Build a dataset to calculate totals, averages, and conversion rates using your own data. Explore how these metrics have been changing over time and set up an ongoing sync to a google sheet to share with other teams.
- Make faster decisions by pulling any KPI within minutes
- Always have up-to-date numbers where you need them using automated Google Sheet syncs
How to define a dataset (cohort activity) [more info]
Understanding your dataset
- What is activity occurrence? [more info]
- What is unique identifier?
- What is revenue impact?
- What is the record count?
- What are the summary metrics?
Adding more features to your dataset
- Add customer attributes to your dataset [more info]
- (later) Add features from another activity to your dataset [more info]
Adding computations to your dataset
- What are computed columns? [more info]
- Adding a label for “First-time” vs “Recurring” based on Activity Occurrence.
- When to use First vs All [more info]
Create a dataset that includes every time a customer did a specific activity (ideally an activity that generates revenue for your company).
- Did you choose ALL or FIRST?
- How many times did that activity happen overall?
- What is the timestamp of the most recent time someone did that activity?
- Now add another column that labels when someone is a FIRST TIME vs RECURRING Visitor?
Computing Counts and Averages
- Understanding counts by activity feature
- Refresher: How Group By tabs relate to the parent tab [more info]
- How to add a group by tab [more info]
- Using column shortcut to add a group by tab for a feature [more info]
- Auto-computed metrics in a group by tab
- Computing additional metrics to Group By tabs [more info]
- Averages, Median, Percentile, etc
Metrics over Time
- Understanding counts over time [more info]
- Using column shortcuts to create a time-based group by tab [more info]
- Using plots to visualize data [more info]
- Saving plots to datasets
- Parent filters [more info]
Using the dataset you created in the last practice, can you calculate how many times it has happened each week?
- Now add a plot to visualize the volume by week
- What if you wanted to understand the average of the revenue for that week? Can you create a plot for that too?
Calculating Conversion to Another Activity
- What are relationships? [more info]
- FIRST INBETWEEN: Used for Conversion Rates
Understanding Append Activity Features
- Did XXX
- Timestamp of XX
- Days to XXX
- Adding more append activity features [more info]
Calculating Conversion Rate [more info]
- Understanding additional default metrics
Calculating Conversion to the SAME Activity (Retention) [more info]
- Using FIRST IN BETWEEN to calculate retention rate
- Relationships [more info]
- FIRST EVER: common for first touch attribution [more info]
- AGG EVER: common for customer LTV [more info]
- What is the likelihood that a customer will do that activity again?
- Can you understand how that retention rate has been changing over time (by week)?
- What if you wanted to understand how it changes as that customer does it more?
Updated about 1 month ago