WHAT DO HANDBAGS AND - Online Event69.59.162.218/NRF/BIGShow/2014/What Do Handbags.pdf• JC Penney...
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Transcript of WHAT DO HANDBAGS AND - Online Event69.59.162.218/NRF/BIGShow/2014/What Do Handbags.pdf• JC Penney...
WHAT DO HANDBAGS AND DIAMONDS HAVE IN COMMON?
APPLYING BIG DATA AND ANALYTICS TO FASHION
Fashion is Art.
Where do Data and Analytics come in?
Average amount U.S. adults spend per month on apparel
Source: Cotton, Inc.
Annual Excess Inventory in Fashion
Source: Green Supply Chain
Of products can bear a Higher Price Source: First Insight
11%
Bytes of data generated each day Source: IBM
of the world’s data is Unstructured
How do you apply BIG DATA
Analytics
Fashion?
P1
SPEAKERS
Nathan Gray Helzberg Diamonds VP Planning & Allocation
Scott Steever Vera Bradley Sr. Director of Strategic Initiatives
Jim Shea First Insight Chief Marketing Officer
Big Data and Analytics at
Scott Steever Sr. Director of Strategic Initiatives
Vera Bradley at a Glance
• Marketing • Merchandising • Product Design &
Development
• Planning & Allocation • Ecommerce • Supply Chain
How We Use “Big Data”
• We partner with trusted third-party resources to augment our internal capabilities.
• This is a journey of a thousand steps, which we have just started…
Challenge:
• Increase productivity of email campaigns
• Increase revenue with fewer, targeted emails.
Email Campaign Execution
Action: • Targeted Email
Campaigns
• Customer Analytics and Segmentation
• Market Basket Analysis
Email Campaign Execution
Results: Fewer emails sent, yielding higher sales! • Emails Sent: 63% Decrease
• Open Rate: 43% Increase
• Click Through: 101% Increase
• Conversion: 275% Increased
Total Revenues: 14% Increase
Email Campaign Execution
Challenge:
• Price products based on consumer value & competitive positioning
• Ensure we hit our margin targets
Pricing Analytics
Action: • Competitive Set
Analysis • Merchandising Pyramid • Margin Analysis • “What Would They
Pay?” online consumer engagements
Pricing Analytics
Pricing Analytics Results: New Product Launch (Baby) Dress & Bloomer Set • By changing the retail price to
$49.00 we made: – 6% more in the Indirect Channel – 2% more in the Direct Channel
than we would have at $48.00
• Increased Margin by: – .8% in the Indirect Channel – .4% in the Direct Channel
Challenge: • Pattern selection: Will the pattern stand out and
resonate?
Pattern Testing
Action: • Pattern Research
– Biometrics – Survey – Focus Groups – Customer Panel
Pattern Testing
Results: • Narrow Working Pattern
Assortment per Season
• Prioritize Inventory Investment
• Inform Marketing Placement
• Inform Visual Merchandising
Pattern Testing
Thank You
Scott Steever Sr. Director of Strategic Initiatives
Big Data and Analytics at
Nathan Gray VP Planning and Allocation, Helzberg Diamonds January 14, 2013
My Background • 25 Years in Retail
• Responsible for all merchandise planning & allocation
activities at Helzberg Diamonds
• Previously: • JC Penney • Payless Shoes • Mervyn’s
Agenda • Who is Helzberg Diamonds?
• Our Business Challenges and Goals
• Using Data and Analytics to Increase our Hit Rate on New Merchandise
• Results
Who is Helzberg Diamonds?
• One of the nation’s largest retailers of fine jewelry
• 230+ stores
• Owned by Berkshire Hathaway
• Based in Kansas City, MO
• We will be celebrating our 100th year in 2014
Our Business • Why is Jewelry so different?
• Three big selling seasons
• High cost of goods
• High retails
• Slow turns
• Aspirational purchase (often by man for woman as a gift).
• High cost of a mistake • Margin difference of one winning SKU (vs a losing SKU) is as
much as $225,000, depending on category.
Challenges and Goals
• Maximize productivity per linear foot.
• Increase inventory turns (sell through %).
• Increase speed to market
• Increase “batting average” of picking winners – above the current 30-35% hit rate on tests.
New Product Introduction
1
CURRENT PROCESS
2 3 4 5 6 7 8 9 0
2 4 7
4
33% Batting Average
How can we
increase our Batting Average?
Vendor presents Candidate new items
2-3 months; Can’t test everything
How many winners did we leave
behind? Merchant Makes Selections for Testing
25-Store Test
Real-time New Product Testing
Applying Data to Diamonds • Started testing online with predictive analytics in Q1 2013 Goals:
• Reduce store testing & accelerate speed to market • Pick more winners & reduce the “dogs” (increase “batting average”) • Modify designs to improve product performance • Raise prices where possible based on market input
• Ran pilot; tested 400+ new products over two seasons.
• Measured accuracy in picking winners
“What Would They Pay?”
Example Output: Summary
Known Strong Performers
Filtering and Predictive Analytics
Qualifies and weights relevant responses based on ability to properly identify the
reference items
Known Weak Performers
Science Behind The Value Score
Reference Items
Example Output
Price Elasticity
Forecasting Average Unit Retail (AUR) Price
Results • Increased batting average from 30-40% to 65% by testing online.
• 80%+ accuracy in picking winners.
• Identified products which can bear price increases (or do not need to be promoted).
• Identified products which customers like but will not bear the planned price
• Made design changes to reduce cost.
• Identified products which had negative sentiment but high Value Scores which performed well (and vice versa)
High Value Score
Item will bear price above planned
MSRP
High negative sentiment
Example: Top Actual Performer
Low Value Score
Item will not bear the MSRP.
High positive Sentiment
Example: Low Actual Performer
• Increasing batting average from 35% to 65% is worth over $7 million per year in GM$.
• We were able to double the number of winners.
• Cost of online testing solution is paid for with a 2% increase in batting average.
Value to Helzberg Diamonds
DISCUSSION Nathan Gray Helzberg Diamonds VP Planning & Allocation [email protected]
Scott Steever Vera Bradley Sr. Director of Strategic Initiatives [email protected]
Jim Shea First Insight Chief Marketing Officer [email protected]
