Give Me Data or Give Me Death: Takeaways from Growth Clinic

Read or watch what we learned from Amplitude's Growth Clinic that featured growth and analytics pros sharing their insights on achieving sustainable growth.

Inside Amplitude
July 27, 2016
Image of Archana Madhavan
Archana Madhavan
Instructional Designer
Give Me Data or Give Me Death: Takeaways from Growth Clinic

Last week we hosted Growth Clinic: Got Data?. This was our third Growth Clinic, where we bring in growth and analytics professionals to share their insights on achieving sustainable growth.

Back in March, we focused on retention, the most critical metric that underlies growth today. This time we looked at the bigger picture, a problem that many individuals face: the inability to access data they need. When individuals across teams are blocked from accessing and analyzing data, either due to the unusability of their analytics platform or being bottlenecked by their data team, it can take days to weeks to get insights about their users. This is wastes precious time that could be used to iterate and improve upon the product.

At Growth Clinic: Got Data? over 150 people joined Josh Curry of MindBody, _Hooked _author and entrepreneur Nir Eyal, Noah Jessop of Publishers Clearing House, and Aron Clymer of Popsugar to learn why data accessibility is so important to organizations. In addition, Amplitude Heads of Product and Design, Justin Bauer and Winnie Wong, shared how we at Amplitude are making bold strides towards making analytics more usable for all.

Couldn’t make it to Growth Clinic: Got Data? Here are a few key takeaways from the event. For more details, be sure to watch the full videos linked below!

Key Point 1: Users communicate through data.

One of the biggest things that concerns Amplitude CEO Spenser Skates is the challenge of making data insights accessible to whoever needs it. According to Spenser, at a truly data-informed company, data access isn’t siloed to analysts and data scientists; anyone should be able to ask deep questions of their data and get the answers they need from their analytics platform.

So, why is data access important? “The actions that users take within a product are how they communicate with us, the product owner. We get that communication every single day through user behavior data,” said Spenser. Having data access means having access to a direct line of communication with your users about your product.

Growth Clinic: Got Data? Kickoff with Spenser Skates (CEO of Amplitude)

Your data can tell you where users are struggling and where they’re succeeding, what features they like and what they don’t. As the product owner, taking this feedback and implementing product changes can lead to huge gains in retention and other success metrics. With better data access, LogMeIn, for example, was able to identify an Aha! Moment, roll out a new onboarding flow, and subsequently increase their user retention by 2x.

Key Point 2: Invest in being more data-informed.

We asked MindBody’s Head of Customer Intelligence Josh Curry what it takes to instill a culture of data at an organization like his. Josh, who interfaces with a number of data-driven teams within the company, said, quite simply, “We had to make an investment in data in order to be better than the status quo.” At one point, MindBody’s Chief Product Officer was the only one who could pull the data they needed. The data team quickly realized the company needed better data access throughout so product development wouldn’t be blocked. Today, MindBody experiences two flavors of data accessibility. The “data nerds,” as Josh puts it, can directly query raw data in their Redshift cluster using SQL. Other teams like marketing and customer success, who used to have to go through Josh, can now track their campaigns and answer their own questions using Amplitude’s interface.

Customer Insights Panel with Josh Curry (Head of Customer Intelligence at MindBody)

During the Got Data Panel, Popsugar’s Head of Data & Analytics Aron Clymer adds for smaller organizations: “Turn all of your employees into analysts. Give them the tools and the data, and teach them how to fish.”

Key Point 3: Stay scientific about your data.

As essential as data access is to building a data-informed culture, better data access comes with its own share of challenges. One thing our experts agree on is that it’s important for everyone to be scientific about how they approach data. Specifically:

  • Clearly define your metrics. Josh Curry of MindBody says when different teams go to their respective analysts, phrasing the same question in slightly different ways, they wind up with what he calls the problem of “dueling analysts.” Without having clearly defined metrics across teams, you’ll end up with different answers to the same question–resulting in a loss of trust. Says Popsugar’s Aron Clymer, one way to avoid a problem like this is to pick robust success metrics at the outset and define them.
  • Maintain skepticism about your data. It’s easy to blindly accept what your data is telling you if it matches your hypothesis. Make sure to dig deeper and question your assumptions.
  • State your hypotheses. One of the best ways to hold yourself accountable for your hypotheses and experiments is to simply write it down, says Amplitude CEO Spenser Skates. It can help to document the reasoning behind designing an A/B test for future reference.

Got Data? Panel with Nir Eyal (author of Hooked: How to Build Habit-Forming Products), Spenser Skates, Noah Jessop (Head of Data at Publishers Clearing House), and Aron Clymer (Head of Data & Analytics at Popsugar)

Key Point 4: Embrace the human side of data.

Data accessibility means not just looking at quantitative data; it also means investigating qualitative data. Says Amplitude Head of Design Winnie Wong, “It’s the qualitative side of things that turns numbers into a person.”

During the new Deep Dive session, Winnie and Amplitude Head of Product Justin Bauer shared how they used quantitative and qualitative data about Amplitude customers to understand a fundamental question: Who exactly were our customers? The product was originally built for analytics power users, of the “Ex-Zynga PM” flavor. But encouraging better data accessibility and data culture meant we had to figure out who else needed analytics. Through quantitative means, we grouped our users into different clusters based on the actions they performed in the platform; through qualitative means, we assigned identities and characteristics to these personas. Ultimately, this research informed many of Amplitude’s new product and design choices.

Deep Dive: Building Products with Customer Data with Justin Bauer (Head of Product at Amplitude) and Winnie Wong (Head of Design at Amplitude)

Also echoing Justin and Winnie’s approach that evening was Nir Eyal, author of Hooked: How to Build Habit-Forming Products. In order to build a more addicting product, Nir emphasizes building context around your behavioral data by understanding consumer psychology. Understanding internal triggers–emotions, routines, daily situations–and coupling that with external triggers like push notifications can lead to explosive growth.

To hear more of what our fantastic speakers had to say, be sure to check out all the videos included in this post. Special thanks to our guests Josh, Nir, Noah, and Aron for being incredible panelists!

About the Author
Image of Archana Madhavan
Archana Madhavan
Instructional Designer
Archana is an Instructional Designer on the Customer Education team at Amplitude. She develops educational content and courses to help Amplitude users better analyze their customer data to build better products.
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