Most eCommerce teams track data but have no repeatable system for turning it into decisions. This guide lays out a three-session weekly eCommerce analytics workflow: Monday anomaly check, Wednesday cohort review, Friday product decision. Each step maps to a specific Stormly report so the whole team works from the same numbers and leaves with one clear action per week.
Your store’s overall checkout conversion rate is 2.8%. That number is hiding the real story: one product converts at 0.4%, another at 9.1%, and the “funnel problem” is actually a product mix problem. This guide shows how to break your eCommerce funnel down to the product level, find which specific SKUs are dragging down your overall CVR, and run a product funnel audit that surfaces decisions you can act on this week.
At $1M in Shopify revenue, your built-in analytics still shows sessions, total conversion rate, and top-sellers by volume. But the decisions that drive your next $1M require product-level data that Shopify was never built to provide: which of your 500 SKUs converts best, which products appear most in abandoned carts, and which customer cohort is about to go quiet. This guide maps exactly where Shopify analytics hits its ceiling, what the specific trigger moments look like, and what changes when you add a product analytics layer built for catalog-scale decisions.
New product launch analytics should tell you more than whether a SKU made money in its first week. It should show whether the product is attracting the right traffic, converting above its category benchmark, getting abandoned at checkout, and creating the kind of customer who comes back. This 30-day framework shows eCommerce teams what to measure on day 1, 7, 14, and 30 so they can decide whether to scale, fix, or pause a new arrival before a month is wasted.
Most churn reporting for an online store tells you who already left. That is too late to save margin, repeat revenue, or the customer relationship. This guide shows how to use ecommerce churn prediction with product-level signals like repeat-purchase cadence, category engagement decline, and AOV drift so you can spot at-risk segments roughly 30 days earlier and act on them inside a practical weekly workflow.
eCommerce product analytics is the layer most store operators are missing when Shopify and Google Analytics still leave them guessing which products convert, which ones leak revenue, and which customers are about to disappear. This guide explains what product analytics actually measures in an online store, where Google Analytics stops, and how Stormly turns product-level CVR, cart abandonment by SKU, retention by category, new-arrival performance, and churn signals into actions a merchandising or growth team can take this week.
Most cohort analysis for ecommerce is still too generic. It tells you when customers bought, not which first-purchase product put them on a high-retention or low-retention path. This guide shows how to build ecommerce customer cohorts around product category, read Stormly’s retention view correctly, and use those cohort splits to change acquisition targeting, merchandising, and retention timing before low-value cohorts eat your budget.
Most stores promote the products that generate the most revenue because those are the easiest to see in a default dashboard. The problem is that your bestseller and your best converter are often not the same item, which means you can keep pouring traffic into the wrong products and wonder why conversion rate, AOV, or repeat purchase rate never improve. This guide shows how to use ecommerce product analytics to separate volume from efficiency, read Stormly’s product-level CVR view correctly, and turn that report into better merchandising and campaign decisions.
Most B2B SaaS teams use product analytics to count signups and conversions. That is the wrong use of the tool. The real value is in the behavioral signals that predict, at the individual user level, which trials are drifting toward churn and which accounts are showing early retention risk – before the window to intervene closes. This guide shows how to set up a practical early warning system without a data science team.
Your churn rate tells you what happened last quarter. It tells you nothing about which customers are deciding to leave this month. The metrics worth tracking are product-level behavioral signals that predict departure three to four weeks before it happens: purchase cadence deviation, category engagement drops, and cohort AOV decline within a product segment. This guide shows how to build an at-risk segment that catches customers while the re-engagement window is still open.
Your Shopify dashboard shows 312 orders this month. GA4 shows 189. Shopify is right. The 39% of purchases GA4 is missing is invisibly distorting every conversion rate, ROAS figure, and attribution decision your team makes. This guide explains exactly why GA4 loses Shopify purchase events by default, what it costs you in real decisions, and what server-side capture actually looks like.
Your store-wide cart abandonment rate of 71% is not one number. It is the average of hundreds of individual product rates, some at 22% and some at 89%, and the recovery email you sent went to customers who abandoned all of them indiscriminately. This guide covers how to diagnose cart abandonment at the product level, what the three distinct leak types look like, and how to fix the right one instead of masking the symptom with a discount.
Most eCommerce dashboards are filled with metrics that describe what happened last week without pointing toward a specific next action. Sessions, revenue, and overall conversion rate tell the store-level story while masking everything that matters at the product layer. These 7 KPIs are all product-level metrics, and each is tied to a specific decision you can make this week.
You open Shopify Analytics every Monday and stare at sessions, revenue, and conversion rate for 30 minutes before picking something basically at random to work on. This four-step routine takes 15 minutes and answers the three product-level questions Shopify does not surface by default: which products had unusual moves this week, which are driving cart abandonment, and which customer segments are overdue for re-engagement. It ends with one assigned action, not a list of insights to revisit next week.
Shopify Analytics reports what happened at the store level accurately. What it cannot tell you is which of your 340 products is sitting in 60% of your abandoned carts, which specific product a customer first bought that predicts whether they come back in 30 days, or which category is losing momentum three weeks before it shows up in your revenue chart. These are the five product-level questions that drive actual merchandising decisions, and they require a different analytics layer than what Shopify provides.
Shopify analytics works for beginners, but growing brands hit its limits fast. Compare Shopify reporting vs advanced analytics tools and see when it is time to upgrade to Stormly.
GA4 is notoriously inaccurate for ecommerce. Discover the real reasons behind revenue mismatches, attribution errors, and missing conversions, and what better tracking looks like.
Running an ecommerce store without real analytics is like flying blind. You need to know which products are moving, where customers drop off, and what’s actually driving revenue, not just traffic. But here’s the problem: most analytics tools weren’t built for ecommerce. They track clicks and sessions, but they can’t tell you which SKUs are dragging down margins, which customer segments are worth doubling down on, or why your checkout funnel loses half its visitors between the cart and the confirmation page.
Most GA4 alternatives for ecommerce solve only one part of the Shopify tracking problem. This updated guide explains what actually has to work in 2026: accurate confirmed-order capture, usable acquisition context, and product-level reporting that tells you which SKUs, categories, and customer cohorts deserve action next. If your GA4 dashboard is still missing purchases or flattening everything into session metrics, this is the comparison that matters.
New products are exciting, but they are also risky. Some will fly off the shelves. Others will sit quietly and soak up budget, attention, and precious space on your homepage. The New Arrivals Performance report shows exactly how each new SKU is doing from the moment it lands. You get a clear read on awareness, interest, and purchase, plus the practical steps to turn promising newcomers into consistent revenue.
Every ecommerce team talks about conversion. Fewer talk about the exact moment where money leaks out of the basket. That is what cart abandonment is all about. Our Cart Abandonment Report gives you a clear view of where customers add items to cart but do not buy, down to the SKU, brand, and category. It is practical, it is actionable, and it plugs right into the tools you already use: Shopify, Adobe ecommerce, or Google Tag Manager.
In eCommerce, getting new customers is expensive. Keeping them is where real growth happens.
The problem? Most brands only realize someone’s gone when it’s already too late.
That’s starting to change. With the help of AI analytics, leading retailers can now predict when customers are likely to churn, and act before they do.
Stormly is helping eCommerce teams make this shift by turning their data into clear, predictive insights that keep customers coming back.
The most successful eCommerce brands don’t guess. They rely on data to understand how customers behave, what drives sales, and where to focus next.
But with so much information scattered across tools and reports, turning data into action can be painfully slow.
That’s where Stormly comes in. It gives eCommerce teams a clear view of what’s working, automates routine analysis, and helps them find new ways to grow. The result is faster decisions and higher revenue, without spending half the week building reports.
All four tools have funnels, cohorts, and segments. The real question for an eCommerce operator is whether any of them can tell you which of your 500 SKUs is driving your best customers back, or which product is sitting in 40% of abandoned carts, without custom event tracking, a dedicated data team, or a CSV export. This comparison answers that question directly for GA4, Mixpanel, Amplitude, and Stormly.
Stormly is the only product analytics platform built for e-commerce. Get actionable insights into product performance, size conversion, and A/B tests, with no coding required.
Learn what are data insights and harness them to boost smarter business decisions. Our guide reveals key data collection, analysis, and practical applications.
Boost your e-commerce store’s performance using predictive product analytics. Learn how Stormly helps personalize experiences, prevent churn, and increase conversions.
Set up advanced product analytics in 5 minutes with Stormly’s Google Tag Manager integration: deeper insights, no code, smarter decisions.
Stormly improves dashboard speed and report scalability for large teams. Learn how our R&D study delivered faster analytics and reduced load time by 50%.
Stormly, a trailblazer in the world of product analytics, is at the forefront of utilizing the newest user interface paradigm that Nielsen Norma group has deemed a revolutionary shift in computing history. This shift, called “Intent-Based Outcome Specification”, is driven by advanced Artificial Intelligence systems, such as OpenAI’s GPT-4, and is paving the way for a new interaction model, where users specify their desired outcomes instead of specifying each step for the computer to follow.
Stormly’s innovative approach empowers product managers to not only understand the data better but also to make informed decisions tailored to their product’s specific needs. Today, we’re excited to announce the groundbreaking integration between Stormly and Chat GPT-4, a leading AI technology. This powerful alliance promises to revolutionize the product analytics industry, making data analysis more intuitive and actionable than ever before. By fusing Stormly’s robust analytics capabilities with Chat GPT-4’s advanced AI-driven insights, we have created a unique product analytics tool that feels like having a personal AI-powered product manager by your side.
In today’s competitive digital landscape, product managers are constantly seeking new ways to improve their products and create a seamless user experience. Traditional A/B testing and user journey analysis are well-known techniques used to optimize product performance. However, these methods may not be sufficient to truly understand the complexities of user behavior and data challenges. This article explores the importance of the aha moment metric and how Stormly is revolutionizing the way companies approach product data experimentation.
When it comes to driving e-commerce success, nothing is more important than making sure you have the right infrastructure and tools in place. Without a reliable system that offers insights into customer behaviour and market trends, it’s impossible to keep up with your competitors. Stormly provides great value for webshop product managers looking to get an edge over other businesses by allowing them to analyze their customer data quickly and efficiently. While Amplitude or Mixpanel boast similar capabilities, we believe that Stormly brings something extra when it comes to understanding user behaviour in the digital landscape, featuring superior analytics power that makes predicting future performance easier than ever before. In this blog post, we’ll discuss why Stormly is an ideal choice for those seeking an effective way of improving their e-commerce store’s performance compared to its competition!
Product managers - how would you like a tool to help you leverage greater accuracy in your product usage metrics?
With more accurate product usage metrics, it’s possible to gain unprecedented insight into user behavior and keep track of performance trends.
Wouldn’t it be great if there was an easier way to make sure that the insights gleaned from these metrics were valid and could lead to effective decision making processes?
Well now there is - with relative event filtering at Stormly, getting pinpoint accuracy in product usage stats just got a lot simpler. Read on as we explore this exciting development and what it might mean for you!
Are you looking for a comprehensive tutorial on using Stormly? You’ve come to the right place! In this article, we will go through step-by-step instructions to understand how to leverage the features of Stormly analytics platform and start analyzing your data in no time.
Whether you’re an experienced user or just starting out with Stormly, this detailed tutorial will provide all the insights necessary to maximize your benefit from it. So put on your learning caps, let’s get started!
Getting the most out of Stormly starts with understanding how user and event reports differ. Before diving in, it’s important to comprehend these variations first so you can make your analysis as thorough and accurate as possible. Once that’s complete, embracing even complex product questions is within reach!
As a product manager, you have to juggle many balls at once - working with both your engineering team and your stakeholders to make sure the right features are getting built into your product. So which tool should you use to help you manage this process effectively? Stormly or Heap? In this blog post, we’ll compare the two tools so that you can make an informed decision about which one is best for your team.
So you’re a product manager and you need to start doing some product analytics. You’ve heard good things about both Stormly and Looker, but you’re not sure which one is the right tool for you. This can be a tough decision, but don’t worry, we’re here to help. In this blog post, we’ll compare and contrast Stormly and Looker, so that you can decide which one is the best tool for your needs.
Which tool is better for Product Analytics? Stormly or Google Analytics? This can be a difficult question to answer, especially since both tools offer a lot of features and benefits. In order to make the best decision for your business, you need to understand the pros and cons of each tool. In this blog post, we will compare Stormly and Google Analytics and help you decide which tool is right for your product analytics needs. Stay tuned!
Data is the lifeblood of any successful product manager. You can’t make informed decisions without tracking and analyzing how your products are performing, but which tool should you use? Choose Stormly or Tableau to organize all that data into something useful for yourself! Here’s a comparison between these two products so we’ll have more information on what each offers.
If you’re a product manager, then you know that data is essential to your success. You need to be able to track and analyze how your products are performing in order to make informed decisions about how to improve them. So which tool should you use for product analytics? Stormly or Power BI? Here’s a comparison of the two tools so you can decide for yourself.
Are you looking for a better way to understand how your users are using your product? Or, are you trying to track user engagement and growth? If so, then you’re probably wondering if Stormly or Amplitude is the right tool for you. In this blog post, we’ll compare and contrast both tools, so that you can decide which product analytics is better for your needs. Stay tuned!
Choosing the right product analytics can be the difference between success and failure for your product. With so many options available, it can be difficult to decide which one is best for you. In this post, we’ll compare Stormly and Mixpanel to help you make a decision. Both Stormly and Mixpanel are popular choices among product managers, but they have different strengths and weaknesses. Let’s take a closer look at each one.
Which product analytics tool is best for you? That is a question that all product managers must ask themselves from time to time. In this blog post, we will be comparing and contrasting Stormly and Pendo – two of the most popular product analytics tools on the market. We will break down each tool’s features and help you decide which one is right for your team. Let’s get started!
Most product managers track various key performance indicators (KPIs) to measure the success of their product. But few focus on the aha-moment, that magical instant when users understand how your product works and what it can do for them. Why is the aha-moment so special? And how can you make sure your product delivers an amazing aha-moment experience for users? Read on to find out.
Do you ever feel like you’re not sure what to build next for your product? You’re not alone. Figuring out which features to prioritize can be a difficult task, especially when your data is telling you different things. In this blog post, we’ll explore how to use qualitative and quantitative data to optimize your product roadmap. We’ll also share some tips on how to make sure that your data-driven decision-making is effective. So, if you’re looking for guidance on what to build next, read on!
Are you looking for a better way to manage your product data? Stormly could be the tool for you. Stormly is a cloud-based platform that makes it easy to collect, organize, and analyze your product data. In this article, we’ll introduce you to the basics of using Stormly. We’ll cover how to create an account, run Insights, create Dashboards and generate reports. Ready to get started? Let’s go!
In the past, product managers have relied on code to track data and analytics. However, advances in artificial intelligence (AI) are making it possible to get all the same insights without any coding. This means that product managers can now focus on their products and user experience, rather than on data analysis. In this blog post, we will explore why no code approach to analytics is the future and how you can get started.
Anyone who has been paying attention to the news recently knows that a recession is on the horizon. While there is no way to know for sure when it will be at the highest point, there are ways to prepare your business for potential downturns. One of those ways is by using product analytics to predict how your business might be affected. In this blog post, we’ll explore how you can use product analytics to do just that. Stay ahead of the curve and recession-proof your product with the help of analytics!
Percentiles are critical for making more informed product decisions, based on the actual usage of large groups of users. By comparing percentiles of different segments and behavioral cohorts, we can identify positive and negative patterns in our data over time. This can allow us to anticipate how future values might change based on current or past trends and make adjustments as necessary. This is our second article from our series on using percentiles with product analytics. In this article, we’re going to dive deeper and show you how to forecast, discover trends and detect anomalies in percentiles based on product metrics.
Data analytics can be tricky, especially when the numbers are based on averages. In reality you might find that what’s happening in your product isn’t always reflected by averages, and conclusions may not always hold up to scrutiny! This is why Stormly has always provided more insightful aggregation metrics, such as median and histograms. This shows a more realistic distribution of metrics. For example, our Product Feature Analysis insight shows not only the average times a user interacted with a feature, but also a full distribution of that usage for each feature.
Google Analytics 4 has been released, and with it comes a lot of new features and changes. If you’re like many people, you might be considering making the switch from your current analytics platform to Google Analytics 4. But before you do, there are some things you should know. In this blog post, we’ll take a look at some of the pros and cons of using Google Analytics 4. We’ll also show you how to migrate your data over to the best alternative for Google Analytics, so that you can make an informed decision about whether or not to switch. So without further ado, let’s get started!
As anyone who has ever used Stormly knows, we are constantly striving to make our product better. Our team is always working on new ways to improve the user experience and make it easier for our customers to get the results they want. One of the ways we have done this is by making it easier to narrow down users in any report. For example, you can now ask questions like: give me all users that played a dance song of at least two minutes in length in the last 4 days. This change makes it much easier to get the specific results you are looking for, and we are confident that our users will find it to be a valuable addition to Stormly. Read on to know more about this unique feature!
Whether you’re a product or marketing manager or data analyst, your job requires choosing and using the right tools. But what if there were a tool that could eliminate the need for five other tools?
As a product manager or marketing manager, you know that analytics are important. But what are the basic metrics you should always measure? In this blog post, we’ll break it down for you. We’ll also give you some tips on how to use these metrics to improve your products and marketing campaigns. So read on – your insights await!
Most product feature retention advice assumes you run a SaaS app. For an online store, the real question is which products, categories, and first-purchase experiences actually bring customers back. This updated guide reframes product feature retention for eCommerce, shows how to measure it inside Stormly’s product and category retention reports, and explains how to turn those curves into better merchandising, lifecycle, and churn-prevention decisions.
If you are a product manager, then you know that it is important to track your product’s analytics. This helps you figure out which items in your product lineup convert best with customers. In order to do this, you need to use the right tools and follow the right steps. In this blog post, we will discuss how to find out which items convert best with the use of product analytics. We will also provide tips on how to increase conversion rates for your products. So, if you want to learn more about this topic, keep reading!
If you’re like most product managers, you’re constantly juggling a million tasks and trying to find ways to automate or optimize your work. Well, we have some good news: Stormly’s newest feature can help you detect new segments or anomalies in your data as they arise. This means that you’ll be able to respond more quickly and effectively to changes in your customer behavior or product performance.
We are excited to announce the release of our unified funnel steps feature! This new feature allows you to see all of your funnel steps in one place, making it easier to track your progress and identify any areas that need improvement. This means that you can now take any number of events and combine them into a single funnel step. This allows you to get a true understanding of how your customers are interacting with your brand.
This week, we’re excited to announce a new feature at Stormly: the ability to format individual values on charts and tables. This is a great way to customize your data visualizations for greater clarity and insight. For example, you can now rename a funnel step or line chart series, and apply separate formatting to that value with its own prefix, formula, decimals, etc.
Anomaly detection is the process of identifying unusual or unexpected activities in data. Implementing anomaly detection can be a daunting task, but with the right tools it can be easy and relatively painless. In this post, we will explore some of the options for implementing anomaly detection and show how they can help you identify and troubleshoot problems in your data. We will also take a look at some of the challenges associated with detecting anomalies, and how to overcome them. So read on to learn more about how to implement anomaly detection!
The goal of any business is growth. Achieving this requires making accurate forecasts for what the future holds. Doing so isn’t easy for product managers though - predicting customer behavior is often an inexact science. However, there are various techniques that can help make forecasting a little less daunting. In this blog post, we’ll discuss some of the most effective methods for doing analytics forecasting. We’ll also look at examples from real-world businesses who have applied these techniques successfully. By reading this post, you will learn how to better understand your customers’ needs and wants, set achievable goals for your product, and more.
Segmentation is a critical process for all product managers. By dividing your users into groups, you can better understand and cater to their needs. In this guide, we’ll explore the different types of user segmentation, and show you how to apply them to your own products. So, whether you’re just starting out in product management or you’re looking for new ways to improve your user base, read on for everything you need to know about user segmentation!
As a product manager, you know that finding your product’s aha moment is key to its success. But how can you do that quickly and efficiently? In this post, we’ll share some tips on how to find your product’s aha moment fast. So read on and find out how you can make your product successful!
When it comes to product management, there are a few key roles that people tend to think of. These include the product manager, the product owner, and the UX designer. While all of these roles are important, there is a lot of confusion about the difference between the product manager and the product owner. In this post, we will explore the role of the product manager and explain what sets them apart from the product owner. We will also discuss why it is important for both roles to work together to create successful products.
As a product manager, you’re constantly working to keep users engaged with your product. But what does that really mean? And how can you make sure users remain hooked? In this blog post, we’ll explore what user engagement is and offer some tips on how to foster it. Stay tuned!
Your webshop data can tell you a lot about how your business is doing and what you should be focusing on. In this blog post, we’ll go over some product metrics that you should keep an eye on based on your webshop data. By tracking these, you’ll be able to make better decisions about which areas to focus on and improve your overall sales performance. So, let’s get started!
If you’re not familiar with analytics or don’t know how to get started, this can seem like a challenging task. But don’t worry - in this blog post, we’ll walk you through everything you need to know about getting started with product analytics.
As a product manager, it’s important to have a strong understanding of product analytics. This essential data can help you make better decisions about your products and their future. But what is product analytics, exactly? And more importantly, what can it do for your products? In this post, we’ll explore those questions and more. So read on to learn everything you need to know about product analytics!
Sales forecasting can seem daunting, but with the right tools and approach it can be easy and accurate. This blog post will walk you through the steps to forecast sales, using historical data and trend analysis. Armed with this information, you’ll be able to make sound decisions about your product’s future. Stay tuned for more tips on how to improve your forecasting skills!
Collecting product data is essential to understanding how your products are performing in the market. However, sorting through all of that data can be daunting. Here are some of the most important insights you can glean from your product data. By understanding these key findings, you can make more informed decisions about your products and their future success.
Dashboards turn raw e-commerce data into decisions. Here are the key benefits of dashboards for product analytics teams, from tracking cart abandonment and purchase funnels to sharing insights across your org.
What does it mean to have a successful product management strategy? And how can you ensure your products reach their full potential? In this post, we’ll explore the essentials of a successful product management strategy – from setting achievable goals, to creating an effective workflow. We’ll also offer tips and advice on how to overcome common challenges faced by product managers. So if you’re looking to take your products to the next level, read on for insights and inspiration!
No matter how much experience you have, transitioning into a new product manager role is always a challenge. The good news is that there are steps you can take to make the process easier and set yourself up for success. In this blog post, we’ll share four tips that will help new product managers settle into their role. Stay tuned for more insights on how to excel in your PM career!
In order to make effective product decisions, product managers need data. But simply having data is not enough. Product managers also need to be able to visualize that data in order to understand it and see trends. Data visualization tools can help them do this, and they are an essential part of any product manager’s toolkit. In this blog post, we will explore why data visualization is so important for product managers and discuss some of the best tools available.
Making decisions about product development can be difficult, but using data can make it easier. By looking at what your users are doing and how they are using your product, you can get a better understanding of what needs to change or stay the same. Data can help you determine what features to focus on, what areas need improvement, and when it’s time to call it quits on a project. So how do you use data to make better product decisions? Let’s take a look.
In today’s competitive marketplace, product led analytics is essential for driving growth and staying ahead of the competition. By understanding customer behavior, you can make changes to the product that improve the user experience and increase conversions. Don’t miss out and learn more about product led analytics!
If you’re a product manager, then you know that tracking key product metrics is essential to steering your product in the right direction. But what are the key product metrics that you should be tracking? And how do you track them effectively? In this blog post, we’ll discuss six key product metrics that every product manager should track. We’ll also provide tips on how to track these metrics effectively. So if you’re looking for ways to improve your product management skills, then read on!
Being a successful product manager isn’t easy - it requires a lot of skill and experience. That’s why it’s important to have the right tools at your disposal. In this blog post, we’re going to share a few tools that are especially helpful in a job of a product manager. These tools include prototyping and design tools, as well as analytics. With these tools in your arsenal, you will be able to take your product strategy to the next level!
Most product managers would agree that Power BI is a great tool for reporting and data visualization. However, many find that it does not help improve their product. In this blog post, we will explore some of the reasons why Power BI might not be the best tool for product management and suggest the best alternative. Stay tuned!
As a product manager, you’re likely already familiar with Tableau. It’s a popular data visualization tool used by many organizations to help them understand their data better. But despite its popularity, Tableau doesn’t actually help improve your product. In this blog post, we’ll explain why and offer some alternatives that will be more beneficial for your product team.
So you’ve heard of product led growth, but what does that really mean? And more importantly, how can you make it work for your business? In this post, we’ll break down what product led growth is and explore some tips for putting it into action. Stay tuned!
If you’re a product manager, then you know that tracking active users is one of the most important things you can do to measure your product’s success. But what happens when your active user numbers start trending down or suddenly spike up? How do you know if it’s just a normal variation, or if there’s actually something wrong with your product? In this blog post, we’ll show you how to use forecasting and anomaly detection insights from Stormly to keep tabs on your active users metric and detect any unexpected changes. Stay ahead of any potential problems before they happen!
At Stormly we’re all about product-led analytics. Our goal is to make sure we give you the insights needed to improve your product metrics.
There are plenty of tools out there that can tell you what your conversion rate is, but none of them will show you what behavior should be changed in your customer journey. And this is really the only way to find out how to improve your product metrics.
In this article we’ll show you how to get to the right insights that will improve your product goals, in two easy steps. Let’s dive right in!
All products, no matter how successful they are, need to constantly be tweaked and improved in order to stay ahead of the competition. One way to measure it is by looking at how sticky your product is. ‘Active Users’ insight from Stormly can help you do just that. This metric measures how many people are using your product on a regular basis. Knowing how sticky your product is can help you make decisions about where to focus your efforts and improve your product’s user experience.
No doubt you’ve heard the term ‘Daily Active Users’ thrown around a lot lately. It seems like every company is bragging about how many DAUs they have. But what does that number actually mean? Is it an important metric? And more importantly, is it a bullshit, well, a vanity, metric?
When it comes to choosing a tool for product analytics, there are a lot of options out there. Two of the most popular choices are Stormly and Mixpanel. So, which one should you choose? In this blog post, we’ll compare some of the biggest benefits of using Stormly over Mixpanel. Stay tuned!
If you’re looking for an affordable product analytics tool that offers the features of Amplitude, but is European-based, look no further than Stormly. It is a European alternative to Amplitude that’s growing in popularity among product managers. Like Amplitude, Stormly provides insights into user behavior, but it’s much cheaper and easier to use. Plus, it has all the features you need to track your product’s success.
Do you ever feel like you’re throwing spaghetti at the wall and seeing what sticks? Implementing new features into your product can be a lot like that. You never really know how well the new added features will be received by your users. If you know that issue, you’re not alone. Product managers often struggle with measuring the success and adoption of new features. In this blog post, we’ll share some tips on how to do just that.
Product analytics tracks how users behave inside your product. Marketing analytics tracks how they find it. Here’s a side-by-side breakdown of goals, data types, platforms, and when to use each.
NetDoktor, like many others, uses Google data to find out more about their readers. However, sending your personal information through servers that are controlled by an American company, means that intelligence agencies can demand Google to hand over data from European citizens.
Considering that risk, the Austrian data regulator officially announced that, by using Google Analytics, NetDoktor was found guilty of breaking GDPR.
Product managers are responsible for developing and managing pricing models, which is a very important part of the product development life cycle. For this reason, it’s critical that you choose the right pricing model in order to maximize revenue and satisfy customers’ needs.
How many times have you opened Google Analytics, looked at one of the reports, and as a result, got an insight that led you to an idea on how to actually improve your product? It’s probably close to zero.
In this blog post, we’ll walk you through the process of getting the most out of Stormly Dashboards and show you how you can look at the same Insights from different angles. Read on to get started!
Having a possibility to modify the things like “days” and “hours” may seem small but can make a huge difference when looking at charts. This blog post will walk you through some easy formatting tips for making your dashboards look great!
The new Netflix documentary “The Social Dilemma” portrays how popular social services like Facebook, Instagram, or Google manipulate the users without them even realizing it.
As a tech person, with a marketing and UX background, I decided to share my view on a few aspects discussed in the film.
One of the basic but most effective forms of experimentation while building a product or running an ad campaign is A/B testing. It sounds very trivial, however those simple changes might significantly improve your conversions and what follows, revenue.
We know, as a Product Manager, you’re probably looking for the next best analytics tool to replace your current one. Stormly is an upgrade from Amplitude and is perfect for most use cases.
With so many tools and integrations out there, it can be hard to keep track of them all. Fear not! Stormly is now integrated with MParticle.
It’s so frustrating to hear that a customer is unhappy with your product. Especially when you’re not sure what the problem is! One way to do this is by using Stormly’s User Journey Insight - which lets you see where people are dropping off inside your product or app.
Most analytics tools were built for SaaS product teams, not eCommerce operators. This comparison looks at the one question that matters: can the tool tell you which of your 500 SKUs is driving your best customers back, without custom event tracking, data exports, or a data team? Here’s how Amplitude, Mixpanel, GA4, and ContentSquare stack up against Stormly for eCommerce product decisions.
When you are working on a product, there is an overwhelming amount of user research, data gathering and analysis. It can be too easy to get caught up in the details and lose sight of the big picture. But it’s not enough to just know what users say they want or even how they act; you also need to understand why people do things so that your product performs as expected, every time.
Product features can be a make or break deal for consumers considering purchasing your product. That’s why it is crucial to figure out what’s important to them by analyzing what features you have and comparing their intensity and usage relative to other product features you have.
Yogile’s success story started when it only took 5 minutes for Yogile to run Insights and tie the analysis together. As a result, they doubled their conversion rate by discovering the Aha-moment and redesigning its user journey. Want to double your conversion too? Read how to do it in a few simple steps!
You see a drop in sales for the last few days, and start to panic. By running a forecast you will know if this decrease in sales is expected or a real problem. A forecast may indicates that because of seasonality, your sales sales are always down 30% starting this time of the year.
Amplitude recently announced their new Milestone Analysis. While doing this analysis can be useful in some cases, it’s nowhere close to uncovering your true aha-moment. Read why.
Based on different sources and industries, the overall shopping cart abandonment rate is somewhere between 60% and 80%. We collected four of the most common ways to decrease the abandonment rate and dig into the problem a little deeper.
One of the most common challenges when trying out a new data tool is collecting historical data and being able to use it for analysis.
It’s probably needless to say that TechCrunch for years, has been one of the top online publishers focusing on the tech industry. Thousands of startup founders try every day to get the editor’s attention to their product. A dream is to get featured, which means getting the attention of the leaders in the tech industry and if lucky, opening the door to endless business and investment opportunities.
Until recently, most businesses were following their strategies set out for this year. Right now, most companies have seen their plans invalidated by the global pandemic we are in at the moment.
Only a few weeks ago, a vision of a global pandemic and a nationwide quarantine seemed like something surreal. The beginning of 2020 looked promising and some assumed that the expected market breakdown will eventually not happen. But here it is.