Google Analytics vs. Microsoft Power BI vs. New Relic

Google Analytics is particularly well suited for tracking and analyzing customer behavior on a grocery e-commerce platform. It provides a wealth of information about customer behavior, including what products are most popular, what pages are visited the most, and where customers are coming from. This information can help the platform optimize its website for better customer engagement and conversion rates. However, Google Analytics may not be the best tool for more advanced, granular analysis of customer behavior, such as tracking individual customer journeys or understanding customer motivations. In these cases, it may be more appropriate to use additional tools or solutions that provide deeper insights into customer behavior.

Has significantly improved collation of data and visualisation especially with business across Europe. Has given me the ability to see the Site availability at the click of a button to see which Site is in the "money" and seize opportunities based on Market data

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New Relic its an excellent tool for monitoring services used on the SAAS universe, like web servers, relational and nosql dbms, reverse proxies, text databases, etc. Its also a powerful tool to monitor resource usage on said servers. However, its not well fitted to monitor custom services - if you need to generate alerts based on logs or database information, for example

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• Multiple reports to see website use and behavior
• Allows you to customize reports with days, weeks, months, and years
• You can build out a dashboard to easily view stats from multiple websites in one place
• You can share analytics reports via the dashboard, automatically emailed PDFs or in other formats

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• Options for data source connections are immense. Not just which sources, but your options for *how* the data is brought in.
• Constant updates (this is both good and bad at times).
• User friendliness. I can get the data connections set up and draft some quick visuals, then release to the target audience and let them expand on it how they want to.

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• It gives us insights of applications, infrastructure, clouds very well.
• The alerting system in New Relic helps us to easily identify the root cause which reduces the MTTR.
• It has new features related to AI which helps to troubleshoot any problem in a very short time it gives future predictions also.

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• Data sampling is somewhat inaccurate on the free tier - this is addressed in premium but is expensive.
• Some of the UI is very similar in naming when presenting different data, some in-situ information might be useful.
• Gotchas around filtering and data validation.
• Implementation can be tricky, it can take a lot of time and expertise to get a full, accurate picture of your metrics.

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• It would be easier for users could Microsoft Power BI and Excel used the same programming languages.
• Would like to see the online version of Microsoft Power BI be as powerful as the desktop version.
• Publishing a Microsoft Power BI file online and then having to save the file is somewhat redundant.
• Would like to export each page or chart as an image.

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• And while powerful, building tailored dashboards with organ-specific metrics (such as energy load variance across regions) can be difficult to navigate. The UI isn't as drag-and-drop easy, and query-based widgets typically involve some trial and error for non-devs.
• Alerts may be hypersensitive or over general. I We often get a spam of non-critical alerts while doing load testing, all overhauling to me alone and making it difficult to identify actual issues especially in energy systems where spikes are very common.
• With our expanding fleet of Iot devices, the per-host pricing model is becoming expensive, quickly. More detailed billing based on microservices, or that works at sensor level, would make it more adaptable for energy platforms.

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We will continue to use Google Analytics for several reasons. It is free, which is a huge selling point. It houses all of our ecommerce stores' data, and though it can't account for refunds or fraud orders, gives us and our clients directional, real time information on individual and group store performance.

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Microsoft Power BI is an excellent and scalable tool. It has a learning curve, but once you get past that, the sky is the limit and you can build from the most simple to the most complex dashboards. I have built everything from simple reports with only a few data points to complex reports with many pages and advanced filtering.

The only issue that we have had with New Relic is that the price might be a little expensive for smaller companies. The amount of data you store in New Relic impacts the cost, and can get away from you if you don't work closely with the vendor. Overall though the application is top notch.

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Google Analytics provides a wealth of data, down to minute levels. That is it's greatest detriment: find the right information when you need it can be a cumbersome task. You are able to create shortcuts, however, so it can mitigate some of this problem. Google is continually refining Analytics, so I do not doubt there will be improvements

Automating reporting has reduced manual data processing by 50-70%, freeing up analysts for higher-value tasks. A finance team that previously spent 20+ hours per week on Excel-based reports now does it in minutes with Microsoft Power BI's automated Real-time dashboards have shortened decision cycles by 30-40%, enabling leadership to react quickly to sales trends, operational bottlenecks, and customer behavior.

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I have given this much rating as I am used New Relic in different sectors and for different use cases like its K8s monitoring, infra monitoring, full stack monitoring as compare to other tools New Relic gives data in a formatted and connected way, and also it is giving us value for money. It also launches new features day by day which helps users to track the issue very quickly. It also supports OTel integrations which is the latest trend of observability tools. thats why I had given this much rating to New Relic.

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We all know Google is at top when it comes to availability. We have never faced any such instances where I can suggest otherwise. All you need is a Google account, a device and internet connection to use this super powerful tool for reporting and visualising your site data, traffic, events, etc. that too in real time.

Never observed an outage

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This has been a catalyst for improving our site's traffic handling capabilities. We were able to identify exit% from our sites through it and we used recommendations to handle and implement the same in our sites. We have been increasing the usage of Google Analytics in our sites and never had any performance related issues if we used Analytics

there are times where browser cache will cause issues that require you to clear your browser before continuing.

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The Google reps respond very quickly. However, sometimes they can overly call you to set up an apportionment. I'm very proficient and sometimes when I talk to reps, they give beginner tutorials and insights that are a waste of time. I wish Google would understand my level of expertise and assign me to a rep (long-term) that doesn't have to walk me through the basics.

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It is a fantastic tool, you can do almost everything related with data and reports, it is a perfect substitutive of Power Point and Excel with a high evolution and flexibility, and also it is very friendly and easy to share. I think all companies should have Power BI (or other BI tool) in their software package and if they are in the MS Suite, for sure Power BI should be the one due to all the benefits of the MS ecosystem.

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The support team has been really helpful and resolved most of the issues on time. However, for a couple of issues, several follow-ups were needed to elicit a reasonable response. The issue was deeply technical and could have been investigated only by their Architects, and bringing them into the ticket took longer than needed

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love the product and training they provide for businesses of all sizes. The following list of links will help you get started with Google Analytics from setup to understanding what data is being presented by Google Analytics.

1. How to Use Google Analytics for Beginners – Mahalo’s how-to guide for beginners.
2. A beginner’s guide to Google Analytics – A free eBook walking you through Google Analytics from setup to understanding what data is being presented.
3. Getting to Know Your Google Analytics Dashboard – The title says it all! This is a brief post with one goal: to introduce you to the Google Analytics dashboard.
4. Google Analytics for Beginners: How to Make the Most of Your Traffic Reports– This guide doesn’t cover setup, but it does a great job of helping you to better understand the data being presented.
5. Google Analytics Video Tutorial 1: Setup – A video presentation that walks you through Google Analytics setup.
6. Google Analytics Video Tutorial 2: Essential Stats – A video presentation that introduces you to some of the most important data being presented in Google Analytics.

I think my biggest take away from the Google Analytics implementation was that there needs to be a clear understanding of what you want to achieve and how you want to achieve it before you start. Originally the analytics were added to track visitors, but as we became more savvy with the product, we began adding more and more functionality, and defining guidelines as we went along. While not detrimental to our success, this lack of an overarching goal resulted in some minor setbacks in implementation and the collection of some messy data that is unusable.

It was integrated with our erp easily and was accessible on cloud.

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It's better to start by implementing New Relic in one project and test everything. Try to follow best recommended practices and read all the official documentation. Everything seems well tested. Then, start by installing agents to the rest of your projects and keep a close look to all logs and metrics New Relic gives you.

I have not used Adobe Analytics as much, but I know they offer something called customer journey analytics, which we are evaluating now. I have used Semrush, and I find them much better than Google Analytics. I feel a fairly nontechnical person could learn Semrush in about a month. They also offer features like competitive analysis (on content, keywords, traffic, etc.), which is very useful. If you have to choose one among Semrush and Google Analytics, I would say go for Semrush.

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Microsoft Power BI is free. If I didn't want to create a custom platform (i.e. my organization insisted on an existing platform that I *had* to use), I'd use Microsoft Power BI. For any start-up or SMB, I'd just use Claude & Grok to build it quickly, also for free. Would not pay for Tableau or Sigma anymore. Not worth it at all.

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Data Dog has solutions that look more attractive, but not at their price point. We have also tried to build a solution straight from the Cloud, where our business is built, but some things are too hard to replicate. This shows that New Relic is useful and helps our efficiency.

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Google Analytics is currently handling the reporting and tracking of near about 80 sites in our project. And I am not talking about the sites from different projects. They may have way more accounts than that. Never ever felt a performance issue from Google's end while generating or customising reports or tracking custom events or creating custom dimensions

Agent deployment is easily integrated into our workflow. Adding the agent to new servers is quick and painless

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• It has helped us gain understanding of what is going on on our website.
• It has helped us determine areas that need fixing (i.e. pages with extremely high bounce rates may need to be redone).
• It has helped us understand our biggest avenues for bringing traffic to the website and business in general.
• It has helped guide our website redesign.

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• Power BI usage reduced the effort of analytical reports creation by about 80%
• Empowered all the level of employee to be more vigilant of the data and business insights, gained the profit of 8% overall.
• AI-powered predictive analytics improved forecasting accuracy by 17%, that topped the overall sales.

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• We were able to quickly identify our most time consuming APIs. In some cases we were able to bring down times for some apis from 4s to 200ms.
• We were able to identify our slowest database queries and optimize them for quicker response times.

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