Predictive Intel Makes Product Strategic

Everybody wants their business' most revenue-impacting functions - Product, CS, Sales, Marketing - to run on predictive intelligence. But most struggle to make this a reality.

Welcome to Beyond The Click by Balboa Solutions. In today's issue we're giving our take on the new Pendo Predict offering, including:

1. Why predictive intelligence matters

2. What Pendo Predict does (in layperson's terms)

3. What it means for the Product org

Let's dive in.

The B2B Hamster Wheel Never Stops 🐹

Product-led companies will always face the same Big 3 existential challenges to their business model:

1. Conversion: how to turn your free users into paying customers?

2. Expansion: how to get your paying customers to increase their spend?

3. Churn: how to prevent your paying customers from leaving your product?

The first two are about growing, while the last is about not shrinking. It’s a bit of a B2B “hamster wheel,” but continually solving for each of these problems is vital for a product business to succeed.

But most product-led companies fall behind in this race. The reason is the SCALE of the Big 3. On any given day, you might have:

1. Thousands of customers coming up for renewal - churn risk

2. Thousands more hiring, growing, and expanding usage - expansion opp

3. Hundreds of thousands of active free users - conversion potential

But you WON’T have enough account managers or CSMs to handle them all 1:1. So, we triage – we try to discern the narrow subset of these 3 groups that is most likely to “do the thing” this quarter, and we focus on those. AKA, aligning organizational efforts to user intent.

It’s a great strategy, but only if your definition of “most likely” is solid. The phrase “garbage in, garbage out” is used so much in B2B that it’s starting to lose its meaning, but it applies here.

It’s a massive problem, and it’s why we found Pendo’s recent acquisition of Forwrd.ai (now Pendo Predict) so compelling. 👇

Pendo Predict and the Big 3 🔭

Pendo Predict is a complex product, but from our perspective it really does 6 things:

1. Data Integration 💾

Pulls in intent, demographic, firmographic, engagement, and activity data from your CRM, etc. to combine with your usage data from Pendo.

2. Data Prep 🖥️

Filters and normalizes the data into categories a predictive model can work with, such as “200-500 employees” instead of a hundred unique employee counts.

3. Business Logic 💼

Helps the user choose and define the business outcome they are solving for, like churn.

4. Cross-correlation 🔄

Tells you which factors, like product feature usage, page views, and customer calls, are most correlated to that business outcome.

5. Predictive Scoring 🚦

Trains a model on those predictors that scores each of your accounts on their likelihood to “do the thing" (e.g. Red/Yellow/Green), and explains the factors behind the score.

6. Outcome Enablement 🚀

Pushes score data into systems of record like Pendo, Salesforce, and Slack to make it actionable.

These aren’t revolutionary concepts. Most high-performing product-led companies already do some version of the above list today (the Big 3 require it). But the DIY method for triaging your most urgent customers carries its own problems:

• Manually gathering data across systems and repeated lookups to stitch information together

• Trying to select the right predictors and normalizing data across disparate sources while avoiding post-fact fields.

• Manually doing correlation analysis and common business sense checks to identify predictors

• Updating and retraining internally built models (more expensive than the initial build)

• Finding DIY methods to get score data into workflows, systems of record, or directly to teams.

Why This Matters 📢

For Product leaders, this predictive capability represents a strategic shift from reactive to proactive, and it makes the Product org a key driver of revenue. We see product teams sitting on goldmines of behavioral data that never make it into revenue decisions because there's no bridge between "user clicked Feature X 47% less this month" and "account manager should call this customer today." When the predictive signals automatically flow into CRMs and trigger customer success workflows, it supercharges the ROI on your Pendo investment.

It also enables cross-functional alignment. When Product can surface which features correlate with retention, CS can build targeted interventions. When Sales sees engagement scores next to upsell probabilities, they prioritize outreach intelligently. When Marketing understands which behaviors predict conversion, they design campaigns that drive those actions.

The result? Product becomes the strategic revenue partner that shows other teams exactly where to focus their efforts, backed by data instead of intuition. It's the difference between hoping your product improvements help retention and knowing exactly which improvements drive the highest business impact.

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