How A Cloud Guru is solving their marketing attribution challenge with Supermetrics and Snowflake

How A Cloud Guru is solving their marketing attribution challenge with Supermetrics and Snowflake

Key takeaways

  • A Cloud Guru is a global e-learning company on a mission to teach both individuals and businesses “how to cloud”
  • The SaaS company’s growing analytics team was looking for a way to improve the flexibility and fidelity of their marketing and customer data — especially when it came to measuring customer acquisition cost and return on ad spend
  • Since A Cloud Guru was already migrating their data warehouse from Redshift to Snowflake, Supermetrics for Snowflake was chosen as the marketing data pipeline for aggregating data from Google Analytics and various paid media platforms
  • The team was considering Funnel and Stitch as alternative data pipelines, but Supermetrics won out as it had high-quality connectors to all the necessary data sources
  • With Supermetrics and Snowflake in place, the analytics and marketing teams at A Cloud Guru are better able to create flexible reports in Looker and identify which levers to pull to grow the business

Quick facts

Industry: E-learning

Founded: 2015

Size: 600+ employees

Markets: Global

A Cloud Guru is an e-learning platform on a mission “to teach the world to cloud.” What started from a single cloud certification course in 2015 has grown into a global company with offices in Austin, Texas; London, United Kingdom; and Melbourne, Australia.

Zach Cooper works at A Cloud Guru as the Director of Analytics. His 10-person team is responsible for all things data and analytics, from data modeling to data warehousing, and from reporting to delivering insights and actionable recommendations to the business.

Growing out of spreadsheet-based marketing analytics

Like many growing marketing and analytics teams, A Cloud Guru was using Supermetrics for Google Sheets for marketing analytics and reporting. But as the business evolved and the team grew in size, spreadsheets could no longer handle the team’s analytics needs.

Zach explains, “When you have two people in your startup, Sheets is fine. It gets you the important information you need and allows your small team to focus on other things instead. But as the company grows, you’ll start getting into those questions around ad spend, attribution, and wanting to match it all together. And at that point, those Sheets-type solutions become trickier than they’re worth.”

He continues, “At a growing SaaS business like ours, you always end up having discussions around the SaaS magic number, CAC, ROI, and conversion. When people are looking for levers to pull to grow the business, that’s the first and most important dataset that gets brought up time and time again. And  in my experience, there are a couple of core questions like ‘how do we make sense of our digital footprint?’ and ‘how well do we understand the impact of our ad spend?’ that end up determining which SaaS companies succeed and which ones don’t.”

In addition to the need to solve more advanced business problems, Zach’s team also had the foresight to start setting the growing analytics team up for success.

Zach says, “You end up adding a lot of people who have done this thing three, four times before at larger companies, and they tend to be used to a certain fidelity of tool and solution. As you grow and start to hire for specialized roles, there’s a lot of pressure to get the right tool for the job, and not just have a splattering of tools, or something that’s halfway there and worked for a while.”

He continues, “We’re bringing on senior digital analysts and they’re going to be tackling a lot of big problems, including custom attribution on top of our fairly simple first touch/last touch model. And I don’t want them to even have to think about spend data, really. I just want it to be there for them to use and to join to at the end of their process.”

And for these reasons, Zach and his team decided to start looking for a solution that would help them consolidate their marketing, advertising, and sales data.

Moving into Snowflake with Supermetrics

To make sure that A Cloud Guru’s growing analytics team would have clean data and modern tools at their disposal, they decided to migrate from Redshift to Snowflake.

Zach explains, “We were in a situation where we had to decide if we wanted to plan for the future or get stuck in the past. And in that scenario, we’ll always plan for the future. We’re a SQL-native analytics team, and getting our data into Snowflake created a far more flexible, easy-to-join, native dataset for us.”

And when it came time to start thinking about the data pipelines, a homegrown solution was never really on the table.

Zach says, “A homegrown solution was never something we would seriously consider. Even if it got brought up, it was dismissed pretty quickly because I’ve seen what happens with them. It’s one of those things where even if you get someone to build it initially, a year later that same team just won’t have the bandwidth to update it. And so it always makes more sense to have someone else do it from the start.”

Before the A Cloud Guru team settled on Supermetrics as their marketing data pipeline, they also evaluated Funnel and Stitch.

Zach says, “With Funnel, we quickly noticed that they didn’t cover all the data sources we needed and their pricing might also have been an issue for us. With Stitch, we actually got pretty far. The only issue was that Stitch didn’t connect with Reddit, Quora, and LinkedIn Ads, and the question was: Do we look at a tool for just those three, or do we go with Supermetrics because they have everything?”

And even though Zach and his team had nothing against using several different pipeline tools, Supermetrics won out in the end.

Zach explains, “If you’re given the simple question of ‘would you rather go with one or two pipeline tools?’, you choose one tool. But at the end of the day, if there was even a slight discount for using two different ones and the outputs would work together, then I wouldn’t mind using two. Our team is pretty technical, so I’m sure they could handle it.”

Cleaner and more flexible datasets, better attribution, and self-service analytics for the marketing team

Zach and his team have only been using Supermetrics for Snowflake for a few months, but they’re already seeing considerable improvements in the way they’re now able to surface information.

Zach says, “The most important thing for us is having flexible datasets that help us understand ad spend and its true impact on the business. In the past, we’ve been plagued by good but not great Google Analytics implementation that has led to duplication in conversion reporting. And because of that, it’s been really hard to tell what the actual conversion is. Understanding paid conversion is a really important question for us. It’s sort of like the catalyst for attribution.”

He continues, “At the end of the day, we want to know if we pull a lever and spend this much this month, how much true conversion that equates to. It’s the same thing on our B2C and B2B funnels. Of course, it’s more complicated on the B2B side, but I would rather collect this data in one data warehouse for a year, and then when the question comes up be like, ‘alright, here’s the answer,’ instead of being like, ‘let’s start figuring it out now.’”

Another key goal for the analytics team at A Cloud Guru is to help the marketing team answer many of their own questions with Looker.

Zach explains, “Sarah from our marketing ops team has already recreated some flexible reports in Looker to replace what we used to have in Sheets. And what Sarah will continue to do is to train up the ads team on what the data actually means.”

Next up, the analytics team will focus heavily on attribution and ROAS reports.

Zach says, “As we go forward this year, we’ll tackle attribution more head on. After that, we’ll build some calculator-oriented reporting where you can look at a specific dataset and see the ad spend, return on ad spend, and then very easily make decisions off of that.”

Overall, even though it’s early days, Zach is positive about the impact Supermetrics and Snowflake will have on the business.

He says, “If you don’t have something to handle aggregating all of that data, it’s a pretty big headache. It’s actually painful. And what you see in smaller marketing teams is one person pulling all that data together once a day. That’s mind numbing work. And Supermetrics fixes the problem of data availability. It’s high impact, low effort. Supermetrics does a really good job of taking care of work that no one should have to do manually.”

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