Table of Contents

• Why Traditional Due Diligence Often Falls Short
• AI Advantage: Neural Analysis
• We Start with the Customer Job, Not the Product
• We Uncover Unmet Needs: The Leading Indicator of Growth
• AI Advantage: Predictive Need Analysis
• We Validate Product-Market Fit Through Custom Effort Scoring
• What Strong Product-Market Fit Looks Like in JTBD Terms
• What Weak Fit Looks Like
• We Assess Whether the GTM Strategy Aligns with Urgent Needs
• AI Advantage: Message-Job Alignment
• We Use JTBD to Estimate Repeatability Across Segments
• We Use JTBD to Inform Post-Close Strategy Before the Deal Closes
• AI Advantage: First 100 Days Prioritization
• JTBD as a Signal for Long-Term Value Creation
• JTBD Reduces Strategic Drift
• To Sum Up: A Better Way to Evaluate Growth Before You Invest
• Ready to Assess Growth Potential with Confidence?

Why Traditional Due Diligence Often Falls Short

When evaluating potential acquisitions, most investors focus on traditional metrics: financial health, operational efficiency, competitive landscape, and leadership strength. These are useful foundations—but they primarily reflect the past.

At thrv, we understand that growth-focused investing is about the future: Will this company grow? Can it generate new revenue quickly and predictably? Most importantly, will that growth drive a premium valuation at exit?

This is where traditional due diligence often misses the mark. Financial statements show historical trends but can't predict what will unlock the next revenue chapter. Market sizing studies estimate the total addressable market (TAM) but don't reveal whether a company is solving problems customers urgently need addressed.

At thrv, we go beyond traditional due diligence by using AI to analyze customer jobs, uncover unmet needs, and project scalable growth opportunities. Our proprietary platform applies machine learning to customer research—enabling faster, more accurate assessments of value creation potential.

We help investors move beyond backward-looking indicators by providing a measurable way to assess customer demand, product alignment, and expansion potential—before capital is committed. Our Jobs to be Done framework offers a forward-looking lens into whether a company can deliver repeatable, scalable growth after acquisition.

AI Advantage: Neural Analysis
Our proprietary operating system processes thousands of customer data points in hours—not weeks—to identify patterns human analysts might miss and accelerate the due diligence timeline.

We Start with the Customer Job, Not the Product

During due diligence, it's tempting to begin with what the company has built: features, market positioning, pricing, and existing customer metrics. We take a different approach, starting with the customer's Job to be Done—the goal they're hiring the product to help them achieve.

When we help firms assess a potential acquisition, our first question is: What job is the customer trying to complete? If that job is important, underserved, and persistent, it signals real market opportunity. If not, even a talented leadership team may struggle to sustain growth.

AI enables us to analyze thousands of qualitative data points—such as interviews, reviews, and usage patterns—to identify core jobs faster and with less bias. This accelerates our understanding of what customers are truly hiring the product to do.

Our Jobs to be Done analysis allows investors to:

• Identify whether the company is solving an urgent problem
• Evaluate whether customers are satisfied with current alternatives
• Determine how much upside exists if the company can satisfy the job better than competitors

For example, a payroll software platform might frame its value around integrations and user interface (UI). But our analysis often reveals the real job customers need to accomplish is "ensure every employee is paid accurately and on time with minimal manual oversight." If current solutions create friction in that job, the growth potential lies in solving that problem—not launching more integrations.

Starting with the job makes it easier to assess whether the company aligns with a real, underserved need—and whether the market opportunity remains open.

We Uncover Unmet Needs: The Leading Indicator of Growth

Growth doesn't come from what's already working. It comes from addressing what isn't—and doing it better than anyone else.

That's why we focus due diligence around unmet needs. Using our proprietary JTBD software, we help investors evaluate how well the company satisfies specific steps in the customer's job. Each step is measured by:

• Importance: How critical is this step for the customer?
• Satisfaction: How well is this step being served today?

Our software uses AI to detect patterns in unmet needs across job steps. It analyzes survey data and qualitative feedback to surface the needs most likely to drive growth—before competitors recognize them.

The biggest opportunities emerge where importance is high and satisfaction is low. These are areas where customers are willing to switch, pay more, or expand usage if someone can solve their problem more effectively.

When a company already addresses one or more of these unmet needs, it often indicates growth runway. And if they're not—but the need still exists—it presents an opportunity for investors to guide post-close strategy and accelerate value creation.

AI Advantage: Predictive Need Analysis
Our AI models don't just identify current unmet needs—they predict which needs are likely to become more critical over the investment horizon, giving PE sponsors insight into long-term value creation opportunities.

We Validate Product-Market Fit Through Customer Effort Scoring

Product-market fit (PMF) exists on a spectrum—and when evaluating a potential acquisition, the question isn't just if PMF exists, but where and how much opportunity remains to deepen it.

Traditional due diligence might examine usage retention, feature adoption, or net expansion to gauge PMF. These metrics have value, but they're lagging indicators. What matters more—especially when assessing future growth—is understanding how well the product satisfies unmet customer needs in their job.

Our platform scores product-market fit by assessing customer effort and willingness to pay to get the job done. This approach helps PE sponsors quantify risk and prioritize post-close moves with precision.

Our customer effort scoring gives PE investors a quantitative view of product-market fit. Here's how we approach it:

1. Break down the job into 10-20 steps and 50-100 customer needs
2. Survey the market to measure customer effort for each need
3. Generate customer effort scores that reveal which needs represent the highest-value growth opportunities

What Strong Product-Market Fit Looks Like in JTBD Terms

A strong fit means the product:

• Satisfies unmet needs in underserved job steps faster and more accurately than competitors
• Creates customer value by reducing the effort required to execute the job
• Generates revenue growth because customers willingly pay to get their job done better
• Has low churn because the product is aligned with the stable customer job (not just due to high switching costs)

You can see this in our data: high customer effort scores (CES) that decrease after product usage across multiple job steps = a clear indicator that we've achieved product-market fit.

What Weak Fit Looks Like

Conversely, if a product has high satisfaction on low-importance job steps—or if the highest-opportunity needs remain completely unmet—that's a warning sign. Even strong top-line numbers may mask deeper issues that could emerge post-close as churn, slow sales, or failed expansion efforts.

By using our JTBD software to run this analysis during due diligence, investors can avoid those risks and identify where to focus post-acquisition.

We Assess Whether the GTM Strategy Aligns with Urgent Needs

You can have an excellent product, but if the company's marketing and sales strategy doesn't reflect the actual pain customers feel, you won't win consistently—or grow efficiently.

In our work with portfolio companies, we often find that go-to-market (GTM) teams default to generic personas, vague positioning, and feature-based messaging. The problem? These approaches fail to speak directly to what customers are struggling to accomplish.

We use AI to evaluate GTM content—ads, sales scripts, web copy—and detect whether messaging aligns with the job language and emotional triggers uncovered in our JTBD analysis. This ensures every touchpoint reinforces the customer's struggle and desired outcome.

The result is a disconnect:

• Sales cycles are longer than necessary
• Conversion rates are lower, even with decent inbound
• Messaging focuses on product benefits, not customer struggles

We assess GTM alignment by mapping the company's messaging and sales process to the Job to be Done. Using our JTBD process, we evaluate:

• Are campaigns built around high-opportunity unmet needs?
• Do sales scripts and demos focus on job completion—not just features?
• Is there language-market fit? Do prospects immediately recognize the problem being described?

When a company speaks to a customer's most urgent need, demand increases—even if the product hasn't changed. We've seen portfolio companies boost pipeline performance and reduce customer acquisition cost (CAC) just by reworking messaging around high-friction job steps.

For investors, this is a crucial due diligence checkpoint. If the product is solid but GTM is off-track, there's often a quick win post-close. But if both product and GTM are misaligned with what customers care about, it's a much steeper climb.

AI Advantage: Message-Job Alignment
Our AI analyzes marketing content and sales materials against customer interview language, scoring how well GTM assets align with the vocabulary customers use to describe their struggles.

We Use JTBD to Estimate Repeatability Across Segments

One of the most powerful levers for private equity returns is repeatability: can the company take what works and expand it into adjacent markets or verticals?

Too often, this question gets answered with top-down assumptions: "If it works for manufacturing, it will work for logistics." But that's only true if both segments are trying to complete the same job, in the same way, and are currently underserved.

AI allows us to cross-map job steps and unmet needs across verticals, flagging where the same struggle appears in different contexts. This reveals scalable growth paths beyond surface-level TAM assumptions.

That's where our JTBD method shines. Instead of guessing at repeatability based on industry overlap, we test it by mapping jobs and needs across segments. With JTBD survey data, we can:

• Identify whether new segments have the same unmet needs
• Evaluate how those customers currently solve the job
• Determine if the company's product can be repositioned or lightly adapted to meet those needs

This allows investors to move from "total addressable market" to total addressable job—a much clearer predictor of expansion potential.

A Repeatability Example

Consider a SaaS company that helps HR teams automate new hire onboarding, currently strong in mid-market tech companies. Can it grow in healthcare?

With our JTBD analysis, we find that the core job—"ensure new hires are fully onboarded with minimal friction"—is just as important in healthcare. But satisfaction is lower due to more regulation and fragmented systems. That's a green light. The need exists, it's underserved, and the company's product is close enough to serve it with modest adaptation.

For investors, this unlocks a credible growth thesis based not on guesses—but on validated demand across job-aligned segments.

We Use JTBD to Inform Post-Close Strategy Before the Deal Closes

Growth doesn't start after the deal closes—it starts during due diligence. The best investors walk into ownership with a focused, evidence-based plan to create value from day one. But too often, post-close strategy is reactive, based on internal interviews or lagging performance metrics.

Our Jobs to be Done framework gives investors a head start. It turns early customer insight into a roadmap for the first 100 days and beyond—one that's grounded in real demand and validated through data.

Our AI-driven platform builds a "First 100 Days" playbook tailored to each acquisition. It prioritizes actions based on job severity, opportunity scores, and segment demand—so PE firms don't lose time after close.

We work with firms during due diligence to:

• Identify which unmet needs are most urgent and underserved
• Prioritize 1–2 jobs or job steps that can unlock growth in the short term
• Align early initiatives (feature development, GTM messaging, sales enablement) with those needs

This isn't about trying to address everything at once. It's about focusing post-close energy on the right thing, right away.

What This Looks Like in Practice

Imagine you're evaluating a company with a strong base of SMB customers and modest enterprise adoption. Our JTBD analysis reveals that enterprise buyers have higher unmet needs in areas the product already supports—but messaging and onboarding don't reflect it.

That insight becomes your 90-day growth sprint post-close: reposition the product, build onboarding that solves the job better, and enable sales to tell a clearer story. Instead of taking six months to diagnose growth bottlenecks, you walk in with a plan ready to execute.

This is what makes our JTBD method so valuable—not just for understanding growth potential, but for activating it immediately after acquisition.

AI Advantage: First 100 Days Prioritization
Our AI-powered platform analyzes past successful growth initiatives across our portfolio to recommend which job steps are likely to yield the fastest ROI when addressed post-acquisition.

JTBD as a Signal for Long-Term Value Creation

When evaluating a company's long-term potential, investors need more than a strong first year—they need a clear line of sight to sustainable, compounding value. This is especially critical when targeting a multiple expansion play or preparing for a strategic exit.

Jobs to be Done offers a powerful signal for long-term value creation by answering one key question: Is this company positioned to solve a recurring, meaningful problem that customers will continue to face in the future?

By continually tracking user behavior and survey feedback, our AI tools monitor how well the product satisfies evolving job needs. This enables strategic pivots that maintain alignment over time—driving compounding returns.

We've seen that companies anchored around high-opportunity jobs:

• Evolve more effectively as customer expectations shift
• Launch features and services that expand wallet share naturally
• Tell a better story to strategic buyers at exit

This is because they're not built around a static product—they're built around helping customers succeed. And as long as that job remains relevant, the company has permission to grow alongside its customers.

JTBD Reduces Strategic Drift

Without a unifying customer need, companies often lose focus as they scale—chasing trends, building features no one uses, or entering markets they're not equipped to serve. JTBD helps anchor decision-making so that every investment, hire, and initiative maps back to the customer's progress.

That clarity compounds. It strengthens internal alignment, accelerates roadmap planning, and makes leadership transitions smoother. For PE firms, that means fewer surprises and more predictable returns.

To Sum Up: A Better Way to Evaluate Growth Before You Invest

When it comes to evaluating a company's growth potential, you can't afford to rely on assumptions. Market size, revenue trends, and usage data may tell you what has happened—but they don't tell you what's possible next.

With AI integrated into every step of our JTBD methodology, we give investors a future-facing lens on value creation. Our approach replaces guesswork with scalable, data-backed insight—so you can invest with confidence.

We help investors uncover what customers are trying to do, where they're struggling, and how well the company is positioned to help. This leads to better due diligence decisions, faster post-close execution, and more confidence in the exit narrative.

Our JTBD process and software make growth potential measurable—so that investors can focus capital and strategy on what really drives value: solving unmet customer needs better than anyone else.

Ready to Assess Growth Potential with Confidence?

Ready to assess growth potential with the precision of AI and the clarity of Jobs to be Done? Contact us to see how our platform reveals insights traditional due diligence misses—and how we can help your next investment outperform.

Visit thrv.com to learn how we can help you evaluate and execute your next investment with confidence.

Case Study: How Target Used Our JTBD Platform to Drive Growth

See how we helped Target's Registry team reverse declining revenue and achieve over 25% top-line growth by identifying and addressing critical unmet needs in their customers' jobs to be done.