🚀 Abbiamo raccolto un pre-seed di $1.5M per alimentare la nostra missione di trasformare l'esperienza di shopping online.

Transformando l'esperienza di shopping.
  • 22nd Dec '25
  • Snaproom
  • 9 minutes read

5 Best Shopify Analytics Tools of 2025

Running a Shopify store is a bit like hosting a dinner party. You want everything to go smoothly, from the appetizers to the dessert. And you definitely want to know how many guests had second helpings—or in our case, how many customers hit ‘checkout’ versus just browsing the menu. Today, we'll tackle various aspects of your e-commerce journey. From balancing those multiple touchpoints like a circus performer (I know the feeling) to figuring out what customers really want after they ‘add to cart.’ Trust me, this exploration into performance metrics isn’t just for the number-crunchers; it’s for anyone looking to make every sale count, as I learned the hard way after misplacing my best-selling product. So, grab a drink, kick back, and let’s unpack some insights that might just turn your Shopify store from ordinary to extraordinary.

Key Takeaways

  • Evaluate your store performance with simple metrics and avoid analysis paralysis.
  • Utilize multiple touchpoints to create a richer experience for your customers.
  • Gain insights into customer behavior through effective data tracking.
  • Leverage the customer journey to improve marketing strategies.
  • Use data insights tools to make informed decisions without breaking a sweat.

Now we’re going to chat about the fascinating world of Shopify’s analytics features. These tools can really tickle your fancy if you’re running a store there. However, they might leave you wanting more as your business blooms. Let’s get into the nitty-gritty!

Analyzing Your Shopify Store Performance

Shopify offers a nifty suite of analytics right out of the box. It's like getting a free pair of socks with a fancy pair of shoes—nice, but not quite enough to strut your stuff!

For anyone just starting, these native reports are like a gentle nudge on a bicycle—it gives you an idea of whether you’re heading in the right direction. But for anyone planning to sprint ahead, they might feel a bit like a tricycle.

Every Shopify plan gives you some basic goodies, including:

  • Sales performance: This will let you peek at your total sales, revenue, and all the other numbers that make your accountant swoon (or cringe!)
  • Customer insights: Curious about whether your customers are loyal or just passing through? This feature gives you the scoop on new versus returning customers.
  • Traffic metrics: Here’s where you tally up your visits and see where folks are finding you. It’s like collecting little breadcrumbs.
  • Product analytics: Know which products are buzzing and which ones are gathering dust in the corner.
  • Basic funnel data: Want to understand your store’s conversion rate? This helps see where things might get lost, like socks in the dryer.

But here’s the kicker—if you’ve leveled up to Advanced Shopify or Shopify Plus, you can unlock deeper reporting tools. Yet, even with those, many brands find they’re left in high water when they need:

  • Cross-channel attribution: Shopify typically sticks to a last-click model, and doesn’t track all those little interactions sprinkled across platforms. So good luck figuring out how that Facebook ad got you a sale!
  • Marketing insights: You won't get a clear picture of your campaign ROI since the built-in tools are as basic as a salad without dressing.
  • Segmentation and customization: Sure, you can create reports with higher tiers, but analyzing behavior based on marketing intent can feel like piecing together a puzzle at midnight.
  • Alternative attribution modeling: First-touch or custom models? Not in Shopify’s current toolbox, leaving many users in the dark like a cave dweller.

If the free analytics feel like getting the short end of the stick, don’t fret! There are some stellar analytics apps out there that can help, including:

With these tools in your corner, you’ll be ready to tackle those sales like a pro! Let’s keep those sales climbing—after all, nobody likes a downturned graph!

Next, we’re going to chat about how to truly get to the heart of customer interactions through a method known as multi-touch attribution. It’s like following a breadcrumb trail to understand how every little interaction can lead to that coveted purchase.

Understanding Multiple Touchpoints

Multi-touch attribution (MTA) is all about tracking those various interactions customers have with a brand—not just the last click that sealed the deal. Remember that time when we thought a last-click model was adequate? It’s like giving a “Best Supporting Actor” award to the person who brought the popcorn at a movie night! Sure, they played a role, but what about the lead-in, the build-up? This method allows us to see the full picture:
  • Better Budget Allocation: Let’s be honest, no one wants to throw money at ads that do absolutely nothing. MTA helps identify where the cash should actually flow.
  • Resource Optimization: It’s a huge bummer to realize you’re throwing dollars at campaigns that just sit there, gathering proverbial dust.
  • Improved Creative Targeting: The beauty of MTA? We can see which ads hit different notes on the marketing melody. Some are ballads, while others are more like pop anthems.
  • Time-to-Purchase Insights: Knowing how long it takes for customers to make a purchase across channels feels like having the crystal ball we all want in marketing.
Without MTA, it’s like playing a game of charades—guessing and hoping someone will get it right. A solid tool for MTA isn't just a nice-to-have, it’s speaking the language of robust analytics.

The Platform Puzzle

Imagine a platform that connects every sale to every interaction. Talk about solving a puzzle! Some folks rely on the foggy data of Google Analytics, but there’s a better way. Attribution platforms use straightforward, clean customer data gathered right from the source (think direct ad platform integrations). It’s like getting a behind-the-scenes pass to see what really drives those conversions. And instead of vague estimations, these tools help us accurately calculate things like ROAS—no more guessing games here! Here are a few ways MTA can be a lifesaver for analytics:
  • Sales and Spend Connection: This platform syncs ad costs with sales data from platforms like Shopify. It’s like a tightrope walker balancing, giving us a view of ROAS down to specific campaigns and keywords. No more wasted spending on what doesn't work!
  • Customer Journey Overview: This aspect is pure gold. If a customer hears about a brand on a podcast, then clicks through a Facebook ad, signs up via email, then purchases after a chat, the platform tracks all of it! Understanding how these channels merge makes strategy feel less like throwing darts at a wall.
  • Real-Time Reporting: Why juggle between spreadsheets? This tool combines everything into real-time dashboards. Instant insights on ROAS by channel? Yes, please!
By removing the guesswork from analytics, MTA platforms allow brands to make savvy decisions that lead to efficient growth. So, for those serious about marketing—that add-on isn’t just an extra; it’s the star of the show. Keep your eyes peeled; the analytics landscape is ripe for improvement!

Now we are going to talk about customer analytics platforms, those handy-dandy tools that help us peek behind the curtain of our businesses. They’re like the backstage pass at a concert, letting us see which customers are jamming to our tunes, what they’re buying, and their shopping habits over time.

Understanding Customer Behavior Better

Unlike some attribution tools that only discuss channel performances, customer analytics platforms dive deeper. They analyze order history, browsing behavior, and email interactions, revealing insights that can enhance our strategy. Remember the last time you found a forgotten item in your cart? These platforms help us understand what led customers to that moment.

For Shopify merchants, these platforms are practically essential. They help us…

  • Spot high-value customers based on actual behavior.
  • Create smart segments for personalized campaigns.
  • Identify churn risks and jump into action.
  • Measure customer lifetime value (LTV) to align with our goals.
  • Recognize repeat purchase patterns for optimized re-engagement.

At the end of the day, we want to build meaningful relationships; these tools are crucial in defining who keeps our lights on and how we can keep them coming back for more.

Two names that often pop up in this category are Klaviyo and Omnisend. Both are designed to mesh seamlessly with Shopify and give us more clarity on our customers. Let’s break them down.

Klaviyo Analysis

Klaviyo is renowned for its email and SMS marketing prowess, but it’s also a powerful player in customer analytics. It’s like discovering your favorite cookie recipe and realizing it includes the secret ingredient—deep insights!

Strong Qualities

Klaviyo connects directly to our Shopify store, providing an uninterrupted stream of customer activity. With this data, we can categorize customers based on:

  • First versus repeat purchases
  • Products they buy
  • Time since their last order
  • Email engagement history

It even harnesses predictive analytics to project customer behaviors—like who might drop off or when they’re likely to return. Imagine having a crystal ball for your shop!

Limitations

However, Klaviyo doesn’t give a full picture outside its messaging ecosystem. If we have a robust strategy involving paid ads or influencer campaigns, it may miss those vital touchpoints—like inviting someone to a party and forgetting to send the invite.

Omnisend

Omnisend. For those diving into E-commerce, Omnisend offers a user-friendly platform heavy on email and SMS—but it also packs a solid punch with analytics. It’s like finding a Swiss Army knife in the toolbox!

What It Does Well

This tool easily integrates with Shopify, syncing real-time customer data. From order history to engagement with previous messages, it helps us cater to our audience effectively. We can segment by:

  • How often they buy
  • Types of products
  • Interaction with previous messages
  • Total revenue generated

Omnisend’s workflows allow us to automate welcome messages and cart recovery emails, making it super easy to stay engaged—all while making it look effortless!

Shortcomings

Feature Klaviyo Omnisend
Integration Direct with Shopify Direct with Shopify
Predictive Analytics Yes No
Email Automation Strong Strong
Cross-Channel Insights No Limited
User-Friendly Moderate High

Both tools have their strengths and challenges—the key is figuring out which works best for us and our goals. After all, we’re not in this game to play hide and seek with customer data!

Now we are going to talk about a vital aspect of online sales that can often be overlooked: how visitors actually feel when browsing a Shopify store. We’ve all been there—like wandering through a maze with no cheese at the end. It’s all about website behavior analytics, a behind-the-scenes look at what gets customers clicking or what sends them running for the hills.

Understanding Customer Journeys

Google Analytics and Shopify reports tell us the basics: visitor counts, sales volumes, and drop-off rates. Website behavior analytics takes it up a notch to answer the ever-elusive question of *why*. These analytical superheroes use tools like heatmaps, session recordings, and even click-tracking to lay bare how each visitor interacts with our site. Imagine watching a movie of your customer’s shopping experience—where they hesitate, where they dance around the checkout button like it’s hot coal, and what catches their eye (or doesn’t). Understanding this is as crucial as figuring out how to open a jar of pickles—messy if we don’t get it right! Here’s what we can glean from keeping an eye on customer behavior:

  • Spotting friction points during browsing and checkout
  • Identifying attention drop-offs on crucial product pages
  • Pinpointing mobile usability issues that could be killing sales
  • Highlighting gaps between traffic sources and the actual engagement

Getting a handle on this can feel like discovering a secret sale. Wouldn’t we all want more conversions from those precious clicks? By analyzing user behavior, we can make informed decisions that improve the user experience—think better navigation, optimized product pages, and a smoother mobile experience!

One tool that has gained popularity among Shopify users is Hotjar. It’s not just a catchy name; it has serious mind-reading capabilities! Hotjar dives into your store’s user interaction—cleaning up the mess left by standard analytics—with helpful heatmaps and session recordings.

Hotjar: Tool for eCommerce Insights

Hotjar allows us to peek into the way users interact with our store. Think of it as a backstage pass to the concert of customer behavior. From tracking clicks to pinpointing drop-offs, we’ve got our eyes glued on the action.

Strengths of Hotjar

With Hotjar, it becomes crystal clear what’s working and what isn’t. Its heatmaps reveal which sections of a page drive the most attention. Watching session recordings allows us to uncover hidden challenges—like that one time my friend got lost in the checkout jungle because the button was too low! For anyone on Shopify, using this tool to reduce cart abandonment is a game-changer. We can observe where potential customers are interrupted—were they frustrated by a poorly-designed form field? Did a funky layout confuse them on mobile? Knowing this gives us a chance to make impactful changes, such as:

  • Raising the “Buy Now” button’s profile
  • Simplifying the cart process
  • Fixing those sneaky distractions on mobile

These tweaks might seem simple, but trust us, they can have a significant impact on sales. It’s like adding whipped cream to your coffee—suddenly, it’s not just a drink; it’s a treat!

Challenges with Hotjar

Hotjar shines bright, but it’s not without its quirks. Sifting through session recordings can feel a bit like searching for a needle in a haystack, especially if we aren’t sure what we’re after. It’s best used alongside other metrics to help clear up confusion and target our focus.

Now let’s chat about something close to the heart of e-commerce: those fancy analytics platforms that help us make smart decisions. Ever tried flipping a coin to decide what to sell? Spoiler alert: it doesn’t work. So, we’ll explore tools that provide a clearer picture of what’s really going on in our stores.

Tools for E-Commerce Data Insights

So, advanced analytics in e-commerce aren't just about pretty graphs; they help us get to the nuts and bolts of why some products are flying off the shelves while others gather dust. Need to know which items are just taking up space in the warehouse? These tools have your back. Consider how they dig deep into things like profit per product, inventory turnover, and the impact of discounts. For all the Shopify aficionados out there, having the right insights can be as good as finding 20 bucks in an old jacket. You know the feeling!

One platform that stands out is Glew.io. This tool hooks up with Shopify and a variety of other marketing platforms and dishes out insights like they’re on a buffet spread:

  • Find out which products keep customers coming back for more.
  • See how bundling items or upselling influences what people spend.
  • Get a handle on how seasonal trends can mess with your stock levels.
  • Discover which combos of products make the best long-term customers.

All About Glew.io

Glew.io isn’t just some flashy dashboard. It’s built to help Shopify sellers delve deeper into their product performance, inventory status, and what makes customers tick. Forget basic metrics; Glew offers a treasure trove of data to know what’s really boosting—or busting—your profits.

Strengths of Glew.io

Once you integrate Glew with your Shopify store, it syncs up your order information, product listings, and customer data like a well-oiled machine. You end up with automated reports that lighten the load and clarify your entire operation—from managing stock to understanding customer loyalty.

Here are a few things Glew does really well:

  • Detailed Product Analytics: Discover which SKUs bring in the most cash versus just being the most popular. See how discounts shape your bottom line and watch how inventory flows with customer interest.
  • Cohort Analysis: Group your customers by how they got to you or when they made their first purchase. Follow their journey and understand their behavior over time.
  • Insights into Repeat Purchases: Learn what brings back those loyal shoppers who keep their wallets open instead of going silent after one buy.

Where Glew.io Could Improve

The flip side? Glew can be a bit much for smaller brands or teams just dipping their toes into data. For those folks, the depth can feel like trying to drink from a fire hose. And then there’s the pricing model. As your data needs grow, so does your bill, which can give you sticker shock. Some of the snazzy features—like forecasting and advanced reports—only come with pricier plans. But hey, sometimes you’ve got to spend a little to make a lot. Right?

Now we are going to discuss how to effectively build a Shopify analytics setup that feels less like a Rubik's Cube and more like a smooth Sunday morning stroll.

Constructing Your Shopify Analytics Framework

With countless Shopify analytics tools at our disposal, it's surprisingly easy to find ourselves in a situation where everything looks good on paper but resembles a jigsaw puzzle in practice. The secret sauce? Having a clear plan—starting with a solid foundation and building on that as we grow.

Know What You Need and Keep It Simple

Before we dive into a sea of tools, we need to take a good hard look at the data that actually matters. Imagine a small team juggling a couple of paid ads; they don’t need the same arsenal as a 20-person growth squad managing endless campaigns and trying not to trip over inventory.

So, let's ask ourselves some key questions:

  • How many channels are we throwing our money at?
  • What’s our sales cycle like? A week, a month, or more like 'forever'?
  • Are we primarily DTC, B2B, subscriptions, or running a brick-and-mortar circus?
  • How often do we need to wave our performance reports around?
  • Who on our team will actually be using this treasure trove of data—marketers, operations, finance folks, or the executives looking for the next big thing?

This little exercise helps us figure out where to kick things off without throwing cash at tools we don't even need. Nobody wants to pay for a yacht when they only need a rowboat!

Layering Our Analytics Stack

There’s no need to rush into this. Building a Shopify analytics setup is like a delightful three-course meal—it comes together in stages:

  1. Start with Customer Data: Tools like Klaviyo or Omnisend serve as the first course, providing a hearty hub for customer insights. They help us segment our audience and create those irresistible outreach campaigns that keep customers coming back for seconds!
  2. Add Attribution: Now, this is the main course. Proper attribution ties together all our channels and connects our spending to revenue. Without it, every other tool is reporting like lone wolves on a snowy night.
  3. Incorporate Behavioral Analytics: Tools like Hotjar are your best friends here. They tell you how visitors interact with your site, helping identify and smooth over the bumps that are scaring away potential buyers.
  4. Integrate Product and Inventory Analytics: For brands grappling with extensive inventories, tools like Glew.io become our advisors, helping us see the bigger picture of profits and stock trends.
  5. Add Retention and LTV Insights: This part is crucial as we expand. Tools like RetentionX can help us shape long-term strategies for keeping our customers happy and coming back.

Consider Practical Realities

Let’s be real about a few things:

  • Budget: Be sure we know how pricing works. Some platforms have costs tied to order volume or features, and nobody enjoys discovering those hidden fees on Friday night.
  • Technical Know-how: Some tools come with a side of advanced features. Choose ones that won't leave our team feeling like they just took a rocket science class.
  • Team Capacity: A shiny dashboard isn’t useful if nobody has the time or the will to keep it updated. Automation is our best buddy here, but we must ensure the platforms we choose are ready to serve insights without needing constant babysitting.

Integration Is Key

Now, let’s remember, an analytics stack is not just a hodgepodge of software—it’s a system that needs to work in concert. For that to happen, we need seamless data integration. Most of the modern tools provide ways to link up with Shopify, either through:

  • Native Shopify Apps: These are simple to install and sync important data like orders and customers in real time. Easy peasy!
  • Third-party Connectors: Think of tools like Segment or Zapier—great for ferrying data between platforms that don't directly communicate.
  • Custom APIs: These offer flexibility, but they come with a side of development resources and maintenance. A bit of a commitment, if you will!

No matter which route we choose, our goal is clear: ensure our marketing, product, and customer data flows smoothly into one reliable source—without the manual copying and pasting that sets off anxiety.

At the end of the day, having Attribution at the heart of our stack helps to unify everything. With accurate and actionable data rolling in from various sources, we can finally make informed decisions that guide our efforts forward.

Conclusion

By keeping an eye on your Shopify performance and remaining quirky yet professional in how you interact with customers, you can cultivate loyal relationships. The tools available today can make deciphering data feel less like deciphering hieroglyphics and more like flipping through a favorite comic book. Remember to lean on customer feedback like you would on an old friend; it can offer invaluable perspectives. In the end, analyzing your store's performance isn't just about numbers, it’s about building a vibrant community of satisfied customers who look forward to returning to your virtual doorstep.

FAQ

  • What analytics features does Shopify offer for store performance?
    Shopify offers features such as sales performance, customer insights, traffic metrics, product analytics, and basic funnel data.
  • What is multi-touch attribution (MTA)?
    MTA tracks various customer interactions with a brand, providing a comprehensive view of how customers arrive at a purchase, rather than just focusing on the last click.
  • How does MTA improve budget allocation?
    MTA helps identify where marketing dollars should be spent by assessing the performance of different channels and interactions.
  • What are customer analytics platforms used for?
    Customer analytics platforms analyze order history, browsing behavior, and email interactions to provide insights that can enhance marketing strategies.
  • How does Klaviyo assist Shopify merchants?
    Klaviyo offers email and SMS marketing capabilities while providing in-depth customer analytics, including customer segmentation and predictive behaviors.
  • What does Hotjar provide for e-commerce insights?
    Hotjar gives insights into user behavior through heatmaps and session recordings, helping merchants understand customer interactions and identify friction points.
  • What type of information does Glew.io offer?
    Glew.io provides detailed product analytics, cohort analysis, and insights into repeat purchases, helping brands manage their inventory and customer loyalty effectively.
  • What should be considered when building a Shopify analytics framework?
    Key considerations include understanding data needs, budget limitations, technical know-how, team capacity, and ensuring seamless integration of tools.
  • How can automation assist in managing analytics?
    Automation helps streamline data collection and reporting processes, reducing the need for manual updates and enabling teams to focus on analysis rather than maintenance.
  • What role does attribution play in a Shopify analytics stack?
    Attribution unifies the data from various channels, connecting spending to revenue and enabling more informed marketing decisions based on accurate and actionable insights.