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Unified Reporting Initiative Magento reporting reimagined

The Problem

Magento Advanced Reporting Dashboard (Left) and MBI Dashboard (Right)

The Magento platform is part of the Adobe Experience Cloud and for many years it has been a leading force in the E-commerce industry. The Magento platform has three main areas where you can view reporting: Magento Admin, Advanced Reporting and MBI. All three areas display data using different sources of truth and visual look and feel. This makes for a very inconsistent and disjointed experience for the user as they may be going back and forth between programs.

Unified Reporting Initiative

The Unified Reporting Initiative is a project of the Digital Experience team lead by the following members:

  • Dustin Ground, Manager and User Experience Designer
  • Tina Moore, Senior UX Designer
  • Daniel Rios, Product Manager
  • Catherine Chiodo, Senior User Experience Researcher

The initiative was created to develop a uniform, concise approach to generating reports throughout the whole Magento platform.

My Intern Project

My role as UX Designer Intern was to assist the team with the Initial Research Phase, which focused on discovery to figure out the client’s use of data and the type of decisions they make around data.

Competitive Analysis

My first task was to conduct a competitive analysis in 4 categories and 3-5 companies per category. The focus was placed on both features and approach to data within these systems. Based on insight from our team members the following 4 categories were determined:

  1. Business Intelligence Tools
  2. E-Commerce Platforms
  3. Order Management Systems
  4. Behavioral analytical solutions
Feature Matrices for Business Intelligence Tools, E-Commerce, Order Management Systems and Behavioral Analytics Solutions

Business Intelligence Tools

Each of the categories was broken into subcategories to investigate. Extensive research was done for each platform in order to gain good understanding of each system. For example, for Business Intelligence tools some of the features that were looked at were the following:

  • Deployment Data: Looking into how platforms are allowing users to connect to their data sources, either from a cloud and/or on-premise.
  • Slice and Dice Data: How are platforms allowing users to break data information into smaller components such as segmenting, viewing and comprehending data in a database.
  • Building Data: How are users building data? With code or without code, visually perhaps?
  • Mental Model: The platform's system of building analytics, metrics or free-form
  • Integration Features: What other 3rd party systems are users able to connect to import data or share data with?
  • Collaboration Features: How are users able to collaborate their data insights with others within the organization or outside.
  • Visualization Features: What type of visuals do these platforms provide for their users? Dashboards, charts, heat maps, line charts...
  • Predictive Features: What type of predictive features are they providing for users that require advance analytics, machine learning or AI.
  • OLAP (Online Analytical Processing): Enables users to easily and selectively extract and query data in order to analyze from different perspectives.
Business Intelligence Tools Feature Matrix

Discovery Interview Sessions

Companies that participated in User Interviews

I participated with client research in the form of user interviews and took handwritten notes in 9 one-hour-long discovery interviews sessions.

We spoke to a variety of Magento clients that spanned differently sized organizations, product usage and offered a spectrum of roles that included E-Commerce Director, Digital Strategy Manager, Website Director, Digital Marketer and Content and Social Media Manager. These sessions spanned across country and international time zones.

Questions asked revolved around the user's background, data workflow, and future of data usage for their role. Participants were also encouraged to share their screens and walk through their processes. The desired outcome of these interviews was to help us identify overarching themes for a consolidated reporting offering.

User Interview Sample Questions:

  • What are your main responsibilities? Who do you report to? Who is reporting to you?
  • How do you and your company use data?
  • How do you track your business health on and what frequency basis?
  • What are you currently using for day to day reporting?
  • Thinking over the last few months, was there a major decision you had to make using data?
  • Do you use any tools for data outside of Magento?
  • How would you like to use data within the Magento platform?
  • What would make reporting in Magento better?

Research Synthesis

Affinity Mapping Session

In order to interpret all the data from our user interview sessions we organized and carried out an all day affinity mapping diagraming session.

An affinity mapping diagraming session is helpful to help interpret large disparate data sets, like is the case of 9 user interviews. The purpose is to be able to see emerging themes and begin looking at the larger story by being able to identify insights, user needs, pain points or any gaps not perceived prior.

Preparation for Affinity Mapping Session

Typed handwritten user interview notes

Broke down user interviews into key insights, thoughts, quotes into 1 thought per card

Cut them all into individual key insights cards

Created User Profiles to help us reference back during session

Affinity Mapping Diagraming Process

First step in the affinity mapping diagraming process is pulling insights and key ideas from user interview concept cards which was done prior to exercise.

Second step is grouping insights by similar ideas.

Affinity Mapping Diagraming Step 1 & 2

Third step is adding "I statements", depicted below by the blue post-its, these help understand overall user.

Fourth step is adding high level theme, depicted below by the large golden post-its.

Affinity Mapping Diagraming Step 3 & 4

The result is that we can tell a story of this data set by looking at these larger themes and be able to view all the individual insights and concepts that helped create it.

Findings:

Sample of themes that were identified are the following:

  1. Using data for performance monitoring
  2. Education Needs
  3. Sharing Feature
  4. Forecasting/AI Features
Example of one overall theme

We were able to achieve some of the goals we came in wanting to know:

  • Deeper understanding of user personas
  • Defining the life cycles of a decision
Affinity Mapping Diagraming: User Personas and Life Cycle of a Decision

Affinity Mapping Session Video

Results:

  • Increased user empathy through updated personas
  • Understanding competitive strengths & weaknesses
  • Greater understanding of how users use reporting
  • Discovered additional, actionable insights such as the need for increased education

Next Steps:

With Initial Research Phase done, the next phase of the Unified Reporting Initiative will be Conceptual Ideation.

All insights and outputs gained through the research process will provide a user focus direction as concrete concepts will be created of how to apply a new approach to data and reporting throughout the Magento platform.

There were many additional learnings that resulted from this exercise. We identified gaps that can be addressed in future product work, new areas of possible research and insights that influence projects other teams are working on.

Credits:

Created with an image by 6689062 - "financial analytics blur"