We recently had the pleasure of chatting with Angela Fleming, VP of Product at FreeAgent, a cloud accountancy software solution that's part of the NatWest Group. Angela's got a fascinating background spanning automotive tech, retail, and now fintech, giving her a unique perspective on building data-driven, customer-centric products. We dove into how she structures her product org, leverages data for decision-making, and fosters a culture of innovation. So grab your favorite analytics dashboard, and let's jump in!
Q: Angela, can you give us an overview of your role at FreeAgent and how you structure your product organization?
Angela: Of course! I joined FreeAgent in 2020 as Head of Product, working closely with our CPO who was also a co-founder. When he moved into the CEO role, I stepped up to VP of Product on the executive team. In this role, I'm responsible for overseeing the entire product department and ensuring we have a happy, high-performing team that's delivering against our company and product strategies.
Under my purview, we have several key functions:
1. Product Management: Our core product teams working on feature development and improvements.
2. Product Operations: A new function I introduced this year to support our product managers in three key areas - business and data insights, market and customer insights, and processes and best practices.
3. Commercial Operations: Focusing on commercial partnerships and agreements.
4. Project Management: Ensuring smooth execution across our initiatives.
We also work closely with our User Research team and Data Analytics & Data Science teams, which serve as crucial support functions for our product org.
Q: That's a fascinating structure, especially the Product Operations function. Can you elaborate on why you introduced this role and how it's impacting your team's work?
Angela: Absolutely. I introduced the Product Operations function in January of this year, and while it's still in its infancy, we're already seeing some interesting outcomes.
One of the main drivers was to alleviate some of the strain on our Data Analytics team. We found we were often using them for relatively straightforward analyses when we really needed them focused on more complex, in-depth work. By bringing in Product Ops, we can handle more of the "low-hanging fruit" analyses in-house, freeing up our data scientists for the really tough problems.
For example, one of the first projects our Product Ops team tackled was looking at the relationship between Net Promoter Scores (NPS) and churn rates. We wanted to know if there were any indicators in our NPS data that could help predict churn. While we didn't find a clear correlation, just having a definitive answer to that question was valuable. It helps us focus our efforts elsewhere and avoid making assumptions based on incomplete data.
Another key focus for Product Ops has been maximizing the value we get from our customer support and success teams. These teams are on the front lines talking to customers every day, and there's a wealth of information in those interactions. We're working on ways to better capture and analyze feature requests and customer pain points from these conversations, without adding extra burden to our support staff. The goal is to surface these insights to our product managers in a more manageable, actionable way.
Q: It sounds like you're very focused on data-driven decision making. How do you balance quantitative data with qualitative customer insights in your product process?
Angela: It's definitely a balancing act, and one that we're constantly refining. We have several channels for gathering both quantitative and qualitative data:
1. Quantitative: We use tools like NPS surveys, churn analysis, and product usage data to get a high-level view of how we're performing and where there might be issues.
2. Qualitative: Our User Research team conducts in-depth interviews and usability studies. Plus, as I mentioned, we're working on better ways to capture insights from our support and success teams' daily interactions with customers.
3. Market Research: Our Product Ops team is also focused on gathering broader market insights to inform our strategy.
We use an ICE (Impact, Confidence, Effort) framework for prioritization, and all of these data sources feed into that process. The quantitative data often helps us identify areas to investigate further, while the qualitative insights give us the context we need to truly understand the problem and design effective solutions.
It's also worth noting that we're always looking for ways to automate and improve our data analysis. For example, we've done a lot of work with machine learning for transaction categorization, which is a key feature for our users. And our data science team is currently working on some exciting AI prototypes that could further enhance our product.
Q: Speaking of AI, what developments in the product management space are you most excited about?
Angela: AI is definitely a hot topic right now, and we're exploring it carefully. Our approach is very much focused on solving real user needs rather than just implementing AI for the sake of it.
Some of the AI applications we're most excited about are actually internal - tools that could help our support or sales teams work more efficiently or share information more effectively. We're also looking at ways AI could enhance our existing features, like our transaction categorization or financial insights.
Beyond AI, I'm really excited about the potential for more personalized, data-driven insights in fintech products. At FreeAgent, two of our core user needs are "nailing the daily admin" - making financial tasks less laborious - and "being better at business." We're constantly looking for ways to automate routine tasks and provide actionable insights that can help our users make better business decisions.
Q: Lastly, can you share a bit about how you foster collaboration and innovation within your team and across the broader organization?
Angela: Absolutely, this is something I'm really passionate about. We put a lot of emphasis on having a clear vision and strategy that everyone understands. We share our company strategy with the entire business towards the end of August each year, and then each department and team develops their own strategy that ladders up to the company goals. This gives everyone a clear understanding of how their work contributes to our overall mission, which I find is hugely motivating.
We also use a "three amigos" approach to collaboration, both within the product org and at the executive level. For example, I work closely with our CTO and Director of Design as the product "three amigos." We have similar trios at different levels of the organization to ensure we're always getting diverse perspectives on our work.
At the executive level, we meet daily for stand-ups and have longer tactical meetings weekly. This keeps us aligned and allows us to quickly address any cross-functional issues that arise.
Lastly, we put a lot of emphasis on creating an environment where people feel empowered to share ideas and take risks. Some of our best innovations have come from giving teams the space to experiment and iterate. It's all about creating that balance of clear direction and autonomy that allows creativity to flourish.
Conclusion
Our chat with Angela offers a masterclass in building a data-driven, customer-centric product organization. Her emphasis on cross-functional collaboration, strategic use of data, and fostering a culture of innovation provides a roadmap for any product leader looking to level up their team's performance.
Key takeaways:
1. Invest in dedicated Product Operations to bridge the gap between data science and product management.
2. Balance quantitative metrics with qualitative insights to get a full picture of customer needs and product performance.
3. Approach new technologies like AI with a focus on solving real user needs, not just innovating for innovation's sake.
4. Foster collaboration through clear communication of strategy and cross-functional "three amigos" teams.
5. Create an environment that balances clear direction with autonomy to drive innovation.
Whether you're just starting your product management journey or you're a seasoned veteran, Angela's insights remind us of the importance of staying connected to our customers, leveraging data effectively, and always striving to solve real user problems.
Thanks to Angela for sharing her wisdom and experiences. Now it's your turn - how are you balancing data and customer insights in your product decisions? What challenges have you faced in building a collaborative, innovative product culture? Drop us a comment and let's keep the conversation going!
