Saving Budget on Sample by Mixing Real and Synthetic Respondents

How DataDiggers Reduced Cost per Completed Interview by 35% Using a Hybrid Sampling Approach

🎯 The Challenge

A global consumer electronics company was preparing to launch a new smart home product line across three international markets. The project required feedback from two distinct audiences:

• Tech-savvy consumers interested in connected devices
• Small business professionals responsible for office tech purchases

The research team faced several roadblocks:

• High CPI, especially among B2B profiles (averaging $12–15 per completed interview)
• Feasibility issues in some subsegments and geographies
• Tight timelines to support fast decision-making

The client’s objective was to lower overall project cost and reduce fielding time — all without compromising the reliability or depth of insights.

💡 The Solution: Hybrid Sampling with Real and Synthetic Respondents

To meet the challenge, DataDiggers proposed a hybrid sampling strategy that combined:

• Real respondents from our global MyVoice proprietary panels (CPI: ~$2–3 for consumers, ~$10–15 for B2B)
• Synthetic respondents from Syntheo (flat fee: $0.50 per interview) for hard-to-reach or cost-prohibitive segments

Synthetic respondents were generated using Syntheo’s AI-powered digital personas, built from high-integrity training data based on millions of verified profiles across our global respondent pool. These personas were designed to realistically simulate survey behavior, decision logic, and answer patterns of their real-world counterparts.

We applied a rigorous data validation process:

• Synthetic data was benchmarked against real results to ensure parity
• Bias checks were conducted at segment level
• Simulation modeling using Modeliq validated responses under multiple outcome scenarios
• Correlix was used for bias correction and statistical balancing

This approach allowed the client to maintain data quality while significantly reducing their cost per interview.

📊 The Results

By combining real and synthetic sampling, the client achieved:

The synthetic respondents—priced at only $0.50 per complete—allowed the client to reach difficult segments without inflating the total sample cost. For every 1,000 synthetic completes, the client saved over $2,000–$10,000, depending on the profile they would have otherwise sourced from real respondents.

🔍 Why It Worked

✅ Precision Targeting: MyVoice panels provided high-quality real data from well-profiled respondents
✅ Validated Synthetic Personas: Syntheo delivered low-cost responses with modeled realism
✅ Cross-Validation + Benchmarking: Ensured that synthetic insights aligned with real-world trends
✅ Simulation Capabilities: Modeliq allowed scenario testing without additional fieldwork
✅ Data Integrity Protocols: With AI-based fraud detection, digital fingerprinting, and ISO-certified practices, data was reliable and compliant

🧩 The Tools Behind the Success

• Syntheo – Delivered realistic synthetic respondents at $0.50 per complete
• Brainactive – Managed the entire research workflow, from targeting to reporting
• Modeliq – Simulated market outcomes using both real and synthetic datasets
• Correlix – Applied statistical modeling to correct potential bias and enhance robustness
• MyVoice Panels – Provided verified, engaged respondents for the real component

📢 Client Testimonial

“Using synthetic sampling with DataDiggers gave us the confidence to scale insights without blowing our budget. It felt like unlocking a new research capability—fast, flexible, and still dependable.”
— Global Insights Manager, Consumer Electronics Brand

🧭 Key Takeaways

• Mixing synthetic and real respondents can reduce total CPI by over 30%, especially when targeting niche or B2B profiles
• Syntheo’s $0.50 flat fee per synthetic complete offers unparalleled cost-efficiency with rigorous quality control
• With validation protocols and advanced modeling tools, hybrid data designs are viable for decision-critical research

Brands no longer have to choose between speed, cost, and quality — with DataDiggers, you get all three