Improving Forecast Accuracy in B2B Tech

Client Profile:‍

A global B2B technology company developing infrastructure software solutions for enterprises in financial services, logistics, and telecom.

Challenge:‍

With limited primary data in niche segments, the company’s forecasts for product demand and user adoption were often skewed or incomplete. They needed a scalable way to:

• Correct bias in existing research datasets
• Simulate behavior in new or underserved segments
• Strengthen business case projections for leadership buy-in

Solution:‍

The company partnered with DataDiggers to integrate Correlix into their insight workflow.

What They Did:

• Applied Correlix to correct bias in legacy survey datasets where certain regions or personas were underrepresented.
• Augmented datasets synthetically to simulate outcomes across new product segments.
• Tested different go-to-market scenarios using synthetic overlays on existing research inputs.

Results:

• Reduced forecast variance by 30%, increasing reliability in planning cycles
• Identified key blind spots in underrepresented user groups
• Improved stakeholder alignment with more confident, evidence-based projections

Client Quote:

"Correlix helped us validate what we suspected — and uncover what we didn’t. We’ve never had this level of clarity in our market simulations."

Takeaway for You:‍

If you operate in a niche B2B environment with incomplete data, Correlix can help you fill the gaps — responsibly, rigorously, and at scale.

‍

👉 Explore Correlix → Book a demo