Case study

Productiv + UTA

Zoom uses Productiv to understand application and feature usage.

UTA accelerates Zoom feature adoption by 113% with Productiv

Challenges:

Manual, time-consuming collection & analysis of app usage data
Limited visibility into impact of training on feature & app adoption
No measurement of in-app collaboration

Results:

20% reduction in time spend on data gathering and analysis
113% increase in Zoom screen sharing in 30 days
59% increase in Box user engagement
422% rise in Box files shared externally

United Talent Agency (UTA) is a global talent and entertainment company with more than 1,400 employees that represents pioneering artists, storytellers, entertainers, and brands. UTA created a technology adoption team to ensure its agents have the right tools and training to work effectively.

Before the team could enable agents, they needed to figure out which ones need to be trained and what they need to be trained on. But identifying those individuals and their needs was a challenge.

Why UTA Needed Productiv: In order to identify which agents to train, the team was exporting usage and adoption metrics from each application, compiling them in a spreadsheet, and then creating visualizations to go along with the data. It was an extremely time-consuming process. They often relied on stale, out-of-date data on app usage because it would take too much time and effort to obtain current information. As a result, some agents who needed training were passed over while others were offered training too late. Additionally, the team had limited visibility into whether the training resulted in more adoption and usage.

Visibility into User- and Feature- Level Activity

The user- and feature-level visibility Productiv provides improves the assessment of the training provided by the team. When a training is held, the technology adoption team annotates app usage charts. Then, they monitor those charts for changes in app and feature usage following the training. They can now confidently answer questions such as, “Did training on Box Sign increase the use of Box and decrease the use of other electronic signature applications?” When UTA rolled out a pilot for Zoom Phone, the team used Productiv to track usage. They trained a team of UTA speakers, used annotations to mark when the training happened, and monitored to make sure their weekly usage numbers stayed above 80%.

Automated Tracking of Usage and Provisioning

With the Productiv SaaS Intelligence™ Platform, the technology adoption team has automated tracking of usage and provisioning data. Out-of-the-box visualizations provide quick insights into data trends. They also have granular, user-level engagement data available to better inform them on what teams to train. For example, if a new feature is added to an app, they can see what agents have the greatest adoption of the app, making them good candidates for training on the new feature. Or they could see who is a heavy user of a related feature for even more targeted selection of agents to train. Putting these insights into action, the team’s training on Zoom screen sharing resulted in 113% more agents using screen sharing within a month.

Insight into In-App Collaboration

The team can now track and visualize collaboration taking place within apps. After providing additional training on Box, they were able to see that it resulted in more collaboration between internal teams and an increase in files shared externally between agents and clients. With an increase of 422% in the use of Box with external clients, they are more confident that sensitive files aren’t being leaked or shared unnecessarily and their security posture is maintained.

"Before Productiv, I would personally spend 7-8 hours a week pulling data and analysis on application adoption to present to the CIO & IT team. Now, it’s instantaneous! There are always more questions than we can answer, and with Productiv we can easily dive into details in real time to view and segment the data, instead of manually and inefficiently reworking spreadsheets.”

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