How to import existing data

Integrating SimpleStats into your existing application doesn't mean leaving behind your historical data. Recognizing the value of your application's past insights, we've developed the Data Import feature. This functionality enables a smooth transition by allowing you to seamlessly import your existing data into SimpleStats, ensuring that you retain access to all historical metrics and insights.

INFO

The Data Import feature is not available on the free subscription plan.

Supported Formats

The Data Import supports the following file formats: xls, xlsx and csv.

Import Capabilities

The import feature is designed to manage substantial volumes of data efficiently. Therefore, unless you approach the limits of your subscription, we encourage you to import the entirety of your data. This capability ensures that you can leverage the full extent of your historical insights without reservations.

Importing User Data

Though it is not mandatory, it's highly recommended to first import the user data and only then the corresponding payment data. To start a new import, you have to provide a supported file format containing the user data to import.

Allowed User Fields

The following fields are allowed:

Core fields:

Key	Type	Description
id	mixed required	The user id.
time	string required	The time when the user has registerd. Format: Y-m-d H:i:s, before or equal now

Optional fields:

Key	Type	Description
ip	string nullable	The ip of the user. (does not get stored)
user_agent	string nullable	The user_agent of the user. (does not get stored)
track_referer	string nullable	The tracking referer of the user.
track_source	string nullable	The tracking source of the user.
track_medium	string nullable	The tracking medium of the user.
track_campaign	string nullable	The tracking campaign of the user.
track_term	string nullable	The tracking term of the user.
track_content	string nullable	The tracking content of the user.
location_country	string nullable	The location country of the user. (If the ip is set, we take the country that refers to it.)
location_region	string nullable	The location region of the user. (If the ip is set, we take the region that refers to it.)
location_city	string nullable	The location city of the user. (If the ip is set, we take the city that refers to it.)
device_type	string nullable	The device type of the user. (If the user_agent is set, we take the device type that refers to it.)
device_platform	string nullable	The device platform (OS) of the user. (If the user_agent is set, we take the device platform that refers to it.)
device_browser	string nullable	The device browser of the user. (If the user_agent is set, we take the device browser that refers to it.)
page_entry	string nullable	The page entry point of the user.

Here is an example of how such an SQL query may look like:

SELECT
    id,
    DATE_FORMAT(created_at, '%Y-%m-%d %H:%i:%s') as `time`
FROM
    users
WHERE
    1;

With Condition

Sometimes you may not want to count all users as "valid" registrations. So you may only export the users which pass a certain condition, such as the user has verified their email address.

The query could look like this:

SELECT
    id,
    DATE_FORMAT(created_at, '%Y-%m-%d %H:%i:%s') AS `time`
FROM
    users
WHERE
    email_verified_at IS NOT NULL;

Now export the output of the query, save the file and then you can upload the file inside the app to start a new import!

INFO

Please note, the provided queries serve merely as examples. Your actual table structures and data might vary significantly. The implementation is completely up to you!

WARNING

The first row of your import file must be a heading row (a row in which each cell contains the key of the allowed fields)!

Simulated Natural Login Behavior (SNLB)

Coming soon: In many cases, historical login data for users isn't readily available. To address this, we're introducing an upcoming feature that allows for the optional inclusion of a last_known_activity field. This field could correspond to the updated_at attribute, a last_login field, or any similar date in your users table that best approximates the user's most recent activity.

By supplying this information, we will generate simulated login entries to mimic natural login patterns, based on the assumption that each user logged in at least once a week from their registration date to their last known activity. This enhancement aims to provide a richer, more accurate representation of your historical user engagement over time.

Importing Payment Data

After you've imported your user data, you may start another import for your payment data. Again you have to provide a supported file format containing the payment data to import.

Allowed Payment Fields

The following fields are allowed:

Key	Type	Description
id	mixed required	The payment id.
stats_user_id	integer required	The user id associated with the payment.
time	string required	The time when the payment happened. Format: Y-m-d H:i:s, before or equal now
gross	numeric required	The gross amount of the payment in cents. (e.g.: $1 = 100 Cent)
net	numeric required	The net amount of the payment in cents. (e.g.: $1 = 100 Cent).
currency	string required	The ISO-4217 currency code of the payment. (e.g.: EUR, USD, GBP ...)

Assuming the table is called transactions, here is an example of how such an SQL query may look like:

SELECT
    id,
    user_id AS stats_user_id,
    total AS gross,
    total - tax AS net,
    'USD' AS currency,
    DATE_FORMAT(created_at, '%Y-%m-%d %H:%i:%s') as `time`
FROM
    transactions
WHERE
    1;

With Condition

Sometimes you may not want to count all payments as "valid". So you may only export the payments which pass a certain condition, such as having a "completed" status.

The query could look like this:

SELECT
    id,
    user_id AS stats_user_id,
    total AS gross,
    total - tax AS net,
    'USD' AS currency,
    DATE_FORMAT(created_at, '%Y-%m-%d %H:%i:%s') as `time`
FROM
    transactions
WHERE
    status = 'completed';

Now export the output of the query, save the file and then you can upload the file inside the app to start a new import!

INFO

Please note, the provided queries serve merely as examples. Your actual table structures and data might vary significantly. The implementation is completely up to you!

WARNING

The first row of your import file must be a heading row (a row in which each cell contains the key of the allowed fields)!

DANGER

Remember that Gross and Net must be stated in cents!