Use Cases

How to add live SaaS metrics and PLG triggers to HubSpot, through

Yves Delongie
Yves Delongie
July 5, 2023
How to add live SaaS metrics and PLG triggers to HubSpot, through

Lots of modern SaaS vendors have opted to use HubSpot to support their marketing, sales and/or customer success processes. HubSpot nicely assembles different departments around a unified set of customer data, and —while not the cheapest solution around— delivers decent value for money.

However, when it comes to getting SaaS metrics and PLG intelligence into HubSpot, you suddenly stumble against a rather difficult and expensive venture of needing to create custom objects and processes. This requires work from at least development, product and business teams. offers a smart, more powerful and much more affordable alternative.

Why you’d want live SaaS data in HubSpot

Whether you’re planning to conduct a product-led growth (PLG), a hybrid product-led/sales-led growth (PLG/SLG), or even a more efficient sales-led growth (SLG) motion, having live data you can rely on will only benefit your daily work.

Indeed, this kind of live behavioural intelligence allows you to better prioritize and personalize outreach, to get smarter instant alerts when something important happened on your platform and generally to have a better view of who your customers are. The difference between engaging with or without such live metrics is comparable with driving to a new destination with or without a GPS (or map). It’s still possible, but soo much unnecessarily harder.

Why native HubSpot isn’t fit to conduct a PLG motion

The most essential elements of conducting a PLG or hybrid SLG/PLG motion are:

  • Identifying platform contacts, companies ...and relationships when operating a MAMU B2B SaaS!
  • Receiving platform events and screen views, both with metadata.
  • Learning and analysing behavioural patterns (properties, events and screen views, pages...) in function of stage conversions, expansions and churn.
  • Build a scoring system with PLG signals.
  • Engage with PQAs/PQLs across a wide variety of engagement platforms, of which HubSpot is just one of them...

None of these above are natively supported by HubSpot, as HubSpot simply wasn’t purpose-built for this use case.

Yet we recognise HubSpot’s underlying core to be powerful enough that one could build missing parts and have it all tailored to supporting above requirements. But why do so when one can add a complementary platform to fill in the gaps? And at a fraction of normal enterprise pricing?

Connecting your SaaS platform to HubSpot

Data collecting in

When connecting a SaaS platform to —over a CDP like Segment or natively through’s 100%-Segment-compatible SDKs— immediately starts collecting platform data, events, and screen views as well as website pages and campaign information. Each of these items is linked to at least one user, one account, or on a unique combination of one user within one account (relationships: see this article).

Example: User Elon musk, being an admin in account SpaceX, trigger the event “send invoice”. Somewhat later, same user Elon Musk, being simple user in account Tesla, trigger that same event “send invoice”. will show on user Elon Musk’s timeline 2 events, and 1 event on each Tesla and SpaceX’s timeline.

Data enrichment from- and to HubSpot

Next to timeline data, also collects and enrich users and accounts with data from 3rd party sources, such as Stripe, Chargebee, Intercom, other CDP/Segment sources, etc... as well as from HubSpot itself! If you have created additional company and contact properties in HubSpot, manually or for example through ClearBit, Datagma, InfoLead... you’ll see those appear in as well, ready to be analysed and processed.

Account information from HubSpot records, available in to be analysed and processed.

As such, you get a full centralized ‘customer 360’ view on each user and account with all timeline and property data, from all connected sources. automatically gets app updates on all these properties and continuously processes this data. This is then used to eventually compute platform intelligence properties that will be mapped against custom properties in HubSpot. (More about computed properties in next sections.)

Mapping app- and computed properties to HubSpot properties, enables live sync’ing.
No need for synchronization playbooks

This results in having live platform intelligence in HubSpot, without the need to create syncronization playbooks in — Data all magically gets live sync’ed to HubSpot upon user accessing your SaaS platform.

Data objects and computed properties

The data being collected from you platform can be associated with 3 data objects: users (often mapped against contacts or persons in connected apps), accounts (often mapped against companies or organizations in connected apps) and relationships. The latter is almost never supported in connected apps, yet extremely important in PLG motions.

Example: User Elon musk is an admin in account Tesla, and the owner of account Twitter. How would you store the property Role (being admin or owner or user)? Not on account level as you have different users with different roles within the account. Not on user level as 1 user can be part of different accounts, holding different roles. In, Role is a relationship property that exists between exactly 1 user and 1 account.

And while most CRMs and marketing automation platforms simply do not support this, enables sophisticated playbooks that will make use of these relationship properties when deciding which users from which accounts to engage with.

But at least as important as relationship properties are’s computed properties. They allow for creating data fields that is processed out of timeline events, account-user-relationship conditions and even mathematical equations.

The traditional way to getting behavioural intelligence in HubSpot would be to ask developers to create counters and other metrics. With, business people do that themselves in literally a few clicks.

Example: User Elon musk, being an admin in account SpaceX, and being the owner of account Tesla, logs into each account on a regular basis.’s analytics showed that ‘more than 7 logins per account per 7 days, from at least one user’ is an important indicator for account conversion, so you created a PLG signal from that. (More on signals in next sections) Yet, next to an ON-OFF signal, you really would love to actually see in HubSpot how many times a user logged in the last 7 days. The traditional way would now be to ask developers to create a login counter. With, business people do that themselves in literally a few clicks.

Of course, all these computed properties in, next to all other-app and platform properties, can now all be live-sync’ed into HubSpot.

Advanced SaaS Analytics and Segments/Cohorts

Out-of-the-box, offers advanced customer analytics that focusses on how users/accounts behave when being acquired, when converting and expanding, and when churning. The outcome provides answers on questions such as:

  • Which are the most important differentiating properties (from Intercom, HubSpot and others) between conversions and non-conversions?
  • Which features and screen views happened during the last week before conversion, expansion or churn?
  • How are product feature usage evolving over time, and which accounts used key features most during the last 7 days? And is conversion, expansion or retention subsequently growing as well?
  • Which marketing channels and campaigns were instrumental in acquiring new lead accounts? (Not just users!!)
  • Which are the differences between 2 segments, such as ‘customer longer than 1 year’ vs ‘new customers that already churned’? Or simply between long-term customer staying customers and ‘long-term customers churning’ during the last 3 months? offers very specific PLG-related analytics that won’t be seen in traditional product analytics tools, as these latter simply do not know what it means for an account to convert, to expand or to churn.

The essence of having this kind of PLG-/customer-journey-based analytics is to see which elements of your platform are important —specifically for conversions, expansions and churn— to then be able to quickly create segments, signals and other computed properties that matter, based on these elements.

Segments —often referred to as cohorts— can be used for any classification, from ICP over territorial to product usage, and can of course all be live-sync’ed to HubSpot.

PLG signals and scores

Next to previously covered SaaS intelligence, that until now mostly handled ON-OFF/boolean states —Is someone part of the segment or not?— also offers more gradual intelligence such as manual and PLG scores. Use cases vary from onboarding scores over customer fit scores to eventually conversion/expansion and churn scores.

A ‘manual score’ is a set of rules, each with their own rule condition which output can either be true or false, and each with their rule weight. When a score gets created, rule conditions and weight are manually set, and the score output is then calculated as:
Score = Sum(conditions{0|1} * weight) / Sum(weights)
This is basically a weighted average on boolean conditions.

You can create as many manual scores as needed. But when it comes to product-led growth scoring, thus related to conversions, expansions and churn, there is one special system-baked-in scoring system that should be used. The difference between’s PLG scoring model and its manual ones are:

  • Rules are called (PLG-) signals.
  • A signal condition is typically created through’s machine learning, and only rarely manually through analytics.
  • Each signal has 2 weights; they’re called positive and negative signal impact.
  • Signal impacts are not static but are continuously dynamically adapted over time, conform the impact it has on a user/account converting/expanding or churning.
  • Each customer journey stage will have a set of PLG signals associated. User/accounts in different stages will thus have different PLG signals being checked for.
  • Depending on the customer journey stage a user/account is currently in, a conversion or expansion score will be calculated. However, both are stored in the same computed property ‘conversion score’.

All scores, weather manual or PLG, are stored as user-/account- computed properties and can thus be live-sync’ed to HubSpot. So are the PLG signals itself.

Signals with positive and negative signal impact per stage

With HubSpot lacking any product-behaviour-based scoring, this is a game changer for anyone conducting a data-driven sales process from within HubSpot.

See all properties that could be live-sync’ed to HubSpot on:

Advanced workflows through playbooks

Now that all behavioural intelligence and PLG metrics are live-sync’ed to HubSpot, it’s time to create behavioural and PLG-driven workflows in that will orchestrate activities in HubSpot.

A HubSot expert may now be puzzled over the reasons for creating playbooks in, knowing how powerful HubSpot workflows based on live-sync’ed properties could be. And while we agree HubSpot to be a powerful (marketing) automation tool, it lacks certain capabilities to be practical in typical PLG environments:

  • It’s still not actually possible to create account-based user workflows in HubSpot, based on both company and contact properties. Example: If a company’s health score > 75%, send emails to its users that were active the last 7 days and have a user’s health score > 50%. That’s all done with 1 condition in
  • HubSpot has no notion of user-account relationship properties, and thus cannot create playbook conditions on those. Example: If a company’s health score > 75%, send emails to its admins and owners’ (while these contacts may have other roles in other companies).
  • It not possible to take coordinated synchronous actions in other tools from within HubSpot. Example: If a company’s health score > 75%, send emails to its users and at the same time, instruct Intercom and MailChimp to start appropriate actions themselves with those same users., unlike HubSpot and most other tools, was built from the ground up to conduct product-data-driven B2B account-based automations, out of frustration that no other tool could offer what was needed in a PLG environment. Yet, also recognizing those other tool’s strengths, was also built to orchestrate actions in those tools, rather than trying to do everything itself.

These actions are specific to the apps that are connected to; and for HubSpot, they are:

  • Add a contact to a static list, so a marketing email campaigns (HubSpot workflows) can start.
  • Remove a contact from a static list, so previous campaigns would immediately stop for given contact.
  • Create a task for a HubSpot user, associated to 1 contact, to 1 company or to 1 specific contact and 1 specific account. The title and content of those tasks can dynamically be composed with all user/account properties available in


HubSpot is well-recognised as a premier marketing automation tool, a CRM and to a lesser degree customer support platform for organisations of all sizes, across a wide range of industries including SaaS/Software. However, when it comes to conducting a hybrid sales-led/product-led (SLG/PLG) or pure product-led (PLG) go-to-market strategy, HubSpot lacks necessary features to be a viable solution.

Adding to HubSpot changes all that. With product usage data and computations —PLG signals, cohorts and scores to name a few— being live-sync’ed to HubSpot, growth teams suddenly get the necessary properties to start seeing product-qualified accounts and -users (PQAs/PQLs).

Having then additionally start HubSpot workflows, allows for a more advanced granular engagement with these PQA/PQLs, otherwise simply not possible with current HubSpot features.

For everyone serieus about adding PLG to your existing SLG motion, feel free to go on, register your free trial, and connect both SaaS platform and HubSpot to it. You’ll be opening a whole new world of possibilities within HubSpot...

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