Cox 2M sends legacy analytics tool to the scrapyard and reduces time to insights by 76% with ThoughtSpot and Google BigQuery

Challenge

Like many data-driven businesses, particularly those powered by real-time, event-based data in perpetual motion, Cox 2M was fighting with one hand tied behind its back. The insights and growth opportunities buried in the colossal volume of information the company absorbed–1.5 million-plus IoT device messages per hour, 13 billion-plus new rows of data per year, and more than 2.6 terabytes of data generated per year from just their automotive auction solutions alone–were frequently stifled by the limitations of their inefficient and antiquated legacy business intelligence tools.

We needed analytics insights that aligned with our startup mentality. We were looking for a tool that focused on speed, scalability, ease of use and would help us better understand and address our customers’ needs.

Josh HortonSenior Lead, Data Strategy & AnalyticsCox 2M

For Josh Horton, Senior Lead, Data Strategy & Analytics at Cox 2M, and his data team, these tools had to undergo constant engineering cycles. Each inbound request meant a new dashboard had to be created; for a single ad-hoc report request it typically took more than five hours to respond, which meant by the time any meaningful insights were derived, the intelligence was often redundant or irrelevant to the business that inquired.

“I was looking at a frustrated leadership team that wanted to speed up time to insight and a lean data team who were spending most of their time handling the ad hoc requests,” explains Josh. “Frustration apart, we were incurring a massive cost of $90,000+ to service ad hoc requests. We needed a solution to streamline and accelerate time from insight to actions, which would also positively impact the service cost, bringing it down.”

Solution

Josh wasn’t looking for just any tool. He wanted business intelligence solution a business intelligence solution that went beyond traditional dashboarding and reporting, one that delivered a data experience that could be leveraged by any user, irrespective of technical expertise or experience. A short evaluation of the market put the spotlight on ThoughtSpot. The fact Cox 2M’s parent company, Cox Communications, was already a trusted user of the analytics platform meant its capabilities shined brightest.

Josh and his team leverage ThoughtSpot’s machine learning and AI-Powered Analytics to gain insights from their sprawling data estate quicker and simpler than ever before, and natural language search ensures they don’t have to build a new dashboard for every query. “ThoughtSpot uses natural language querying, which puts users at ease as they can frame questions naturally, without the need for specific technical skills,” says Josh, underlining just one way ThoughtSpot has made data insights more accessible.

Often, data framework transformation, underpinned by a new tool, comes with significant cost and consternation as the new tool can’t work in synergy with the company’s existing stack. This wasn’t a problem with ThoughtSpot, as it connects directly with Cox 2M’s existing data stack, including PubSub, Dataflow, Data Stream, Data Form, and Google Bigquery, and serves as its modern data stack experience layer. This means it can seamlessly manage billions and trillions of rows of live data to deliver real-time data insights.

Impact

Josh points out, “Earlier it took more than five hours, that’s 20-plus hours per week, to handle ad hoc requests. But ever since ThoughtSpot was introduced to our data stack, time to actionable insights has reduced by 76%, courtesy natural language querying. This also ensures all stakeholders can benefit from actionable insights, which allows us to execute a holistic growth strategy.” With ThoughtSpot, relevant insights can be found in real-time, which allows business users to make critical decisions without a strict reliance on the data analytics team.

Now, Josh and his team can shift away from tedious ad-hoc business questions and IoT device diagnostics and troubleshooting—allowing them to spend more time on complex, value-driven initiatives that improve customer engagement and ROI. This includes more meaningful inputs to optimize auction strategies, reduce customers’ fuel usage on properties, predict engine issues, and reduce vehicle maintenance costs.

A customer wanted to identify all 2022 Mazda models whose batteries were failing as soon as they were delivered from the vehicle manufacturer. With our legacy tools, this process would have taken 5 hours, but with ThoughtSpot, we got the answers to our customer’s query in just 1.5 hours.

Josh HortonSenior Lead, Data Strategy & AnalyticsCox 2M

ThoughtSpot’s integration with Google BigQuery allowed Josh and his team to also reduce the time spent structuring their data by a staggering 75% which means time to structure data has plummeted from a few hours per dashboard to just 15 minutes. Even the time for data visualization has reduced from an hour per chart or graph to minutes with ThoughtSpot Liveboards. This transition was supported by ThoughtSpot SI implementation partner, InterWorks.

The cumulative benefits of accelerated insights and alleviated data engineering personnel translates to more than $70,000 saved annually on cost-to-serve. But for Josh and his team, this is merely the beginning. They hope to drive even more actionable benefits to their customers, courtesy of ThoughtSpot.

“We are confident ThoughtSpot will continue supporting our analytics needs and initiatives and help us continue to maximize the true power of data for Cox 2M and its customers,” Josh adds.

What's next

Data was already at the heart of Cox 2M, but now data teams can unearth deeper insights faster and improve their decision-making velocity. ThoughtSpot has made data, resultant analysis, and insights more accessible and further democratized the company’s data culture by ensuring all users can unearth answers quickly, irrespective of technical know-how. Looking ahead, Josh and his team intend to leverage more of ThoughtSpot’s capabilities, further scaling its data offerings, future-proofing its data environment, and extending the benefits experienced internally to its customers.