CODECADEMY FOR BUSINESS — founded in 2019 to expand Codecademy’s interactive code training services from individual consumers to other businesses, had a small sales team and members of other teams helping them on the side. After two years, the company recognized the need for a full-time team dedicated to B2B growth. I was marketing hire #2.
Codecademy didn’t confidently know who their B2B target audience was and it was hindering their ability to develop effective marketing, sales, and product strategies.
Create a set of buyer persona profiles the sales, marketing, and product teams could use to develop more effective growth strategies.
The first ever B2B buyer personas made it possible for the marketing, sales, and product teams to develop more targeted, strategic growth strategies that drove 49% YoY growth.
I started by collecting existing insights to establish a baseline of knowledge, assess what needed validation, and identify gaps for further analysis.
Between research findings and first-hand knowledge from Codecademy for Business founding members, there was a lot of valuable information already available, but none of it was organized or synthesized for a more strategic understanding of our target audience.
The sales team had the most frequent and direct contact with prospective buyers and customers. They shared high level details about buyer demographics, problems, and training needs they gathered from conversations in the last couple of years.
A jobs-to-be-done (JTBD) study and product market fit (PMF) survey completed earlier that year provided qualitative and quantitative data about customers and prospective buyers that explained why and when they choose us.
I used our CRM (Hubspot) and analytics tool (Looker) to analyze the 500+ contacts in our database and validate learnings. When I hit a wall with their reporting, I continued analyzing exported data in Excel.
In addition to my previous experience with buyer persona templates, I researched new, alternative template designs I could draw inspiration from.
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I was particularly interested in the types of information different persona profiles included, especially those from companies in similar industries as ours, and started narrowing down our specific needs and requirements.
Based on conversations with the persona profiles’ end-users, I decided on the following inputs:
I started with a slide template from our brand deck and created a prototype for a single persona to get a sense of how content would fit and made adjustments as needed.
Once I landed on a design that was easy to read and more polished than early Codecademy for Business artifacts, I collected feedback from marketing, sales, and product stakeholders. I addressed all feedback and questions and got the positive confirmation I needed to finalize the remaining persona profiles.
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The metric we initially looked at was engagement, a leading indicator of whether our new targeted, more personalized tactics were moving us in the right direction, and they were.
In the first 3 months, we achieved:
Higher ad conversion rates at different stages of the ad funnel.
Higher email engagement rates with prospects.
The most requested piece of marketing collateral from the sales team was the customer case study. My persona work helped direct efforts by telling me whose stories we needed to focus on.
In addition to knowing who our buyers were, we needed to understand commonalities in how different customers were using our solution. Once the buyer personas helped surface more success stories, I was able to compare and identify our top use cases.
The use cases I developed with the team in 2021 were critical to the GTM strategy of a new product tier that launched later that year. They continued to be useful for messaging and positioning in following years. One of the use cases identified, technical onboarding, became a 2024 priority for the product team.
Do what you can with what you have.
There are a lot of challenges that come with being a new team under a nascent business unit in an established company, and I often got caught up with wanting to fix how the team was operating without being realistic about our constraints — time, resources, and business objectives.
Determine how good or bad the data is early on.
I learned how poor our customer data quality was when it came time to analyze it. We were able to apply a band-aid fix so I could work with slightly better data, but it still wasn’t optimal.I should’ve evaluated the health of our customer data sooner so I had a better understanding of what I was up against and more runway to address data problems before analyzing it.
