New Feature Enables Business Teams to Move Faster by Conducting Granular Data Analysis on the FlyÂ
DataGPT, the leading provider of conversational AI data analytics software, announced Dynamic Benchmarking, giving business users the power to analyze data by date range and perform head-to-head comparisons of specific segments within the data over the same period of time.
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Created in response to a request from a Fortune 100 media and entertainment company, DataGPT is the first conversational AI data analytics software provider to offer Dynamic Benchmarking. Unlike stagnant dashboarding tools that lack this level of granularity, Dynamic Benchmarking allows marketing and data teams to quickly find the highest-performing segments of cohorts across two different time ranges using Conversational AI prompts in everyday language.
“We are proud to unveil Dynamic Benchmarking, a testament to DataGPT’s commitment to innovation and meeting the evolving needs of our customers,” said Arina Curtis, CEO and co-founder, DataGPT. “Today, we set a new standard in conversational AI data analysis. Dynamic Benchmarking underscores our dedication to providing nimble and efficient solutions that deliver valuable insights and power informed decision making for businesses everywhere.”
Echoing an overwhelming demand from its customers, DataGPT’s development of Dynamic Benchmarking cements the company as one that actively listens to its users, and quickly strives to meet the needs of its customers and the broader market. Dynamic Benchmarking enables users to cover deeper and wider analytics than ever before.
“DataGPT has transformed the ease and speed in which I can use our data. Other BI and dashboard tools were just simply too complex and time intensive to get answers,” says Dan Calzone, Director of Growth, Plex. “But with DataGPT, it’s like having a personal data analyst at my fingertips. I can finally answer not just what happened but why, without waiting hours or days for a new dashboard to be created.”
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Key features of Dynamic Benchmarking include:
- Segment Isolation – Segments are a group of individuals who share a common characteristic or experience within a defined time range. For example, a new product or campaign launch. While many BI tools can analyze user behavior over time, Dynamic Benchmarking offers the ability to isolate segments and shift the timeline for head-to-head comparisons.
- Versatile Analysis – Most traditional tools are unable to assess data using launch date or lifecycle as a basis for comparison. Dynamic Benchmarking provides a flexible tool that can be applied to various scenarios, allowing users to analyze data from different perspectives and gain comprehensive insights.
- Increased Efficiency – Dynamic Benchmarking is powered by DataGPT’s proprietary Lightning Compute Engine, which is 90 times faster than traditional databases. Enabling 15 times cheaper analysis and 600 times faster query running than standard BI tools, Dynamic Benchmarking enhances efficiency, reduces costs and makes data analysis more accessible for businesses of all sizes.
“Traditional data analysis tools are slow, inefficient and lack the capacity to compare all data points based on launch date or lifecycle,” continued Curtis. “Now, by using Conversational AI to perform analysis, business users are free from relying solely on data teams to conduct sophisticated head-to-head segment comparisons.”
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