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Badge Blink SEO

Comprehensive SEO Reporting and Analytics Platform for Digital Marketing Agency Clients

Project Duration

4 months

Client Industry

Telecommunications

Target Markets

United States

Technology Stack

Client Overview

We Understand Our Clients Best to Provide them the Best Solutions

Blink SEO is a digital marketing agency offering specialized SEO services to clients across various industries. They manage multiple campaigns and datasets per client and needed a unified analytics infrastructure. Their focus is on delivering actionable SEO insights by combining crawling, keyword, and backlink data through a centralized platform.

Solutions Delivered

Unified SEO reporting and insights Automated daily data ingestion pipelines

Custom Looker dashboards for clients Scalable Google Cloud-based infrastructure

Team Composition

Data Engineer

Cloud Architect

BI Developer

Project Manager

Engagement Type

Contractual hiring

Key Challenges

Key Challenges

Eliminating Data Gaps, Inefficient Reporting, and Weak Customer Understanding

Disconnected

Data Consolidation

Fragmented data across multiple clients and third-party tools like ScreamingFrog, DataForSEO

Inefficient Reporting

Operational Complexity

High manual effort in maintaining reports and handling campaign-level data at scale

Limited Intelligence

Scalability

No centralized warehouse for unified processing and client-level reporting

Strategic Roadmap

To build a scalable and efficient data foundation, we must first consolidate fragmented client and tool data into a unified schema. Automating extraction from APIs like ScreamingFrog and DataForSEO is key. Aligning dashboards to client-prioritized KPIs—such as keywords, SERP rankings, and backlinks—ensures relevance as the architecture scales with growth.

● How do we consolidate data from all clients and tools into a unified schema?

● How can we automate data extraction from ScreamingFrog and DataForSEO APIs?

● What dashboards and KPIs do clients care about the most (keywords, SERP, backlinks)?

● Can this architecture scale as the agency adds more clients and tools?

Execution Approach

Modular, Scalable Infrastructure for SEO Data Pipelines

To support multi-client SEO operations at scale, we built modular ETL pipelines using Python-based Cloud Functions for efficient and automated data processing. For high-volume ingestion tasks, we deployed scalable virtual machines on Compute Engine to handle API-based data collection from tools like ScreamingFrog and DataForSEO.

All processed data is stored in BigQuery, creating a centralized warehouse that supports seamless querying and cross-client analysis.

On top of this foundation, we designed customized Looker Studio dashboards tailored to each client’s SEO KPIs—such as keyword rankings, backlink profiles, and SERP visibility—ensuring accessible, real-time insights that align with marketing goals and performance tracking.

Execution Diagram
Business Impact

BUSINESS IMPACT

Timely and Unified Reporting

Operational Efficiency Gains

Enhanced Data Accuracy

Stronger Client Relationships

Business Impact Illustration

40%

increase in reporting efficiency across all clients

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35%

boost in data accuracy through automation

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50%

faster dashboard delivery using modular templates

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20%

rise in client satisfaction from real-time insights

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