When it's hard to tie certain campaigns or assets to the pipeline generation, what other metrics we can consider?
Whenever I’m reporting on PMM results, I include a slide called “PMM across the funnel.” This allows me to showcase how specific PMM programs impact the effectiveness of the entire team. For example, a lot of competitive projects/sales enablement efforts have nothing to do with pipeline generation, and are more focused on cycle times, competitive win rates, and close rates. In-product campaigns or assets associated with a product launch may be tied to adoption for a specific user segment, and other efforts may be directed at driving G2 reviews/customer NPS. Even things outside the funnel (like PR metrics) can be useful to look at, especially when PMM is responsible for new messaging or demos tied to a big event like Dreamforce. Looking at how we support results for all GTM teams and funnel stages is a great way to highlight all the ways PMM supports company growth, not just pipeline generation.
I think my first question here is why you aren't able to? If you are creating content (blogs, whitepapers, webinars, etc) you should be measuring high level metrics like views, downloads, registrants. Ideally, you don't stop there though. These are really high level metrics that don't necessarily signal success. You should be able to take these metrics a step further and understand how they continued through the marketing funnel. Did they engage with any other content, did they become a lead, did that lead convert, etc?
If you aren't able to double click to those meaningful metrics (for now) lean on those high level engagement metrics as a signal.
Really tough question! To start, it's worth noting that even the best attribution mechanism has blind spots. It's just a fact, and it's likely to be true for a while. Ultimately, you'll need to embrace some of the "art" of marketing to understand what's going on and improve it.
With attribution limitations known, you'll want to break a campaign into two components: the content; the distribution. Admittedly, much of this will also incorporate qualitative feedback loops, so "metrics" may be a generous label. Regardless, the goal of the exercise is to figure out if both the content and the distribution are effective.
To evaluate content effectiveness, you'll want to gather feedback/response specifically from your target audience. If it's a video, how long is your target audience watching? If it's a webinar, what questions are you getting? Are people offering unsolicited feedback? If the content lives on social media somewhere, what kind of organic reactions is it getting? For all of these, you'll want to make sure you're filtering your aperture to look at your desired audience.
The distribution side of the evaluation requires that you are using multiple mechanisms. Let's say you have a specific point/message in a piece of content. That message ends up in a webinar, organic LI posts, a LI article, and a blog post. This list is likely much longer, but the point is clear. The one metric that is closest to apples-to-apples across these is impressions (or some version of it). When comparing these, you'll want to remind yourself that not all impressions are equal. A person taking time to attend a webinar is very different than somebody scrolling past a LI post that a connection liked.