Data Discrepancies: Why Cross-Platform Marketing Data Doesn’t Always Match

Scratching your head about why your Google Analytics data doesn't match other platforms, like Meta Ads or Shopify? Our digital marketing experts explain why that occurs and why it's okay here.

Data is the fuel that powers marketing strategies, but what happens when the numbers don’t add up? One of the most commonly asked questions we receive as a digital marketing agency is “why doesn’t my Google Analytics data match my Website or Meta Analytics data?” 

Although data discrepancies can be frustrating, they don’t have to be a bad thing. 

There are many reasons why it may occur and the good news is, it’s not a huge deal. In this guide, our Delivery Team experts unravel the mysteries of data discrepancies and shed light on why they occur, so you can feel confident in your marketing strategies no matter what platforms you’re using. We’ll touch on: 

  • What data discrepancy is 
  • Main reasons for cross-platform data discrepancies
  • Strategies for more accurate cross-platform data 

Let’s dive into it.

What is ‘Data Discrepancy’ in Marketing?

Data discrepancy refers to inconsistencies in data when comparing information from various marketing analytics platforms or sources. 

For example, data from Google Analytics 4 (GA4) may not always match data from Meta Ads or Shopify, leading to variations in metrics such as website traffic, ad impressions or engagement rates. This can be confusing, because which platform is actually correct? 

Main Reasons for Cross-Platform Data Discrepancies 

Attribution Window Differences

Data discrepancies across different marketing platforms are often caused by different attribution windows. An attribution window refers to the timeframe during which a conversion is attributed to a particular ad, campaign, or channel, and can greatly influence the reported performance and effectiveness of each channel. 

For example, while Google Analytics 4 uses a default 30-day attribution window, Meta Ads uses a 7-day click or 1-day view window. This means if someone makes a purchase after clicking on your Meta Ad 8 days ago, GA4 will attribute it to your Meta Ads while Meta will not. 

GA4 also does not support “view-through” conversions (i.e., someone did not click through but saw the ad then purchased), meaning that it will not match up with data from social media ad platforms that are able to track them. 

Conversion Value Differences 

These attribution window differences can create variances in conversion value (revenue from your ads/channels) from each platform because, at the end of the day, they’re all recording differently. 

There will also always be some overlap with which platform gets the “credit” for each dollar, because users interact in multiple ways with your ads & website and it’s hard to pinpoint exactly what made them convert.. 

Long story short, you cannot compare apples and oranges. 

User Privacy Settings

The accuracy and completeness of digital marketing data collection is increasingly being impacted by users’ privacy settings. Specifically, many people now enable ad blockers, cookie blockers, or opt-out of tracking all-together. Learn more about the aftermath of Apple’s iOS14 update for marketers here. 

As Google moves towards a ‘cookie-less future,’ the latest version of Google Analytics – GA4 – works with Google Tag Manager to track User ID instead of cookies. Meta Ads does still use first and third party cookies to track data, as do CMSs like Shopify, Wix and WordPress. Therefore, data discrepancies can occur on different platforms depending on how each platform collects user data and what data users have respectively allowed digital platforms to collect. 

Time Lag & Time Zones 

Time lags in reporting and different time zones can also impact marketing data discrepancies. 

Firstly, different platforms may have varying time lags between collecting, processing and reporting their data. For example, it usually takes up to 12 hours for GA4 to report accurate data on all reports and AI enquiries. We recommend checking out the GA Data Freshness Table to learn time lags on certain metrics – a RealTime report is available for select ones. 

On the other hand, it usually takes Meta Ads up to 24hrs to display accurate data. Try waiting a day or two before comparing data between platforms to minimise huge discrepancies. 

Secondly, different platforms measure data in the time zone they are set to, which may cause variances in data if the time zones being compared are different. For example, if your Shopify data is set to your local Sydney time zone but your Pinterest Ads are set to Greenwich Mean Time (GMT), the data may be different even if you’re comparing what looks like the ‘same’ time zone. 

Strategies for More Accurate Cross-Platform Data 

  1. Consistent Tracking Implementation: Implement consistent tracking codes, pixels or tags across marketing platforms to ensure data is uniformly collected.
  2. Regular Data Audits: Conduct regular audits of data collected from different marketing platforms to identify any major differences. 
  3. Standardised Data Definitions: Use standardised definitions and naming conventions for your data fields and metrics across all platforms to avoid misinterpretation. 
  4. Validate Data Sources: Verify the accuracy and reliability of the data sources used by different marketing platforms, such as third-party integrations or data imports. 
  5. Talking to your Digital Agency: Always feel free to reach out to your digital agency if you have any questions or concerns – that’s what they’re there for! At Springboard, we endeavour to answer any questions you may have as clearly and transparently as possible by avoiding all that confusing tech lingo. 

Final Data Discrepancy Tips

It’s not always a perfect science when it comes to ad platforms and analytics tools like GA4. While this is frustrating, it doesn’t have to be a bad thing. 

Take your data with a grain of salt. Because these marketing platforms report on things like the health of your ads, user behaviour and overall trends in your marketing channels, their purpose is to help inform where you spend time and money. Even if that data is only 90% accurate, it’s still going to give you a great idea of where to allocate your marketing spend. 

Naturally different purposes require varying data. So, be prudent in exactly how you use your marketing data. For example, you wouldn’t use GA4 data for your business’s quarterly financial reports, but rather data directly from your bank or point-of-sale (POS) systems because they are not affected by users’ devices & settings.

That’s All, Folks

In conclusion, data discrepancies happen and it’s okay! 

By understanding why they may occur and how your marketing data informs your overall strategy, you can still make informed decisions about where you spend valuable time and money and how you optimise your marketing strategy over time. 

At Springboard Digital, we’re all about dropping the confusing lingo to help you focus on what matters most – improving your marketing strategy to grow your business and hit your goals. If you have any questions on this topic or about getting started with our 3 core digital marketing services, please feel free to contact our friendly Client Success Team here

Until next time, 

The Digital Marketing Team at Springboard Digital.

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