What is Crazy Egg and what are its top alternatives?
Crazy Egg is a user-friendly heat mapping tool that allows website owners to visualize how visitors interact with their site through heat maps, scroll maps, and more. Key features include A/B testing, session recordings, and user feedback tools. However, Crazy Egg can be expensive for small businesses and lacks advanced features like real-time analytics and detailed segmentation.
Hotjar: Hotjar offers heat maps, session recordings, surveys, and user feedback tools. It also includes features like funnels and form analytics. Pros include an affordable pricing structure and a wide range of features, while cons compared to Crazy Egg may include a less polished user interface.
Mouseflow: Mouseflow provides heat maps, session replays, funnels, and form analytics. It also offers features like feedback widgets and user-centric reporting. Pros include robust analytics capabilities, but cons compared to Crazy Egg could include a higher price point.
Lucky Orange: Lucky Orange offers heat maps, live chat, visitor recordings, and form analytics. It also provides features like conversion funnels and real-time analytics. Pros include a comprehensive set of tools, but potential cons compared to Crazy Egg may include a steeper learning curve.
FullStory: FullStory provides session replay, heat maps, and monitoring features. It also offers advanced search and segmentation capabilities. Pros include powerful analytics tools, but cons compared to Crazy Egg might include a higher cost for additional features.
Inspectlet: Inspectlet offers session recordings, heat maps, form analytics, and user feedback tools. It also includes features like error tracking and A/B testing. Pros include a range of useful tools, but cons compared to Crazy Egg could involve the pricing structure.
ClickTale: ClickTale provides heat maps, session replays, conversion analytics, and mobile app analytics. It also offers features like behavioral targeting and customer journey analysis. Pros include advanced analytics capabilities, while cons compared to Crazy Egg may include a complex implementation process.
VWO: VWO offers heat maps, A/B testing, visitor recordings, and user surveys. It also includes features like targeting and personalization tools. Pros include a robust set of optimization features, but cons compared to Crazy Egg could include a higher price for additional functionality.
Smartlook: Smartlook provides session recordings, heat maps, and conversion funnels. It also offers real-time analytics and event tracking capabilities. Pros include a user-friendly interface, but cons compared to Crazy Egg might include fewer customization options.
Ptengine: Ptengine offers heat maps, session replay, and A/B testing features. It also provides visitor segmentation and behavior tracking tools. Pros include a simple setup process, while cons compared to Crazy Egg may include limited integrations with other platforms.
ClicData: ClicData provides customizable dashboards, data visualization tools, and real-time analytics capabilities. It also offers features like data transformation and sharing options. Pros include extensive customization options, but potential cons compared to Crazy Egg could involve a focus on broader analytics rather than user behavior tracking.
Top Alternatives to Crazy Egg
- Hotjar
See how visitors are really using your website, collect user feedback and turn more visitors into customers. ...
- Google Analytics
Google Analytics lets you measure your advertising ROI as well as track your Flash, video, and social networking sites and applications. ...
- Mouseflow
Mouseflow records videos of your site visitors and generates heatmaps highlighting areas users are clicking, scrolling and ignoring. Immerse yourself in their behavior to maximize conversions and customer satisfaction. ...
- Optimizely
Optimizely is the market leader in digital experience optimization, helping digital leaders and Fortune 100 companies alike optimize their digital products, commerce, and campaigns with a fully featured experimentation platform. ...
- ClickTale
ClickTale tracks every mouse move, click and scroll, creating playable videos of customers’ entire browsing sessions as well as powerful visual heatmaps and behavioral reports that perfectly complement traditional web analytics. As a fully hosted subscription service, ClickTale is cost-effective and quick to set up. ...
- Inspectlet
Inspectlet records videos of your visitors as they use your site, allowing you to see everything they do. See every mouse movement, scroll, click, and keypress on your site. You never need to wonder how visitors are using your site again. ...
- VWO
Conversion Optimization Platform is an all-in-one data analytics, research, and testing suite to optimize your websites and applications to achieve the desired goal. ...
- JavaScript
JavaScript is most known as the scripting language for Web pages, but used in many non-browser environments as well such as node.js or Apache CouchDB. It is a prototype-based, multi-paradigm scripting language that is dynamic,and supports object-oriented, imperative, and functional programming styles. ...
Crazy Egg alternatives & related posts
Hotjar
- Doesn't work with iframe4
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Sometimes #ad-blocking addons can cause a real headache when working with JavaScript apps. Onboarding assistants (Appcues + elevio ), chat (Intercom) and product usage insight (Hotjar) have all landed on their blacklists. I guess there is a perfectly good reason for this that I just don't know.
In order to fix this, we had to set up our own content delivery service. We chose Amazon CloudFront and Amazon S3 to do the job because it has a good synergy with Heroku PaaS we are already using.
Segment has made it a no-brainer to integrate with third-party scripts and services, and has saved us from doing pointless redeploys just to change the It gives you the granularity to toggle services on different environments without having to make any code changes.
It's also a great platform for discovering SaaS products that you could add to your own – just by browsing their catalog, I've discovered tools we now currently use to augment our main product. Here are a few:
- Heap: We use Heap for our product analytics. Heap's philosophy is to gather events from multiple sources, and then organize and graph segments to form your own business insights. They have a few starter graphs like DAU and retention to help you get started.
- Hotjar: If a picture's worth a thousand words, than a video is worth 1000 * 30fps = 30k words per second. Hotjar gives us videos of user sessions so we can pinpoint problems that aren't necessarily JS exceptions – say, logical errors in a UX flow – that we'd otherwise miss.
- Bugsnag: Bugsnag has been a big help in catching run-time errors that our users encounter. Their Slack integration pings us when something goes wrong (which we can control if we want to notified on all bugs or just new bugs), and their source map uploader means that we don't have to debug minified code.
- Free1.5K
- Easy setup926
- Data visualization890
- Real-time stats698
- Comprehensive feature set405
- Goals tracking181
- Powerful funnel conversion reporting154
- Customizable reports138
- Custom events try83
- Elastic api53
- Updated regulary14
- Interactive Documentation8
- Google play3
- Industry Standard2
- Advanced ecommerce2
- Walkman music video playlist2
- Medium / Channel data split1
- Irina1
- Financial Management Challenges -2015h1
- Lifesaver1
- Easy to integrate1
- Confusing UX/UI11
- Super complex8
- Very hard to build out funnels6
- Poor web performance metrics4
- Very easy to confuse the user of the analytics3
- Time spent on page isn't accurate out of the box2
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We used to use Google Analytics to get audience insights while running a startup and we are constantly doing experiments to lear our users. We are a small team and we have a lack of time to keep up with trends. Here is the list of problems we are experiencing: - Analytics takes too much time - We have enough time to regularly monitor analytics - Google Analytics interface is too advanced and complicated - It's difficult to detect anomalies and trends in GA
We considered other solutions on a market, but found 2 main issues: - The solution created for analytic experts - The solution is pretty expensive and non-automated
After learning this fact we decided to create AI-powered Slack bot to analyze Google Analytics and share trends. The bot is currently working and highlights trends for us.
We are thinking about publishing this solution as a SaaS. If you are interested in automating Google Analytics analysis, drop a comment and you'll get an early access.
We will implement this solution only if we have 20+ early adaptors. Leave a message with your thought. I appreciate any feedback.
In order to accurately measure & track user behaviour on our platform we moved over quickly from the initial solution using Google Analytics to a custom-built one due to resource & pricing concerns we had.
While this does sound complicated, it’s as easy as clients sending JSON blobs of events to Amazon Kinesis from where we use AWS Lambda & Amazon SQS to batch and process incoming events and then ingest them into Google BigQuery. Once events are stored in BigQuery (which usually only takes a second from the time the client sends the data until it’s available), we can use almost-standard-SQL to simply query for data while Google makes sure that, even with terabytes of data being scanned, query times stay in the range of seconds rather than hours. Before ingesting their data into the pipeline, our mobile clients are aggregating events internally and, once a certain threshold is reached or the app is going to the background, sending the events as a JSON blob into the stream.
In the past we had workers running that continuously read from the stream and would validate and post-process the data and then enqueue them for other workers to write them to BigQuery. We went ahead and implemented the Lambda-based approach in such a way that Lambda functions would automatically be triggered for incoming records, pre-aggregate events, and write them back to SQS, from which we then read them, and persist the events to BigQuery. While this approach had a couple of bumps on the road, like re-triggering functions asynchronously to keep up with the stream and proper batch sizes, we finally managed to get it running in a reliable way and are very happy with this solution today.
#ServerlessTaskProcessing #GeneralAnalytics #RealTimeDataProcessing #BigDataAsAService
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Optimizely
- Easy to setup, edit variants, & see results50
- Light weight20
- Best a/b testing solution16
- Integration with google analytics14
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Hey all, I'm managing the implementation of a customer data platform and headless CMS for a digital consumer content publisher. We're weighing up the pros and cons of implementing an OTB activation platform like Optimizely Recommendations or Dynamic Yield vs developing a bespoke solution for personalising content recommendations. Use Case is CDP will house customers and personas, and headless CMS will contain the individual content assets. The intermediary solution will activate data between the two for personalisation of news content feeds. I saw GCP has some potentially applicable personalisation solutions such as recommendations AI, which seem to be targeted at retail, but would probably be relevant to this use case for all intents and purposes. The CDP is Segment and the CMS is Contentstack. Has anyone implemented an activation platform or personalisation solution under similar circumstances? Any advice or direction would be appreciated! Thank you
related ClickTale posts
- Does what it says perfectly4
- Easy setup3
- Feature rich1
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JavaScript
- Can be used on frontend/backend1.7K
- It's everywhere1.5K
- Lots of great frameworks1.2K
- Fast898
- Light weight745
- Flexible425
- You can't get a device today that doesn't run js392
- Non-blocking i/o286
- Ubiquitousness237
- Expressive191
- Extended functionality to web pages55
- Relatively easy language49
- Executed on the client side46
- Relatively fast to the end user30
- Pure Javascript25
- Functional programming21
- Async15
- Full-stack13
- Setup is easy12
- Future Language of The Web12
- Its everywhere12
- Because I love functions11
- JavaScript is the New PHP11
- Like it or not, JS is part of the web standard10
- Expansive community9
- Everyone use it9
- Can be used in backend, frontend and DB9
- Easy9
- Most Popular Language in the World8
- Powerful8
- Can be used both as frontend and backend as well8
- For the good parts8
- No need to use PHP8
- Easy to hire developers8
- Agile, packages simple to use7
- Love-hate relationship7
- Photoshop has 3 JS runtimes built in7
- Evolution of C7
- It's fun7
- Hard not to use7
- Versitile7
- Its fun and fast7
- Nice7
- Popularized Class-Less Architecture & Lambdas7
- Supports lambdas and closures7
- It let's me use Babel & Typescript6
- Can be used on frontend/backend/Mobile/create PRO Ui6
- 1.6K Can be used on frontend/backend6
- Client side JS uses the visitors CPU to save Server Res6
- Easy to make something6
- Clojurescript5
- Promise relationship5
- Stockholm Syndrome5
- Function expressions are useful for callbacks5
- Scope manipulation5
- Everywhere5
- Client processing5
- What to add5
- Because it is so simple and lightweight4
- Only Programming language on browser4
- Test1
- Hard to learn1
- Test21
- Not the best1
- Easy to understand1
- Subskill #41
- Easy to learn1
- Hard 彤0
- A constant moving target, too much churn22
- Horribly inconsistent20
- Javascript is the New PHP15
- No ability to monitor memory utilitization9
- Shows Zero output in case of ANY error8
- Thinks strange results are better than errors7
- Can be ugly6
- No GitHub3
- Slow2
- HORRIBLE DOCUMENTS, faulty code, repo has bugs0
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Oof. I have truly hated JavaScript for a long time. Like, for over twenty years now. Like, since the Clinton administration. It's always been a nightmare to deal with all of the aspects of that silly language.
But wowza, things have changed. Tooling is just way, way better. I'm primarily web-oriented, and using React and Apollo together the past few years really opened my eyes to building rich apps. And I deeply apologize for using the phrase rich apps; I don't think I've ever said such Enterprisey words before.
But yeah, things are different now. I still love Rails, and still use it for a lot of apps I build. But it's that silly rich apps phrase that's the problem. Users have way more comprehensive expectations than they did even five years ago, and the JS community does a good job at building tools and tech that tackle the problems of making heavy, complicated UI and frontend work.
Obviously there's a lot of things happening here, so just saying "JavaScript isn't terrible" might encompass a huge amount of libraries and frameworks. But if you're like me, yeah, give things another shot- I'm somehow not hating on JavaScript anymore and... gulp... I kinda love it.
How Uber developed the open source, end-to-end distributed tracing Jaeger , now a CNCF project:
Distributed tracing is quickly becoming a must-have component in the tools that organizations use to monitor their complex, microservice-based architectures. At Uber, our open source distributed tracing system Jaeger saw large-scale internal adoption throughout 2016, integrated into hundreds of microservices and now recording thousands of traces every second.
Here is the story of how we got here, from investigating off-the-shelf solutions like Zipkin, to why we switched from pull to push architecture, and how distributed tracing will continue to evolve:
https://eng.uber.com/distributed-tracing/
(GitHub Pages : https://www.jaegertracing.io/, GitHub: https://github.com/jaegertracing/jaeger)
Bindings/Operator: Python Java Node.js Go C++ Kubernetes JavaScript OpenShift C# Apache Spark