🚀 Andrew Miller: Monograph, Senior Growth Product Manager

Market-to-Revenue

Meet Andrew Miller, Senior Growth Product Manager at Monograph. Do your research. Deeply understand how your customers make money. Run lots of tests. Trying to understand user behavior. Double diamond model. The rugged landscape model. Feedback loops. AB testing. Fake door tests. Aligning continuous delivery on the engineering side with go-to market.

13 insights. 6 rapid-fire questions. Show transcript.

What are 3 ways that your team converts your market into revenue?

As a product manager, a lot of my work is situated sometimes a little bit upstream from GTM. My teams tend to be made up of designers and engineers, and I do work closely with sales, marketing, and CX more on the GTM side. It’s a huge part of my job to ensure that we're building the right things so that we can take those to market and convert them into revenue.

1. Do your research. Part of that process, to start, do your research. It's important to have confidence in what you're building and feeling confident that you're building the right thing. Have a hypothesis that when you take this product, or this feature, to market, you can convert it to revenue. When you're doing your research, you want to have a balance of qualitative and quantitative data. Go talk to customers to get your qualitative. Dig into your application database, data warehouse, industry stats, and market figures to get your quantitative.

For the second piece, I’ll split it into 2 categories, B2B and B2C.

1. So in a B2B context, one of the things that's super important is to deeply understand how your customers make money. The better that myself and my team understands the business of our customers, the better we can make product decisions, because we're making those in the context of asking ourselves, “What's going to make our customers as successful as possible?” And that tends to be the best way to convert your product into revenue.
2. On the B2C side, run lots of tests. Make small changes in your product and messaging. Observe the resulting behavior. Note any impact on your revenue. This is totally applicable to B2B as well, but I map it to B2C here because when you're dealing with consumers, you tend to have a much wider range of variability and it can just be a little bit more difficult to keep a pulse on long-term trends and patterns. So always be testing.

What is 1 hard problem that you recently overcame?

1. Aligning continuous delivery on the engineering side with go-to market. One hard problem that's very timely. Continuous delivery, to put it simply, is when engineers are able to continually deliver updates to the code base on production. It's great on the engineering side because small incremental scopes of work that are continuously delivered to production results in fewer dependencies between engineering teams, results in less risk with each deployment because they're small deployments, and allows engineering teams to move super fast, which is awesome. However, on the go-to market side, this can actually create quite a bit of complexity because you have a go-to market team that's really trying to figure out, “How do we talk about this product or this update? How do we frame our product in a way that the market is going to react positively to it?” Meanwhile, the product is constantly changing, so it makes it a little bit difficult to grab on to certain messaging points for the GTM team. And so this is something that I'm working on, but really the entire product team at Monograph is working on right now, and Pete and Dixon are leading the charge. At least on my team, one of the solutions that we arrived at recently, quite simply, is feature flags. It's actually helped a lot because I was talking with Steven, my engineering manager, and explaining some of the dynamics there, we aligned on using feature flags because that allows the engineering team to continually deliver to production without those updates actually being available to customers yet. That gets the GTM team time to come up with the right messaging, and create their own strategies, to take it to market all at once, so they're not taking a feature that's constantly evolving to market.

What is 1 roadblock that you are working on now?

1. Trying to understand user behavior. I'm at a new company, I'm at Monograph, I've been here for just over three months, and I'm really trying to understand user behavior. So, your application database, it's going to have lots of information about the records that your users are creating and manipulating, which is really insightful. We've been digging into that, but it won't typically tell you how your users went about doing it. It won't reveal their behavior in the product. For this, you need event tracking. You need solid instrumentation throughout your product that can capture and reveal the story of their behavior. Setting that up is a highly cross-functional effort in which product and engineering need to be super, super aligned. So, we've got a really good team working on this right now. It's a hard project, but it's fun, and I'm excited.

What are 3 mental models that you use to do your best work?

I love this question. I love mental models. I've got probably four books that are just filled with models. Some mental models, and just other models. Three that I do tend to fall back on often and work out:

1. Double-diamond model. I see this most commonly applied to product management, but I think it's a wonderful, general model that can be applied to many, many contexts. So in the double diamond model, you have two diamonds next to each other, if you kind of just visualize that. If you go from left to right, the first time it opens up and then it closes. And then, the next time it opens up and then it closes. So what the model captures is a sequence of divergent thinking, followed by convergent thinking, followed by divergent thinking again, followed by conversion thinking. And typically, what I see is the first diamond is focused on product discovery, product definition. So you're exploring different feature ideas. You're exploring, you're diverging, and then you converge on the right feature. Then, you hand it over to engineering and then they're figuring out how they want to build it, and then they're delivering. I think it works great for go-to market as well, just applying divergent, followed by convergent thinking in go-to-market.
2. The rugged landscape model, which is one of my favorites. So this one, if you imagine you're on a vast landscape and there's peaks and valleys all around you at different heights and depths. Your goal is to get up as high as possible. And so, one thing you could do is look around you, as far as you can, and find the highest peak, and start walking to it and walk up that peak. You might think when you get there, “You won.” But really, what you've found is your local maximum, which is different than the global maximum, which are two important terms in the rugged landscape model. So your local maximum is the highest peak that you can see. Whereas, your global maximum, if you zoom out all the way and look at the entire landscape that you can't see at once, there's probably some peak out there in the distance that's way higher than your local maximum. So, how do you find it? Finding your local max is good, but really we want to get to the global max. So one efficient way to go about finding a global maximum is to start in many different locatio...