Order Splitting on Shopify: How It Impacts Your Analytics (and What to Do About It)

Decoding the Impact of Order Splitting on Your Shopify Analytics

Hey everyone! I was just diving into a fascinating discussion in the Shopify Community about order splitting and its sneaky effects on analytics. User TSAvi kicked things off, wondering about the impact of splitting orders (think separating pre-orders from in-stock items) on key metrics. It turns out, it's a bit of a rabbit hole, but totally worth understanding.

The original poster, @TSAvi, was specifically asking about how splitting orders affects Shopify's built-in analytics – things like order count, Average Order Value (AOV), conversion rate, revenue reporting, and marketing attribution. It’s a really important question because if your data is skewed, you’re making decisions based on inaccurate information!

The Downside of Split Orders: A Metric-by-Metric Breakdown

Here's the lowdown, based on what the community shared:

• Order Count: This one's pretty straightforward. Splitting an order increases the order count.
• Average Order Value (AOV): Since you're dividing the total revenue across more orders, your AOV will naturally decrease. Dolia_goprofit pointed this out in the thread, and it's a crucial point to consider.
• Revenue: The total revenue stays the same, which is good! But it's distributed across multiple orders, making it harder to get a clear picture at a glance.
• Conversion Rate: This is where things get tricky. As dolia_goprofit mentioned, conversion rate can become misleading. If a single customer session results in multiple orders, your conversion rate might appear artificially inflated.
• Marketing Attribution: This is a big one. Splitting orders can mess with your marketing attribution, especially if the "child" orders are created later. They might end up being attributed to "Direct/None," even if the customer originally came from a paid ad.

The Alternative: Split Fulfillment, Not Orders

One of the most valuable insights from the thread was the suggestion to split fulfillment instead of orders whenever possible. Dolia_goprofit emphasized this, saying that if you want clean analytics, keeping everything under one order and splitting the fulfillment process is the way to go. Only split into multiple orders if the operational benefits *really* outweigh the analytics headaches.

When Order Splitting Makes Sense (and How to Mitigate the Damage)

Okay, so sometimes you *need* to split orders. Maybe you're dealing with pre-orders, backorders, or shipping items from different warehouses. Maryzico chimed in with some practical advice here. Splitting is indeed operationally useful, but it will skew order-based metrics.

So, what can you do? The key is to track and tag those split orders separately. Here's a breakdown of how you can approach this:

1. Tagging: Implement a system to tag split orders. You could use a specific tag like "Split Order" or something more descriptive, like "Pre-Order Split."
2. Custom Reports: Use your Shopify data to create custom reports that exclude or specifically analyze split orders. This will help you get a clearer picture of your overall performance.
3. Analytics Apps: Explore Shopify apps designed to handle order splitting and provide more accurate analytics. Some apps might automatically track and adjust metrics for split orders.

Keeping Your Data Clean: A Few Extra Tips

Beyond tagging and custom reports, here are a few other things to keep in mind:

• Consistent Naming Conventions: Use clear and consistent naming conventions for your tags and order notes. This will make it easier to analyze your data later on.
• Communicate with Your Team: Make sure your team understands the impact of order splitting on analytics and how to properly tag and track these orders.

Ultimately, understanding how order splitting affects your Shopify analytics is crucial for making informed business decisions. While it can introduce some complexity, with the right approach, you can mitigate the damage and maintain a clear view of your store's performance. The community discussion highlighted the importance of weighing the operational benefits against the potential impact on your data – and that's a balance every store owner needs to consider!