Simulating Enterprise Software Adoption in Modeliq

A global B2B software company approached DataDiggers with a crucial challenge: before launching a new enterprise productivity suite across multiple international markets, they needed to understand potential adoption barriers, usage intent, and long-term retention drivers — without access to live market data or the ability to test with real clients at scale.

Using Modeliq, our synthetic simulation engine, DataDiggers created a dynamic, high-fidelity model of the buyer journey. The result: evidence-backed go-to-market recommendations, faster stakeholder alignment, and a significant reduction in time-to-insight compared to traditional fieldwork — all while maintaining the rigor of real-world validation.

The Challenge: Forecasting Behavior Without Market Exposure

The client, a large-scale B2B SaaS provider, was preparing to launch a modular enterprise software suite targeting mid-sized businesses (100–500 employees) across North America, the UK, and DACH.

However, their product was still in beta, and:

• No real adoption data was available
• Direct access to end-users (IT admins, ops managers) was limited
• Regional market dynamics were highly variable
• Timelines were tight — delaying rollout by 3–6 months could mean major opportunity costs

They needed predictive insight, not just perception data, to confidently answer:

• What are the key friction points in adoption per region and role?
• How do software trial outcomes influence renewal or expansion?
• Which pricing model (subscription vs. freemium) drives higher conversion at scale?

Our Solution: Synthetic Simulation in Modeliq

Modeliq enabled us to simulate the enterprise adoption journey using synthetic agents modeled after actual mid-market IT and business decision-makers, powered by advanced data logic and scenario modeling.

Step 1: Building the Synthetic Cohort

We created a multi-layered simulation population based on:

• Real-world benchmarks from DataDiggers’ proprietary B2B panel (MyVoice)
• Synthetically enhanced personas informed by Correlix — correcting for regional bias and incomplete data
• Deep profiling across 70+ variables: industry vertical, digital maturity, procurement structure, and risk appetite

Each synthetic persona reflected behavioral probabilities learned from actual enterprise adoption patterns gathered over the last 24 months.

Step 2: Designing Behavioral Scenarios

We modeled key decision nodes, including:

• First contact with marketing (demo, referral, webinar)
• Initial trial setup and team feedback
• Pricing sensitivity by department
• Switching costs and stakeholder influence
• Cross-sell and upsell dynamics post-3 months

Each scenario was tested across multiple market contexts using probabilistic weighting — allowing us to simulate two or more years of adoption dynamics in a matter of hours.

Step 3: Validating Assumptions

While simulations don’t replace real user testing, they do reveal actionable directional insights:

• Benchmarked against legacy product performance
• Calibrated using existing CRM and NPS data
• Cross-validated with a small qualitative sample via Brainactive

Key Results

In under 10 days, the client received a full simulation dashboard from Modeliq — enabling fast, data-informed decision-making.

“Modeliq gave us the confidence to move forward. We didn’t just get answers — we got a predictive map of what to expect, and how to adapt.”
— VP of Product Strategy, Client Company

Why Modeliq?

Speed, precision, and foresight. Modeliq bridges the gap between hypothesis and market reality using synthetic insights that are:

• Faster than traditional research (results in days, not weeks)
• Scalable across complex multi-market strategies
• Flexible — easily adjusted as new data or assumptions arise
• Validated against actual behavior data to ensure real-world integrity

Unlike AI-generated personas used in early-stage exploration (e.g. via Syntheo), Modeliq is purpose-built for simulation and forecasting, making it ideal for pre-launch diagnostics, stress-testing strategies, and refining customer journey assumptions.

About DataDiggers

Founded in 2015, DataDiggers is a technology-driven market research agency delivering fast, reliable, and globally validated insights. From our AI-powered platforms Brainactive, Syntheo, Modeliq, and Correlix, to our ISO-certified quality controls and 30+ proprietary panels worldwide, we enable smarter decisions for brands and agencies alike.

Whether you're exploring new ideas, validating assumptions, or simulating future scenarios — DataDiggers empowers you with data that doesn’t just inform, but performs.

Ready to simulate your next strategic move?
Contact us or explore how Modeliq can help forecast your success — with speed and precision.