What metrics do you track to measure the effectiveness of your product marketing efforts?

To get a full view of our product marketing impact, I track metrics that touch every stage of the customer journey:

• Pipeline: This is the big one—it’s the clearest measure of success. By working closely with marketing and sales, we track the revenue impact of our campaigns and product launches. Pipeline shows us the revenue potential we’re generating and is the most direct link between PMM work and company growth.

• Product Adoption & Engagement: After launching a new feature or product, I watch closely to see if customers are not only using it but also finding real value. It is super important to track adoption rates and engagement, because this lets us know if our product is valuable to customers and if they are using it. 

• Win Rates: We need to know if our positioning is hitting the mark with our target audience. A higher win rate in key segments means our messaging is doing that. If win rates drop, it’s a clear sign we need to change how we are speaking to the value of our solution. 

• Content Engagement: Content like white papers, webinars, and product demos tells us how well we’re capturing interest. I track views, click-throughs, and feedback from both customers and sales teams to understand what’s working and where we can improve.

This varies a lot by company, but for the most part, product marketing metrics should tie closely with business metrics such as revenue (bookings, MRR, ARR, etc.), pipeline (opportunities created, dollar value of opportunities, etc.), and product (signups, trials, usage, etc.). Product marketing at PLG companies tends to track metrics related to product activations, product usage, and churn. For sales-led orgs the metrics are related to revenue and pipeline with additional metrics for sales performance and enablement, as well as content usage and influence.

In most cases, you will have top-level metrics that are not necessarily PMM owned (e.g. revenue) but are influenced by the work that PMM does. You will also want to track more granular metrics related to work that PMM drives (e.g. content downloads, sales readiness, competitive win rates, etc.).

In setting up your product marketing metrics, ask yourself:

• What impact will our PMM work have on ?

• Is our work aligned to key business metrics? Which ones?

• What part of our work is not tied to a business metric? How do we want to measure its effectiveness?

• Are all stakeholders across the business aware and supportive of our PMM metrics?

In the end, the metrics you set will help guide the team and align them on the priorities for the business and for themselves. Iterate and get others in the company to weigh in so that you have clear understanding of how your metrics impact others and how you will track them over time.

At AssemblyAI, we track PMM effectiveness through program-specific metrics that align with our dual PLG and sales-assist motion. Let me break this down by our key programs:

For Competitive Intelligence:

• Win/loss rates against specific competitors

• Competitive battle card usage rates by sales

• Feature comparison coverage (% of key features we've documented vs competitors)

• Competitive mention rate in deals and how it changes over time

For our Self-Serve Motion:

• Developer documentation engagement metrics

• Time to first API call & upgrade after signup

• Conversion rates at different usage tiers

• Feature adoption rates

For Sales Enablement:

• Sales content usage and effectiveness scores

• Ramp time for new sales team members

• Win rates for deals where PMM materials were used

• Deal velocity changes after enablement sessions

For Product Launches:

• Developer signups within first 30 days

• Feature/usage adoption rates

• Coverage and sentiment in developer communities

• Pipeline influenced by new features

For Win/Loss Analysis:

• Reasons for wins/losses categorized by themes

• Price sensitivity patterns

• Technical requirements gap analysis

• Competitor displacement rates

The key is that we tie these metrics back to two core business outcomes: developer adoption rates for our PLG motion and pipeline influence for our sales-assist motion. This helps us stay focused on impact rather than just activity metrics.

What I've found particularly effective is measuring the delta – how these metrics change after specific PMM interventions. For example, if we release new competitive battle cards, we track the before and after win rates against that specific competitor.

It really depends on the initiative and the top-down business objectives driving said initiative. In general, most product marketing efforts aim to increase demand, sales efficacy, or product adoption. I'll pick two for each category of work.

1. For demand related work like major product launches or web projects, we like to look at top of funnel metrics like organic traffic and conversion rates.

2. For sales enablement efforts, it most often boils down to average deal size and win rates.

3. For adoption work streams, it's usually either product (SKU) attach or feature activation (as % of total customer base).

This is of course acquisition motion dependent (PLG vs. sales-led and everything in between) and you can always drill down to more granular metrics. But we like to focus on the highest order north star metrics.