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?
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