Shopify Analytics vs. Reality: Are Sessions Being Silently Filtered?

Decoding the Shopify Analytics Mystery: Are Sessions Vanishing?

Ever felt like Shopify Analytics isn't telling the whole story? You're not alone. I recently stumbled upon a fascinating discussion in the Shopify community, started by abhishektaparia, that dives deep into this very issue. The question? Whether Shopify silently filters sessions beyond the usual bot detection. It's a rabbit hole worth exploring, especially if you rely on data to make informed decisions for your store.

The Discrepancy Dilemma

Abhishek, like many of us, noticed a significant difference between session counts in Shopify Analytics and a third-party platform (Cooee, in their case). After some digging, they pinpointed the "missing" sessions as originating from VPN/proxy IPs, devices with suspicious fingerprints, and unusual multi-store browsing patterns. Their post on the Shopify community forum titled "Does Shopify Have Undocumented Session Filtering Beyond Bot Detection?" sparked my curiosity and led me to write this post.

It's not just about bots creating fake sessions, but what appears to be legitimate-looking traffic that Shopify might be silently filtering out even before it registers as a session. This raises some serious questions, especially for app developers and anyone heavily invested in analytics.

Here’s a quick recap of the original observations:

1. Traffic from VPN/proxy IPs (London, Italy, etc.)
2. Devices with suspicious fingerprints (emulated Android devices with atypical browser engines)
3. Multi-store browsing patterns from single IPs. Stores’ base region is totally different. One store is based out of India and another from London. No similarity or relation between stores.

Why Should You Care?

If Shopify is indeed filtering traffic at the edge, before sessions are even created, it has implications for how we interpret our data. We need to understand:

• What criteria are being used for this filtering?
• Is this documented anywhere (because it doesn't seem to be!)?
• Should third-party tools be replicating this filtering to maintain consistency?

Digging Deeper: What Could Be Happening?

While there weren't definitive answers in the original thread (it was more of a question posed to the community), it does highlight the need to consider the following:

• Shopify's Infrastructure: Shopify likely employs various security measures to protect its platform and merchants from malicious activity. These measures might include filtering traffic based on IP reputation, device fingerprinting, and behavioral analysis.
• Data Accuracy vs. Security: There's a trade-off between providing completely unfiltered data and ensuring the security and stability of the platform. Shopify might prioritize the latter, even if it means some legitimate traffic gets inadvertently filtered.
• Attribution Challenges: Cross-domain tracking and attribution are notoriously difficult, especially with increasing privacy restrictions. Multi-store browsing patterns, as Abhishek pointed out, could be particularly challenging to track accurately.

What Can You Do?

While we might not have a definitive answer to whether Shopify employs undocumented session filtering, here are a few steps you can take to investigate and mitigate potential data discrepancies:

1. Compare Data Sources: Regularly compare session counts and other key metrics between Shopify Analytics and your third-party analytics platforms (Google Analytics 4, etc.).
2. Segment Your Traffic: Use segmentation features in your analytics tools to identify patterns in the traffic that Shopify might be filtering. Look for discrepancies based on location, device type, and other relevant dimensions.
3. Implement Robust Tracking: Ensure your tracking code is properly implemented and configured to capture as much data as possible. Consider using server-side tracking to improve data accuracy and bypass some browser-based tracking limitations.
4. Review Shopify's Documentation: Keep an eye on Shopify's official documentation for any updates or clarifications regarding session filtering and data accuracy.
5. Engage with the Community: Share your findings and experiences with other Shopify merchants and developers in the community. Collective knowledge and collaboration can help uncover hidden patterns and potential solutions.

It's crucial to remember that no analytics platform is perfect, and discrepancies are bound to occur. The key is to understand the potential sources of these discrepancies and adjust your analysis accordingly.

Ultimately, the conversation started by abhishektaparia serves as a valuable reminder to be critical of our data and to continuously question the assumptions underlying our analytics. By comparing different data sources, segmenting traffic, and staying informed about platform updates, we can gain a more complete and accurate picture of our store's performance. Keep those questions coming in the Shopify community – they help us all learn and improve!