1) The document discusses teaching non-expert analysts at ModCloth to use data visualization tools like Tableau through training sessions and office hours. 2) It outlines challenges like technical jargon and different stakeholder needs, and strategies used like tailored training, interactive exercises, and dedicated support hours. 3) Usage data from February shows over 100 people accessing preconfigured reports, with many more taught to pull their own data and create reports through these training efforts.

1. Data Visualization GUIs and the
Advantage of Teaching Non-Expert
Analysts
Krystal St. Julien
Data Analyst – ModCloth
Data Visualization Summit – 4/10/14

2. What is ModCloth?

3. 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.

4. A place where data inspires fashion
“It would be
PERFECT – if it
wasn’t for the
weird ruffle by
the waist……?”
~ Morgan

5. Alice Loeb
Head of User
Experience
Research
Kate Zimmerman
Lead Analyst
Link Doucedame
Analyst
Frances Fontanilla
Senior Analyst
Aiyesha Ma
Data Scientist
Shawn Davis
VP of Analytics
Lauren
Anderson
Senior BI Analyst
Julia King
Sr. Mgr. of
Analytics
Anna Peterson
Analyst
Krystal St. Julien
Analyst
Julia Kirkpatrick
Sr. Researcher
Laura Paajanen
Researcher
Cherie Yagi
Researcher
ModCloth
Data Team

6. 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

10. GUIs can make analysis easy:
1. Preconfigured Reporting

11. GUIs can make analysis easy:
1. Preconfigured Reporting

12. GUIs can make analysis easy:
1. Preconfigured Reporting

13. GUIs can make analysis easy:
1. Preconfigured Reporting

14. GUIs can make analysis easy:
1. Preconfigured Reporting

15. GUIs can make analysis easy:
1. Preconfigured Reporting

16. GUIs can make analysis easy:
1. Preconfigured Reporting

17. GUIs can make analysis easy:
2. Data Storage

18. GUIs can make analysis easy:
2. Data Storage

19. GUIs can make analysis easy:
2. Data Storage

20. GUIs can make analysis easy:
2. Data Storage

21. GUIs can make analysis easy:
2. Data Storage

22. GUIs can make analysis easy:
3. Data Extraction

23. GUIs can make analysis easy:
3. Data Extraction

24. GUIs can make analysis easy:
3. Data Extraction

25. GUIs can make analysis easy:
3. Data Extraction

26. GUIs can make analysis easy:
3. Data Extraction

27. 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!

28. Insights gathered while training
stakeholders to use
analytics/visualization tools

29. 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

30. 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

31. 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?

32. 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

33. `
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.
?

34. 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

35. 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…

36. 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…

37. 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

38. Enticing visuals make all the difference

39. 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

40. 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.”

41. 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!

42. 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.”

43. Practical trade-offs in training
stakeholders to pull and visualize
their own data

44. 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

45. 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

46. QUESTIONS?
http://www.linkedin.com/pub/krystal-st-julien/56/320/a62/
@roskiby
ModKrystal