Previously, we learned about dashboards, which help Data Analysts fill a frequent need for the same data. Here, we will learn how Analysts deal with one-off requests for data.
What is an ad-hoc request?
An ad hoc request is a request for data or an analysis that does not need to be repeated on a weekly or daily basis. Many different departments make ad hoc requests from data analysis teams. Product might want an end-of-quarter report on the success of an initiative. Finance might need a list of users who haven't made payments in the past month. Engineering might ask for the total number of clicks on a particular button.
Case: Ad Campaign Performace
Let's examine a case study. The marketing team at your company just wrapped up their New Year Resolution ad campaign. Now, they want to know how this campaign affected sales for January. Marketing asks the analytics team to provide the total revenue from users who had clicked on one of these ads.
Making an ad hoc request
A good request should be specific. Marketing's request asked for a specific number that is easily defined. A good request should also include the context; in this case, measuring the success of January's ad campaign.
Providing the context can help analysts spot any additional data that might be helpful. Here, a good analyst might also include the total revenue for January of both this year and last year to provide context for the revenue from the ad campaign.
Finally, a good request should include a priority level and a due date. This will help the analytics team handle the many ad hoc requests that they receive.
Handling ad hoc requests
If you're managing an analytics team, ad hoc requests are tricky because they are unpredictable and they can "steal" time away from scheduled work, like A/B Tests and Dashboarding.
A good strategy for handling ad hoc requests is to use a ticketing system, like Trello, JIRA, or Asana. A ticketing system allows internal customers, like Product, Finance, or Engineering, to submit requests for ad hoc analysis.
Ticketing systems can help ensure that requests are specific and include a due data and a priority level. The data team, whether isolated. hybrid, or embedded, can then assign the tickets to an appropriate analyst.
Meta-analysis of Ad hoc requests
Once a ticketing system is in place, an analyst can track the frequency and duration of ad hoc requests and improve scheduling for future quarters.