Marketing Assistant

"Level 4 marketing wizard on a quest for data insights one blog post at a time."