Post on 27-Jun-2015
description
Presented by:
Krystal St. JulienData Analyst, ModCloth
From Marketing to Merchandising: Using Tableau to Enable ModCloth Stakeholders with the Power of Data
What is ModCloth?
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.
A place where data inspires fashion
“It would be PERFECT – if it wasn’t for the weird ruffle by the waist……?”
~ Morgan
A place where data inspires fashion
“It would be PERFECT – if it wasn’t for the weird ruffle by the waist……?”
~ Morgan
Link DoucedameJunior Analyst
Aiyesha MaData Scientist
Shawn DavisVP of Analytics
Lauren AndersonSr. BI Analyst
Julia KingSr. Mgr. of Analytics
Anna PetersonAnalyst
Krystal St. JulienAnalyst
Julia KirkpatrickSr. Researcher
Cherie YagiResearcher
ModCloth Data Team
Christine WuSr. Web Analyst
Andy SevastopoulosLead Analyst
Jobs currently executed by ModCloth Data Team
• 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
• Development of Data Products
• Teaching Stakeholders About Data, How to Use it, and How to Present it
Jobs currently executed by ModCloth Data Team
• 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
• Development of Data Products
• Teaching Stakeholders About Data, How to Use it, and How to Present it
Jobs currently executed by Analysts AND stakeholders!
Jobs currently executed by ModCloth Data Team
• 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
• Development of Data Products
• Teaching Stakeholders About Data, How to Use it, and How to Present it
Jobs currently executed by Analysts AND stakeholders!
Why invest the time and energy in making data stakeholder-friendly?
• 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!
• Communicating about algorithms can be difficult in the abstract.
Immediate Delivery!
Tableau as a data-product prototyping tool
Tableau as a data-product prototyping tool
Insights gathered while training stakeholders on Tableau
Hurdles to overcome when teaching non-technical stakeholders
• Some common stakeholder challenges include:
• Misunderstood jargon/misaligned data communication
• Different stakeholders will have different goals/needs
• Lack of knowledge of the tool’s full capability and data available
• Some common stakeholder challenges include:
• Misunderstood jargon/misaligned data communication
• Different stakeholders will have different goals/needs
• Lack of knowledge of the tool’s full capability and data available
Hurdles to overcome when teaching non-technical stakeholders
Optimized data sources
Optimized data sources
Optimized data sources
Dimension and measure aliases
product_discount_at_sale_indicator_number
product_discount_indicator_number_based_on_current_retail_price
Database names:
Tableau names:
onMouseOver tooltip definitions
• Some common stakeholder challenges include:
• Misunderstood jargon/misaligned data communication
• Different stakeholders will have different goals/needs
• Lack of knowledge of the tool’s full capability and data available
Hurdles to overcome when teaching non-technical stakeholders
ModCloth has MANY data use-cases
Merchandising Assortment planning – What are customers purchasing?
Finance Sales reports and dashboards
Human Resources Reviewing company stats
Public Relations Data gathering for press cards
Product Mangers Data diagnostics – What is going well/failing on our site?
Operations/Shipping
What are customers ordering? Identification of fraudulent orders
Marketing Marketing channel performance reporting
Implement team/topic specific training
Intro training: Tableau navigation
Topic-specific:Dashboards and Data sources
Super-user:Tableau desktop
Results of 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.”
• Some common stakeholder challenges include:
• Misunderstood jargon/misaligned data communication
• Different stakeholders will have different goals/needs
• Lack of knowledge of the tool’s full capability and data available
Hurdles to overcome when teaching non-technical stakeholders
Training should include exercises showing stakeholders what can be done
• Filter on date• Bring in “Vendor Name” dimension• Bring in “Count of Products” measure• Multiple visualizations can be useful
• Allow ~5 minutes of individual work time per question
• Go through the question as a team using the following steps:
• What filters will we need?
• What dimensions do we want to see?
• What are we trying to measure?
• Which visualization would you prefer to see if someone were presenting this data to you?
Lather, rinse, repeat… implement office hours
• We currently host 4 hours of Tableau office hours a week
• ~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.”
Stakeholders can learn from Super Users!
Finance Merchandising Marketing
• Provided with Tableau Desktop
• Allowed to create and modify dashboards
• First line of defense for team-questions
What non-technical stakeholders at ModCloth have done with Tableau
Objective: Collate a list of Tops and their associated Lengths.
Click and drag metrics into place
Pull data about the company without pinging a database
Question: Do customers consider reviews more helpful when the reviewer’s measurements are associated?
Click and drag metrics into place
Use a quick calculation to get Avg Count of Helpful Votes per Review
Use “show me” to visualize data as bar chart
Quick ad hoc analysis – answering a question
Objective: Find the running sum of new customers that are placing repeat orders over time.
Write logic to find the date difference between date when order number = 1 and date when order number = 2
Click and drag metrics into place
Implement a quick calculation to produce running total
Trended analysis for dashboarding
Practical trade-offs in training stakeholders on Tableau
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
Usage at ModCloth
• Last quarter, of ~200 potential Tableau users outside of the analytics team,…
• MC analytics completed 2 hours of training and ~26 hours of office hours, contributing to:
• 120 users logging-in
• 114 users looking at readily available dashboards
• 96 users accessing data via a data source
• 30 users publishing at least 1 workbook to share
• an estimated >220 additional “requests” being resolved by teaching stakeholders how to use Tableau
Most of these users were trained in Jan or Feb of 2014 (8 hours offered)
My balance of time before/after training implementation
JOB/SKILL BEFORE
AFTER
Data pulling and Data Delivery 15 5
Ad Hoc Analysis (for business/strategy recommendations) 35 20
Dashboard/Automated Analysis Development 25 20
Data Warehousing (creating and storing data) 10 10
Data Modeling and Prediction 5 20
Development of Data Products 0 5
Teaching Stakeholders About Data, How to Use it, and How to Present it 10 20
My balance of time before/after training implementation
JOB/SKILL BEFORE
AFTER
Data pulling and Data Delivery 15 5
Ad Hoc Analysis (for business/strategy recommendations) 35 20
Dashboard/Automated Analysis Development 25 20
Data Warehousing (creating and storing data) 10 10
Data Modeling and Prediction 5 20
Development of Data Products 0 5
Teaching Stakeholders About Data, How to Use it, and How to Present it 10 20
QUESTIONS?
http://www.linkedin.com/pub/krystal-st-julien/56/320/a62/
@roskiby
ModKrystal
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