My team and I recently had the pleasure of chatting with Steven Hunt, the Vice President of Product Management at Skytap. Steven's been around the block a few times in the tech world, and boy, does he have some stories to tell. From his days as a self-proclaimed "Windows guy" to leading product teams at various startups and established companies, Steven's got a unique perspective on how to use data to drive product decisions and ultimately, business growth.
We dove deep into how product teams can work hand-in-hand with sales and customer experience to create a data-driven culture that actually moves the needle.
Q: Steven, you've mentioned that product teams need to pay attention to a broad cross-section of the business. Can you elaborate on how you see the interplay between product, sales, and customer experience?
Steven: Absolutely. At Skytap, and really in any B2B SaaS company, the product team is constantly juggling inputs from various parts of the organization. On one side, we've got the customer experience team bringing us insights about what's preventing customers from being successful - things like time to value, support ticket resolution times, and so on.
But we're also keenly focused on net new customer acquisition. What's holding us back in the sales cycle? As a smaller company in growth mode, we're very much in account acquisition mode. As companies grow, that focus often shifts to a more equal balance between new logos and existing customer success. And if you're really big or have a broad portfolio, you might be more focused on driving consumption within your existing customer base.
The key is to align all of these perspectives with the overall company goals and use data to inform our product strategy and roadmap decisions.
Q: That's interesting. How do you approach measuring success across these different areas? What metrics do you typically focus on?
Steven: In my opinion, product teams should be looking at both usage and revenue metrics. At Skytap, since we're an infrastructure-as-a-service company, we have metered rates for compute and storage resources. So we can directly tie usage to revenue.
But even for companies with different pricing models, you can often extrapolate revenue impact from usage data. The important thing is to understand how your work as a product team contributes to dollar attribution. If your company is revenue-oriented (and let's face it, most are), you need to be able to draw that line.
We also look at things like time to value for new customers. We'll do customer journey research to identify blockers that are elongating that metric and tackle those issues in our roadmap.
Q: It sounds like you're dealing with a lot of different data sources. How do you go about gathering and prioritizing all this information?
Steven: Great question. We start by setting our product strategy to align with overall company goals. Then we track KPIs against those objectives. Beyond that, we're looking at various indicators that help us understand how to evolve the product roadmap and support the go-to-market motion.
For qualitative feedback, we do a mix of internal leadership calls, direct customer interactions, and leveraging various input channels like Slack, CRM data, and dedicated feedback emails. In previous roles, I've used tools that use machine learning to analyze this feedback, identify patterns, and even attribute dollar values to different themes.
I'm a big believer in understanding the process manually first, then implementing tools to do it at scale once you have a good handle on things.
Q: You've emphasized the importance of cross-functional collaboration. Any tips for fostering that kind of culture, especially for smaller teams or startups?
Steven: I'll be blunt here - anyone not doing this is operating old school. Success comes through collaboration, full stop. It starts with having shared success targets at the company level. Then, it's crucial to have regular meetings where cross-functional leaders, including product, customer experience, and others, are reviewing data together and understanding how different metrics relate to each other.
For example, if I'm just looking at usage metrics in isolation, I might miss the fact that our pricing structure is creating a situation where revenue isn't growing in line with usage. By having these cross-functional conversations, we can identify and address these kinds of misalignments.
It's really about creating a culture where everyone understands how their metrics tie back to overall company goals and how they interrelate with other teams' metrics.
Q: Last question - for someone just starting to implement this kind of data-driven, cross-functional approach, what's the first thing you'd recommend they focus on?
Steven: Start with the basics. Set up metrics to understand usage trends and gather qualitative feedback from various channels - sales, customer success, customer experience, and so on. Then, create a quantifiable agreement on how to identify what's most actionable.
If your goal is revenue-oriented, attach metrics like opportunity dollars or net retention dollars to that feedback. Look at the frequency of different types of feedback and the metrics attached to them. This will help you prioritize where to focus your efforts.
And don't forget about customer satisfaction! CSAT scores can be a valuable additional data point to consider alongside these other metrics.
The key is to start somewhere, iterate, and keep pushing for that alignment between teams and goals.
Conclusion
There you have it - a masterclass in data-driven product management from Steven Hunt. It's clear that success in today's fast-paced tech world isn't just about building cool features; it's about creating a culture of collaboration and using data to align product decisions with broader business goals.
Whether you're at a scrappy startup or a tech giant, there are valuable lessons here about breaking down silos, leveraging both quantitative and qualitative data, and always keeping your eye on the prize (aka revenue... let's be real).
Big thanks to Steven for sharing his insights and experiences. Now, it's your turn - what data are you using to drive your product decisions? How are you fostering collaboration between product, sales, and customer experience? Drop us a comment and let's keep the conversation going!
