Product Marketing Managers (PMM) don’t have many purpose-built tools for their role.

When you think about it, most of the tooling that PMMs use is repurposed from the broader sales and marketing stack. Fan-favorites like Hubspot and Ahrefs can provide immense value, but when it comes down to it, the product marketing function still involves a lot of manual effort.

We hear a lot about AI and automation in GTM circles. For example, Sales teams using AI to email prospects and to automate compliance questionnaires. But you don’t hear much about its impact on the Product Marketing side. Why is that?

Do us data nerds just not understand the role?

Is there some deep technical hurdle that AI can’t get over?

Is there a conspiracy to keep automation out of the PMM org?

Why Product Marketing Tasks Cannot be Automated (or Can They?)

What if the explanation were as simple as you just can’t automate the duties of a product marketer.

Hear me out.

1. Understanding customer challenges and pain points cannot be automated

PMMs bridge the gap between the customers and the Product, Sales, and Marketing teams. They take customer pain and product feedback as inputs to produce powerful messaging as outputs.

This recurring loop serves as the foundation for all great product marketing programs. It’s different for every product and it can feel more art than science. Sure, you can build a formal process around gathering feedback, but no amount of tooling can replace the value of a 1:1 conversation with the customer.

This process requires empathy, trust, and listening to multiple sources of feedback. It also involves constantly revisiting your content to measure its impact. Perhaps in the future we’ll see more automation here. But for now, we rely on human PMMs to get it right.

It takes a (human) village

Compelling, differentiated messaging is tough to create even for a human. Getting a machine to do it is a whole other problem.

Matt Krumholz, Director of Competitive Intelligence, Splunk

2. Robots can’t builds bonds with the sales org

The success of a Product Marketing team heavily depends on cultivating a close relationship with their other customer: the sales org.

Working in the role requires both product and people skills. It cannot be understated how important it is to spend time with the sales teams and understand their unique pains, nuances, and experiences in the field.

  • What messaging is working?
  • How are the new demos being received?
  • Did you get much traction from that blog post?
  • What did the customer like about the new sales pitch?

Great product marketers have these conversations on a daily basis. They join sales calls and attend QBRs. They run training sessions and gather feedback on content. Some PMMs even analyze win/loss reports to get deeper insights into the sales funnel.

You’ll rarely see a Sales Kickoff or team activity that doesn’t have a product marketing person in attendance.

I once got stuck in traffic for 4 hours with a sales and product marketing leader. It was one of the best product conversations we ever heard. A year’s worth of content ideas was strategized on that highway jam.

How do you automate that?

3. Original, compelling content cannot be automated

Generate some headlines. Write a blog post. Create the demo. Ship it. Done.

Product Marketing output is the culmination of multiple diverse sets of inputs. The inputs are tough to gather, the outputs are difficult to measure. It feels like more art than science.

Yes, maybe you can generate copy, but product marketing is more than just copy. That’s what a lot of people get wrong about the role. Crafting compelling, differentiated messaging is tough enough for a human. Getting a machine to do it is a whole other problem.

Are we automating art?

Enterprise pain points involve multiple stakeholders with very different experiences. That makes messaging more of an art than a science. Distilling it down with AI would oversimplify the nuances and complexities that enterprises face.

Lani Leuthvilay, Product Marketing, PlainID

And yes, there are some obvious use cases of AI for product marketing. But how does a machine know what your value proposition is? Where is the customer feedback coming from? Does your messaging sound lame or punchy?

An AI can help write your next blog post, but it cannot invent effective messaging that resonates. That messaging has to come from somewhere. For now, that’s going to be a human.

Product Marketing AI Meme

So what is being automated by PMMs?

Product marketing is more art than science, that’s for sure. But while the artsy part of the role is still handled by humans, the science is already seeing automation.

  • Measurement and analytics
    Calculating the efficacy of marketing campaigns is notoriously tough, especially when trying to gauge ROI, but some folks are combining signals to paint this picture – using a mix of tools such as Salesforce and Hubspot to assess Win Rates, MQL and SQL volume, and even product usage analytics with products such as Pendo. These may not be purpose-built for the PMM org, but they help to paint a picture using the numbers.
  • Automating internal content distribution
    Creating content is one thing. Getting people to adopt and use it is a whole other painful process. One of the PMM’s greatest pains is getting the teams to use the right content/message/asset/whatever. That’s why automating knowledge across the sales org can unlock immense productivity gains. We’re already seeing Product Marketing teams using tools like 1up to drive the use of sales assets, product messaging, and powerful content across the sales organization.
  • Content personalization
    There is a ton of opportunity for AI here. The ability to curate product demos, sales videos, landing pages, and even marketing messaging based on user segments can be a game-changer. We’re still in the early days, but tools like Reprise and Vidyard are already showing the potential of hyper-personalized messaging.

So by the looks of it, we’re seeing less manual effort around the measurement and mechanics of product marketing outputs. If this trend continues, we’ll continue seeing more automation on the science and more humans on the art side of things. And while there is no robot that can take the place of a resourceful and experienced PMM, new tools are now hitting the market that can make their lives much easier.