Shopify store analytics: how to measure the performance of your store

Shopify is the biggest e-commerce platform in the world and has seen rapid development since 2000. More than 4 million stores generate approximately 3 billion dollars yearly with the help of excellent, straightforward technology. While the store creation is seamless, analyzing the entire data around a profitable Shopify store that generates traffic fromshopi various channels might be difficult.

A deeper focus on privacy introduced through regulations like GDPR or CCPA and privacy-protecting technologies like those introduced with the iOS14+ update make it even harder for brands to track their result and accurately attribute sales to the right channels and campaigns. The analytics module in Shopify is comprehensive but lacks visibility beyond its platform. This is where software tools and platforms can enhance the reporting and analytics of online stores and offer compelling insights into profit-generating marketing activities.

Benefits of creating a Shopify-based eCommerce

Shopify is the largest eCommerce platform in the world for a range of reasons: it's easy to use, offers stellar 24/7 support, access to an endless knowledge base comes with a multitude of plug-and-play functionalities offering access to an ecosystem of more than 8000 apps to explore all possibilities around eCommerce.

Ease of use

Any store with an internet connection can easily digitalize any aspect and go online in less than 24 hours. Shopify is very easy to use, even for non-technical people. This is probably the main reason why more than 75% of the world's e-commerce live on the platform.

24/7 support

When it comes to needing help with software, few things are more annoying than being unable to establish a relationship with a real person. Shopify is a very customer-centric eCommerce solution offering 24/7 support that comes in handy, especially when revenue and profits are at stake. Their response times are almost instant, and businesses can rely on professional help for any issue that might occur.

A multitude of plug-and-play functionalities

As an e-store grows and develops into a profitable business, more and more needs are identified, from worldwide shipping and integrations with several couriers to inventory management issues and even tax challenges. Thus, opting for Shopify can be an easy way to manage all related obstacles and demands of increasing complexity. The Shopify app store features over 8000 apps in categories like finding products to sell, customizing the store, attracting customers, delivering goods, or scaling the business. Here is a list of the best Shopify apps to increase sales.

What is Shopify analytics?

The analytics page in the Shopify Dashboard might be the most accessed by store owners for a very simple reason: on this page, the health of a store is displayed together with metrics that indicate orders and sales, order value, conversions, returning customers rates, top landing pages revenue, and even sales by POS locations.

This data is crucial to understanding where a business is situated and helps grasp a store's performance. The Analytics module of Shopify allows store managers to create diverse reporting on acquisition, behavior, customers, finance, inventory, marketing, product, and many other reports. This information is extremely useful for marketers and store owners to market their products and grow their revenue and profits.

While the Shopify Analytics tab available in the Shopify dashboard has incredible data related to the most relevant e-commerce metrics, the available information will not go beyond the Shopify platform.

Limitations of Shopify analytics

Any store in the Shopify ecosystem must be aware of the analytics discrepancies concept, which refers to the different factors influencing the reporting and analytics capabilities of Shopify and highlights how data can vastly differ. Factors accountable for these differences are discrepancies between Shopify analytics and third-party tracking services such as Google Analytics or cookie-based customer data collection.

For example, some reasons for the above disparities stem from different ways of counting page loads, search bots, reporting, customers using browser extensions to block Google Analytics from tracking their sessions, or simply users that don't allow JavaScript or cookies.

If a DTC runs various marketing campaigns on different channels, the reporting and analytics capabilities of Shopify is limited to the data stored in cookies by Shopify. This creates an array of issues related to attributing credit to the right traffic sources, scaling the most suitable ones, and choosing the right channels that perform best. When costly CTRs, CPAs, and traffic are involved, the accuracy of data used in making such decisions is crucial. Overcoming the limitations of Shopify analytics is possible with analytics tools that go beyond the data available from advertisers or restricting customer journeys to specific browsers via cookies.

Privacy regulations impact on analytics and attribution

The latest privacy regulations, such as the General Data Protection Regulation (GDPR) and the ePrivacy Directive introduced by the EU or the CCPA in the State of California, hinder data collection and make analytics flawed. Research showed that before the iOS14+ update, approximately 70% of iOS users shared their IDFA(Apple's identifier for advertisers). Today, estimates indicate only 5% of US consumers, while globally, approximately 13% of iOS users share their IDFA. Thus, there is no surprise that these limitations introduced with the release of Apple's iOS14 led to gaps in the data tracked and reported by ad networks. These privacy regulations led to inaccurate attribution, decreased ad performance and increased the overall cost of running ads.

First-party data and its importance for accurate Shopify store analytics

Relying on data from advertising networks and third-party data aggregators is cumbersome, to say the least. According to Gartner, by 2025, 75% of the world's population will have its personal data covered under privacy regulations. This means that access to data about consumer behavior will become less and less available, bringing first-party data to attention. Under first-party data lies personal information a business collects through its own means, like marketing assets or website data.

For example, behavioral data, subscription, and social data are considered first-party data. They have an increased value as it is free to collect and an indicator that current or potential customers are willing to hear from the brand and engage. But the value of first-party data goes beyond a stellar customer relationship as brands can harness its power to understand the results of their marketing efforts. Boston Consulting Group showed in a study that marketers using first-party data see a lift in marketing efficiency, generating nearly double the revenue from a single ad or placement.

How to overcome Shopify analytics' drawbacks with Admetrics

Admetrics Data Studio is an all-in-one AI-based marketing platform designed for online stores to improve all marketing aspects through accurate data, attribution, and unique insights. Below we list a series of features that help DTCs and Shopify-based brands overcome Shopify analytics' limitations.

Cross-device and cross-browser attribution

Admetrics leverages a mix of privacy-compliant technologies and machine learning to track customer journeys across browsers and devices and therefore increases the accuracy of performance indicators by attributing sales to each touchpoint of the journeys. By closing these tracking gaps and leveraging omnichannel attribution, marketers can again confidently scale their ad budgets.

Privacy-compliant tracking system

Admetrics unifies 1st party with paid and unpaid media data and provides deep, actionable insights into the performance of all campaigns, ads, and creatives across all channels. The cross-device tracking systems implemented by Admetrics are 100% GDPR and CCPA compliant and thus facilitate e-commerces and marketers to work with EU-based customers without infringing local regulations.

Data passback to Meta

To improve the reporting capabilities of ad networks, Admetrics users can opt for data passback to Meta. By enabling a server-to-server data pass-back to Meta, algorithm performance and ad efficiency are improved. Sharing your first-party marketing data with platforms like Meta is crucial for optimizing ad targeting, decreasing the cost per action, and measuring results.

First-party data used to model predictive audiences

With Admetrics, the power of first-party data is maximized by creating AI-based predictive audiences which use first-party data to anticipate the likelihood of a prospect converting to a certain action. Predictive audiences use artificial intelligence to analyze user behavior on-site and identify patterns based on which customer segments are created and classified as having a high, medium, or low purchasing intent. These segments can be used for retargeting or seeding lookalike models for prospecting new customers.

Landing Page Analytics

To complement Shopify store analytics, Admetrics offers a range of unique features such as landing page analytics which measures the performance of each landing page and accurately understands metrics like conversion rates, add-to-cart rates, profits (CM1-3), customer acquisition metrics, and many more. With these detailed analytics, marketers can assess the value of landing pages and improve ad strategies and content accordingly.