Mobile Money Usage and Behavioural Research for Emerging Payment Platforms

Understanding how people use mobile money is the difference between a product that scales and one that stalls. At Research Bureau, we deliver rigorous, actionable behavioural research tailored to emerging payment platforms — mobile wallets, agent networks, remittance flows, QR payments, USSD services, and bank-led digital wallets. Our work blends quantitative scale with qualitative depth to reveal the true motivations, barriers, and behavioural patterns that determine adoption, frequency, value, and retention.

We work with fintechs, payment service providers, telcos, banks, regulators, investors, and NGOs to design evidence-led strategies that accelerate user growth, reduce fraud, improve UX, and optimize pricing and incentives. Share project details for a tailored quote, contact us via the contact form on this page, click the WhatsApp icon, or email [email protected].

Why behavioural research matters for mobile money platforms

Mobile money is not only a technology problem — it is a human problem. Adoption, frequency, and value transfer hinge on perceptions of trust, ease, social norms, and incentives. Superficial metric-tracking (downloads, active users) misses the behavioural levers that move KPIs. Our research uncovers:

Real incentives and disincentives that shape user decisions.
Hidden friction points in onboarding, KYC, agent interactions, and transaction flows.
Segment-specific behaviours by age, region, income, and use-case.
Lifecycle triggers that predict churn, reactivation, or upsell opportunities.

These insights translate directly into product changes, marketing strategies, agent training, and compliance improvements that drive measurable outcomes.

Who we help

We design research programs for a wide range of stakeholders in the fintech ecosystem:

Fintech startups launching wallets, lending, or payments.
Established banks expanding into digital channels.
Mobile network operators (MNOs) building or scaling mobile money.
Payment orchestration platforms and PSPs.
Merchant acquirers and agent networks.
Regulators and development partners assessing financial inclusion initiatives.
Investors performing due diligence on user traction and business risks.

If you’re evaluating user behaviour, optimizing conversion funnels, or preparing for a pilot/scale rollout, our research converts uncertainty into a clear roadmap.

Our services — full-stack behavioural research

We combine research expertise, data science, and product strategy to produce research that directly informs decision-making.

Quantitative user surveys — representative, stratified sampling for market sizing, feature prioritisation, pricing sensitivity, and segmentation.
Transaction log analysis — behavioural cohort analysis, funnel metrics, anomaly detection, agent performance and liquidity patterns using server-side logs or partner-provided datasets.
Qualitative research — in-depth interviews, ethnography, and contextual inquiry to surface motivations, workarounds, and emotional drivers.
Usability testing & prototype validation — remote and in-person usability tests to reduce onboarding time and increase task success rates.
Behavioural experiments & A/B testing — experiment design, power calculations, implementation, and causal analysis to validate interventions (e.g., incentive changes, messaging, flow redesign).
Field agent network studies — agent onboarding, liquidity, cash-out/cash-in dynamics, and service quality assessments.
Fraud and risk analytics — behavioural risk models, velocity checks, device and network indicators, and funnel-based fraud detection insights.
Longitudinal panels — tracking cohorts over time to measure habit formation, retention drivers, and life-event impacts.
Regulatory & compliance impact assessment — user impact studies for KYC changes, fee structures, or policy shifts (privacy-conscious and neutral).
Implementation support — design sprints, stakeholder workshops, product prioritisation, and roadmaps grounded in evidence.

Our approach — rigorous, pragmatic, ethical

We apply a structured framework that balances methodological rigor with business urgency.

Discovery & hypothesis framing: We align with stakeholders, key metrics, and regulatory constraints.
Research design: We choose the right mix of methods (surveys, logs, experiments, qualitative) and define samples, power, and success criteria.
Field execution: We recruit, deploy, and monitor using secure infrastructure and trained interviewers.
Analysis & modeling: We apply statistical models, segmentation, and behavioural frameworks to extract causal and predictive insights.
Actionable outputs: We deliver clear recommendations, prototypes, KPI dashboards, and prioritized roadmaps.
Implementation & iteration: We support experiment rollouts, monitor outcomes, and refine interventions.

This ensures work is both academically sound and product-ready.

Methodologies in detail

We match methods to business questions. Below are common research needs and our recommended methods.

Product-market fit and TAM estimation:
- Representative surveys, usage diaries, and transaction aggregation.
Onboarding friction analysis:
- Usability testing, funnel analytics, and reflow testing.
Pricing and fee sensitivity:
- Conjoint analysis, discrete choice experiments, and A/B tests.
Fraud and misuse detection:
- Transaction graph analysis, anomaly detection models, and agent behaviour audits.
Agent network dynamics:
- Agent surveys, liquidity modeling, geospatial mapping, and ethnographic fieldwork.
Habit formation and retention:
- Longitudinal cohort studies, push-notification experiments, and behavioural nudges.

Each method comes with planned deliverables and expected timeframes, tailored to your operational constraints.

Example deliverables

We provide clear, usable outputs your teams can act on immediately:

Research brief and hypothesis map
Sampling and field plan
Cleaned datasets and reproducible code notebooks
Statistical models and segmentation outputs
Visual dashboards with cohort and funnel analytics
Usability heatmaps and task completion metrics
Behavioral experiment reports with p-values and confidence intervals
Prioritised product roadmap and recommended interventions
Training materials for agents and customer support

Deliverable type	Typical contents	Business value
Quantitative report	Survey methodology, sample representativeness, key metrics, segments	Market sizing, feature prioritisation
Transaction analysis	Cohort retention, ARPU, N-day retention, anomaly flags	Churn reduction, fraud mitigation
Usability report	Task success rates, error types, redesign recommendations	Faster onboarding, higher conversion
Experiment results	Design, power analysis, effect sizes	Evidence-based product decisions
Field study deliverable	Agent network map, liquidity heatmap, field notes	Better agent onboarding and liquidity planning

Case studies — anonymised, practical impact

Below are anonymised examples showing the types of outcomes our clients typically achieve. Results vary by context; these are illustrative of the value of evidence-led changes.

Case study A: Wallet adoption lift for a mid-size MNO

Challenge: Low onboarding completion despite high download rates.
Approach: Combined UX testing, transaction funnel analysis, and A/B testing of onboarding flows.
Outcome: Reduced onboarding time by 35% and increased completed registrations by around 22% in targeted cohorts. Recommendations led to streamlined KYC prompts and contextual help at key drop-off points.

Case study B: Agent network liquidity optimisation for a PSP

Challenge: Frequent cash-outs from agents led to liquidity shortages and service downtimes.
Approach: Agent surveys, POS transaction logs, and geospatial modelling.
Outcome: Redesigned liquidity incentive and cash-in fee structure reduced stock-outs by over 30% and increased average daily active agents.

Case study C: Fraud reduction for a neo-bank

Challenge: High chargeback/fraud incidents in specific merchant categories.
Approach: Transaction graph analytics and device fingerprinting combined with behavioural triggers.
Outcome: Implemented velocity checks and behavioural score thresholds, reducing suspicious transaction rates and maintaining legitimate conversion.

KPIs and metrics we optimise

We orient research to the metrics that matter for growth, risk, and sustainability.

Adoption & activation: download-to-activation ratios, KYC completion rates.
Engagement & frequency: transactions per user, value-per-transaction, ARPU.
Retention & churn: 7/30/90-day retention, cohort decay rates.
Conversion: onboarding funnel step-by-step conversion.
Agent metrics: active agents, turnaround time for liquidity, average load amounts.
Risk signals: fraud rate, chargebacks, suspicious account flags.
Revenue: take rates, NPS/CSAT for merchant services, fee sensitivity.

All KPI baselines and targets are defined with stakeholders during project kickoff.

Data sources and integrations

We work with a range of data inputs to produce robust findings:

Backend transaction logs and server API logs.
Mobile SDK telemetry (events, screens, errors).
Agent POS and acquirer logs.
Third-party data: telco metadata, credit bureau aggregates, demographic datasets.
Primary data collection: surveys, interviews, diaries.
Geospatial and market data for agent mapping and density analysis.

We can work with anonymised datasets or under NDAs and integrate with your analytics stack (e.g., Snowflake, BigQuery, AWS) where required.

Security, privacy and compliance

We design research with data protection and trust as a priority. Our standard practices include:

Data minimisation and anonymisation before analysis.
Encrypted data transfer and storage using industry-standard protocols.
Access controls and role-based permissions for project teams.
Compliance with relevant privacy frameworks; we can align with POPIA, GDPR, and client-specific security policies.
Ethical participant recruitment and explicit informed consent for primary data collection.

We never engage in practices that compromise user privacy or regulatory requirements. Tell us your compliance checklist and we will incorporate it into the project plan.

Sampling, recruitment and field logistics

High-quality insights start with representative samples. We recruit using a range of channels depending on the context:

Platform user lists and in-app recruitment for product users.
Random-digit sampling or telco partner lists for representative consumer surveys.
Field recruitment for agent studies and ethnography.
Third-party panels for hard-to-reach segments.
Snowball and referral sampling for niche communities (e.g., remittance corridors).

We provide recruitment quotas, screening criteria, and substitution rules, with clear documentation so results remain defensible.

Pricing models and timelines

We offer flexible engagement structures to match project scope and budget. Typical models include:

Fixed-price project for scoped research phases.
Sprint-based retainer for iterative testing and product partnership.
Hybrid: fixed research initiation + per-experiment pricing.
Data analysis or consulting hourly engagements for analytics support.

Below is an illustrative table of timelines and price ranges (actual prices depend on sample sizes, geographies, and complexity).

Project type	Typical timeline	Indicative cost range*
Discovery & pilot survey	4–8 weeks	$8,000–$25,000
Full quantitative study (national)	8–14 weeks	$25,000–$75,000
Behavioural experiments (per test)	4–10 weeks	$6,000–$30,000
Agent network field study	6–12 weeks	$15,000–$50,000
Longitudinal panel (6 months)	6+ months	$30,000+

*These ranges are indicative. Request a customised quote by sharing project details.

How we ensure research translates to product impact

Research is valuable only when converted into action. Our engagement includes hands-on implementation support:

Prioritised recommendation lists tied to expected KPI impact.
Design sprints and prototype creation to fast-track changes.
Experimentation blueprints with sample sizes and tracking specs.
Stakeholder workshops to align product, risk, and operations teams.
A/B test monitoring and post-implementation retrospectives.

We measure post-research impact and will help you establish dashboards to track ROI.

Common questions we solve

Which user segments should we target for growth to maximise revenue?
What are the main causes of onboarding drop-off and how to fix them?
Which fee structures lead to sustainable take-rates without losing users?
How can agent networks be optimised for liquidity and coverage?
Which behavioural signals predict fraud or misuse early?
What nudges improve repeat usage and reduce churn?

If your question is not listed, share it — we’ll design a study that answers it.

Example research plan (condensed)

Kickoff & stakeholder alignment (1 week): define KPIs and data access.
Data audit (1–2 weeks): assess logs, SDK events, and available integrations.
Mixed-methods design (2 weeks): stratified survey, qualitative plan, experiment blueprint.
Fieldwork & data collection (4–8 weeks): recruit, test, and monitor.
Analysis & modelling (2–4 weeks): cohorts, predictive models, segmentation.
Delivery & workshop (1 week): present findings, roadmap, prioritized recommendations.
Implementation support (ongoing): experiment rollouts and performance monitoring.

Total typical duration: 8–16 weeks, depending on scope and geography.

Risks and mitigation

We proactively manage research risks to protect timelines and data quality:

Low response rates: use multi-channel recruitment and incentives.
Sampling bias: apply weighting and validated screening.
Data quality issues: implement validation checks and attention filters.
Regulatory changes: build contingency plans for KYC or policy shifts.
Operational constraints: design phased approaches that deliver early wins.

We document assumptions and limitations in every deliverable to ensure clear interpretation of findings.

Why choose Research Bureau

Practical expertise: We combine behavioural science, product research, and data engineering to deliver usable outcomes.
Contextual knowledge: Deep experience across emerging markets and mobile-money ecosystems.
Action-oriented reporting: Findings are prioritised for impact, with clear next steps and implementation support.
Ethical and secure: Research designed with participant welfare, privacy, and regulatory alignment in mind.
Collaborative partnership: We work alongside product, ops, risk, and compliance teams to ensure adoption.

Our goal is not just to produce reports, but to drive measurable growth, reduce risk, and accelerate strategic decisions.

Frequently asked questions (FAQ)

How do I get a quote?

Share project goals, target geographies, desired sample sizes or data sources, timelines, and any compliance constraints via the contact form, click the WhatsApp icon, or email [email protected]. We’ll respond with a scoped proposal and pricing estimate.

Can you work with our analytics and data warehouse?

Yes. We integrate with common analytics platforms and can work with anonymised datasets exported from Snowflake, BigQuery, Redshift, or secure S3 buckets. We follow secure transfer protocols and respect client access controls.

Do you recruit in rural or underserved areas?

Yes. We recruit across urban, peri-urban, and rural contexts using tailored field teams and tele-recruitment as needed. We mitigate logistical challenges through local partnerships and careful sampling design.

How do you handle user privacy?

We anonymise personally identifiable information before analysis, obtain informed consent for primary research, and follow data minimisation principles. We can incorporate client-specific privacy protocols and legal requirements.

What if we only have partial data?

We design hybrid approaches that combine available logs with primary data collection to fill gaps. This allows stronger inference than relying on partial sources alone.

Ready to move from insight to impact?

Share project details for a customised proposal. Tell us:

Your primary business question (e.g., reduce churn, increase activation).
Target markets and segments.
Available data sources (transaction logs, SDK events, user lists).
Desired timeline and budget range.
Any compliance or security constraints.

Contact us via the contact form on this page, click the WhatsApp icon to start a live chat, or email [email protected]. We’ll respond with a tailored scope, timeline, and quote.

Research Bureau — turning real-world behavioural evidence into scalable payment platform strategies. Get in touch today to begin a practical, privacy-conscious research program that delivers measurable outcomes.