Data Analytics Automation: Redefining Product Analytics For PMs

Data Analytics Automation: Redefining Product Analytics For PMs

Iterate AI

Iterate AI

Jan 23, 2025

Data Analytics Automation
Data Analytics Automation
Data Analytics Automation
Data Analytics Automation

Product data analytics have become common in boardroom discussions and casual conversations among product teams. Feature prioritization, roadmap decisions, etc. are made primarily based on data analytics. Thanks to reliable and in-depth data on user behavior.

That being said, setting up and maintaining analytics can often feel like an uphill battle for product managers (PMs). There’s too much dependency on developers to write code and their plates are almost always full. The traditional approach creates delays and inefficiencies. 

Enter data analytics automation–a transformative approach that promises speed and simplicity for PMs. 

The Challenges of Traditional Analytics Implementation

For PMs, the journey of setting up analytics is often riddled with challenges. Here’s a typical scenario:

  • Tedious coordination: PMs spend hours coordinating with developers to instrument events. The back-and-forth involves multiple tools, screenshots, and detailed explanations of event triggers and properties. 

  • Human errors: Relying on spreadsheets and manual processes to track events leads to missed metrics, duplicate events, or incorrect data properties.

  • Developer dependency: With developers already stretched thin, analytics implementation often takes a backseat, delaying insights. It is also a reason for PMs to make under-confident decisions without data.

  • Time-intensive validation: Testing event implementation involves meticulous checks across the product, spreadsheets, and analytics tools like Mixpanel, which is a difficult process.

The Cost of Analytics Debt

When a series of bad decisions—knowingly or unknowingly—are made about analytics instrumentation, it leads to what is known as analytics debt. This is a critical state where the data from your analytics setup is no longer reliable for decision-making.

Analytics debt typically arises due to two reasons:

  1. Prioritizing building over analytics: Early-stage startups often focus solely on building their product without thinking about analytics from the beginning. As their user base grows, their analytics setup fails to scale, resulting in unreliable data.

  2. Improper setup: Lack of knowledge or expertise in setting up analytics leads to incorrect instrumentation, duplicate events, or missed metrics, all of which compromise data integrity.

Hitting this block is a costly setback, forcing teams to halt progress and invest heavily in fixing their analytics infrastructure.

How Iterate AI Simplifies Analytics Setup

Iterate AI transforms the traditional, labor-intensive process into an intuitive and automated experience. Here’s how it works:

Action-based setup

One of the standout features of Iterate AI is its action-based setup. Instead of the traditional process of coding each event manually or relying on spreadsheets to document them, product managers can interact directly with their product interface. You click on an action in your product to create an event. That’s it!

You can easily label the events with Iterate AI. You don’t need a spreadsheet to plan events and write labels.

No-code instrumentation

Iterate AI generates the required event code automatically based on your analytics software such as Mixpanel or Amplitude. Your developer has to approve only approve the code. This saves a lot of developer’s time as they don’t have to understand the events and write code from scratch.

Self-maintaining instrumentation

Iterate AI ensures that your analytics setup is error-free at the point of implementation. Better than that? It ensures that over time. Iterate AI is more like a self-maintaining instrumentation that continuously monitors and updates the system to prevent errors, omissions, and outdated events. So you don’t have to do any deep manual audits.

Duplicate prevention

Duplicate events clutter analytics data, making it difficult to draw accurate insights. Iterate AI addresses this issue with advanced planning tools that identify and prevent duplicate events during the setup process. This ensures that your data remains clean and reliable for decision-making.

Real-time alerts

Immediate notifications ensure teams are aware of any issues, enabling faster resolution and minimizing disruptions.

Data Analytics Automation is Beneficial. Reap the Benefits With Iterate AI

With data analytics automation using Iterate AI, you get:

  1. Improved accuracy: Automated processes significantly reduce human error giving you more reliable data to work with.

  2. Enhanced collaboration: PMs can independently manage analytics setup and maintain dashboards and reports.

  3. Scalability: Automated systems can adapt to growing product needs, ensuring analytics remains strong as the business scales.

Data analytics automation is not just a technical upgrade; it’s a paradigm shift in how teams approach data-driven decision-making. Schedule a demo with us to learn more.

Iterate AI

© 2024 Iterate AI Technologies, Inc. All rights reserved.

Iterate AI

© 2024 Iterate AI Technologies, Inc. All rights reserved.

Iterate AI

© 2024 Iterate AI Technologies, Inc. All rights reserved.

Iterate AI

© 2024 Iterate AI Technologies, Inc. All rights reserved.