Episode: 5

The Convergence of Data Engineering and Marketing with Nic Discepoli of Ruby

with Nic Discepoli

Customer Analytics Lead, Ruby

On this week’s episode of The Data Stack Show, Kostas Pardalis and Eric Dodds are joined by Nic Discepoli for the first of two conversations about Ruby, a startup where he is the customer analytics lead. This Nashville-based company is designed to help families navigate their financial situation in some of life’s most challenging moments, often corresponding with a medical event.

Notes:

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  • Launching Ruby and Nic’s involvement in the company (3:35)
  • Realizing that tracking data manually on spreadsheets was no longer sustainable (7:07)
  • Rundown of Ruby’s toolset (9:50)
  • Challenges with data quality (14:27)
  • Using unique IDs and following UTM parameters through the stack (21:04)
  • Recalculating customer acquisition cost with data (33:05)

Transcription:

Nic Discepoli and Ruby

People with Nic Discepoli’s skill set of navigating the worlds of data engineering and analytics will be in high demand. Although he doesn’t consider himself a developer, he’s tackling his startup’s need for building out the stack, something hard for a startup to take the time to do in the early stages when they’re focusing on getting customer feedback and driving adoption. He writes SQL and JavaScript, which can be pretty rare for someone who is consuming the data at an early-stage startup, but could be a sign of things to come for more and more start-ups.

Nic helped formulate the idea for Ruby while working as a research analyst looking at industry trends and identified the need for providing people with financial guidance in terms of reducing medical bills and safely transitioning management of finances from an individual to a family circle.

The company has developed web apps and is in the process of building out its first mobile app. Nic identifies tech integrations on the marketing and operations side that will work for the entire business and integrate with the stack and writes event code to track users, analyzes that on the back end and reports that to stakeholders.

The need to build out some data infrastructure was first apparent after putting out early marketing material and campaigns and seeing that the conversions weren’t matching up with what they were seeing in their email database. “We wanted to build from the ground up and have a 360-degree view in mind and the thought was if we took the time to build it on the front end, it would not be as hard to retrofit something to a stack that wasn’t designed to work that way.”

Tool Set

Nic walked through the tool set that Ruby is utilizing. For collection, for their web apps, Ruby uses AnalyticsJS managed through Segment for all of the front end code and that sits on top of their marketing web sites. They utilize Google Tag Manager’s robust triggering system and Nic writes the could to fire those off for Segment to read. Developers use the .NET SDK on the back end and they will be implementing with Xamarin as their mobile tool of choice.

Nic spent some time discussing Ruby’s use of Google Tag Manager. For Nic, he notes that “It helps me as a non-developer to write code and save the developers time.”

One of the biggest advantages he found was being able to insert code when you don’t necessarily have access to the underlying HTML. “I don’t want to dive into the HTML of our WordPress site every time that I want to fire off a new event. It also saves us from having to deal with custom JavaScript triggers,” he said. “We implement one tag in the header of our site and then I can take advantage of Google Tag Manager’s really robust triggering system and by filtering things, you can get really dynamic with how you’re firing events.”

He’ll then use custom javascript to grab things off the page dynamically and insert variables into scripts. They pull UTM parameters from the URL string with its attribution information and put that into whatever event they want to fire, like a sign-up event.

They further incorporate Google’s Data Studio to help visualize the data for analysis and to provide charts and filters for analysis.

Nic has definitely run into situations where he’s faced challenges with the quality of the data and has worked on emphasizing standardized implementation practices. “As someone who’s implementing the code that’s running a lot of the front end events,” he said, “and someone who’s using them, I’ve definitely been there where it’s like, ‘I don’t know if I’m seeing this number right now because I wrote the query wrong or I wrote the original code wrong.’ Sometimes it’s a little bit of both.”

Better Understanding Customer Acquisition Cost

One way that Nic has been able to use data to influence business decisions is to help Ruby better assess true customer acquisition cost. “The one really powerful set that we’ve been using is actually around the idea of trying to understand each anonymous user’s individual customer acquisition cost,” he said. “Typically when you think of customer acquisition cost, you’re taking the sum of the amount of money you spent on a campaign divided by the number of conversions that you got. It’s an aggregate function.”

They sum all of the spend and conversions in a given day by every unique ad ID that comes through their system. They then assign that back to a unique table with user anonymous IDs on it. They use a dynamic ID to pull in their first and last touch and the attribution data around that. They can see the timestamp difference in values and how many page views it took for them to convert and that data set has been particularly useful and flexible. Nic was using it to identify what audiences were most efficient to acquire but then shifted to testing landing pages against each other and was able to very quickly layer in the landing page name and variation to test against each other. It provided a more accurate view of the cost per acquisition.

For now the focus for Ruby is developing its mobile app and learning how to best market that. The company is also building out a new website to Webflow.

The Data Stack Show is a weekly podcast powered by RudderStack. Each week we’ll talk to data engineers, analysts, and data scientists about their experience around building and maintaining data infrastructure, delivering data and data products, and driving better outcomes across their businesses with data.

RudderStack helps businesses make the most out of their customer data while ensuring data privacy and security. To learn more about RudderStack visit rudderstack.com.