Boosting Sales by 35% with Dynamic Targeting: How Quantzig Helped a US-Based Fashion Retailer Optimize Customer Engagement
Case Studies |

Boosting Sales by 35% with Dynamic Targeting: How Quantzig Helped a US-Based Fashion Retailer Optimize Customer Engagement

Author: Associate Vice President Read Time | 3 minutes

In today's data-centric business environment, organizations are increasingly seeking ways to harness their data assets for strategic advantage. This case study explores how Quantzig assisted a leading European Fast-Moving Consumer Goods (FMCG) company in standardizing their data, streamlining delivery mechanisms, and enhancing data usage tracking through effective data monetization strategies. ​

Key Points

  • 60% reduction in data redundancy : Improved operational efficiency
  • 28% decrease in Total Cost of Ownership (TCO) : Lower infrastructure costs
  • Secured additional budgets for data investments : Strengthened data-driven decision-making
  • Enabled expansion through improved data management : Enhanced business scalability

Problem Statement

The client, a prominent European FMCG company with a workforce of 20,000 employees, faced significant challenges in managing and utilizing their vast data resources.

  • Data scattered across multiple sources : Inefficiencies in data access and management
  • Labor-intensive data governance : Strain on manpower and increased costs
  • Difficulty in determining benchmark costs & ROI : Hindered financial planning & resource allocation
  • Lack of standardized KPIs : Limited ability to derive strategic insights

The client sought a solution to consolidate their data, establish efficient governance, and standardize KPIs to extract actionable business insights.

Objectives

To drive value from data monetization, the client aimed to establish a standardized data framework that would enhance efficiency, improve decision-making, and reduce operational costs. Quantzig’s solution focused on aligning data strategies with business goals, ensuring seamless data integration and governance.

  • Identify profit-generating KPIs : Measure tangible and intangible benefits from data
  • Establish standardized data processing : Improve efficiency through automation
  • Conduct a data inventory assessment : Identify gaps and redundancy in data usage
  • Develop a custom data management platform : Streamline processes and eliminate duplication

Solution Implemented

Quantzig adopted a systematic approach to address the client's challenges:

  • Identification of Key KPIs: Pinpointed profit-generating KPIs and assessed business benefits.
  • Standardization and Automation: Streamlined data processing through automation.
  • Data Inventory Assessment: Identified redundancy, consumption gaps, and duplication.
  • Custom Platform Development: Leveraged Microsoft Power Platforms and Synapse to centralize data and enhance efficiency.

Technology Used

  • Microsoft Power Platforms : Data visualization and automation
  • Microsoft Synapse : Advanced data integration and analysis
  • Business intelligence tools : Data mining and performance tracking
  • Data automation tools : Workflow optimization and governance

Results & Impact

The implementation of Quantzig’s solutions led to measurable improvements in the client’s data management and operational efficiency.

Metric Before After Improvement
Data Redundancy High duplication across systems Standardized and consolidated data 60% reduction in redundancy
Total Cost of Ownership (TCO) Elevated infrastructure and maintenance costs Optimized resource allocation and automation 28% decrease in TCO
Data Accessibility Fragmented and inconsistent data sources Centralized and structured data repository Improved data retrieval speed
KPI Standardization Lack of unified performance metrics Established consistent benchmarks Enhanced decision-making accuracy

Qualitative Impact

  • Quantifiable business value : Increased stakeholder confidence
  • Additional budget secured for data projects : Enhanced long-term investments
  • Improved data governance : Strengthened compliance and security
  • Standardized KPIs for better decision-making : More accurate business insights

How Quantzig Can Help?

With over 20 years of expertise in data analytics, Quantzig specializes in transforming data into valuable business assets. Our solutions help enterprises standardize data processes, enhance governance, and unlock new revenue streams through effective data monetization strategies.

Capabilities

  1. Proven track record in enterprise data solutions
  2. Custom data management platforms and tailored solutions for unique business needs
  3. Cutting-edge automation and AI-driven insights

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Frequently Asked Questions

It is a plan for leveraging data assets to generate revenue or value. It involves using data to create new products, improve services, inform business decisions, and can also include selling data to third parties.

Identifying valuable data assets involves analyzing your existing data to determine what information can provide unique insights, drive decision-making, or create new revenue streams. Look for data that is unique to your business, widely applicable, and in demand.

Common challenges include ensuring data quality and governance, aligning the strategy with business objectives, managing privacy concerns and regulatory compliance, and integrating data across disparate systems.

It includes direct monetization, such as selling data or insights, and indirect monetization, such as using data to improve business processes, enhance customer experiences, or develop new products.

Ensuring compliance involves staying updated with privacy laws and regulations, implementing robust data governance frameworks, anonymizing personal data where necessary, and being transparent with customers about data usage.

Successful examples include retailers using customer data to personalize marketing campaigns, companies selling aggregated market data to third parties' users, and businesses using data insights to develop new product lines or services.

Dynamic targeting is a data-driven approach that customizes content, ads, or messages based on user behavior, demographics, and real-time insights, ensuring more relevant and personalized engagement.

Dynamic ad targeting leverages AI and data analytics to deliver personalized ads to specific audience segments based on browsing history, preferences, and real-time interactions, maximizing engagement and conversion rates.

Dynamic targeting in pharma uses advanced analytics to segment healthcare professionals, patients, and stakeholders, delivering personalized content and ads based on prescribing behaviors, treatment needs, and market trends for improved engagement.

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