Driving Data Literacy with Self-Serve Analytics at Motorsport

Case Study

About Motorsport

Motorsport.com is the place to go online if you want the industry’s most influential voice in motorsport content online. The media group operates more than forty online media publications across 17 languages.

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Audren de Valbray/>

With more than 450 employees worldwide and a growing portfolio of publications, Motorsport produces a massive amount of data that needs to be wrangled for easy analytics.

Chartio and Panoply teamed up to speak with Audren de Valbray, Business Manager, at Motorsport to hear how he and the online publishing conglomerate use the joint offering of Chartio and Panoply to power their data insights.

What was life like before Chartio and Panoply?

Before Chartio and Panoply, it was a labor intensive process to access and visualize our data. We were manually extracting data and putting it into Excel to provide a high-level summary that didn’t allow us to dig deeper.

Our data process was time consuming and presented room for human error. When I joined, I started looking for a better solution to give us back our time and confidence in our numbers.

What were your requirements for a business intelligence tool and data warehouse?

We wanted a solution that enabled anyone in the company to access their data and be able to build a chart.

To that end, our requirements were a data stack that was straightforward, fast to set up and easy to use for non data scientists.

Our proof of concept included the need to enable our Digital Marketing Director to create his massive monthly report in Chartio. He had tried other BI tools like Tableau in the past but stopped using them because of the level of complexity to create a chart.

Why did you choose Chartio and Panoply?

We ultimately chose Chartio and Panoply because we were able to get up and running with the data we needed in a few hours.

One of the reasons we went with Panoply was because we didn’t want to invest time and money into having developers or an engineering team supporting our own Redshift instance. Panoply handles all that day-to-day work we don’t want to absorb into our Motorsport team. Plus, Panoply costs about the same as having our own Redshift instance without the headache of developing or maintaining it.

We ultimately chose Chartio and Panoply because we were able to get up and running with the data we needed in a few hours.

What does your data stack look like?

While we’re still early into our full analytics infrastructure build out, our current stack is comprised of many cloud applications that are stored in Panoply’s self optimizing warehouse with Chartio sitting on top as the visualization/BI layer.

We chose Panoply as opposed to a standard Amazon Redshift instance because we did not have a developer resource to start with and no way to maintain our own warehouse. Plus, Panoply ETLs our Mailchimp, advertising data in Google Sheets, S3 buckets, MongoDB and some of our 50+ social media accounts including Facebook and Twitter into a single location.

We then connect Chartio directly to 60+ Google Analytics views, random CSVs, alongside various MySQL and PostgreSQL databases and the Amazon Redshift data warehouse that is managed by Panoply.

Chartio provides us with one centralized place for all of our data in a format that makes it easy to query and visualize what’s going on in our company.

Who else in the company are using Chartio?

We have people across the company using Chartio and consuming the data that Panoply stores. Marketers, product teams, executives, along with journalists and editors are all actively tracking the metrics they need to make their day-to-day easier.

Since implementing Chartio and Panoply, we’re not just reporting on data but taking action on it. For example, we have built a performance dashboard for our stories. With this dashboard, our editors can identify the best performing pieces of content across our 23 global editions and then translate the best performing stories written by foreign editions, knowing they’ll likely perform well based on prior success.

We also created a dashboard to the topics or genres that are attracting the most engagement. This gives our editors and journalists a data driven way to choose their next story.

Before, finding these insights was a bit of ‘finger in the air’ where we used instinct and intuition to know which content to repurpose - now anyone can simply look at the data to make a decision.

What has been the biggest win for Chartio and Panoply?

It’s the 30x time savings our Digital Marketing Director saves per month.

Before Chartio and Panoply, he pulled in upwards of 40 Google Analytics accounts manually all into a colossal spreadsheet that we called the “mega spreadsheet”.

What used to take him 15 days a month to manually update in a spreadsheet, is now done automatically in Chartio. Chartio and Panoply have given him more time to focus on his job and less time reporting on it.

What used to take him 15 days a month to manually update in a spreadsheet, is now done automatically in Chartio.

What’s your favorite feature of Chartio and Panoply?

What I love about both Chartio and Panoply is their respective ease of use.

With Panoply we can seamlessly connect our many data sources to our data warehouse in one click. This has been amazing, as it saves us from having to allocate engineering or analyst resources to set up and maintain our data infrastructure.

And for Chartio, it’s the Data Pipeline. It gives non-data scientists the ability to blend data from our many sources in a matter of seconds - it’s that easy.

What’s next for data at Motorsport?

Being more data-driven one of the top priorities for us at Motorsport in 2018.

At first, our proof of concept with Chartio and Panoply was focused on taking manual reporting processes we had and automating them as much as possible.

Now that we’ve seen the power of data and analytics within Motorsport, we’re going to invest more in using data as a product within our company.


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