Last week we took a look at some best practices for mobile data collection at the input level.

This week, we turn our attention to best practices at the output level. Following the critical input stage, data is often transferred to corporate departments or regional marketing teams, who in turn proceed with the output—that is, drawing insights and making merchandising decisions based on data analysis.

Of course, there are many ways to optimize this crucial decision-making stage through intelligent data publishing, exporting, aggregating and filtering methods. The common practice of using spreadsheetsis proving to be a more and more laborious and imprecise way to manage the output stage of mobile data collection.  So what does a more sophisticated mobile data collection system look like at the output level?

For one thing, the right tool logically structures and aggregates disparate field data from different locations and input administrators so all the particulars needed for analysis are in one place. Graphical representation of reports, historical data extracts and other data of interest is easy to access and does not require knowledge of complicated formulas or code. Elegant infographics, charts and graphs should be at your fingertips, to make presenting data analysis to colleagues, executives or board members seamless. With the right mobile data collection tool, the time consuming practice of scrambling for and collating input is over; a robust system offers a smooth, productive and pain-free path to actionable insights.

And when you are looking for a specific detail in the data, a smart filtering system is a must. Improved mobile data collection software should provide a simple way to filter by location, date, survey response, photo, employee and more. In this way, customization is of utmost importance across the tool’s functionality, both at the input level and at the output level. Retail teams work differently—even within the same company—and the right system should embrace these differences, allowing managers in charge of output the opportunity to analyze data instinctually instead of being forced to adhere to a method of standardization.

Here at GoSpotCheck, we wholeheartedly embrace these best practices at the output level. That way, we can bring you the mobile data collection software best suited for your company, your unique working style and today’s advancements in retail operations.

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