Strategy to produce a CSV file that is useful to customers

Hello folks, I don’t know how relevant this question might be in this forum, but hope to receive some helpful inputs. What is your strategy to produce a CSV file that is useful to your customers?


Can you share a bit more about who your customers are, what they use your product for, and how they (and you!) would know if the file is useful?

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Before knowing the exact user/scenario, speaking on a high level, I prioritize flexibility for any scenario involving an export action, regardless of whether it’s a CSV or some other mechanism to export data.
Visualizing the data will be subjective to the scenario/user; hence I tended to lean towards providing a data dump via CSV. Our users were comfortable enough to take that into a more specialized app to slice and dice.
But as we moved up the ladder beyond power users, I created an Excel file template that ingested the CSV data to visualize a few insights, which I gave to select customers that needed a bit more “hand-holding.” Eventually, it gave us good data to refine a native implementation of the Excel file. The template turned out to be a good “experiment.”


I have looked at how crypto platforms export CSV files and how crypto taxes application consume CSV files and it seems to be a lot of gaps. It is very easy to dump a CSV file but it seems hard to make a good one that solves the job to be done.

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In the past I’ve used CSV files as MVPs for APIs and other data products. May be a helpful framework.You could see a full integration or app negating the need for a CSV in the long term but a CSV file is a GREAT way to test out the validity and value of the data in the short term.
Bonus: if the CSV process ends up being good enough… you may never need to build the API or the data product but you have the thinking in place anyway.

  • What might an API look like in the future? It’s a developer centric product, working backwards from this can help inform the CSV question. What are they trying to integrate or how does the wider ecosystem already work?
  • What do the users’ current Spreadsheets and flows look like? People have manual workflows everywhere. Getting a walkthrough of these processes will highlight what data they need and how it needs to look.
  • How is this data being presented, viewed and/or transformed? Tableau? Google sheets? Input to a tool? Ingested to a warehouse? Part of an ETL job? Checking out these flows can be informative.

Other specific items to think about:

  • Accuracy (decimal points)
  • Frequency of updates
  • Date / time formats (think global)
  • Granularity
  • Expected formatting for strings
  • Handling breaking changes (header names, new columns, changes to any of the above)