Ohakam Bruno
Marketing Operations & Automation Specialist
New to Contra
Ohakam is ready for their next project!
A documented Standard Operating Procedure and task-tracking system for managing content production and client-facing operational work — built to be handed off to a VA or team member, not just used personally.
The problem: content production and client tasks often live in someone's head rather than a repeatable process, making delegation or handoff difficult.
The work: a 6-step SOP covering content planning, pre-production, editing, hashtag/caption research, publishing, and post-publish monitoring — documented with real tool-specific detail (e.g. editor choice based on device availability) rather than generic steps. Paired with a task delegation tracker covering priority, status, due dates, and notes across recurring content and client-facing tasks.
Note: built during ALX Virtual Assistance certification training and personal practice — presented as sample deliverables demonstrating documentation and operational structure, not drawn from confidential client records.
Result: a reusable framework showing how I'd structure and hand off operational work, not just complete it myself. #freelancerlife
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A content analytics dashboard built in Looker Studio, connected to Google Sheets, tracking views, engagement, and content-pillar performance at a glance for a short-form video brand.
The problem: raw platform analytics (TikTok, etc.) don't show performance broken down by content category — making it hard to see which content pillars are actually working without manually cross-referencing every post.
The build: at-a-glance scorecards for total views, total followers gained, and total engagement (likes + comments + shares), plus a breakdown of views by individual video and by content pillar (Rare Animals / Family Trees / Ancient History) — surfacing which content categories perform best.
Note: built using sample/demo data for demonstration purposes, not live account data. The dashboard structure, connections, and logic are fully functional and could be connected to real data at any time.
Result: a working, reusable reporting template — the kind of dashboard a content or marketing team would use to make decisions on what to produce more of.
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A repeatable AI-assisted scriptwriting system built for AnimalVaultFactz, a documentary-style content brand covering rare animals, species family trees, and animals in ancient history.
The problem: producing consistent, well-researched scripts fast enough to sustain regular posting, without sacrificing accuracy or narrative quality.
The system: every script starts with real research on the topic, then a structured AI prompt (built around the brand's specific "Vault File" format) generates a first-pass draft. Every AI output is then personally reviewed and edited for tone, pacing, and factual accuracy before it's considered ready to film — AI accelerates the draft, but final judgment stays human.
Result: a scalable content pipeline that's produced multiple ready-to-film scripts using this exact process, with the flexibility to speed up or slow down
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A real before/after case study applying Answer Engine Optimization (AEO) principles to short-form video content for AnimalVaultFactz.
The problem: standard social captions are written for scroll-stopping engagement, not for AI answer engines — they bury the actual answer under hooks and flourish, giving AI systems nothing clean to extract or cite.
The work: restructured a real video caption from narrative-first to answer-first — leading with a direct, factual claim in the first 40 words, supported by accurate facts, instead of vague hooks. Also built and validated a working FAQPage schema (JSON-LD) implementation, tested through Google's Rich Results Test.
Note: Google restricted classic FAQ rich-result display to authoritative gov/health sites as of August 2023 — this work focuses on genuine machine-readability and AI-citation readiness (ChatGPT, Perplexity, AI Overviews), not guaranteed search snippet display.
Also included: a 6-step AEO audit framework (establish baseline, prioritize content, evaluate structure, check freshness, categorize, take action) and a measurement approach for tracking AI referral traffic and citation frequency — since AEO doesn't rely on traditional click-through metrics.
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A live, working lead-capture automation connecting a web form, Zoho CRM, and automated email follow-up — built end-to-end, not just configured from a template.
The problem: manual lead entry is slow and inconsistent, and most "automation" demos are theoretical rather than tested.
The build: a form submission triggers Zapier, which creates a new Lead in Zoho CRM with the submitted details, then automatically sends an acknowledgment email to the lead — zero manual steps between submission and first response.
One real obstacle solved along the way: Zoho CRM's free tier doesn't support native workflow automation, so the entire trigger-to-action flow was rebuilt through Zapier instead, including debugging failed field mappings and testing until the automation ran cleanly end-to-end.
Result: a fully published, currently active automation — form to CRM lead to email, working in real time.
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