Reporting & Analysis
24.11.2023
TLDR
Shopify and Google Analytics may provide inconsistent conversion rates due to their different definitions of what a session is and Google Analytics sale tracking limitations. Airboxr's Sales Performance by Date Hop addresses this by combining Shopify's sales data, and Google Analytics session data while also including your ad spend data. This allows for a more accurate calculation of conversion rate while also offering resources for sales analysis, ad spend evaluation, and customer retention strategies.
How do you currently track your Shopify store conversions? Do you look at what Google Analytics tells you? Do you look at what Shopify says? Or… do you not trust either of their reports?
If you’re a little skeptical of each platform, you’re right to be. Neither of these are completely accurate; and we’ll show you why.
In this article, we’ll explore the differences between how Shopify and Google Analytics reports conversions. We’ll also show you how you can create a much more accurate conversions report, using Airboxr.
Why Shopify’s conversion rate isn’t reliable
It’s easy to get a report on your daily conversion rate on Shopify - all you have to do is use the Online store conversion over time report in your Shopify Analytics. The downside to this, however, is that your conversion rate figures might be underestimated simply because of what Shopify counts as a session.
For background, conversion rate in this context refers to the proportion of your store’s traffic that ends up making orders. Shopify’s conversion rate formula is:
Conversion rate = (Total Orders/Sessions) 100
In Shopify Analytics, sessions are simply defined as how many visits your store receives without any time restriction on counting. This means that if a person visits your store, leaves, and returns within 10 minutes before placing an order, Shopify will count two sessions and present a 50% conversion rate.
Google Analytics on the other hand takes a time-bound approach. A session is defined as a group of interactions one user takes within a given time frame. Google Analytics defaults that time frame to 30 minutes. Using the example above, Google Analytics would have only counted one session which would mean a more accurate 100% conversion rate. This key difference means a lot when scaled to the amount of traffic your store receives because Shopify’s inflated session figures would mean an underestimated conversion rate.
Shopify Analytics counts every visit by a user as a separate session, even if the same user returns within 10 minutes of leaving your store. Google Analytics counts two visits within a 30-minute time frame as a single session, giving a more accurate measurement of your total sessions.
Why Google Analytics’ conversion rate isn’t reliable
This doesn’t mean solely relying on Google Analytics figures for calculating conversions on your Shopify store is recommended. You can get your store’s sales data from GA but it’ll never be as accurate as Shopify’s. The main reason for this is that GA sales data depends on trackers.
For example, If someone uses ad blockers, VPNs, or private browsers like Brave, they may not be tracked in GA. Other possible reasons is that tracking failure are if the "thank you" page is not loaded after a payment, or if an upsell/checkout app used by your store is not fully compatible with GA.
How to get the most accurate conversion rate with Airboxr
With Airboxr’s Sales Performance by Date Hop, you can easily get the best of both worlds. It is a daily report of your store’s performance in terms of sales, traffic, ad spend, and customer retention. It pulls your store’s session data from Google Analytics, sales data from Shopify, and ad spend data from Facebook, Google, and TikTok.
With this information, you can easily calculate your Shopify sessions converted vs orders using this calculation:
Conversion rate = (Total Orders/Sessions) * 100
To do this, copy and paste this formula to a new column on your spreadsheet:
=SUM(B2:B)/SUM(C2:C)
You can do this calculation every time you run a Hop for a specified time period; or, you can set this Hop up to a custom dashboard on Looker, and have your conversion rate automatically calculated there. (We can help you set up your Looker as well - ping us on the in-app chat to learn more.)
The main reason this report uses sales data from Shopify instead of GA is that its sales data can be affected by tracking blockers. For example, If someone uses ad blockers, VPNs, or private browsers like Brave, they may not be tracked in GA.
What can this Hop be used for?
This hop can be used for the following:
Conversion/Drop-off rates: With the provided data on daily sessions on your store, you can easily calculate your session-to-order conversion rate in a new column. To go a step further, you can combine this report with our Traffic Over Time Hop to better understand conversion/drop-off rates at different stages of your customer order journey.
Sales Analysis and Revenue Optimization: E-commerce businesses can analyze daily sales, orders, ad spend, and returning customers to quickly identify trends, understand customer behavior, and evaluate promotional impact. Due to the flexibility of your report being in a spreadsheet, you can create pivot tables to make monthly, quarterly, and annual reports from this.
Ad Spend Evaluation and ROI Assessment: The report includes the total daily ad spend across your social advertising channels allowing you to evaluate the effectiveness of your advertising campaigns by correlating ad spend data with sales and traffic metrics. You can also take a closer look at your daily ad channel performance with the DTC Marketing KPIs over Time Hop.
Customer Retention Strategies: Monitoring the number of returning customers on a daily basis provides valuable insights into customer loyalty and retention. To analyze the daily sales generated by returning customers, use the Returning Customer Sale Hop.
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A step-by-step tutorial
Here’s a tutorial on how to run a Sales Performance by Date Hop.
Step one: Select the hop
Search for the hop in the Hops Marketing using the left sidebar in Airboxr.
Step two: Customize your report (Optional)
You can customize the timeline that you want your report to cover and also set a filter to show only dates that meet the set requirements of each metric.
Step three: Run the Hop
You can now run your report.
Bonus: Schedule your report
In order to always have the latest data, schedule your report to run automatically.