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Reviews for analytics platforms services and analysis of user reviews about your competitors

Dog slow application, no way to center the text on certain items, cannot pin open the Format section (it keeps closing when you click off of an object), cannot select and move multiple objects, no way to align objects, no way to right-click and format objects, Ctrl+Z does not work to undo, timelines and G– charts are completely ignored, stupid/weird spaning around objects no way to round corners on fields, field border colors are ignored, no way to autofit tables to visual, no way to turn off autorefresh when designing dashboard to name just a few.

Real review to a real analytics platforms service

The software is teribly slow. To a point that I had to completely remove it from my M1 M– and go with a competitor.

Real review to a real analytics platforms service

Everything feels half-baked. It feels like the product team just wanted to try to match features with leading BI tools for optics, but most lack a lot of real utility/functionality.

They’re just there to fool folks into thinking that it’s feature-rich.

Dashboard+Dataset O– – Dashboard+Dataset ownership and visibility are managed in a completely decentralized manner.

If a dashboard/Dataset has problems (either Q– related or caused by a manual change) as an admin, I’d expect to be able to immediately have access to the problematic asset. Instead, I need to spend an hour or two hunting down the owner of said dashboard/dataset.

Lack of trendlines – Completely unacceptable for a data visualization tool.

Lack of support for map visualizations (this review is only in regards to the US) – The US has many county names that collide (their names match exactly), most visualization tools allow for FIPS, but Q– does not support it.

Z– polygons are unusable as many areas lack polygons.

Emailing reporting – My company needs the ability to email visualizations and reports to ~700 of external customers (mostly banks) on a daily basis, in order to do this, we need to walk each of our customers through setting up a Q– log-in, then we need to work with those customers in maintaining their user accounts.

While we know there are hacky workarounds that we can implement outside of Q–, we don’t for security purposes. So at least for our use case, Q– itself is cheaper than other tools on the market, but we ended up spending more in the long run to maintain our needs.

O– B– – Clearly Q– needs to spend more time to QA the offboarding process as each time we offboard an author or an admin, all sorts of havoc occurs and it takes weeks for the tech support team to help resolve the problem.

“Insights” – It’s a bit of a joke. They likely tossed this “ML” feature in there to be able to use buzzwords to attract potential customers, but it simply doesn’t work.

Buggy

Real review to a real analytics platforms service

It’s hard to handle, something confusing labeling and results can vary between the updates. No downgrading if you use some specific tools inside A–.

Real review to a real analytics platforms service

Perfomormance. There is a bug for totals in reports.

The O– user interface is not great. Getting started takes for ever.

Connecting to on prem databases in a hybrid envirnment is hard and it does not perform well.

If a user logs in through a url that brings them to O–, then logs out because of the odd bug that brings the reports down and then logs right back in they are are brough to DV and have to learn how to navigate.

Real review to a real analytics platforms service

 

Analytics platforms are essential tools for businesses seeking to leverage data for strategic decision-making. However, many competitors fall short in critical areas, leading to dissatisfied customers and lost business opportunities.

Based on customer reviews, we’ve identified the top mistakes that competitors in the analytics platform industry make and provide actionable solutions to help you outperform them.

 

Complicated user interface and experience

 

What competitors get wrong: Many analytics platforms have a complicated and non-intuitive user interface. Customers often complain about the steep learning curve and difficulty in navigating the platform, which hampers their ability to efficiently analyze data.

 

How to do it better: Prioritize a clean, intuitive user interface. Conduct usability testing with real users to identify pain points and streamline the user experience.

Simplify navigation and ensure that key features are easily accessible. Provide comprehensive onboarding processes, including tutorials, guided tours, and help resources, to assist users in getting up to speed quickly.

By offering a user-friendly interface, you can enhance customer satisfaction and differentiate your platform from competitors.

 

Limited integration capabilities

 

What competitors get wrong: Competitors often provide limited integration options with other tools and platforms, making it difficult for users to incorporate analytics seamlessly into their existing workflows. Customers frequently express frustration over the lack of seamless integrations.

 

How to do it better: Enhance your platform’s integration capabilities by supporting a wide range of third-party applications, such as CRM systems, marketing automation tools, and e-commerce platforms. Provide robust APIs and webhooks to facilitate custom integrations.

Collaborate with popular software providers to develop seamless integrations. By offering extensive integration options, you can attract users looking for a comprehensive, interconnected analytics solution.

 

Inaccurate or delayed data

 

What competitors get wrong: Many analytics platforms suffer from issues with data accuracy and timeliness. Customers often report discrepancies in data and delays in data updates, which can lead to misinformed decisions.

 

How to do it better: Invest in robust data validation and real-time processing capabilities to ensure that your platform provides accurate and up-to-date data. Implement stringent data quality checks and automated error detection systems.

Regularly audit and test your data processing workflows to identify and resolve issues promptly. By delivering reliable and timely data, you can build trust with your users and outperform competitors.

 

Inadequate customization options

 

What competitors get wrong: Many analytics platforms offer limited customization options, restricting users to predefined dashboards and reports. Customers often desire more control over how their data is presented and analyzed.

 

How to do it better: Provide extensive customization options, allowing users to create personalized dashboards, reports, and visualizations. Offer a variety of chart types, filters, and widgets to enable users to tailor their analytics experience to their specific needs.

Ensure that customization features are easy to use and accessible even to non-technical users. By enabling greater customization, you can attract users seeking flexibility and control over their data analysis.

 

Poor customer support

 

What competitors get wrong: Poor customer support is a significant issue among analytics platforms. Users frequently report slow response times, unhelpful support staff, and a lack of comprehensive resources to resolve their issues.

 

How to do it better: Differentiate your service by offering exceptional customer support. Provide multiple support channels, including live chat, email, and phone, with quick response times.

Ensure your support team is well-trained and knowledgeable about the platform. Offer a comprehensive knowledge base, FAQs, and tutorial resources to help users resolve issues independently.

Highlighting your commitment to customer support can build trust and loyalty among users.

 

Limited scalability and performance issues

 

What competitors get wrong: Many analytics platforms struggle with scalability and performance issues, leading to slow query responses and difficulties handling large data sets. Customers often experience frustration when the platform cannot meet their growing data needs.

 

How to do it better: Ensure that your platform can scale efficiently to handle increasing data volumes and user demands. Invest in scalable cloud infrastructure and optimized database management systems.

Regularly test your platform’s performance under various conditions to identify and address bottlenecks. By providing reliable scalability and high performance, you can cater to businesses of all sizes and needs, attracting a broader range of users.

 

Insufficient data security and privacy measures

 

What competitors get wrong: Competitors often fail to implement robust data security and privacy measures, leaving customers concerned about the safety of their sensitive information. Data breaches and compliance issues are common complaints.

 

How to do it better: Prioritize data security and privacy by implementing strong encryption, access controls, and regular security audits. Ensure compliance with relevant data protection regulations, such as GDPR and CCPA.

Provide transparency about your security practices and offer features like role-based access controls and audit logs. By emphasizing data security and privacy, you can reassure customers and build a competitive advantage.

 

Lack of advanced analytics capabilities

 

What competitors get wrong: Many analytics platforms offer basic reporting and visualization tools but lack advanced analytics capabilities, such as predictive modeling, machine learning, and deep data mining. Customers often seek more sophisticated tools to gain deeper insights.

 

How to do it better: Enhance your platform with advanced analytics features, including predictive analytics, machine learning algorithms, and natural language processing. Provide tools for data scientists and analysts to build and deploy custom models.

Offer training and resources to help users leverage these advanced features. By offering cutting-edge analytics capabilities, you can attract users looking for powerful and comprehensive data analysis tools.

 

Conclusion

 

By addressing these common mistakes made by competitors, your analytics platform can stand out in a crowded market.

Focus on delivering a user-friendly interface, robust integration capabilities, accurate and timely data, extensive customization options, exceptional customer support, reliable scalability, strong data security, and advanced analytics features.

By prioritizing these areas, you can enhance customer satisfaction, build loyalty, and ultimately, outperform your competitors in the analytics platform industry.

 

Is this what you expect to see at the end of the article? No!

Oh, you think your analytics platform can rise above the teeming masses of data-crunching tools out there? How delightful.

Here’s your master plan to outshine the competition by correcting their glaringly obvious mistakes.

First, a user-friendly interface. Because nothing says cutting-edge analytics like software that even your grandmother could navigate.

Clearly, those data scientists need everything to be as simple as possible.

Robust integration capabilities? Naturally.

Because users just love spending their precious time making sure your platform plays nice with every other tool in their arsenal. Integration is the ultimate thrill ride.

Accurate and timely data? Groundbreaking.

Because everyone is just dying for the chance to look at numbers that actually mean something. Who knew data could be so useful when it’s correct and up-to-date?

Extensive customization options? Absolutely.

Because who wouldn’t want to spend hours fine-tuning every little aspect of their analytics dashboard? Personalization is the spice of life.

Exceptional customer support? A must.

When your users hit a snag, they want a support team that treats their issue like a five-alarm fire. It’s only analytics, but let’s pretend it’s a matter of national security.

Reliable scalability? Of course.

Because your platform is destined to become the next big thing, and you need to be prepared for the inevitable flood of users. Dream big, my friend!

Strong data security? Essential.

Because nothing says peace of mind like knowing your precious data is locked down tighter than Fort Knox. Cybercriminals are just waiting to pounce on those sweet, sweet analytics.

And let’s not forget advanced analytics features. Because what’s the point of having an analytics platform if it can’t produce the most convoluted, brain-melting insights possible?

The more complex, the better!

By focusing on these oh-so-critical areas, you’ll not only enhance customer satisfaction and build loyalty but also leave your competitors in the dust. Because who wouldn’t be loyal to a platform that assumes they need everything simplified and handled for them?

 

Conclusions?

 

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Autor: Julia Monterey
Julia is an expert in Internet marketing with over 10 years of experience. She specializes in attracting clients and increasing sales for small and medium-sized businesses. Her work spans the markets of Europe, Asia, and North America. Julia's extensive background makes her a valuable asset for companies seeking to expand their online presence and boost revenue.
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