Digital Transformation for Market Research
AI-call verification across 100% of your sample, real-time field dashboards and automated deliverables for studies that still depend on manual operations.
The 3 tech challenges in Market Research
Back-checks that only cover a sample
Phone supervision verifies 10–20% of fieldwork. The rest goes unaudited, and a single late finding can compromise an entire study.
Field coordination via spreadsheets and calls
Routes, schedules, replacements and interviewer supervision are managed by hand. Without real-time visibility, quota problems surface at day's end — or the study's.
CATI with rising costs and high turnover
Running a survey call center keeps getting more expensive and harder to scale for project peaks. Training an interviewer takes weeks; projects arrive in bursts.
Data quality under pressure
The industry faces fabricated data, bot responses and online panel fraud. Catching it with manual review doesn't scale to today's study volumes.
Deliverables that take weeks
Open-end coding, cross-tabs and report assembly eat the time between field close and client. Meanwhile, the decision that motivated the study doesn't wait.
How the I+C+S framework solves this
AI for Market Research
Voice agents for back-checks and hybrid CATI; automatic open-end coding and data fraud detection.
Cloud for Market Research
Real-time field-operations dashboards and pipelines connecting capture, validation and delivery in a single flow.
Talent for Market Research
Bilingual data scientists and engineers integrated into your research projects in 5 days, without hiring overhead.
Industry challenges
Back-checks that only cover a sample
Phone supervision verifies 10–20% of fieldwork. The rest goes unaudited, and a single late finding can compromise an entire study.
With AI calls, verification covers 100% of the sample — at the cost of today's sample.
Field coordination via spreadsheets and calls
Routes, schedules, replacements and interviewer supervision are managed by hand. Without real-time visibility, quota problems surface at day's end — or the study's.
CATI with rising costs and high turnover
Running a survey call center keeps getting more expensive and harder to scale for project peaks. Training an interviewer takes weeks; projects arrive in bursts.
~US$0.40 per AI call vs US$7–12 human, with instantly elastic capacity.
Data quality under pressure
The industry faces fabricated data, bot responses and online panel fraud. Catching it with manual review doesn't scale to today's study volumes.
AI anomaly detection across 100% of records — not a sample.
Deliverables that take weeks
Open-end coding, cross-tabs and report assembly eat the time between field close and client. Meanwhile, the decision that motivated the study doesn't wait.
72% of insights buyers already use generative AI in at least one stage (GRIT 2025).
Regulatory frameworks we operate under
Habeas Data (Colombia)
Respondent personal data processing: informed consent, purpose limitation and data-subject rights in every study.
General Data Protection Regulation
Applies in multinational studies and when global clients require it contractually.
International standard for market and social research
Quality standard for the full study cycle: sampling, fieldwork, processing and reporting — AI-assisted processes included.
International code on market research
The profession's ethical principles: transparency with participants, also when AI takes part in data collection.
How we implement in this industry
Real patterns we have delivered, not theoretical slides.
Back-checks with AI calls
Automatic verification of completed interviews: the AI calls, confirms the interview happened, validates key answers and records auditable evidence.
Outcome: Total supervision (100% of the sample), not sample-based.
Hybrid human + AI CATI
Voice agents absorb volume, extended hours and short questionnaires; the human team takes complex cases and in-depth interviews.
Outcome: Elastic capacity for project peaks, without growing payroll.
Real-time field dashboard
Quota progress, per-interviewer productivity, interview geolocation and live quality alerts throughout the field operation.
Outcome: Same-day corrections, not at study close.
AI-powered analysis and deliverables
Open-end coding, automatic cross-tabs and first report drafts generated with AI on validated data.
Outcome: Deliverables in days, not weeks.
Our playbook for this industry
A repeatable method refined across 13 years and 7 countries.
Study-cycle assessment
We map fieldwork, supervision, processing and delivery, and quantify where automation yields the most margin and speed.
Pilot on a real study
We pick one process — e.g. back-checks — and run it with AI alongside the current method, comparing coverage, cost and findings.
Scale-up by service line
We extend automation to CATI, field dashboards and deliverable generation, study by study.
Continuous operations and governance
Quality monitoring, continuous model improvement and ISO 20252 / ICC-ESOMAR compliance across automated processes.
Industry signals you should know
Common tech stack
Questions from companies in this sector
Studies show completion rates above email and high consistency on structured questionnaires. For sensitive instruments we design A/B tests against the current method before scaling, and hybrid mode always keeps delicate interviews in human hands.
Yes. Agents are configured from your existing questionnaires and integrate via API with your field, CATI or panel software. No platform migration needed to start.
Face-to-face fieldwork benefits from supervision: AI back-checks across 100% of interviews, progress dashboards and automatic transcription/analysis of qualitative sessions. AI augments fieldwork — it doesn't replace it.
Data lives in your infrastructure and jurisdiction, with informed consent, minimization and per-interaction traceability. Flows are designed to align with Habeas Data, GDPR and ISO 20252.
A back-check or short-CATI pilot runs within weeks on a real study, with metrics comparable against your current method before deciding to scale.
What if your next study went to field with twice the supervision at a fraction of the operating cost?
Conversemos sobre cómo la tecnología puede impulsar tus resultados.