AMA: Gusto Head of Demand Generation, Jordan Hwang on Building a Demand Generation Team

I generally like to communicate through two types of vehicles: Weekly progress updates - this is meant to convey what's happening now * Performance metrics (absolute numbers, performance vs. goal, YoY %) * Drivers of above performance (i.e. what's causing it) * Adjustments that will be made given the drivers (i.e. what are we doing differently?) * Where we're stuck (i.e. how readers can assist) Monthly progress updates - this is meant to convey overall progress against a larger strategic plan * Performance (monthly to give context) * Initiatives that we committed to doing at the start of the plan (more context as to the what and the why) * Progress of those initiatives * Bottlenecks * Adjustments that we'll making based on what we learned (this reflects more against initiatives and where we're spending time)

For me, it all boils down to what's the most impactful. Generally speaking, we find more short-term and long-term success by going for depth vs. breadth. The key question to answer is: How do you know where to place your bets? I like to use a betting framework for this. The key is to understand, as cheaply as possible, what's the most likely to return against the use of resources (people, effort, money, etc.). We can understand this through the use of money or data (qualitative and quantitative). Once we've shipped a few things (campaigns, experiments, etc.), it becomes clear whether or not we've got something that has legs. The key is to lean into those with legs and stop doing things that don't. Doing that provides impact early, and gives both you and the company breathing room. Once you've reached that stage, you can go back and figure out the ones that didn't show a lot of early success and determine why. 

The biggest thing that many demand generation teams miss is a Revenue metric. Typical ones to think of are: * ARR * Customers * Pipeline ($ based) * # of Opportunities For many demand generation teams, there's a tendency to believe that their job is done when the lead is there (MQL, PQL, etc.). The reality of the situation is that the job of the entire function is to drive impact across customers and revenue. If we're providing low quality leads that doesn't ultimately translate into pipeline and revenue, then we're missing the intent of our job.

Known impact above all else. Find the most impactful thing to work on as quickly as possible. To get there, I use the following. 1. Create a short list of items to focus on by using: * Critical thinking (i.e. who's my desired customer, what matters to them, where do they hang out, etc.) * Pattern matching (i.e. other businesses/business models do it this way * Historical data (i.e. what's working in the past) 2. Use the above and start small and scrappy * Forms before databases * One-offs before templates * Do what's unsustainable 3. Measure the results from the above and find what works 4. Begin understanding why it's working 5. Use the above to understand where it makes sense to build infrastructure to support. Infrastructure is meant to make things easier and more scalable. There's no point in doing that on something that's not important. Once you have that, it becomes a prioritization conversation around the asks. Would your CEO rather that you spend time on something that's delivering known results, or pet projects? Do any side projects conflict with what you've learned from the above?

Understand what's currently working when you come in, and accelerate it. If you're in an established business, they must be doing something right to be generating demand and revenue right now. Understanding what that is will help you from a prioritization and early impact standpoint. Over time, understanding why helps you identify other areas of impact that you can spin up that match where prospects are and the internal GTM flywheel.

Our demand generation team has three major pillars: * Website - responsible for our corporate website. While they care about impact, they also need to service other needs for the company beyond pure demand generation. They're held to a slightly different standard, as a result. * Acquisition - responsible for acquiring new leads. We have it split between Organic (SEO), Paid, and Channel (BD partnerships) * Customer Marketing - responsible for educating and upselling/cross-selling customers There's multiple teams that live within those major pillars that are structure more tactically, but the three pillars comprise the major differences in expectations and OKRs that would be associated there.

For me, the best demand generation candidates are growth-oriented, have customer empathy, and have a strong quantitative bent. For growth-oriented, this means that they likely have some combination of the following: * Natural curiosity - What's working/not working? Why? What can I do differently? * Self-awareness - What could I/we have done differently? * Drive - A desire to make their numbers, regardless of the circumstances For customer empathy, this means that they understand who the customer is, and what their circumstances are. Demand generation is much more impactful if one can meet the customer where they are, both physically, mentally, and psychologically. Out of the three, nailing this produces the most outsized returns. I left the strong quantitative bent as the lowest priority because it's generally something that most candidates have, so it's the least differentiating. However, there's an aspect of this that's important, which is not only a comfort in working with numbers, but being able to meld the numbers with an understanding of what's happening. The cherry on top is experience. It's always great if they have it, on top of the above. However, I've generally found that folks who possess the above three qualities will be able to quickly make up any experience gaps versus someone who doesn't possess the above.

Be comfortable being junior, and the first demand generation hire. This means that you're acknowledging two things: * You don't have a lot of outside experience to draw on * You don't have someone inside the company who will be able to provide you with a lot of coaching/guidance If you acknowledge that, though, that gives yourself the permission to do much of the following: * Ask a lot of internal questions that help you learn (Why do we do this? Why does that work?) - feel free to play both the "junior card" and the "new card" * Reach out to experts (i.e. people who are acknowledged as best at the things you're trying to learn, or are in companies that are doing those things really well) to ask questions and understand * Just go out and experiment and learn, because the chances of you getting the right answer without just going for it are going to be low As always, the key in this learning isn't to understand the what, but the why behind it. If you talk to experienced people, and ask the right questions, you quickly learn the following: * What they're doing that's working, and why it's working * What they tried in the past that didn't work * Where nuance matters, and what's seemingly insignificant is actually significant You can then map that back against what you're learning about the uniqueness of your company, and begin to put together a sense for what fits/doesn't fit. From there, you can go for it and learn.

My general framework is as follows: * PMM is likely to bring the best holistic qualitative insights to the table from the work that they're doing * Demand Generation is likely to bring the best live quantitative data to the table from the work that they're doing Because of that, it's a give-and-take from a responsibility standpoint. * Both PMM and Demand Generation should bring ideas to the table around what can/should be tested * They should be able to workshop those ideas together for refinement. * Example 1: Demand Generation sees some program-specific trending that causes them to want to focus on a particular theme. They bring it to PMM for more ideation as PMM can provide useful context/color based on their work. Together they come up with some ideas for testing. * Example 2: PMM has run a large customer insights study to understand key value props for the product. They bring those findings over to Demand Generation to refine based on program, audience, etc. Together, they come up with some refined ideas for testing. Decisions on what gets acted on are dependent on who's responsible for the number (this is generally Demand Generation). They're ultimately responsible for deciding, based on impact, when they'll be able to do such a test. However, by refining the ideas together, there's also alignment about importance, etc.