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Case Study: Cox 2M cuts time to insights 88% and saves $70,000+ a year with ThoughtSpot

Cox 2M Case StudySourced & dated by Case Study Desk
Key facts · TL;DR
Company
Cox 2M
Industry
Commercial IoT
Challenge
Legacy analytics tools made ad hoc requests slow and costly
Headline result
-88% time to actionable insights

Key results

-88%
Time to actionable insights
via natural language querying
-75%
Time to structure data
from hours per dashboard to ~15 minutes
$70,000+
Annual savings on cost-to-serve

The challenge

Cox 2M's legacy analytics tools created bottlenecks, with ad hoc requests taking more than five hours each while the team processed over 1.5 million IoT messages hourly and 13 billion data rows a year. Handling these requests cost the business over $90,000 annually.

The solution

Cox 2M implemented ThoughtSpot's AI-powered analytics with natural-language querying, integrated with Google BigQuery and its existing data infrastructure, so business users could ask questions in plain language and get accurate answers.

ThoughtSpot's Generative AI fulfills the promise of business users querying the data in natural language and getting back accurate answers.

JH
Josh Horton
Senior Lead, Data Strategy & Analytics, Cox 2M

The results, in context

With natural-language querying, time to actionable insights reduced by 88%, and time spent structuring data fell 75% (from a few hours per dashboard to about 15 minutes). The changes delivered more than $70,000 in annual savings on cost-to-serve.

Products used

ThoughtSpot ThoughtSpot AnalyticsThoughtSpot Search & AIThoughtSpot BigQuery integration