Product analytics is different for B2B teams. Here’s how.
When it comes to measuring metrics like adoption, activation, and retention, B2B teams are playing a different ball game than their B2C counterparts.
It’s just the nature of the products. Signing up for Netflix is nothing like purchasing a no-code email and landing page-building solution for your marketing team.
The entire decision-making process behind the purchase is different—which means there are some major differences between how you should look at B2B product analytics and B2C product analytics.
I spoke to Mixpanel customers and members of our own product team to come up with three important considerations to keep in mind when you’re deciding on objectives, which metrics to track, and how to interpret that data in a B2B product.
B2B product analytics vs B2C product analytics: 3 major differences
The goals, focus areas, and nature of the relationships you’re analyzing are all quite different in B2B compared to B2C. In particular, three differences directly impact a team’s approach to product analytics.
Your users
In B2C, you’re focused on the individual—if you want to get someone to sign up for Netflix, they’re the only person you have to convince. “Users” and “customers” are usually the same person, which keeps things simple.
In B2B, on the other hand, you’re segmenting users by industry, business size, and job title, just to name a few. Your customers aren’t always your users, and they’ll all have different levels of experience with your product and different training needs.
One product leader at a company who uses Mixpanel told me the biggest challenge when you go upmarket is balancing the needs of your end users—the ones actually clicking through your product every day. Even though you’re optimizing for teams as you scale up, you can’t forget about the individual.
To make things even harder, many users may not even know anything about your company or product. They’re not the ones Googling new software to try—most likely, someone on their team (your champion) introduced your solution to them and they didn’t have a say in the matter. They’ve just got to learn how to use it.
Different users, different motivations, different usage patterns. The result: You’re going to be looking at a lot more data points.
Pro tip: There’s no such thing as an “average user.” It's easy to look at an account and think, “Oh, they’re building 500 emails a month and they have 50 users, so each user is building 10 emails a month.” That’s never how it is. Often there’s one power user who’s skewing the data. You’ve got to look deeper and figure out why that one person became a power user—and why the others maybe aren’t using the tool at all.
Your goals
For B2C companies like Tinder, the main objective is to get more people to sign up.
In B2B, your mindset is more along the lines of: “If this team has 30 people, how can we unlock the entire team and turn them all into power users?”
It’s a lot tougher because, in B2B, there might be 20 people involved in making a decision. Just because someone likes your new feature doesn’t mean they’ll end up adopting it—they’ll likely have to get their whole business unit on board too.
B2B product teams will find that this can complicate goals (and dashboards) quite a bit because now you’re looking at a lot more steps. Whereas Tinder’s signup process might take a few minutes, an enterprise platform’s adoption flow will take weeks, if not months.
Your data-gathering approach
In B2C, you might gather the bulk of your insights by looking at adoption metrics and talking to your users.
In B2B, you have to monitor your metrics, talk to your customers and users, and:
- Work with your sales team to understand what problems prospects are having.
- Keep an eye on feature adoption trends.
- Build relationships with your CSMs (Customer Success Managers) to understand your customers’ goals and annual timelines. For example, you might learn that one of your customers makes all their technology decisions in November, so if you want to upsell them on new products or features, you should do it before then.
It’s essential to pair your qualitative data with quantitative data; you can’t get the full picture from just looking at either hard numbers or subjective feedback.
“Make sure to continue monitoring customer feedback [after a product launch] via different channels—support tickets, events, case study interviews—sometimes you’ll even see product feedback on social media channels.”
Read more about how to plan successful B2B product rollouts here.
All that being said, there’s a critical difference between being data-informed and being data-driven. One Mixpanel customer told me their product team sees data as more of a starting point for digging into trends. There are always nuances and, as insightful as data can be, it’s not always wise to make all your decisions purely based on data.
Do you have the right tools to support your B2B product analytics strategy?
All in all, data can be the sharpest tool a B2B product team (and their cross-functional partnering teams) has at their disposal. It’s why there’s more data thrown at these teams than ever before, which can be overwhelming.
Mixpanel’s self-serve analytics makes it easy for technical and non-technical teams alike to quickly sift through the data and uncover the relevant insights they need to get to work on their most important B2B product KPIs.
Find out more about how Mixpanel works for B2B and SaaS here.