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Project Duration
5 months
Client Industry
 Saas and Tech
Target Markets
USA

Batch

Unified Analytics Platform for Data-Driven and Strategic Business Growth Decisions

Technology Stack

No items found.

Client Overview

Challenges in Modeling Subscription and Business Metrics

Batch is a customer engagement platform that helps brands deliver personalized mobile marketing campaigns through push notifications, in-app messaging, and analytics. By enabling real-time communication and behavioral targeting, Batch empowers businesses to improve user retention and drive mobile growth. The company supports marketers with scalable tools for campaign automation, audience segmentation, and actionable insights.

Solutions Delivered

Unified backend architecture with

centralized data pipelines

Harmonized datasets across

finance, marketing, operations

Real-time dashboards with clear,

intuitive visualizations

Self-service analytics enabled

through Looker Studio

Team Composition

Data Engineer

SQL Developer / Data Analyst

Looker Studio Developer / BI Analyst

Data Governance & Quality Specialist

Engagement Type

Part Time Contract

Key Challenges

Challenges in Achieving Timely and Unified Business Insights

Limited Insights

Decision-making was hindered by manual reporting and delayed access to insights


Fragmented Analysis

Inconsistent and disconnected datasets across business units


Low Reporting Efficiency

High time investment required for basic analytics


Strategic Roadmap

To support faster and more accurate decision-making, we needed to unify fragmented datasets from finance, marketing, and operations into a single, trusted environment. Automating manual reporting workflows was key to increasing efficiency and reducing delays. We prioritized selecting a scalable platform that could support real-time data access and flexible dashboarding. The goal was to deliver intuitive, stakeholder-specific analytics while ensuring data quality, governance, and long-term maintainability.

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To overcome fragmented reporting and enable data-driven decision-making, we consolidated multiple data sources—including finance, marketing, and operations—into a unified BigQuery warehouse. SQL-based transformations were used to harmonize and cleanse data across business units, ensuring consistent, high-quality inputs.

Execution Approach

Centralized Architecture for Scalable, Cross-Functional Analytics

To overcome fragmented reporting and enable data-driven decision-making, we consolidated multiple data sources—including finance, marketing, and operations—into a unified BigQuery warehouse. SQL-based transformations were used to harmonize and cleanse data across business units, ensuring consistent, high-quality inputs.
Automated dashboards were built in Looker Studio to serve real-time insights to various stakeholders, from executives to analysts.
Additionally, we developed modular analytics layers to support both exploratory data analysis and routine operational reporting, creating a flexible foundation that scales with the business and empowers self-service access without over-reliance on engineering teams.

BUSINESS IMPACT

Accelerated Decision-Making
Reduced Reporting Workload
Increased Data Trust
Improved Cross-Functional Collaboration

30+

hours per week eliminated from manual reporting via automation.

35

boost in operational efficiency through streamlined data access.

40%

faster decision-making enabled by real-time key metric visibility.