Use Cases

Supporting B2C & B2B GTM motions, simultaneously

Yves Delongie
Yves Delongie
June 19, 2023
Supporting B2C & B2B GTM motions, simultaneously

The need for supporting mixed B2C & B2B environments

Many modern SaaS companies that focus on product-led growth start by attracting single (paying) users and then expanding those licenses into team licenses. This approach has been successful for products such as GitHub, Railway, and Sentry, among others.

Understanding both user and account level activity is crucial in predicting single-user to multiple-user/team expansion and multi-user to single-user retraction.

Some might suggest considering teams of a single user to avoid the additional work. However, enrichment data is often stored differently for users and teams (e.g., Stripe subscription data), making that option impractical. Additionally, downstream engagement through CRMs, marketing platforms, or support ticketing systems requires user and account abstractions, particularly when users are both part of teams and have single-user licenses.

Subscription data flexibility

When collecting subscription data from platform, Stripe or Chargebee, data must be properly formatted and linked to either user, either account/team objects. journy.io allows for mixed data input.

So you may have user billing done inhouse, with data being shared through your own platform, yet have team billing being handled by e.g. Stripe. In journy.io you choose which properties from which sources belong to which objects.

Stripe being set up to enrich the account/team object.

Reviewing revenue metrics

To effectively manage revenue metrics for both users and account/teams, it is crucial to group revenue streams correctly and take appropriate actions. With its latest update, journy.io now provides various SaaS-specific metrics, such as MRR, base currency, MRR base, and renewal date, for both users and account/teams, and groups them by object and stage.

The user- and account/team stage views display MRR in their own currency, while sums are shown in the converted base currency.

When a user has a single license, MRR and other revenue metrics are typically shown at the user level. If the user converts into a team license, the recalculation will occur on both the user and team objects, which reflects the omission of user revenue and the addition of team revenue.

Combining SaaS Metrics on user and account/team level

The next step into supporting mixed B2C/B2B environments is the ability to create business-specific metrics —in journy.io, it’s called (computed) properties— that reflects progress in transversing your customer journy stages. Moreover, these metrics often need to take into account that users can be part of different teams, and thus support multi-account-multi-user mixed B2C/B2B environments.

Starting from native properties on user, account and relationship level, journy.io offers computations on unique relationship conditions between the different aforementioned data objects.

A few examples:

  • Count the increase/decrease of active users. Following example creates a property for each account/team, that holds the amount of users that were active during the last 14 days, compared to the previous 14. days.
  • Count the amount of accounts a user is part of, where account properties have specific conditions. Following example will create a property for each user, holding the amount of accounts/teams that user is part of, that holds more than 9 users.
  • Provide a % of team users that have certain conditions. Following example will compute a property for each account/team, holding the % of users that have an individual churn score ≥ 75%.

The possibilities for creating meaningful properties, tailored to your specific business needs, are endless. Our additional math computing module allows you to create any mathematical function on all computed properties, giving you even more flexibility.

Your newly created business-specific metrics are now ready to fuel segments, scores, signals, and playbooks, all of which are required to conduct a proper mixed-environment product-led growth (PLG) motion. Additionally, these metrics can be live-synced to destinations of choice, such as Salesforce, HubSpot, ActiveCampaign, Appcues, etc., to ensure that your local engagement flows in these apps always hold latest PLG information.

PLG metrics can be live-sync’ed to any destination.

Mixed user-team engagement playbooks

Once the data is ready to support your environment, lets start building engagement playbooks. As with properties, these playbooks need to cover both single users and specific users from specific teams…which could eventually turn out to be the same users.

journy.io provides great flexibility in creating these playbooks. It starts with a wide range of possible entry conditions, both on individual user and account/team level.

Playbook on account/team level, using user conditions as a playbook entry condition.

Once established which accounts/teams are to enter a playbook, actions towards most promising users within these accounts/teams must be considered, in order to achieve conversion/expansion/retention goals.

journy.io provides a wide range of actions, made available through the connections you’ve made. If you’ve connected HubSpot, you’ll be able to e.g. add users to email lists or add tasks related to users and accounts. If you didn’t connect HubSpot, you simply won’t see these actions appear.

When HubSpot is connected, you could add most promising users from product qualified accounts to HubSpot email lists.

Conclusion

SaaS companies that focus on product-led growth often start by attracting single users and then expanding those licenses into team licenses. Understanding both user and account level activity is crucial in predicting conversion, expansion and retention.

With its latest update, journy.io allows for flexible data collection and revenue metric management for both users and account/teams.

Additionally, journy.io offers computations on unique relationship conditions between users and accounts/teams to create business-specific metrics that fuel segments, scores, signals, and playbooks for a proper mixed-environment product-led growth (PLG) motion.

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