#DataViz14: Stakeholder empowerment in using data vis GUIs @ ModCloth
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Transcript of #DataViz14: Stakeholder empowerment in using data vis GUIs @ ModCloth
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Data Visualization GUIs and the Advantage of Teaching Non-Expert Analysts
Krystal St. Julien
Data Analyst – ModCloth
Data Visualization Summit – 4/10/14
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More than a fashion retailer…
Our Mission: To inspire personal style and help customers feel like the best version of themselves.
Our Purpose: To democratize fashion and decor around the world.
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A place where data inspires fashion
“It would be PERFECT – if it wasn’t for the weird ruffle by the waist……?”
~ Morgan
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Alice LoebHead of User Experience Research
Kate ZimmermanLead Analyst
Link DoucedameAnalyst
Frances FontanillaSenior Analyst
Aiyesha MaData Scientist
Shawn DavisVP of Analytics
Lauren AndersonSenior BI Analyst
Julia KingSr. Mgr. of Analytics
Anna PetersonAnalyst
Krystal St. JulienAnalyst
Julia KirkpatrickSr. Researcher
Laura PaajanenResearcher
Cherie YagiResearcher
ModCloth Data Team
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Jobs currently executed by ModCloth Analysts
• Data pulling and Data Delivery
• Ad Hoc Analysis (for business/strategy recommendations)
• Dashboard/Automated Analysis Development
• Data Warehousing (creating and storing data)
• Data Modeling and Prediction
• Teaching Stakeholders About Data/Data Presentation
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GUIs can make analysis easy: 1. Preconfigured Reporting
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GUIs can make analysis easy: 1. Preconfigured Reporting
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GUIs can make analysis easy: 1. Preconfigured Reporting
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GUIs can make analysis easy: 1. Preconfigured Reporting
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GUIs can make analysis easy: 1. Preconfigured Reporting
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GUIs can make analysis easy: 1. Preconfigured Reporting
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GUIs can make analysis easy: 1. Preconfigured Reporting
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GUIs can make analysis easy: 2. Data Storage
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GUIs can make analysis easy: 2. Data Storage
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GUIs can make analysis easy: 2. Data Storage
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GUIs can make analysis easy: 2. Data Storage
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GUIs can make analysis easy: 2. Data Storage
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GUIs can make analysis easy: 3. Data Extraction
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GUIs can make analysis easy: 3. Data Extraction
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GUIs can make analysis easy: 3. Data Extraction
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GUIs can make analysis easy: 3. Data Extraction
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GUIs can make analysis easy: 3. Data Extraction
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Extra power can be extracted from these tools by teaching/empowering stakeholders
• Our current backlog: over 100 requests
• Wait time for an analyst: a couple of days to several months
• Access to a user-friendly analytics tool means stakeholders can have same-day data delivery!Immediate Delivery!
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Insights gathered while training stakeholders to use analytics/visualization tools
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Hurdles to overcome when teaching non-technical stakeholders as ‘first-time analysts’
• Some common stakeholder challenges include:
• Misunderstood jargon/misaligned communication
• Difficulty approaching the data/asking relevant questions
• Lack of knowledge of the tool’s full capability and data available
• Different stakeholders may have wildly different goals/needs
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Hurdles to overcome when teaching non-technical stakeholders as ‘first-time analysts’
• Some common stakeholder challenges include:
• Misunderstood jargon/misaligned communication
• Difficulty approaching the data/asking relevant questions
• Lack of knowledge of the tool’s full capability and data available
• Different stakeholders may have wildly different goals/needs
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The power of glossaries and well-structured aliases
product_discount_at_sale_indicator_number
product_discount_indicator_number_based_on_current_retail_price
Database names:
Tableau names:• Which metric gives me the data I need?• What do the values translate into?• How should I use this information?
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Hurdles to overcome when teaching non-technical stakeholders as ‘first-time analysts’
• Some common stakeholder challenges include:
• Misunderstood jargon/misaligned communication
• Difficulty approaching the data/asking relevant questions
• Lack of knowledge of the tool’s full capability and data available
• Different stakeholders may have wildly different goals/needs
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`
Teaching through interactivity: Working backward to move forward
The Method:
First, ask stakeholders to create a particular visualization, then, ask the stakeholder to explain which problems are solvable with the data shown.
The Problem:
Stakeholders often do not know what data/visualizations should be used to solve a given problem.
The Goal:
Guide stakeholders to ask the right questions BEFORE determining what data to pull.
????
?
?
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Teaching through interactivity: Working backward to move forward
• Ask Stakeholder:• Visualize a specific data set• What question(s) does this data answer?
• Provide feedback• Repeat…
- Look at data from last quarter ONLY- Find reviews that were deemed helpful by at least 1
shopper- Identify the number of reviews in each product
rating category - Highlight the reviews with customer photos
attached
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Teaching through interactivity: Working backward to move forward
Rating Photo?
Count of Reviews
Which rating categories have the most reviews (helpful)?Which rating categories have the most photos (helpful)?
• Ask Stakeholder:• Visualize a specific data set• What question(s) does this data answer?
• Provide feedback• Repeat…
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Teaching through interactivity: Working backward to move forward
Rating Photo?
Count of Reviews
Which category has the most helpful reviews?
• Ask Stakeholder:• Visualize a specific data set• What question(s) does this data answer?
• Provide feedback• Repeat…
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Hurdles to overcome when teaching non-technical stakeholders as ‘first-time analysts’
• Some common stakeholder challenges include:
• Misunderstood jargon/misaligned communication
• Difficulty approaching the data/asking relevant questions
• Lack of knowledge of the tool’s full capability and data available
• Different stakeholders may have wildly different goals/needs
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Enticing visuals make all the difference
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Hurdles to overcome when teaching non-technical stakeholders as ‘first-time analysts’
• Some common stakeholder challenges include:
• Misunderstood jargon/misaligned communication
• Difficulty approaching the data/asking relevant questions
• Lack of knowledge of the tool’s full capability and data available
• Different stakeholders may have wildly different goals/needs
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Team/topic specific training
“It was tailored to our specific needs and demonstrated how to
access/utilize key reports. (Versus previous training session that was much more general and
hard to follow.)”
“I liked that this training was specific to our category so we
could discuss our team’s needs.”
“I liked how we walked through the specific reports that will be
most useful for our specific team. I walked out of the
training with a clear understanding of the
information I can find in Tableau and how to pull it.”
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Hurdles to overcome when teaching non-technical stakeholders as ‘first-time analysts’
• Some common stakeholder challenges include:
• Misunderstood jargon/misaligned communication
• Difficulty approaching the data/asking relevant questions
• Lack of knowledge of the tool’s full capability and data available
• Different stakeholders may have wildly different goals/needs
Continued support is critical!
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The importance of office hours
• We currently host 8 hours of office hours a week • 4 hours dedicated to Tableau-Only questions• 2 hours dedicated to Omniture-Only questions• 2 hours of multipurpose office hours (open questions)
• ~50% of office hour time is scheduled and used
“[I want to get] individual help
running [my] own reports.”
“Wish we spent more time doing live scenarios,
practicing using the tool, reviewing the metrics
available, how to pull ad hoc reports, etc.”
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Practical trade-offs in training stakeholders to pull and visualize their own data
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Pros and Cons
• Stakeholders do not have to wait for an analyst to come available
• Project iterations are easily accomplished/easy to shift direction
• Analysts can focus on more impactful analyses, models, and predictions
• Appropriate time for teaching/training as well as follow-up training must be allocated
• When tools are updated/changed, additional training is required
• Tools come at a monetary cost
Pros Cons
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Usage at ModCloth
• In February, of ~250 potential Tableau users,…
• MC analytics completed 4 hours of training and 13 hours of office hours contributing to:
• 115 people at our company logging into Tableau
• 112 people accessing a preconfigured dashboard
• 91 people pulling/analyzing data via a data source
• 27 creating and saving their own sustained reports
• an estimated >75 additional “requests” being resolved by teaching people how to use this particular data visualization tool
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QUESTIONS?
http://www.linkedin.com/pub/krystal-st-julien/56/320/a62/
@roskiby
ModKrystal