Field Research for a B2B Marketplace — Candelita

Field Research for a B2B Marketplace Entering New Markets

Latin America Field Research Product Strategy Market Expansion

A global consumer goods company was expanding its B2B digital marketplace into Latin America. Before committing to product decisions, they needed to understand how commerce actually worked on the ground — not how it was assumed to work from headquarters.

13

Countries covered

60+

Establishments visited

39

Opportunities identified

7

Behavioral patterns uncovered

3

Product areas redesigned

Field research — informal commerce, Latin America

How might a digital marketplace succeed in markets where commerce runs on trust, informal credit, and human relationships?

The platform was technically sound. The business case was compelling. But the people it was designed for operated in worlds the product team had never been inside.

The question was not whether the platform could be built. It was whether it was being built around the right understanding of commerce.

Informal commerce isn’t inefficient. It’s optimized for different constraints.

Small retailers managed cash flow daily. Trusted intermediaries who showed up in person and extended informal credit were not costs to be eliminated — they were load-bearing infrastructure.

A product designed around speed and automation risked solving the wrong problem. Real understanding of purchasing rhythms, trust dynamics, and adoption barriers had to come before major product decisions were made.

Three phases. One goal: replace assumption with evidence.

Phase 01 — Enter the field

Observe real purchasing behavior

Visited retailers, wholesalers, and informal operators across Brazil, Ecuador, and Peru. Watched how orders were placed, how trust worked, and where digital tools failed.

Phase 02 — Find the patterns

Synthesize signals across markets

Analyzed behavior across 13 countries — seven consistent patterns emerged across geographies regardless of digital maturity or retailer type.

Phase 03 — Translate into decisions

Convert insight into product strategy

Mapped 39 opportunities to product areas. Aligned product, commercial, and operations teams around findings — so they drove decisions, not just reports.

What the field taught us that data alone could not.

Insight 01

Informal commerce wasn’t broken — it was optimized for trust.

Durable ordering relationships were built on human reliability, not transactional efficiency. The sales rep who showed up on time and extended informal credit was not a distribution cost. He was infrastructure.

Implication Digital onboarding had to reduce perceived risk before it could reduce friction. Trust signals needed to be core — not a later addition.

Insight 02

Convenience meant predictability, not speed.

Retailers didn’t need faster. They needed reliable. Knowing an order would arrive when promised mattered more than shaving time off the ordering process. Uncertainty was the problem — speed wasn’t the solution.

Implication Order visibility and expectation-setting were higher-priority investments than automation. Confidence through transparency mattered more than speed.

Insight 03

Adoption friction started before the first order.

Barriers appeared before any product interaction — unclear registration, an illegible value proposition, and prior experiences that overpromised created ambient skepticism the platform had to earn its way past.

Implication Activation strategy mattered as much as product UX. The work to bring a retailer onto the platform began before the first screen.

“Trust was infrastructure.

Key finding — B2B Commerce field research, Latin America

IMPLEMENTATION COMPLEXITY → STRATEGIC IMPACT → HIGH IMPACT · LOW COMPLEXITY HIGH IMPACT · HIGH COMPLEXITY Priority opportunities (acted on) Deprioritized or deferred

Simplified representation. Identifying details removed.

How findings changed product decisions.

Finding

Retailers needed visible trust signals before a first order. Existing onboarding provided none.

Decision

Redesigned onboarding to lead with order guarantees and delivery commitments — not feature explanations.

Finding

Order uncertainty drove drop-off after first purchase. When fulfillment was opaque, trust evaporated.

Decision

Prioritized order tracking and proactive delivery communication as core features — not post-launch additions.

Finding

New buyer activation required in-person introduction and early human support — not digital self-service alone.

Decision

Built a hybrid activation model pairing digital onboarding with field support during the critical first-order window.

Finding

Market readiness varied significantly. A single expansion model risked expensive missteps across geographies.

Decision

Established market-specific entry criteria based on digital literacy, trust infrastructure, and retailer density.

What changed.

Key product assumptions revised before entering the roadmap — reducing downstream course-correction costs.

Product, commercial, and operations teams aligned around a shared behavioral model, resolving persistent prioritization disagreements.

Three product areas — seller onboarding, order tracking, buyer activation — redesigned from field findings and shipped in subsequent cycles.

Expansion sequencing became criteria-driven rather than instinct-driven.

Research framework documented and made reusable — a repeatable methodology for future market entries.

The biggest risk in expansion isn’t execution. It’s assumption.

What looked like a distribution problem was a trust problem. What looked like a technology adoption challenge was a value proposition challenge. These distinctions are invisible from a dashboard.

Teams that invest in ground-level understanding before they commit make better decisions at every level that follows.

Facing a similar challenge?
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Candelita engagements are led by Jennifer Dopazo and tailored to each client.