Client Success Story

How SunTec India became a Human-in-the-Loop Data Engine behind a Leading Market Intelligence Platform

99%

Data Accuracy Achieved

40%

Reporting Efficiency Improved Accuracy

700K+

Records Processed Monthly Accuracy

Service

  • Data Processing
  • Data Management

Platform

  • Client’s Proprietary Platform
THE CLIENT

A Leading Market Research & Competitive Intelligence Platform

The client operates a subscription-based competitive marketing intelligence platform serving brands across the United States and Canada. The platform automates large-scale marketing data collection and delivers timely insights on competitors' campaigns, products, pricing, and promotional strategies. By consolidating multi-channel marketing activity into a single searchable system, it empowers brands to respond faster, benchmark pricing effectively, and maintain their competitive edge.

PROJECT REQUIREMENTS

End-to-End Ad Campaign Data Processing across 11 Industries and 6+ Media Channels

The client relied on a network of incentivized partners who continuously collected industry-wide marketing data from diverse sources and submitted it to the client's portal. They needed our data processing services to manage that data. The scope covered the following campaign types:

  • Email and Direct Mail campaigns
  • Print Media advertisements
  • Social Media and Mobile Digital campaigns
  • Energy Pricing and Custom Monitoring
  • Retail campaigns
  • Telecom campaigns
  • Banking, Credit Card, Mortgage, and Loans campaigns
  • Automotive campaigns
  • Consumer services campaigns
  • HR/Payroll/HCM/PEO campaigns
  • Insurance campaigns
  • Investments/Annuities campaigns
  • Real Estate campaigns
  • Shipping campaigns
  • Technology campaigns
  • Travel & leisure campaigns

The client required all campaign data to be de-duplicated, cleansed, standardized, and classified. We had to deliver analytics-ready datasets that fed directly into competitive marketing intelligence reports for their subscribers.

A TWO-DECADE-LONG PARTNERSHIP

From a Single Service in 2006 to 85% of the Client's Data Operations Today

When this project began, the scope was limited to data standardization. Over the years, impressed with the quality of service delivered, the client expanded the engagement to cover end-to-end data processing, new channels, new industries, visual annotation, and quality assurance. Today, SunTec India manages approximately 85% of the client's campaign data processing workload with a dedicated marketing data management team of over 200 resources.

PROJECT CHALLENGES

High Volume, Inconsistent Data Structures, and Duplicate Records across Channels

The client's data collection model was designed for coverage, not consistency. That trade-off created a set of recurring operational challenges that we needed to solve at scale.

  • Massive Data Volume with Daily Deadlines

    Processing over 700,000 campaign records every month across six or more media channels meant that even small inefficiencies cascaded into significant backlogs. The team had to maintain consistent daily throughput without compromising accuracy.
  • Inconsistent Data Structures across Industries

    Campaign data arrived from multiple partners in varying formats — emails, scanned print ads, social media screenshots, PDF mailers, and web captures. Each industry had its own data hierarchy, terminology, and classification logic, making data standardization a persistent challenge.
  • Manual Processing Bottlenecks

    A significant portion of campaign data — particularly from print media, direct mail, and energy pricing — could not be processed through automation alone. Handwritten annotations, low-resolution scans, and non-standard layouts required manual intervention, which slowed turnaround.
  • Duplicate Campaign Records

    Multiple partners often submitted the same campaign through different channels or at different times. Without a rigorous deduplication process, the same campaign could appear several times in the client's platform, skewing competitive analysis for the end users.
OUR SOLUTION

Structured Ad Campaign Data Processing through a Unified Workflow

Rather than treating each campaign channel as a separate process, we built a unified data processing framework that applied consistent standards across all media types while allowing for channel-specific handling where required. Across all channels combined, the team processed over 700,000 campaign records every month. The solution covered the full data lifecycle: capture, cleansing, deduplication, classification, structuring, quality assurance, and delivery.

1

Email & Direct Mail Data Processing

We processed approximately 500K+ email and direct mail campaigns per month through a single standardized workflow. Each campaign record went through PII redaction (removal of personally identifiable information), duplicate elimination using OCR-based validation, accurate campaign date capture, and structured extraction of key fields — company name, product, offer details, target audience, and industry sector.

2

Print Media Campaign Research & Processing

For print media, we processed over 11,000 advertisements monthly. Unlike email or social media campaigns — which were submitted directly by the client's partner network — print advertisements had to be actively sourced. Our web research team identified and collected relevant ads from digital editions of newspapers, online news publications, and brand and competitor websites. Each sourced advertisement was then structured into a searchable, mapped campaign record following the same classification and formatting standards applied across all other channels.

3

Social Media & Digital Campaign Monitoring

Our team processed over 37,000 digital campaigns per month, captured from social media platforms, third-party websites, and online video channels. This included sponsored ads, display banners, and video promotions from defined brand and competitor accounts. Each captured campaign was reviewed, classified by industry and campaign type, and structured, detailing what was being promoted, through which format and channel, and the likely target audience based on offer messaging and product category.

4

Energy Pricing & Custom Monitoring

We captured over 62,500 data points every month related to energy pricing and promotional offers. Each record was analyzed to extract product details, pricing tiers, offer validity, company information, and target audience. We also validated copies and variants to ensure accurate campaign tracking, converting raw data into sector-specific competitive reports.

5

Telecom, Retail & Financial Services Campaign Processing

Campaigns from telecom, retail, and banking/financial services sectors were processed by identifying the primary service or product, promotional offer, bundle details, response channels, and customer segment. For banking and credit card campaigns, our team captured mortgage rates, loan terms, and card benefits across all media channels. For retail, we structured product promotions, brand communication, and seasonal offer messaging. Each sector's output followed a standardized format while preserving industry-specific nuances.

6

Visual Annotation for Retail Campaigns

We performed product-level visual labeling of retail marketing emails/PDFs to identify featured products, brand placement, and promotional elements. This visual annotation layer enabled the client's subscribers to measure promotional value, compare brand visibility across competitors, and evaluate merchandising effectiveness — insights that text-based data processing alone could not deliver.

7

Data Standardization & Intelligent Classification

Across all channels, we applied a consistent data standardization framework that included content conversion into structured formats, sensitive data removal, OCR-based duplicate validation, industry and sector mapping, audience segmentation, campaign type categorization, and multi-level quality checks. Every record was classified by industry, product, offer type, audience, and campaign channel, creating a unified taxonomy that made cross-channel and cross-industry analysis possible for the client's platform.

8

Quality Control Framework

We implemented a multi-level quality assurance process that included validation checks at the operator and QA lead levels, accurate campaign dating and version control, and consistent data entry standards across the team. Error rates were tracked weekly, and persistent issues were addressed through retraining and template refinement. Regular calibration sessions with the client ensured that evolving classification rules and new campaign types were absorbed into the QC process without disrupting delivery timelines.

BEHIND OUR APPROACH

Why Human Judgment Remained Central to This Data Processing Engagement

Campaign data processing at this scale was fundamentally a domain knowledge and human judgment challenge — not an automation problem.

  • The input data was too inconsistent for reliable automated classification. A scanned print ad from an energy provider, a social media screenshot of a telecom bundle offer, and a PDF mailer for a credit card promotion each demanded different interpretive logic, even when the final output format was identical.
  • Classification decisions compounded this complexity. Determining whether a campaign was a product launch or a seasonal promotion, whether two similar records were duplicates or intentional creative variants, or which audience segment a banking offer targeted — these judgments depended on context that shifted by industry, by channel, and by season. The operators making these calls needed to understand not just the data in front of them, but the competitive landscape behind it.
  • The cost of error was equally significant. The client's subscribers — brands paying for competitive marketing intelligence — relied on this data to inform strategic decisions. A misclassified campaign or undetected duplicate eroded the platform's credibility with its paying users.

For these reasons, we built a human-in-the-loop data processing framework, supported by OCR and automated data validation tools where they added efficiency, but driven at every critical decision point by trained operators with deep domain expertise.

PROJECT OUTCOMES

We enabled the client to standardize multi-channel marketing data, reduce processing backlogs, and scale delivery across new industries — all while maintaining strong accuracy and turnaround time.

Achieved 99% Data Accuracy Improved from 70% over the course of the engagement through continuous process calibration, multi-level quality checks, and operator retraining cycles.

Improved Reporting Efficiency by 40% Enabling the client to deliver faster competitive insights to subscribers by eliminating processing bottlenecks through a single standardized data pipeline.

85% Data Processing Workload Managed Processing 700,000 records per month with a dedicated team of 200+ resources.

3x Surge Capacity without Additional Onboarding Handling seasonal and industry-driven demand spikes — particularly during peak campaign periods in banking, retail, and energy — with cross-trained operators.

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