Hex.tech vs. Mode Analytics

Hex.tech is an excellent tool for a product intelligence or product analytics team that wants to enable widespread use of available data for decision-making. It requires some SQL experience in many cases but makes it possible to go far without complex querying skills.

Incentivized

After launching a new contact pathway in a help experience, Mode Analytics can help provide insight into the sentiments from users as well as the engagement with any written content. Numeric outputs are easier to manage, whereas more nuanced/emotional feedback is sometimes hard to quantify (though not impossible if you get creative).

Incentivized

• Powerful interactive notebook environment
• Balances the need of code and non-code users
• Provides free and easy sharing to viewers of analyses across the company
• Responds promptly to support requests and needs
• High quality native charting capabilities

Incentivized

• Easy to use (click a button and get right to SQL).
• Security First (everything is locked down by default).
• The White Label feature is super easy to skin -- our embedded reports look just like our app!

Incentivized

• Limited support for R notebooks
• Limited sharing outside of the app (e.g., no slack integration)
• Some Python knowledge needed for highest levels of aggregations

Incentivized

• Date ranges aren't always the most intuitive to set, strangely
• Faster refresh rates would be ideal
• Would love more dynamic mobile device integration (alerts, etc)

Incentivized

For the advanced user already familiar with Python. It is just the same tool, already managed and connected to the data.

Incentivized

Mode has dedicated agents who are online in a chatroom, ready to take on any questions and provide helpful feedback.

Incentivized

Hex.tech is the easiest to use, most enjoyable experience, most powerful environment, and most cost scalable of all the above.

Incentivized

• Tableau is a huge pain to edit or create dashboards, by comparison. It can make better looking visualizations, but in practice, letting users drill down and change dimensions slows the end user experience so much that it's often not worth it.
• Looker is amazing for data modeling, but you have to get your whole business all in on it to take advantage. Viz capabilities are similar.
• Databricks has a lot of functionality overlap, but the visualizations are terrible. Databricks' great strength is that you can use notebooks to do anything with code.

Incentivized

• Increased visibility into analyses with free membership tier across company
• Increased capacity for self-service analytics among R&D stakeholders (e.g., product managers)
• Improved productivity of data science team with ease of use

Incentivized

• It has allowed us to monitor ongoing financial transactions written to our SQL data tables in real-time and that helps us to monitor user transaction activities in real-time
• Using Mode we have been able to also track users who undertake fraudulent financial transactions; preventing financial losses to our users
• Mode's collaborative abilities have been very helpful in sharing transaction monitoring workload across our compliance and cybersecurity team

Incentivized