Motorsport Network Reduces Data Reporting Time by 30x on AWS

With Panoply, an APN Advanced Technology Partner, AWS Data & Analytics Competency Partner, and AWS Redshift Service Delivery Partner

Bringing the World of Racing to Life for Online Users Everywhere

Fans around the world follow and celebrate car racing. From internationally renowned racing series such as Formula 1 to regionally prominent series like the Asian Le Mans Series, racing continues to be a favorite sport for millions to follow. The Motorsport Network team defines success by the company's ability to provide motorsport fans with news, updates, insights, and imagery they'd be hard-pressed to find anywhere else.

The company owns and operates over 40 website properties across many languages. With millions of page views daily and no shortage of results to track and stories to report, the company sought to deliver a more curated and up-to-date end-user experience for Motorsport Network readers by becoming data-driven in its business decision-making. The Motorsport team realized they were missing key ingredients for driving data insights: a centralized location for data, a seamless ability to pull in data from multiple sources, a tool to analyze the data, and a tool for presenting the data visually to different audiences.

"When I joined the company, our approach to data was manual in nature, and our data was not centralized in any one location," says Audren de Valbray, data and insight director at Motorsport Network. “It took a very long time to report on our data. We weren’t using a business intelligence tool and we did nearly everything in spreadsheets. While we were already creating millions of web pages, we didn't have internal capabilities to gather, analyze, visualize, and report on our data.” As de Valbray and team built a business case for implementing data analytics and BI tooling—specifically Chartio, an APN Advanced Technology Partner—to meet its needs, the company began exploring Panoply on AWS.

Turning to Panoply to Create a Self-Serve Analytics Platform

The Panoply team’s goal is to simplify data management and provide users with an easy-to-use, scalable, and intuitive smart data platform.

“We call ourselves an all-in-one data management solution,” says Jason Harris, data evangelist at Panoply. “Our data warehouse is built on top of Amazon Redshift and makes data ingestion run very quickly. Panoply can ingest data from over 100 data integrations so that companies like Motorsport Network can consolidate data from excel spreadsheets, third-party sources, and applications in minutes.” Panoply is proud to run on AWS. “When customers hear we sit on top of AWS, it gives them additional confidence in the solution we’ve developed,” says Harris.

For de Valbray, Panoply’s data warehouse running on Redshift, its platform's ease-of-use, and its fast integration with Chartio were crucial differentiators. "We host all of our websites on AWS. Knowing Panoply uses Redshift was validation enough for our chief executive officer for exploring the tool," says de Valbray. "Panoply automates so many of the tasks required to connect, structure, and analyze our data and had integrations with most of the tools we were using. Given my lack of time and engineering resources to put toward the solution and to run and manage a data warehouse, its ease of use proved critical for us to get up and running quickly.”

“We host all of our websites on AWS. Knowing Panoply uses Redshift was validation enough for our chief executive officer for exploring the tool.”

- Audren de Valbray, Data and Insight Director at Motorsport Network

Using connectors from Panoply, Motorsport Network began by bringing a few gigabytes (GB) of data into Panoply. Today, the company has brought over a terabyte (TB) of data into Panoply and is planning to increase its footprint to 3 TB in the coming months.

With over 40 Google Analytics accounts and a range of data sources—including Google Sheets, MailChimp, Twitter, and Facebook—Panoply’s seamless integrations and smart platform make it easier for Motorsport Network to handle the extract, transform, load (ETL) process in a single location. “We are bringing all of our Google Analytics and Facebook data into Panoply now and taking advantage of the data compression and automatization capabilities we get through Panoply,” says de Valbray. “We are then able to connect Chartio directly to all of our databases and the Panoply data warehouse for easy querying and visualization of our data.”

Reducing Reporting Time by 30x and Enabling Teams Across the Organization

When the company’s digital marketing director previously wanted to report on the company’s 40+ Google Analytics accounts, it would take about 15 days per month to update a spreadsheet manually with the information. Using Panoply, the director can now update and report on data in seconds. Having this capability enables the marketing team to spend more time analyzing and visualizing data and providing new insights to business users across the organization who want to drive new business outcomes and optimize website user experiences.

“Today, we have dashboards available to us that inform all of our business units,” says de Valbray. “Business users can explore the performance of the content produced, grouped by types of content, and analyze different factors such as: Does the content increase the number of subscribers? How are our ads performing in certain markets? What is the long-term value of subscribers? The power of Panoply and Chartio combined have demonstrated to us why it’s so important to the business that we focus on understanding our data.”

As Motorsport Network continues to build its data-driven strategy, the international publisher is now focusing building its content recommendation engine and enhancing the artificial intelligence tooling used within its content management system. The company plans to continue to take advantage of Panoply as its data sources grow and scale over time.

Motorsport Network Logo 600x400

About Motorsport Network

Motorsport Network is the online destination for millions of car and racing fans. Through its integrated digital ecosystem, the company is unlocking more opportunities and experiences for its fans.

Challenge

Motorsport Network owns and operates over 40 website properties across many languages. With millions of page views daily and no shortage of results to track and stories to report, the company sought to deliver a more curated and up-to-date end-user experience for Motorsport Network readers by becoming data-driven in its business decision-making. The Motorsport team realized they were missing key ingredients for driving data insights.

Solution

The team built a business case for implementing data analytics and BI tooling and began exploring options. They chose to use Panoply on AWS. Motorsport chose to use Panoply, built on Amazon Redshift, because of its ease of use and integration with Chartio. Using connectors from Panoply, Motorsport Network began by bringing a few gigabytes (GB) of data into Panoply. Today, the company has brought over a terabyte (TB) of data into Panoply and is planning to increase its footprint to 3 TB in the coming months.

Benefit

When the company’s digital marketing director previously wanted to report on the company’s 40+ Google Analytics accounts, it would take about 15 days per month to update a spreadsheet manually with the information. Using Panoply, the director can now update and report on data in seconds. Having this capability enables the marketing team to spend more time analyzing and visualizing data and providing new insights to business users across the organization who want to drive new business outcomes and optimize website user experiences.

About Panoply

Panoply is an AI-driven cloud data platform. Built for the cloud, Panoply delivers fast time to insights by eliminating the development and coding typically associated with transforming, integrating, and managing big data. Panoply's proprietary machine learning and natural language processing algorithms automatically enrich, transform, and optimize big data.

Published January 2020