FEATURED BUILD · AI MARKETING INTELLIGENCE

Turning fragmented marketing data into an intelligent decision workspace.

An owned AI marketing intelligence and dashboard-builder product connecting live performance data, configurable analysis, AI insight and campaign quality control.

01PUBLIC PRODUCT

Launch live product

ProductAI intelligence & dashboard builder

ModulesAnalytics, AI insight and campaign QC

RoleProduct strategy, system design and build

StatusPublic product · evolving

Interface dataDemonstration data

01 · The challenge

Marketing teams often move between disconnected platform reports, static dashboards and manual quality-control checklists. That fragmentation slows diagnosis, makes context difficult to share and separates performance analysis from campaign operating standards.

02 · My diagnosis

The opportunity was not another reporting dashboard. It was one configurable decision workspace that could connect live marketing data, reusable analysis components, AI-assisted interpretation and campaign QC without hiding the underlying evidence.

The work began by reframing what the system actually needed to accomplish—not by starting with a channel feature or a preselected tactic.

Evidence views

Four complete views of one marketing intelligence product.

Complete Omnivision Pro homepage with three product modules — **Product Home**One entry point connects Meta quality control, Google quality control and the live dashboard workspace.

Complete Omnivision Pro Meta Dashboard with AI insight, scorecards and charts — **Dashboard Builder**AI insight, executive scorecards and performance trends are assembled in one configurable decision workspace.

Complete Omnivision Pro Meta campaign quality-control workspace — **Meta Intelligence**Campaign, ad-set, creative, audience and tracking evidence is reviewed through a dedicated Meta quality-control workspace.

Complete Omnivision Pro Google Ads quality-control workspace — **Google Intelligence**Search, Performance Max and Demand Gen structures are reviewed with bidding, geography and asset context.

Current capabilities

What the product can do today.

Live data context

Select the advertising account and analysis period that the dashboard should explain.

Configurable views

Compose scorecards, time series, area, bar, combination, donut, creative and data-grid views.

AI insight

Place AI-generated interpretation beside the performance evidence and funnel behaviour it references.

Metrics & dimensions

Choose dimensions, metric overrides and visual treatments for the question at hand.

Filters & export

Apply campaign filters, sorting and date controls, then export the configured view.

Campaign QC

Inspect Meta and Google Ads campaign structures through a dedicated quality-control module.

03 · The system I designed

Connect

Select the live advertising data source and analysis period.

Compose

Build views with scorecards, charts, grids, dimensions, metrics and filters.

Interpret

Place AI-generated insight beside the performance evidence it explains.

Assure

Use the campaign QC module to inspect Meta and Google Ads structures.

04 · Decisions & trade-offs

The judgement behind the work.

Keep the dashboard configurable so one product can support executive, campaign and diagnostic views.
Position AI insight beside visible data rather than presenting opaque recommendations without context.
Retain campaign QC as a dedicated module because quality assurance and performance interpretation have different operating jobs.

05 · Current product scope

configurable view types

advertising-network QC modules

shared intelligence workspace

06 · Leadership reflection

“The central product decision was to connect analysis and operating quality without collapsing them into one generic workflow. The system has to help people see the evidence, configure the question and apply judgement—while remaining explicit about what is live today and what belongs to the roadmap.”