B2B marketing planning is a lot more than flashy tips like “Invest in TikTok ads”. In an effort to investigate how real planning is done in 2022, we reached out and interviewed top marketing leaders, from brands like Drift, Uberflip and Yotpo, trying to uncover the lesser known strategies behind the most successful brands.
Along the way, we discovered smart yet different approaches to planning that we think any B2B marketer can utilize for the coming year.
This is the first in a series of interviews we’ll be publishing in the next few weeks. This time, we sat down with Jason Widup, VP of Marketing at metadata.io. He shares a unique perspective that grew Metadata beyond $10M ARR, with a small marketing team of only 3 people.
Jason explains how he built a successful content-driven brand while always accounting for revenue. Here are the main planning takeaways from the interview:
- Metadata uses a demand model for its marketing planning. It traces the revenue goal back up to the earliest inbound leads they need to produce.
- At Metadata, they don’t collect leads. Instead, they incorporate a content-first approach where content is always available to prospects without requiring email submission. This way, they can educate themselves beforehand.
- Metadata is in the process of updating its target audience, based on historical data it gathered. Before they had historical data, Metadata used to focus on the audience who was easiest to sell. Now that they have enough data that can account for their sales cycle, they can focus on their best audience, the audience who shows the best NRR.
- Metadata manage to optimize their activities with consideration of a long sales cycle by using their own platform. Jason’s team runs various experiments, and Metadata puts some budget behind them, and then figures out what’s working and what’s not in terms of driving revenue.
- Jason revisits Metadata’s planning once a week, to make sure they’re always above target, compared to his demand model. This way, he knows they don’t need to drive more pipeline for the current quarter.
Metadata’s marketing planning process
At Tableau (Jason’s previous role), where we had a 120 person marketing team, you started planning in September, and there was a specific rigor to it. You had a certain amount of budget, approvals and this and that. It’s not like that here.
At Metadata the team is so small (3 people). With that many people, and when you’re growing this fast – things shift.
The planning that we do is around what I call my demand model. Planning is really working backwards from revenue that we need. So here’s our company goals around Net New ARR that we want to hit by the end of 2022.
I have the sales and marketing split. Out of that revenue, I’m responsible for 70, sales is responsible for 30.
Now I know my revenue number and work backward, because I know all the conversion rates [along the funnel]. I know the ASP [Average Sales Price], I know the velocities and I built a demand model for myself that helps me understand revenue. I plug in some numbers, update the conversion rates that we’ve seen, the velocities, and it just tells me exactly what I need to deliver in terms of demo requests.
We don’t track leads at Metadata, it’s all about demo requests, because we don’t gate our content. That demo request is a leading indicator, but again my goal is pipeline generated.
From a company’s perspective, what we’re looking at is how much cash we have, how fast we want to grow. Can we grow that fast with the cash that we have, while maintaining a decent buffer there, in case things happen that we’re not expecting.
We focus on Net Retention Rate as our primary metric, not just Net New ARR. This helps us bring the best customers who are going to renew, because that’s our main goal.
Metadata doesn’t track leads. They incorporate a content-first strategy in their planning
I never thought handing off leads to sales was a good marketing strategy. I was marketed to for a long time. As head of marketing operations at a lot of big companies, I was targeted with a lot of ads. Every new tool I would evaluate. I realized over that 10 years or so the kind of marketing and sales I liked, and the kind I really hated.
I’m trying to do the sales and marketing I like. [This] is really low touch – let me educate myself. Let me learn about you through what you’re doing, through your content, through Linkedin, and ads. But I’m going to figure out 80% of it before I ever talk to somebody.
And that’s where we want to be. We want to be there to support people, and not require them to give me your email address for content. That seems silly to me. If someone consumes that content, it’s valuable enough so psychologically they’re connected to you. Because Metadata just produced some great intelligent helpful content.
And then at some point you’re going to say: They were helpful there, maybe they can be helpful with the platform. And that’s the psychological leap we’re looking for.
Metadata incorporates non-revenue metrics in their planning
We measure organic traffic to the website. That’s really important to us because we’re a content first marketing organization. If that organic traffic isn’t constantly growing, something’s wrong. It means our content’s not resonating. Other website metrics, see what people are consuming. We have scroll depth so they get to 75 percent of this page, 100 percent of this page.
A lot of it is the anecdotal stuff that we hear from people. We do a lot of our content distribution through organic Linkedin, and we spend a lot of time growing our network on Linkedin. This way, we can distribute the content more broadly. And we hear chorus calls all the time: “I saw Jason and Mark’s content. I’m connected with Jason and Mark on Linkedin and they produce really good content.”
You can’t attribute the deal to that, but when you hear it in Chorus calls it means the stuff we’re doing around content, even outside of the metrics is working. We listen to that kind of stuff and we’re always looking for more of that meat that you can’t measure in just metrics and attribution.
Metadata is in the process of changing their audience, based on historical data they gathered
I mentioned that NRR is our north star metric. We recently analyzed that. Who are the best types of customers that drive NRR up? We did this instead of focusing on who we sell easiest to. That’s what we did for the first 6 to 12 months, because we didn’t have all this historical data.
When we focused on the audience we sold easiest to, we brought in a lot of customers who didn’t have any business using our platform. They were hit or miss – someone will get value but a lot wouldn’t. In this one segment, we realized we only have a 65 Net Retention Rate, whereas these other segments were over 100%. Let’s just stop marketing to these people.
There’s a certain criteria where we won’t even take a demo anymore. You’re a B2B marketer, you advertise on Linkedin, sorry you’re not quite big enough.
Metadata manages to optimize their activities with consideration of a long sales cycle by using their own platform
Our feedback loop is this: we measure everything all the way to revenue.
Because of that, we can just feed that back in. Metadata just does it for us automatically. We don’t have to look at it and decide what to do. Instead, we throw a bunch of stuff into Metadata and then let it sort itself out.
We can do a lot of experiments, and Metadata puts some budget behind them. Then we let Metadata figure out what’s working and what’s not in terms of driving revenue, not just click through rates and cost per click.
It takes between three months to six months for us to really understand the actual impact of a new campaign or a new strategy. But we’re always looking at leading indicators on the way there.
Leading indicators are pipeline created, meetings booked, demo requests. As long as we see those leading indicators are close, they can be 20% off. That’s okay, because the conversion rates might be different down below. But as we get closer to revenue those conversion rates should be tighter to what they’ve always been or better.
Jason revisits Metadata’s planning once a week, to make sure they’re constantly above target compared to his demand model
I deal with a lot of anxiety at work, and I use that demand model to basically keep it at bay.
I look at it once a week. I’m looking at it in the current quarter. I make sure that it shows me a negative number so i don’t need to drive more pipeline for the current quarter
That would suck, if I had to drive more pipeline, because our average sales cycle is 90 days. It’s already a quarter, so getting people to convert within 90 days can be difficult.
I look at that one in a quarter to make sure it’s always negative, meaning we have more pipeline than we need. Then I’m always looking at it probably twice a month for the next quarter, just to make sure that I’m still clear, the pipeline hasn’t shifted. Then anytime sales does a big pipeline cleanup I go back in and I redo it.
As you’ve seen, Metadata is both revenue-driven and content first. There’s a misconception that revenue organizations only care about sales, and that content-first marketers don’t account for revenue. Metadata proves you can be both. On the one hand, they run a model that traces revenue along their funnel.
On the other hand, they make sure they produce exceptional content, and measure qualitative data – like mentions of the content in sales calls.
We hope you’ve enjoyed this episode of our 2022 marketing planning series. Next up in our series — Andy Crestodina, CMO of Orbit Media and Tricia Gellman former CMO at Drift. Stay tuned!