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Tableau Conference 2014 Presentation

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Slides Prepared and Presented at the Tableau 2014 Conference

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Tableau Conference 2014 Presentation

  1. 1. From Marketing to Merchandising: Using Tableau to Enable ModCloth Stakeholders with the Power of Data Presented by: Krystal St. Julien Data Analyst, ModCloth
  2. 2. What is ModCloth?
  3. 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. 4. A place where data inspires fashion “It would be PERFECT – if it wasn’t for the weird ruffle by the waist……?” ~ Morgan
  5. 5. A place where data inspires fashion “It would be PERFECT – if it wasn’t for the weird ruffle by the waist……?” ~ Morgan
  6. 6. Krystal St. Julien Analyst Link Doucedame Junior Analyst Shawn Davis VP of Analytics Julia King Sr. Mgr. of Analytics Aiyesha Ma Data Scientist Lauren Anderson Sr. BI Analyst Anna Peterson Analyst ModCloth Data Team Julia Kirkpatrick Sr. Researcher Cherie Yagi Researcher Christine Wu Sr. Web Analyst Andy Sevastopoulos Lead Analyst
  7. 7. 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
  8. 8. 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!
  9. 9. 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!
  10. 10. 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.
  11. 11. Tableau as a data-product prototyping tool
  12. 12. Tableau as a data-product prototyping tool
  13. 13. Insights gathered while training stakeholders on Tableau
  14. 14. 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
  15. 15. 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
  16. 16. Optimized data sources
  17. 17. Optimized data sources
  18. 18. Optimized data sources
  19. 19. Dimension and measure aliases Database names: product_discount_at_sale_indicator_number product_discount_indicator_number_based_on_current_retail_price Tableau names:
  20. 20. onMouseOver tooltip definitions
  21. 21. 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
  22. 22. 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
  23. 23. Implement team/topic specific training Intro training: Tableau navigation Topic-specific: Dashboards and Data sources Super-user: Tableau desktop
  24. 24. 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.”
  25. 25. 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
  26. 26. 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?
  27. 27. Lather, rinse, repeat… implement office hours “[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.” • We currently host 4 hours of Tableau office hours a week • ~50% of office hour time is scheduled and used
  28. 28. 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
  29. 29. What non-technical stakeholders at ModCloth have done with Tableau
  30. 30. Pull data about the company without pinging a database Objective: Collate a list of Tops and their associated Lengths.  Click and drag metrics into place
  31. 31. Quick ad hoc analysis – answering a question 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
  32. 32. Trended analysis for dashboarding 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
  33. 33. Practical trade-offs in training stakeholders on Tableau
  34. 34. Pros and Cons Pros 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
  35. 35. 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)
  36. 36. 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
  37. 37. 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
  38. 38. QUESTIONS? http://www.linkedin.com/pub/krystal-st-julien/56/320/a62/ @roskiby ModKrystal
  39. 39. Please take the session survey 1.Tap to this session on the Schedule tab of the Data14 app 2. Scroll down to “Feedback” and tap through the 3-question survey 3.Tap Send Feedback

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