David Yockelson

No one is going to know or inherently agree on RACI elements...or who can trash those and how. So based on an understanding of what product marketing should be doing/will do - either driven by PMM or participated in by PMM - creating a RACI and gaining agreement for it so that work actually gets done and people are accountable, especially because of the overlap always present between PMM and other functions, is critical.

There is a lot to respond to for this, but the overarching first step must be to have a face to face (or as close to that as possible) meeting with the counterparts or leads to each other function (product, sales, customer success, CEO, demand gen, etc.) to understand their goals WRT strategy, what their needs/expectations are based on what they know about product marketing, and then explain what product marketing REALLY does and what it will do for and with them. Everyone will have a different expectation for product marketing, so job 1 is to set the groundwork on the role, responsibilities, priorities, and eventually, SLAs as needed.

Options: 1) Don't fail. 2) If you're going to fail, do it quickly. 3) Don't take a bunch of money if you are worried more about failing than succeeding (also don't hire anyone). 4) Paranoia, per Andy Grove, is OK; fear and resulting hesitation or "paralysis by analysis" are not. Do your research; make decisions; experiment. If an idea fails, you've learned something. 5) Get help/ask/test ideas in the market. There are so many people willing to listen (for free, even!) and offer the benefit of their experience...but choose wisely, my friend. 6) Figure out who you think your best customers will be and research the heck out of them. TALK to them. Find out what makes them tick.

Which data is being modeled? I've seen companies that model based on existing customers (i.e., which among these represents our best chance to win and thus our ICP) and/or also on a broad set of filmographic, technographic, and other elements from which an ICP would be constructed based on (here's the work) best chance to win based on PMF and the needs of those potential buyers. Most important to get your parameters right so the models reflect those customer types where you have an outside chance to win.

Know your market. Know your product. Know your audience. Demonstrate value to all the stakeholders for whom you are the "connective tissue" by providing insight and mechanisms on how they will succeed. Since you can't do everything at once (though product marketers are expected to), you'll pick the most critical element related to revenue that you can among those options. And you'll create and/or show metrics related to that endeavor that prove that your actions made a difference. After that bowling pin is knocked down...go for the others.

One would hope that some form(s) of usage and/or engagement analytics would be used to understand - based on the patterns exhibited by those early/test users - whether their use cases are fulfilled as expected, whether certain features/functions work as intended, and whether workflows (if applicable) flow as designed. Experiments can/should be automated and instrumented with analytics to provide the best feedback, irrespective of surveys, Q&A, etc.