How to add live B2B SaaS metrics and PLG triggers to Brevo (formerly SendInBlue)?

Many modern SaaS vendors, often small to medium-sized businesses (SMBs), have chosen to leverage Brevo, formerly known as SendinBlue, to streamline their marketing and sales operations. Brevo excels in uniting various departments under a cohesive customer data umbrella, and even given its very competitive pricing, it still delivers excellent value.

However, when it comes to integrating B2B SaaS metrics and Product-Led Growth (PLG) intelligence with Brevo, you encounter a significant challenge that can also be quite costly. This task necessitates the collaboration of development, product, and business teams.

Fortunately, journy.io presents a smarter, more potent, and remarkably cost-effective alternative solution.

Why you’d want live SaaS data and product triggers in Brevo

Whether you're strategizing for a product-led growth (PLG) approach, a hybrid model that combines product-led and sales-led growth (PLG/SLG or PLS), or even aiming for a more streamlined sales-led growth (SLG) strategy, having access to real-time data can significantly enhance your daily operations.

Indeed, this live behavioral intelligence empowers you to make better decisions by enabling you to prioritize and personalize outreach efforts more effectively. It provides instant alerts when crucial events occur on your platform and offers a clearer understanding of your customer base. The difference between engaging with or without such live metrics can be likened to driving to a new destination with or without a GPS (or map); it's still achievable, but the former makes the journey significantly smoother and more efficient.

Why native Brevo isn’t fit to conduct a B2B PLG motion

The most critical components when executing a Product-Led Growth (PLG) or a hybrid Sales-Led Growth (SLG)/PLG strategy include:

1. Identifying Platform Contacts, Companies, and Relationships: Particularly when dealing with a Multi-Access Multi-User (MAMU) B2B SaaS model, it's imperative to efficiently identify and manage contacts, companies, and their interconnections.
2. Receiving Platform Events and Screen Views: The ability to capture platform events and screen views, along with their associated metadata, is crucial for gaining insight into user behavior.
3. Learning and Analyzing Behavioral Patterns: Understanding how users within accounts interact with your platform, including properties, events, screen views, and pages, is key for optimizing stage conversions, expansions, and minimizing churn.
4. Building a Scoring System: Developing a scoring system based on PLG signals helps prioritize and engage with potential qualified leads.
5. Engaging with PQAs/PQLs: Effective engagement with Product Qualified Accounts (PQAs) or Product Qualified Leads (PQLs) across a diverse range of engagement platforms is essential. Brevo is just one of the platforms in this ecosystem.
6. No native support for B2B: There’s simply no way to create automations on what different users, belonging to the same account/group, are doing. This is essential to driving a B2B PLG/PLS motion...

Notably, Brevo doesn't natively support these functionalities, as it wasn't originally designed for this specific use case. While it's true that Brevo possesses a robust core that could potentially be customized to address these requirements, the question arises: why go through the trouble of building these missing components when you can seamlessly integrate a complementary platform that offers these capabilities at a fraction of the cost associated with enterprise-level solutions?

Connecting your SaaS platform to Brevo

Data collecting in journy.io

When you connect a SaaS platform to journy.io, whether through a Customer Data Platform (CDP) like Segment or seamlessly via journy.io's 100%-Segment-compatible SDKs, the platform immediately initiates the collection of a wide range of data. This includes platform-specific events, screen views, website pages, and campaign information. Each of these data points is meticulously associated with at least one user, one account, or a unique combination of a user within a specific account. See previous 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, triggers that same event “send invoice”. journy.io will show on user Elon Musk’s timeline 2 events, and 1 event on each Tesla and SpaceX’s timeline.

Data enrichment to Brevo

Next to timeline data, journy.io also collects and enrich users and accounts with data from 3rd party sources, such as Stripe, Chargebee, Intercom, other CDP/Segment sources, etc...

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. journy.io 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 Brevo. (More about computed properties in next sections.)

This results in having live platform intelligence in Brevo, without the need to create syncronization playbooks in journy.io — Data all magically gets live sync’ed to Brevo 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 journy.io, Role is a relationship property that exists between exactly 1 user and 1 account.

While many Customer Relationship Management (CRM) and marketing automation platforms lack the capability to support these features, journy.io stands out by offering advanced playbooks that leverage these relationship properties. This empowers users to make informed decisions about which users from which accounts to engage with, leading to more targeted and effective interactions.

Equally crucial are journy.io's computed properties, which offer a powerful tool for creating data fields derived from a combination of timeline events, account-user relationship conditions, and even mathematical equations. These computed properties enable users to generate customized data fields that can be invaluable for data analysis and decision-making, providing a level of flexibility and insight that sets journy.io apart.

Traditionally, obtaining behavioral intelligence within Brevo typically required involving developers to create counters and various metrics. However, with journy.io, business professionals can accomplish this task independently with remarkable ease, requiring nothing more than a few simple 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. journy.io’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 journy.io, business people do that themselves in literally a few clicks.

Certainly, all of these computed properties within journy.io, along with any other third-party app and platform properties, can now be seamlessly and continuously synchronized in real-time with Brevo. This integration ensures that your data remains up-to-date and readily accessible within the Brevo ecosystem.

Advanced SaaS Analytics and Segments/Cohorts

Straight out of the box, journy.io delivers advanced customer analytics that center on understanding user and account behaviours during acquisition, conversion, expansion, and churn phases. This comprehensive analysis yields valuable insights into critical questions, including:

1. Identifying Key Differentiators: Which properties, distinct from those found in Intercom, HubSpot, and other platforms, significantly differentiate conversions from non-conversions?
2. Analyzing Engagement: What specific features and screen views were active during the critical week leading up to a conversion, expansion, or churn event?
3. Monitoring Feature Usage Trends: How do product feature usage patterns evolve over time, and which accounts have actively engaged with essential features in the past 7 days? Are these engagements translating into increased conversion, expansion, or retention rates?
4. Attributing Marketing Impact: Which marketing channels and campaigns played a pivotal role in acquiring not just users, but lead accounts as well?
5. Segment Comparison: What are the distinctions between various segments, such as "customers with a tenure longer than 1 year" versus "new customers that have already churned"? Or, for instance, what separates "long-term customers who remain loyal" from "long-term customers who churned" over the last 3 months?

journy.io's out-of-the-box analytics provides comprehensive answers to these critical questions, enabling businesses to make data-driven decisions and optimize their strategies effectively.

journy.io provides highly specialized PLG-related analytics that set it apart from traditional product analytics tools. This distinction arises because traditional product analytics tools lack the contextual understanding of what it truly signifies for an account to undergo conversion, expansion, or churn.

The fundamental purpose of having PLG and customer journey-based analytics is to pinpoint the pivotal components of your platform that directly influence conversions, expansions, and churn. By identifying these critical elements, businesses can swiftly craft segments, signals, and other computed properties that hold significance, all based on these influential factors. This empowers organizations to make informed decisions and take strategic actions that drive growth and retention within their user base.

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 Brevo.

PLG signals and scores

In addition to the SaaS intelligence we've discussed earlier, which has primarily revolved around binary states—whether someone is part of a segment or not—journy.io goes a step further by offering more nuanced intelligence in the form of manual and PLG scores. These scores serve a range of purposes, from guiding onboarding efforts and assessing customer fit to ultimately predicting conversion, expansion, and churn.

A journy.io 'manual score' comprises a series of rules, each equipped with its own rule condition, which can yield either a true or false outcome. Each rule also carries a rule weight. When creating a manual score, users manually define the rule conditions and weights. Subsequently, the score's output is calculated as follows:
Score = Sum(conditions{0|1} * weight) / Sum(weights)
This is basically a weighted average on boolean conditions.

You have the flexibility to create multiple manual journy.io scores as needed. However, when it comes to scoring for product-led growth, which is directly related to conversions, expansions, and churn, there's a unique system-baked-in scoring system that should be utilized. Here's how journy.io's PLG scoring model distinguishes itself from its manual scoring counterparts:

• Rules are called (PLG-) signals.
• A signal condition is typically created through journy.io’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 Brevo. So are the PLG signals itself.

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

See all journy.io properties that could be live-sync’ed to Brevo on: https://help.journy.io/en/articles/8029239-default-computed-properties

Advanced workflows through playbooks

With all behavioural intelligence and PLG metrics seamlessly synchronized with Brevo, the next step is to establish behavioural and PLG-driven workflows within journy.io that will efficiently coordinate and automate activities in Brevo.

A Brevo expert may now be puzzled over the reasons for creating playbooks in journy.io, knowing how powerful Brevo workflows based on live-sync’ed properties could be. And while we agree Brevo 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 Brevo, 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 journy.io.
• Brevo 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 Brevo. 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.

journy.io, unlike Brevo 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, journy.io 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 journy.io; and for Brevo, they are:

• Add a contact to a list, so a marketing email campaigns (Brevo automation) can start.
• Remove a contact from a list.
• Send a Brevo event, so Brevo can decide to start or immediately end an automation.

Conclusion

Brevo has earned recognition as an affordable marketing automation tool, and to some extent, a CRM solution catering to SMB organizations across a wide array of industries, including SaaS and software. However, when it comes to executing a hybrid sales-led/product-led (SLG/PLG) or a pure product-led (PLG) go-to-market strategy, Brevo falls short in terms of essential features.

The introduction of journy.io into the Brevo ecosystem transforms this landscape. By seamlessly syncing critical product usage data and computations—including PLG signals, cohorts, and scores, among others—into Brevo, growth teams gain access to the essential properties needed to identify and engage with product-qualified accounts and users (PQAs/PQLs).

Moreover, enabling journy.io to initiate Brevo automations unlocks a higher level of granular engagement with these PQAs/PQLs, offering capabilities that would otherwise remain out of reach within Brevo's existing feature set.

For those who are serious about incorporating PLG elements into their existing SLG strategy, we encourage you to visit journy.io, register for a free trial, and seamlessly connect both your SaaS platform and Brevo to it. This step will open up a world of exciting possibilities within Brevo, elevating your approach to a whole new level of customer-centricity.