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Product Data Management System
Overview
One of our customers, a European-based online retailer, required a reliable means to keep track of all of its product information in a central system.
Their current usage of Excel spreadsheets to store product information for each distinct KPI, resulted in enormous numbers of sheets with countless rows of data.
This kind of system was found to be both time-consuming and inefficient making it impossible to maintain uniformity across the board.
Duration
6 months
My Role
UX Researcher and Designer
The design team designated me as a single resource for this project, and I was responsible for the following duties:
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Interacted with the stakeholders to understand the scope of the project.
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Suggested that user flows and other research techniques be included before the design process could begin.
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Presented the ongoing work to the clients single-handedly whenever they requested a walkthrough.
Business Type
B2B
B2B (business-to-business), a type of electronic commerce (e-commerce), is the exchange of products, services or information between businesses, rather than between businesses and consumers (B2C).
The Process
We followed a User Centric approach with a series of cycles that concentrated on placing people at the centre of product planning and development. Customer satisfaction has become a priority, and each decision regarding a plan was considered in light of whether it adds value for the customers. We were given the opportunity to include an enthusiastic impact in our product thanks to the user-focused design.
UX Strategy
Qualitative Research: User Interviews
Personal interviews with the stakeholders helped in laying out the objectives for a Product data management system. who have experience with data management. This provided tons of insight into how data management systems are fabricated and how they bring value to organisations
The users who were interviewed were the people who have experience with data management and were under the profiles of:
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Database Managers​
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Product Merchandisers
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Product Information Analysts
This provided tons of insight into how data management systems are fabricated and how they bring value to organizations.
Major pain points discovered upon interviewing
"Delay in accessing important data"
“Redundant data in the database, which reduces the efficiency of the database’s storage space”
“Have to write programs in order to search a database or data set in the existing file management database”
“Data sharing with other users and across the entire organization”
“Need support from individuals in case of missing information from the files in the database”
“No recovery and backup processes to protect the data from outside access”
Surveys
Information administrators and data managers who are answerable for keeping up with the data set for any web based business site clarified that the reports and accounting pages they have are non practical with regards to applying a satisfactory change to the entire structure.
This provided us with an unmistakable understanding of what we should handle first with our item. Moreover, the administrators constantly struggle with creating data models from scratch containing significant properties, LOVs (List of Values), and hierarchies.
Brainstorm
The objective of exploration was to observe the fundamental trouble spots and comprehend the method involved with utilizing a product data management system.
Numerous organizations actually keep all their data base put away in spreadsheets which stores an immense piece of data at the same time
Building data models containing relevant attributes in the hierarchial structure hasn't been imaginable in a similar framework
Estimating key performance indicators (KPIs) that companies use to monitor performance metrics should be possible in the very product data system
Can we apply exact and reliable metadata to information to further develop information quality and findability which extracts key items from content for predictive analytics
Product Initiatives
This product comes in for managing data for product or retailer's data model structure at an enterprise level.
1. Analytics
Drive compelling marketing, increase revenue, and further develop client experience, functional productivity, and risk management.
4. Data Administration
Drive data administration initiatives that guarantee information quality, boost worth, and backing security, protection, and life-cycle prerequisites.
2. Customer Experience
Interface the language of this association with the language of our client to smooth out help and convey the ideal data at the ideal time.
5. Process Automation
Transform the connection among individuals and innovation where astute machines process 80% of the data and raise exemptions for human administrators for handling.
3. Intelligent Contextual Search
Incorporate exact and finish metadata into content administration and search engines to upgrade the pursuit experience.
6. Accessible Attributes
All information models collected in one spot and simple downloadable data models which further modifies the attribute tree.
Defining the MVP
I conducted meetings with the stakeholders to outline the user flow and developed a plan for capturing the MVP. This contributed in understanding the key features and helped in early-stage validation of the product concept.
Identified the following features to be included:
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Combining two sets of hierarchies with the option to select the values that should be connected.
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Incorporating data models into the system from Excel sheets.
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Designing templates which defines the LOVs, attribute names, product descriptions, category listing, and other related information.
UI Design process
User Flows
By creating user flows, we were able to figure out how to give users the relevant information at the right moment, enabling them to finish the intended tasks in the fewest number of steps.
Paper Prototypes
Before moving further with the UI Designs, I scribbled down my initial concepts and showed them to the stakeholders to give them a sense of how their product will be structured.
We made the decision to fully utilise this process and didn't begin creating the final mockups and wireframes until the stakeholders were relatively satisfied with our presentation.
UI Design
I wanted to design a modern, clean, and minimalist user interface for the brand that would communicate progress and reliability for people who are going to be using the product in the future.
Uploading files
Using this component of the system, excel documents are automatically converted into a format that is generated by the system and can be conveniently updated afterwards without having to export them repeatedly.
Mapping Hierarchies
Information about the various attributes that are included in the database is displayed in this section. Mapping the hierarchies entails linking the primary hierarchy's values to the micro hierarchy while also allows for the selection of which values to link and which to ignore.
Building Data Models
This part is used to build data model templates from scratch, which are then applied to any file being imported. If the same format appears to be ideal, the very same template can be used for multiple files; otherwise, a different template can be made.
Future Improvements
There is always room for improvement.
After the final designs were completed, our primary responsibility was to check in with the clients once a week to see if everything was proceeding as planned with regard to the market research. Since I had moved on to other projects, I delivered KT sessions to one of our team's interns so he could understand the procedure we had followed and be ready to participate in stakeholder meetings. Depending on what the stakeholders learned once their product was released, he would modify the designs.
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