ShareView — Retail Analytics SaaS

Challenge

A retail/CSS business sitting on top of huge volumes of Google Ads performance data — products, categories, keywords, auctions — couldn't easily turn it into something its retailers and sales team could act on. The raw data was vast and technical; clients needed clear, trustworthy dashboards, the sales team needed performance and competitive views, and admins needed control over what got published. Doing this manually didn't scale, and the data needed to be both collected reliably and presented in a polished, multi-tenant product.

Solution

We delivered ShareView for Shareight as a two-tier analytics platform. At the base, a Go data-collection service connects to the Google Ads API and continuously aggregates campaign performance — at product, category and keyword level — into a structured database. On top of that, ShareView is a multi-tenant Next.js SaaS that transforms this raw data into client-ready insight: it builds monthly performance snapshots, derives metrics, and benchmarks retailers against their market peers. The platform offers role-based portals for clients, the sales team and admins, with AI assistance (Google Gemini) used to enrich the analysis. It also includes a validation-rate management module for affiliate-network compliance. The whole platform runs on Google Cloud Run.

Project Results

Raw, technical ad data is now collected automatically and surfaced as clean, role-appropriate dashboards for clients, sales and admins. The monthly snapshots give consistent performance views with peer benchmarking, and AI assistance enriches the analysis clients receive. The platform also covers affiliate-network validation-rate management, extending it into compliance.

Features and Benefits

• Automated Data Collection: A Go service syncs Google Ads performance into a structured store every hour.
• Snapshot Analytics Pipeline: Monthly snapshots, classification and metrics turn raw data into consistent insight.
• Multi-Tenant Portals: Separate, role-based views for clients, the sales team and admins.
• Peer Benchmarking: Retailers are compared against market cohorts for competitive context.
• AI-Assisted Insights: Gemini enriches the analysis and insights clients receive.
• Validation-Rate Management: Built-in compliance tooling for affiliate-network validation rates.

Technologies Used

• Go: Data-collection service syncing Google Ads metrics into the database.
• Google Ads API: Source of product, category, keyword and auction performance data.
• Next.js & React: Multi-tenant SaaS frontend and dashboards.
• PostgreSQL: Snapshots, metrics, benchmarks and platform state.
• Google Gemini: AI market-profile classification and insight generation.
• Google Cloud Run: Scalable, containerised hosting and deployment.

Development Process

We treated the system as two tiers from the outset: a reliable data-collection service and a presentation/analytics platform on top of it. The Go collector was built to sync Google Ads performance into structured data, giving the rest of the system clean, consistent source data. On top, we built the analytics layer — performance snapshots, derived metrics and peer benchmarking — feeding multi-tenant, role-based portals. We integrated Gemini to enrich the analysis, and added validation-rate compliance tooling, all deployed on Google Cloud Run.