# Fernanda Oi

Fernanda Oi is a UX Research Manager at Venturus. Oi's work includes UX research and product discovery: helping teams understand users and make better-informed product and service decisions before development.

- Profile: https://b2binfluencer.marketing/creators/fernanda-oi/
- LinkedIn: https://www.linkedin.com/in/fernandaishimoto
- LinkedIn followers: 2,161
- Topics: artificial-intelligence, ux
- Based on 11 dated posts, latest 2026-07-29

## Summary

Fernanda Oi is most useful for UX research and product discovery before development.

- Best for: B2B SaaS brands improving product discovery with custom UX research and design.
- Not for: Broad consumer awareness campaigns needing large reach and measured audience delivery.
- Check first: Confirm paid terms, available formats, audience delivery, and recent post results before contacting.

### Takeaways

- Test AI research tools on a real question before trusting them.
- Discovery aims to find problems before development, scoped to each challenge, not a fixed recipe.
- Build the research function, then introduce it to the whole company.

## Main ideas

- **Test AI research tools on a real question before trusting them**: Fernanda Oi argues that teams should choose an AI deep-research tool based on evidence, not habit. The test uses the team's own question, with three deciding criteria: whether sources fall inside the requested date range, whether they are primary or academic rather than sites that merely cite research, and whether the final text draws connections across findings instead of listing them. The conclusion: ChatGPT is not automatically the best or only option. The preference is conditional; the same post notes that the tool that performed better still freezes at times and returns over-long texts. The argument sits within a wider priority: research efficiency means going deeper without sacrificing time or quality, since more information usually takes more time and deadlines are tight.
- **Discovery aims to find problems before development, with work scoped to each challenge rather than a fixed recipe**: Fernanda Oi argues that discovery work makes a product or service more likely to land by surfacing issues before development rather than after. The method applies UX research and UX design techniques to each engagement, matching a specific challenge to a solution quickly. The work is customised rather than run from a standard playbook. For buyers, the deliverable is assertiveness and knowledge about users, not a packaged sequence of steps.
- **Build the research function, then introduce it to the whole company**: Fernanda Oi treats making a research team visible as part of the work, not an afterthought. They present the team formally, show the organisation who is on it and name the people involved rather than claiming the achievement alone. They name João Maia as the person who created the team, credit the marketing team for the announcement format and thank individual team members by name. They also describe a long-standing difficulty accepting that career wins are the product of their own effort, a tension alongside their habit of deliberately sharing credit.

## Work to read

- [Discovery as a Venturus service, explained in a co-authored article](https://www.linkedin.com/posts/fernandaishimoto_discovery-como-transformar-ideias-em-resultados-activity-7295159371083190273-BP-F)
- [A worked head-to-head test of OpenAI and Gemini Deep Research](https://www.linkedin.com/posts/fernandaishimoto_ia-e-researchers-deep-research-openai-activity-7315162302603788288-58St)
- [Introducing a UX research team to an entire company](https://www.linkedin.com/posts/fernandaishimoto_nos-%C3%BAltimos-dias-apresentamos-a-equipe-de-activity-7100499943567626240-nqhB)
- [Role change: UX Research Manager at Venturus](https://www.linkedin.com/posts/fernandaishimoto_esse-ano-foi-muito-eu-pedi-desafios-mas-activity-7267253858341408769-ucWv)

## Brand relationships

- **Venturus** (employment)
- **OpenAI** (mention)
- **Google** (mention)

## Partnerships

Fernanda Oi's four LinkedIn posts cover UX research practice, product discovery services, team leadership, and AI-assisted research methods. They do not describe sponsored formats, rates, deliverables, or a commercial inquiry route. The commercial context they do establish is service-based: discovery work delivered through Venturus's design portfolio, customised to the client's product challenge rather than offered as a packaged media placement. Buyers should confirm directly with them or Venturus whether a partnership is available and what terms apply.

## Alternatives

- Rafael Soares: Pick Rafael Soares when the discovery question turns out to be a data-foundation question. His posts argue that AI and analytics work succeeds or fails on the quality and organisation of data — information spread across folders, servers, separate clouds, print, email and social channels — and that many companies lack the team or time to fix that before buying tools. If a B2B SaaS company cannot trust its own data enough to research or automate against it, that readiness conversation is closer to the real blocker than a research sprint. He also writes about the internal side of the same rollout: his shared CIO article describes explaining, educating and training employees who fear being replaced, which matters when a data or AI capability has to be adopted across teams.
- Diego Lorenzo Carvalho: Pick Diego Lorenzo Carvalho when the decision shifts from product discovery to commercial execution — specifically, how a manager finds the cause when a sales team misses quota. His posts make the same argument Fernanda Oi makes for research, applied to pipeline: the person closest to the problem should arrive with their own analysis and a named root cause before anyone proposes a fix. His longer post maps a change in the sales manager's role, from owning the number and checking deals one by one toward developing specific skills and conversion metrics with each seller, and having sellers bring their own read of the funnel numbers into pipeline reviews. That is a usable angle for a vendor selling sales-enablement or revenue-operations software to the same B2B SaaS buyer.
- Cynthia Schatzmann: Pick Cynthia Schatzmann when the brief changes to growth and retention in a relationship-driven market with a bilingual US audience. One post describes rebuilding a broker portfolio through daily, direct communication, using dispatcher experience to plan where drivers should be positioned for the best loads, and adding two partnerships on her own initiative — reporting roughly 241% growth in monthly load volume and 158% in gross freight over three months. A second post covers six months at a logistics company, entering an unfamiliar field and a second language, supporting 11 drivers, and reaching $200,000 in delivered loads, published in Portuguese and English. For a campaign that needs first-hand stories about customer success, retention and selling into US freight — rather than product discovery — she has the more directly relevant material.

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AI-assisted summary of public posts. Audience demographics are not available. Engagement appears only where we checked recent posts. Method: https://b2binfluencer.marketing/methodology/