Improving the quality of product content is paramount to achieving eCommerce priorities. Yet unlocking data quality is easier said than done.
Business Impacts: Inaccurate & Incomplete Data
Inaccurate data creates massive inefficiencies to the global commerce ecosystem. Without quality data at the beginning of a process, it is extremely time consuming and costly to manage later.
Hours spent annually manually managing product content for a company with 10,000 SKUs
Online grocery shoppers expect more production information
Reduction in returns from detailed, accurate product descriptions
Error in case height =
- 1,000 fewer cases per truckload
- 20 fewer cases per pallet
- 6 more trucks than necessary
Does This Sound Familiar?
Without guidelines to your data entry process, you risk errors in your data, redundant work, and items sitting idle that could be selling.
Challenges With This Approach
Here are just some of the risks that a missing data quality process can pose.
Why Is Having Good Data Quality Difficult?
Companies often struggle to stay updated with changing requirements and efficiently manage content across multiple channels and siloed data sources.
Creating Data Stewardship Through Continuous Improvement
Establishing a data culture and improving data quality is not a one-time project. It is an ongoing discipline that drives breakthrough results and critical competitive advantages. A simple approach involves the following steps:
- Set content requirements
- Add rules (format)
- Fit for purpose scoring model
- All content evaluated, scored
- Report – Volume, Trends
03. CONTINUOUS IMPROVEMENT
- Feedback and iteration
Data Quality Dimensions
There are many elements that determine data quality, and each can be prioritized differently by different organizations based on their goals.
Data Quality Principles
When the right data is delivered to the right place at the right time, your business wins. Your data should be:
1. Easy to create
- New item setup process
- GS1 compliant
- Single-source system of truth
3. Easy to share
- Company-wide understanding
- Easy-to-use systems (Not email!)
- Access to GS1 network
2. Easy to update
- Attribute accountability
- Clear lines of communication
- Documented rules to protect quality
Short-Term Wins: How to Create & Manage Quality Data
Here are some basic ways to take charge of your data quality and give your customers the best shopping experience online and in-store:
Product Information Management System: Accessible to all with workflows and protections consistent with governance.
Photographer: Hire a professional who understands GS1 Standards and your governance procedures.
Connections: The GS1 Network is important, but also consider other places that your data needs to go.
Data Quality Engine: Completeness, Readiness, Accuracy
Syndigo’s robust Data Quality Engine performs thousands of validations to ensure not only the completeness, but also the readiness and accuracy of your data.
Spell Check, Grammar
Real-Time Readiness Scores
Custom Audit Rules
Supplier Quality Management
Comprehensive Validation Rule-set
End-to-End Content Process for Smarter Growth
It is difficult to distribute data in multiple formats across retailers and internal departments. Managing it all is a drain on internal resources, and a challenge if using multiple solution providers. And if data quality is the driver, then it starts with a single source of truth.
A recent Forrester Consulting study, commissioned by Syndigo, revealed that
94% of participants
believe that having an end-to-end solution to create, manage, syndicate, enrich, and optimize product data would be valuable for retailer integration.
Syndigo is your single end-to-end solution for all content management and distribution, across GDSN, nutrition, core and enhanced content, with analytics & reporting…enabling our clients to provide a single source of truth to their consumers.
Our Content Experience Hub saves time and resources by integrating all product content management in a single place, away from existing process of managing multiple data sources manually and independently.