ShareChat Manages Operations Around the Clock of 160+ Million MAU’s with Locale.ai

“Locale.ai helps us save time and reduce costs as it automates majority of the processes, freeing up a significant number of man hours.”

Shantanu Kumar

Manager - Trust & Safety Operation, Sharechat

Reduced Missed Instances of Edge Cases

Increased Accountability & Visibility

Increase in Operational Gains

Table of Contents
Use Cases

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Challenges

24/7 Operations Lead to Missed Issues

As a social media company, Sharechat’s operations run continuously, catering to over 160 million monthly average users. Manually monitoring and flagging inappropriate content becomes an increasingly daunting challenge in this non-stop environment.

We work in the day and have more hands available to deal with issues at that time, and issues flagged in the night would sometimes get missed when we would come back to work in the morning. With Locale, we can now be worry free that, even if there is an issue, it won’t go unnoticed. Someone in the team will act on it.

Shantanu Kumar, Manager - Trust & Safety Operation, ShareChat

Overlapping Efforts Create Inefficiency

The ShareChat team used to manage flagged content through manual reviews, which was feasible in their early stages. However, at their current scale, tracking responsibility for specific flagged content and actions taken became a complex challenge.

Existing Solutions

Manually Sifting Through Extensive Data

The ShareChat team manually reviewed flagged content around the clock due to the continuous influx of user-generated content. As the company expanded, they increased the team size to manage this growing workload.

Meetings

Regular team meetings were scheduled to address flagged content, determine team responsibilities, and troubleshoot issues. However, this approach became rigid, resulting in delays in resolving problems and making decisions.

We have tried and worked with multiple different tools like Metabase but so far Locale has been the easiest to setup and work with from an operations point of view. I can send additional data which the person needs to act upon on the alert with the alert itself.

Shantanu Kumar, Manager - Trust & Safety Operation, ShareChat

Multiple Tools

The team utilised several tools such as Metabase, Grafana etc but encountered various issues. These challenges encompassed usability, setup difficulties, and the information communicated when they were alerted. Users often had to retrieve information after receiving alerts, leading to inefficient use of time.

Use cases

Flagged Content Alerting

ShareChat's team configured real-time alerts for flagged content, incorporating inputs from their internal models, tools, and user reports. This system allowed them to proactively address flagged content issues, ensuring a safer and more seamless user experience on their platform.

Maintaining TAT

ShareChat's team implemented customised alerts that triggered when specific actions exceeded their predefined turnaround times (TAT). These alerts provided immediate notifications to the responsible individuals, including action priority, and, if necessary, activated an auto-escalation process to ensure timely resolution.

Impact

Operational Gains

Given that a major portion of the process was automated and with alerting in place, the team at ShareChat saves a considerable amount of man hours doing tasks that really matter as opposed to look at dashboards and figure out what when wrong and how.

It is still early for us to say what all benefits we have had after implementing Locale.ai but in the early days of the implementation only we saw that we were able to save over 8 hours of man hours weekly by eliminating manual and repetitive tasks.

Jagdeep Singh, Manager - Trust & Safety Operation, ShareChat

Improved Visibility

After implementing Locale, the team received real-time updates on metrics. This empowered their teams to efficiently monitor and manage operations in real-time, optimising resource allocation and ensuring a seamless experience for the users of the app. Additionally, Locale enabled clear visibility into issue assignments, reducing redundancy and enhancing overall operational efficiency.

Reduced Edge Case Misses

Operating around the clock for over 160 million monthly users, the ShareChat team had varying availabilities. This sometimes led to overlooked issues when transitioning between shifts. However, Locale brought clarity by assigning alerts and tracking responsibilities, ensuring a seamless handoff and preventing issues from slipping through the cracks.

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