As a digital marketing agency, we had the privilege of working with an international company renowned for its engineering and manufacturing of a wide range of solutions, from aerospace technologies to industrial equipment. We carried out an in-depth audit of their marketing-related data ecosystem.
Improve marketing investments
Integrate new data tools
The company also needed advice and support to:
- Validate consistency with its own infrastructure
- Validate the need to integrate new tools in relation to existing systems
To ensure the success of this company's marketing initiatives, we have established several key objectives for this data marketing audit:
Mapping
Data sources: Identify and map all data sources used. Confirm data interconnectivity.
Processes: Define and document data management processes.
Tools: Identify and assess the data management tools in place, mapping them by department.
Data unification
Centralize all data in a single location like a data lake and a CDP to facilitate access and analysis.
Data governance
Implement data governance policies to guarantee compliance and data quality.
Technology recommendations
Propose recommendations on the technological investments needed to improve data management.
Action plan
Develop an action plan to maximize the use of current and future data.
By providing a strategic vision, the audit aims to equip the business with an in-depth understanding of its marketing landscape, enabling it to make informed decisions about allocating resources and expanding investment into new channels.
The main challenges of this audit related to:
Data quality
Ensuring the quality of the data collected and used and exploiting it strategically.
Poor Quality Problems: Inaccurate, out-of-date, and unstructured data.
Qualified Data Characteristics: Accurate, up-to-date, well-organised data
Regulatory compliance
Ensuring that all practices comply with data protection regulations.
Interdepartmental collaboration
Involve different teams and departments in a joint data management project.
Multiple data sources and tools
Managing the diversity and multiplicity of data sources and tools used.
By tackling the challenges identified, the data audit was an essential tool in guiding the company towards sustainable growth and increased efficiency in its marketing activities.
- Diagnosis and Workshops
- Technical and functional data audit: Thorough examination of the functionality and performance of data flows Assessment of systems alignment with business requirements and identification of functional gaps.
- Process
- Strategy
Assessment of needs and constraints:
Reflection and in-depth analysis workshops with stakeholders from the various markets. Surveys to understand the specific needs and constraints of the customer's data environment.
Maturity diagnosis:
In-depth assessment of the data infrastructure level of maturity Identification of strengths and areas for improvement to optimize data usage.
Review of tools and data architecture:
Analysis of relevant software and hardware tools used. Optimizations’ recommendations to improve the efficiency and performance of the data infrastructure (Software optimisation, tool upgrades, infrastructure improvements, network component upgrades, database revamps...).
Data lifecycle and governance:
Detailed analysis of the data lifecycle, from acquisition to end use. Implementation of rigorous measures to guarantee data quality, security and compliance.
Proactive data governance:
Clearly defined data governance responsibilities and processes to minimize risk and build trust.
Data success and strategic vision:
Development of a robust strategy to exploit the potential of data, aligned with business objectives. Optimization of data integration and management, with recommendations for efficient pipelines and resolution of future data marketing challenges.
Strategic action plan:
Development of a detailed action plan based on previous steps findings. A clear roadmap to guide the business towards optimal use of data resources and maximize the impact of marketing initiatives. By following this methodology, we were able to ensure a holistic approach to the data audit, enabling the company to take full advantage of its data and optimize its marketing initiatives.
Our Tools
Data Quality Report
- A detailed report on the current state of data quality, including accuracy, completeness and consistency.
- This has enabled the company to identify gaps and errors in the data and implement corrective actions to improve the reliability and accuracy of the information.
- This has resulted in an increase in the data accuracy rate, with a reduction in data errors from 20% to 5% following the implementation of corrections.
Developing a Data Governance Framework
- A comprehensive framework for data governance, defining the roles, responsibilities, processes and policies for managing and protecting the company's data.
- This has ensured ongoing regulatory compliance, reduces the risks associated with data management and improves data quality through standardized governance practices.
- Following this, the company achieved 100% compliance with current regulations, and also a 35% reduction in data security incidents compared with year N-1.
Efficient Data Architecture
- An optimized design of the data architecture, with recommendations for the technical infrastructure and data management systems.
- This optimization of the architecture has not only improved the efficiency of data management systems by 30% and reduced data management costs by 12%, but also facilitated the future integration of technologies.
Recommendations on the Data Strategy
- Strategic recommendations on how to exploit and maximize the value of the company's data, resulting in an increase of 15% of the ROI.
- A real guide to aligning data management with business objectives, enabling more strategic and effective use of data to support growth and innovation.
Recommendations on Tools
- Specific suggestions on the technology tools to adopt, including the Customer Data Platform (CDP) and the Data Lake.
- This enables the company to implement solutions to unify data from various sources, providing a unified and consolidated view of customer and operational data.
- The company has progressed to the point where it is now able to integrate 75% of new data sources into existing systems within 6 months.
Results
