Navigating the Challenges of Web Analytics: Tips for Success and Staying Calm Under Pressure

As a Web Analytics specialist, I often encounter questions, requests, or tracking issues that I'm unfamiliar with or clueless about. In our fast-evolving digital world, this is a common challenge.

When I started in this industry, this frustrated me greatly. Fortunately, I had Vishal Gor as my manager, who taught me many valuable lessons. Most importantly, he taught me to Zoom Out and take deep breaths when I find myself in difficult situations which helped me a lot in many challenging situations.

I wanted to share this with my network, especially for those just starting their careers in any industry.

Here are the process/steps I follow when I'm facing a difficult query or when the topic is new to me:

Remember to always be kind to yourself. Go easy on yourself, zoom out, and take a deep breath :)

1. Understand the Query: Take a deep look at the email and understand the scope. Is it a question, issue, or request? This sounds obvious, but distinguishing these can minimize lengthy email threads and ensure you have a clear understanding of the sender's objective.
2. Use Documentation: If documentation is provided, use it. This will give you a clear understanding of what you need to do and how to do it.
3. Seek External Help: If you still have trouble understanding or executing the documentation, look up information online. You can find Reddit threads, YouTube videos, or even use tools like ChatGPT to explain and provide step-by-step instructions.
4. Research Internally: If you're in an organization, search internal resources like Notion or Slack for similar keywords.
5. Ask for Help: If you've followed the above steps and still need assistance, ask your team for help. Use a proper format to describe the problem, expected behavior, steps taken, and any related attachments or discussions.
6. Clarify with the Sender: If the query is unclear, ask the sender for more details, attachments, documentation, or schedule a quick call for further explanation.

Here's an example from my experience when I applied the above for a recent challenge I faced: "(unattributable) / (unattributable)" values in GA4:

1. I checked the overall GA4 property setup in GTM and server-side to ensure everything looked correct.
2. I reviewed the website for any strange behavior, like duplicate event tracking, and verified the consent setup.
3. I analyzed the property data for any odd metrics or high percentages of (not set) values.

This initial review took less than 10 minutes. It's essential not to spend more than 10-15 minutes at this stage unless you find something significant.

Next, I searched online and found a Reddit thread discussing a similar issue, linking it to GA4 and consent/reporting identities. I compared multiple GA4 properties with consent setups and identified the rest.

Since there wasn't much discussion on this topic, I synced with my manager, shared my findings, and he agreed with my conclusions.

I'm not perfect at problem-solving, but this is what I've learned from working with my amazing team at Elevar and from the recent 麦肯锡 - Forward Program course, which I highly recommend!

I hope you find this helpful :)