User Engagement Report

Overview


The User Engagement Report serves as a valuable tool for gauging the adoption of various apps within your organization. This report provides a comprehensive list of apps along with their corresponding engagement metrics. Apps are categorized into four tiers: no usage, low usage, medium usage, and high usage. 


Depending on your organization's policies, you can identify apps with low engagement and take appropriate action. Furthermore, apps with no usage can be identified by checking the user details on the Spendflo products page. In such cases, you have the option to deactivate or downgrade licenses, thus optimizing cost savings.


Please note that User Engagement data is only available for apps with a direct integration to Spendflo, apps to which users log in via SAML2 Single Sign-On (SSO), and apps visited by users with the browser extension running.


Viewing User Engagement Report


By default, users that have not logged in to the app in the last 90 days are treated as unused accounts. You can select a different threshold for unused accounts from the dropdown list (or change the default threshold for all apps as described below). Users that have logged in to the app within the threshold period are given a user engagement score of low, medium or high.


How user engagement works 


User engagement is based on the number of logins into the app by the user over the given time period. User engagement data is only available for apps with a direct integration to Spendflo, apps to which users log in via SAML2 Single Sign-On (SSO), and apps visited by users with the browser extension running.


Defining low, medium, and high engagement


Threshold - 30 days


Recency (in days)/Frequency (number of login per day)

High (0-7) [Days]

Medium (8-15) [Days]

Low (16-30) [Days]

High (>5)

High

High

Medium

Medium (2-3)

High

Medium

Low

Low (<2)

Medium

Low

Low


Threshold - 60 days


Recency (in days)/Frequency (number of login per day)

High (0-15) [Days]

Medium (16-30) [Days]

Low (31-60) [Days]

High (>5)

High

High

Medium

Medium (2-4)

High

Medium

Low

Low (<2)

Medium

Low

Low


Threshold - 90 days


Recency (in days)/Frequency (number of login per day)

High (0-30) [Days]

Medium (31-60) [Days]

Low (61-90) [Days]

High (>5)

High

High

Medium

Medium (2-4)

High

Medium

Low

Low (<2)

Medium

Low

Low



Steps to get the User Engagement Report


To get the report, follow the steps below.


1. Open the Reports tab from the Navigation menu



2. Once you've landed on the Reports page, the initial screen that appears will be the Buying Hub Reports. The navigation menu for accessing different reports is located on the left side of the screen. Navigate to the Management Hub section. Locate and click on the User Engagement


3. After clicking on the report, you'll see the report populated. Here all your apps will be represented in a graph and their engagement data of users with no usage, low usage, medium usage and high usage. 

Hover on a particular app and its color, to see the number of users falling in that category. The scale of engagment is provided at the top of the graph for your reference.



The user engagement report and Monthly Active Users graph will have a lag of 24 hours. However, the last access information on the users table will be near realtime.



Sort and Filter


Within this report, you have the flexibility to fine-tune the Engagement threshold using the drop-down filter. You can choose from three options: 30, 60, and 90 days of engagement threshold. This selection dictates how the system categorizes apps into low, medium, and high usage based on your chosen timeframe.


Additionally, you have the ability to sort the report either alphabetically or by the number of users associated with each app.




Sources of user engagement data


User engagement data within Spendflo is sourced from direct integrations with applications and via the "Big Bang" SAML2 SSO protocol. Understanding the source of this data is crucial as it impacts its consistency and overall quality.


Direct App Integrations


Direct integrations with applications enable Spendflo to retrieve valuable user engagement data, including the frequency of user logins. Many apps offer APIs that record user login information, providing insights into user activity. Spendflo considers direct connections as the "gold standard" for obtaining usage data.


The Impact of Session Duration


Session duration plays a significant role in determining user engagement metrics. Some applications allow users to remain logged in for extended periods, posing potential security risks. 

For instance, Slack users often experience long session durations, resulting in infrequent login prompts. Spendflo displays "last accessed" dates for apps like Slack to reflect user activity accurately.


On the other hand, applications like Monday.com default to long session durations, which may affect the accuracy of user engagement data. Spendflo recommends reducing session durations to enhance security and ensure precise usage data.


Chrome Extension


Spendflo's Chrome extension complements OAuth2 authentication methods by providing insights into application activity, such as last accessed dates and monthly usage. While the extension relies on whitelisted applications, its accuracy depends on continuous updates and distinct login URLs.


"Big Bang" SAML2 SSO Apps


"Big Bang" SAML2 SSO apps restrict user logins to SAML2 Single Sign-On protocols exclusively. Spendflo benefits from these apps as all logins are routed through designated Identity Providers, ensuring comprehensive login data retrieval.


Apps like Box.com offer options to enforce SSO, enhancing security and simplifying user authentication processes.


Non-"Big Bang" SAML2 SSO Apps


For applications without direct integrations, user engagement data is limited if users access the app using both passwords and SSO. While Spendflo can capture SSO data from Identity Providers, some user logins may go unrecorded, affecting data accuracy.


OpenID Connect or "Social" Login Access


Access protocols like OpenID Connect, exemplified by "Sign in with Google" or "Sign in with Microsoft," grant users long-lasting access tokens. However, these tokens may skew user engagement metrics as they remain valid for extended periods. While data from OAuth2/OpenID Connect protocols may lack precision, Spendflo enables users to track the "Last accessed" date to gauge recent activity accurately.


Understanding the nuances of user engagement data sources empowers users to interpret metrics effectively and optimize application usage within Spendflo.







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