How a product lifecycle SaaS tripled demos and quadrupled deal size

Business context

A leading SaaS provider in the product lifecycle and bill of materials (BOM) management space had spent years refining a successful freemium model—generating tens of thousands of inbound leads.

By 2024, this engine began to show signs of strain. While interest remained high, deal velocity and average contract size were falling. A growing portion of customers fell into the low-value, high-support segment—eroding margins and diverting resources from enterprise opportunities.

Business goal

Leadership recognized the need for a more focused approach. Without a way to prioritize and proactively pursue ideal customers, high-value revenue was being left untapped. To move forward, the company needed an outbound motion built not on volume—but on signal, segmentation, and strategic targeting.

Our role

That’s when they partnered with our sales development program. Spright was brought in to design a signal-driven outbound strategy focused on segmentation, lead scoring, and sequences built for enterprise-level engagement.

Challenges

• Volume without clarity: Tens of thousands of freemium users, but no consistent segmentation strategy.
• Support burden: Low-dollar customers increasingly occupied CS and AE bandwidth.
• Underused outbound: Inbound filled calendars, but often with low-fit prospects
• Stalled growth: Month-over-month revenue had plateaued; larger deals weren’t progressing

Process

The first priority was to bring structure to an unmanageable volume of inbound leads. Although the database was large, it lacked the segmentation required for precise, high-value targeting. The approach was built around three core pillars:

1. Tiered segmentation model

We implemented a Tiered Account Scoring framework based on:

• Industry fit: Manufacturing-first, with focus on verticals like industrial machinery, contract manufacturing, and precision electronics
• Company stage: Size, employee count, and revenue—pre- vs. post-revenue
• Geographic signal: Strategic regions such as the US Midwest and DACH (Germany, Austria, Switzerland)
• Tech fit: Stack indicators and usage patterns suggesting urgency for BOM automation or PLM upgrades

Using this model, we enriched over 20,000 records through a combination of Python scripting and best-in-class enrichment providers (e.g., Apollo, Clearbit, ZoomInfo). Each contact was then scored and assigned to a Tier (1 through 3), with Tier 1 being ideal targets for enterprise conversion.

2. Outbound platform & playbooks

We set up a custom outbound engine from the ground up, including:

• Email infrastructure optimized for deliverability and domain health
• Outbound calling infrastructure with dynamic scripts aligned to persona pain points
• Sequenced outreach playbooks that combined email, phone, and LinkedIn touches tailored to manufacturing personas—e.g., Engineering Ops Managers, VP of Product, and Heads of R&D

Our outreach was consultative and discovery-led. Rather than pitch product immediately, our SDRs focused on surfacing pain, timing, and internal initiatives that aligned with the company’s key business cases.

3. Signal-driven qualification

Each initial contact was scored not just by fit, but by signal strength during conversations. SDRs followed a consistent framework to assess:

• Complexity of BOMs and need for automation
• Internal pain from disconnected tools (e.g., spreadsheets or legacy PLMs)
• Urgency tied to growth, M&A, or supply chain transformation

This allowed us to funnel only high-quality leads to AEs—increasing demo win rates and deal sizes downstream.

Results

High-impact pipeline growth in under 90 days

Within three months of deploying this outbound motion, the company saw a significant pipeline shift:

• 3× increase in discovery calls and demos, driven by tiered targeting and streamlined SDR workflows
• 4x increase in average deal size, as the team shifted from low-dollar inbound users to mid-market and enterprise manufacturers
• 60%+ month-over-month growth in net new customer revenue, sustained over multiple months
• Reduced support load from small accounts, freeing the CS team to focus on strategic customers

Why it worked

Success came not from doing outbound for the sake of it, but from applying structure, relevance, and precision:

• Found clarity in a chaotic database, enriching and segmenting to unlock signal
• Built for fit, not just activity—targeting industries and personas aligned to the company’s real strengths
• Prioritized repeatability, creating a system that the internal team could scale and eventually own
• Complemented the PLG funnel, instead of competing with it—outbound became the tool to convert inbound interest into strategic revenue

Conclusion

PLG + Outbound = Scalable growth

This success story is proof that product-led growth doesn’t negate the need for outbound—it elevates it. When paired with the right framework, outbound becomes a focused, high-leverage tool that activates the best-fit customers and drives meaningful revenue.

With structured segmentation, precise outreach, and signal-driven qualification, this product lifecycle software company turned an overwhelming freemium funnel into a scalable, enterprise-ready revenue engine.