Observed Signal · Aug 7, 2026 · Product Launch · Source: Digiday · Impact: 3/5 · Sentiment: Positive
Ideally pushes synthetic research into creative process
Ideally, a New Zealand market-research firm founded in 2023, is promoting the use of synthetic audiences and AI-driven consumer insights earlier in the creative process to boost creativity and reduce risk. The company says its platform connects tests across teams so data compounds over time via an AI layer. Ideally has a multi-year partnership with Omnicom Oceania — the agency group has used Ideally in more than 60 tests across 23 brand categories — and reports its service costs about one-tenth of traditional research budgets. Ideally recently launched an AI feature called Research Assistant that drafts consumer-study frameworks from plain-language prompts or briefs. The firm has opened a New York office, says U.S. revenue has grown 400%, and counts Treasury Wine Estates as a foundation customer. Some industry researchers caution synthetic research should not replace deep human-led insight.
A B2B research platform using synthetic audiences and AI has secured a multi-year agency network deal with Omnicom Oceania and launched an AI study-building feature; this may influence how agencies integrate research into creative workflows and reduce research costs, but it is not a major platform policy change.
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Key Takeaways & Evidence Grounding
- Ideally is a New Zealand-based market research firm that started in 2023.
- Ideally uses synthetic audiences and an AI layer to connect tests and compound data across teams.
- Ideally has a multi-year deal with Omnicom Oceania; the agency group has used Ideally in over 60 tests across 23 brand categories.
- Ideally launched Research Assistant, an AI feature that builds consumer studies from plain-language questions or uploaded briefs.
- Ideally opened a New York office; its U.S. business has grown 400% and Treasury Wine Estates is a foundation customer.
Connected Companies & Entities
2 Entities mapped“The multi-year deal, according to Daniel Shaw, Omnicom’s Intelligence lead, gives every Omnicom Oceania agency access to Ideally’s consumer ...”
“Ideally counts Omnicom Oceania as a client, and the agency group has used Ideally in over 60 tests and projects, wending its way into the ho...”
Ontology Mapping & Concepts
Related Market Signals & Shifts
Recent verified developments and strategic activity across this market segment.
Agencies adopt hybrid synthetic audience research
Agencies are increasingly supplementing traditional consumer research with AI-generated synthetic audiences, using a hybrid approach that layers synthetic personas on top of human feedback, syndicated data and social listening. Crowley Webb’s senior VP of data analytics, Andrea Berki-Nnuji, says the agency has used synthetic audiences over the past 18 months but typically vets the output with real humans, estimating fully synthetic datasets reach about 80% of required validity. Vendors and platform selection focus on data provenance, pricing, multi-user capabilities and compliance review. Use cases include concept testing, naming, media messaging and pricing; however, certain contexts such as rare-disease pharma work still require strictly human research.
Synthetic Research Depends on Audience Model Trust
Eric Ayzenberg (Soulmates.ai) argues that the real debate is not AI versus human research but whether the models behind synthetic audiences are trustworthy enough to inform decisions. Citing an evaluation by The Good, he says AI research tools can surface friction, accelerate workflows and provide directional input, but they often fail to reproduce observed behaviour, emotional nuance and the subtle signals needed for high‑stakes decisions. Ayzenberg proposes a three‑step approach: use synthetic audience models for quick directional clarity, use high‑fidelity synthetic models (validated against human data) when behavioural understanding is needed fast, and use traditional recruited field research when observed in‑the‑wild behaviour or regulatory/ investment rigor is required. The piece positions synthetic tools as complementary to human research, not replacements.
Synthetic Research: Promise With a Catch
This MarTech analysis examines the rapid rise of synthetic research—using generative models and synthetic personas to produce market and product insights—and the tradeoffs between speed/cost and scientific rigor. The synthetic data market is projected to grow dramatically, and many insight leaders plan to adopt synthetic approaches for scale and niche sampling. But off-the-shelf LLMs (e.g., ChatGPT, Claude, Gemini) can introduce bias, homogeneity and overly positive responses (the “Pollyanna Principle”), producing outputs that are difficult to validate. The article highlights techniques to improve reliability: fine-tuning models on proprietary survey data, applying a train-synthetic, test-real (TSTR) validation approach, and enforcing governance, transparency and persona provenance checklists. Case studies and experiments (including Stanford/Google DeepMind results and a Dollar Shave Club example) show promise when synthetic methods are benchmarked and verified against real-world data.
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