We claw your business data from the services you use to run your business and expose the secrets it's been keeping from you
- See how your business is
put together - Know how your business is
doing - Change your behavior to
reach your goals faster
Trend view lets you see your lines moving in relation to each other (each has its own Y axis). Compare view should be used to see the difference in the line values (a single Y axis).
In some cases, it can take up to 2 hours for new data to show up.
There is a setting which allows you to choose between counting the number of emails or the number of conversations. If you are seeing more emails than you expect, switch this setting to count the number of conversations.
Our prediction algorithm is a simple mathematical linear weighted approximation of the function by the least squares method.
We use the last 13 full weeks to feed into the prediction algorithm.
After this weighting, we build a system of 2 equations and use a Gaussian method in which the system of equations reduces to triangular form. The solution yields the linear approximation.
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See this blog post: Requesting New Data Extractors In DigMyData
We took inspiration for our churn rate calculation from Steven Noble (@snoble) at Shopify here. The churn rate algorithm we are using is the following: 30 * (number of customers who churned on day x / number of customers at the beginning of day x). Note that we do not include lifetime or complimentary subscriptions in the churn rate calculation (they cannot churn). We do include accounts with complimentary time (assumption is that the complimentary time feature is used to offer a longer trial or sales incentive and the account will eventually carry churn risk).
We calculate the Authorize.net churn rate with the same basic formula as we do for Stripe and Spreedly – but – because the data is not as complete we have to make some assumptions.
How we build subscription data in Authorize.net:
- We build subscriptions/cancellations using Transactions.
- We look at the combination of the CustomerID, Name, and Email fields to build a unique customer.
- If we find multiple transactions with this profile then we have a subscription.
- Calculate the average time period between neighboring transactions
- We identify cancellations when there are no transactions after last transaction + (ATP x 1.5)
- We now have the list of subscriptions/cancellations for our churn rate formula.
The MailChimp subscriber number that you see is the number of confirmed subscribers (double opt-in). Double opt-in is the industry best practice and the MailChimp API makes it impossible for us to show a full history that include single opt-in subscribers. For more information, see MailChimp’s support article on Double Opt-in.