Retail Data Management: Building a Roadmap for Success
By Viral Munshi

More retailers are paying attention to their retail data management strategy and realizing that data is a business currency. The right retail data management strategy provides a competitive edge by tailoring and aligning to the business context of the organization.

But the big question: How do you build the right retail data management strategy? How can you position your roadmap for success?

We share several ways leading retailers are building their data management strategies and the essential elements of a successful roadmap.  

The Effects of a Proper Data Management Roadmap in Ecommerce Customer Satisfaction

A proper data management strategy is vital for the success of any retailer, especially in the digital landscape. Improper data management can lead to data silos, decreased customer satisfaction, and reduced adaptability.

Placing the focus squarely on the customer is key to retailer success. How can you ever truly know your customer without the proper data collection, management, and analytics framework? To achieve this goal, we recommend starting with a proper data management roadmap. This will enable you to build brand value, customer loyalty, and open new opportunities.

The Essential Components of a Successful Retail Data Management Roadmap

There is no exact science behind building the perfect retail data management roadmap because every enterprise handles different data differently. Despite this, there are essential components that must be evaluated in retail data management, whether an already existing roadmap is in place or your organization is at the beginning of building a new one.

For a quick reference, we have outlined the five components of a successful retail data management roadmap in this chart and will delve into more detail below.

Data lifecycle procedures

This component involves identifying the various stages in the data lifecycle, from creation to archival. It's important to define how data will be collected, stored, managed, and ultimately retired.

Access controls

This component includes the policies and procedures for controlling who has access to what data and under what circumstances. Access controls help ensure that sensitive data is protected from unauthorized access.

Master data management

Master data management involves establishing processes and systems for maintaining accurate and consistent master data. This can include information on products, customers, suppliers, and other key entities.

Data cleaning

This component outlines procedures for identifying and correcting errors, inconsistencies, and duplicates in data. By maintaining clean data, retailers can ensure their analytics are accurate and meaningful.

Data analytics

Data analytics involves leveraging data to generate insights and inform decision-making. Analytics can help retailers identify trends, optimize operations, and improve the customer experience.

1. Identify Data Lifecycle Procedures

To build a retail data management roadmap, the data lifecycle must be defined and followed to improve the integrity of the data. The data lifecycle may differ per organization, although each lifecycle consists of similar elements presented in this figure:  

By identifying your enterprise’s data lifecycle and creating company-wide policies to maintain the lifecycle’s validity, you will prevent data loss, inaccurate data creation, and other ethical/legal issues that may occur with the use of inaccurate data.

2. Access Controls

Providing the correct access controls to personnel and users can become tricky the more systems and data are involved. While connected digital ecosystems can make this easier to integrate, it’s important to research access control models corresponding to the necessities of your company. Internal transparency and data governance, which are vital for the success of productivity and customer satisfaction, are enhanced when individuals can receive the right information easily.  

For an existing system that has already implemented access controls, the use of scripts and policy enforcements can help optimize the system. After all, employees may change positions, leave the company, or get promoted, leading to a change in their access.

For ecommerce, customers may also have access controls that allow them to review their own purchase history. Ensuring the proper access controls is crucial so customers cannot access another customer's data showing saved credit card information and purchase history.  

Assessing cross-department access controls helps prevent data silos from building throughout the enterprise. Data silos threaten transparency, data integrity, and collaboration.

3. Master Data Management

Master data is all necessary data for running business operations. The three main master data types are customer data, product data, and financial data.

When working with master data, it’s highly beneficial to create master records that communicate across internal and external data sources and applications for transparency and cohesiveness. This encourages data integrity and cross-channel communication. Master data management systems may also be beneficial in optimizing the management of master data.

4. Data Cleaning Policies

For a retail data management roadmap to be effective long term, the roadmap must include procedures for data cleaning. Data cleaning keeps data valid and prevents unforeseen issues from occurring that, in effect, reduce customer satisfaction.

When data cleaning an existing large system, it’s necessary to:

  • Handle missing data.
  • Remove duplicate data.
  • Maintain consistent formatting.
  • Remove unwanted outliers.

When you ensure cross-departmental teams unite data cleaning policies throughout the company and across systems, you can prevent issues in data integrity. Although centralizing your data with cloud-data warehouses can make the process of data cleaning easier for the entire organization.

5. Data Analytics

Data analytics is an essential component of the retail data management roadmap. Driving decision-making through various analytics can help support the overall goal of growth and prosperity in the competitive ecommerce industry.  

The three C’s of data quality are completeness, correctness, and clarity. Find a platform that fits your business's necessities and fully achieves the three C’s of data quality. Speaking to a specialty consultant can provide you with more awareness about your business's specific needs in terms of data management roadmaps and data analytics.

Manage Ecommerce Data With a Comprehensive Roadmap

Retail data management roadmaps have meticulous necessities that must be thoroughly combed through before implementing policies and new systems. It’s crucial to have a current understanding of your business's needs but also a thorough understanding of the needs your business will have for future growth. Specialty consultants can pick apart your business model in correspondence to technical architecture to optimize the most efficient roadmaps for success, all while providing suggestions and recommendations for future opportunities.

Getting Started

Concord USA is a consultancy that combines technology and industry depth with a get-it-done culture to enable resiliency, efficiency, and innovation. Whether you are trying to improve customer satisfaction, data strategies, security, or other technological issues, Concord can help.

Contact us today to learn more about how to build a customer experience strategy in retail, our Technology and Data Integration Services, and how we can help your business thrive.

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