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"Attention Shoppers: Building Opportunity Based on Customer Behavior Data”Mass retailers face the challenge of converting general shoppers to book buyers. In this presentation, Tara Catogge, an executive at the leading supplier of books to mass merchants, delivers a data-rich examination of category trends and provide examples of how data-based marketing tools can be used to attract consumers at point-of-sale. Tara also enumerates some of the challenges suppliers and retailers face together as they embrace a culture of collaborative, data-driven decision making.
Citation preview
Attention Shoppers: Building Opportunity Based on Customer Behavior Data
Of Distribution ExcellenceLHE
Attention Shoppers: Building Opportunity Based on Customer Behavior Data
“…the brick channel for printed books continues it’s inevitable decline into insignificance”
--Mike Shatzkin
Attention Shoppers: Building Opportunity Based on Customer Behavior Data
“…the brick channel for printed books continues it’s inevitable decline into insignificance”
--Mike Shatzkin
Combined, these retailers represent 25% of total US GDP in 48,000 US locations (that’s a heck of a lot of foot traffic)
Mass Merchants Grocery Specialty
Club Department Drug
*
*
*
*
*
**
*
*
*
*
22,082 retail store locations shipped with 1,600 in-house merchandisers
Sales Breakdown of Distributed Products
LHE
Mass Merchants
69%
Specialty
5%
Other
1%Drug
2%Grocery
7%Distributors
8%
Department
0%
Club8%
Adult Hardcover22%
Mass Market Paperback
20%
Young Adult Hardcover
7%
Series Romance Paperback
3%Kids Hardcover
27%
Trade21%
Units sold by Category Units sold by Channel
Mass Merchant retailers have very high share of blockbuster releases/series
Life to date sales /BookScan/est. for Walmart
TWILIGHT SERIES Market Share(Avg = 20%)
BREAKING DAWN (HC) 45%NEW MOON (TP) 50%
TWILIGHT (TP) 43%ECLIPSE (HC) 46%ECLIPSE (TP) 60%
TWILIGHT (TP) 67%TWILIGHT (Movie Tie In) 72%
NEW MOON (HC) 34%SHORT SECOND LIFE BREE TANN (TP) 49%
TWILIGHT (HC) 34%NEW MOON (Movie Tie In) 74%
BREAKING DAWN (TP) 63%NEW MOON (MASS) 75%
ECLIPSE SPECIAL EDITION 26%ECLIPSE (Movie Tie In) 72%
ECLIPSE (MASS) 78%TWILIGHT: THE GRAPHIC NOVEL 46%
RECENT TITLES MKT SHAREDIARY OF WIMPY KID #5 40%
AWAKENED: HOUSE OF NIGHT 52%HEAVEN IS FOR REAL 25%
ENGAGEMENT IN SEATTLE (MASS) 83%
LHE
Ask the simple questions (that are really
difficult to answer)
LHE
2. What questions do we need answered?Ask the organization and rank the results
6 “Rights” by Sol Price1. Merchandise—brand equity
authors, local interest 2. Time –maintain in-stock while
avoiding over-stock3. Price – profitably priced to show a
value to the consumer4. Place – merchandising standards to
maximize sales5. Quantity – just-in-time inventory to
maximize turns/GMROII6. Format (Right Condition) – paper,
audio, ebook
1. Where is the opportunity to improve?lower returns, increase conversions, improve supply chain
"I guess I've stolen--I actually prefer the word 'borrowed'--as many ideas from Sol Price as from anybody else in the business.“
--Sam Walton
LHE
Ask the simple questions (that are really
difficult to answer)
LHE
2. What questions do we need answered?Make a list!
1. Where is the opportunity to improve?lower returns, increase conversions, improve supply chain
nothing will improve until you
change the corporate culture
3. Are we currently making decisions based on facts?“There are lies, damn lies, and statistics”
-Mark Twain
LHE
Results-Generating Business Analytics
• We all need to collect data (consumer, customer, category, channel,
format, genre, title) and mine that data to uncover patterns and
derive actionable insights
• Invest in analytics tools to understand trends
• Provide business, operational and financial insight to all parties in the supply chain
• Collaborate, Cooperate and Redefine Competition
LHE
SURVEY RESULTS She is cash-strapped and wants a discount on her favorite authorOPPORTUNITY “Right-size” the department through category to space analysis
On-Line BookShopper
Traditional Bookstores Shopper
Mass Merchants / Clubs Book Shopper
Female Book Shoppers 65% 58% 72%
Income < $50k 43% 39% 47%
% of Purchases made because of specific
Author / Series59% 56% 75%
% of Books Purchasedbecause of sale price 32% 15% 34%
% of Purchases Fiction Category 66% 67% 84%
% of Fiction Purchases Romance / Mystery or
Thriller27% 26% 44%
% of Purchases Impulse 55% 61% 78%
Primarily female
Less discretionary spend
Author (brand) loyalty
Value shopper
Heavy Fiction Romance / Mystery / Thriller buyers
Very impulsive
Bowker Consumer Pub Track – 2010 Full Year Results
Talk to the Customer (not the database administrator
or business analyst)
LHE10.0% 12.0%
15.0%17.0%
4.0%5.0%
15.0%
15.0%
8.0%
10.0%8.0%
16.0%
40.0%
25.0%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Walmart Target
How the Customer Learned about the Last Book They Purchased
Retail Browsing
Personnal Recommendation
Publicity
Other
Online Sources
Info From Authors Prior Book
LHE
Book Unit Share has not Moved Significantly (print to e) Among Those that Purchase Books in Mass Merchants
49%46%
79%
14%
87%
8%
82%
9%
46% 48%
76%
17%
82%
12%
84%
10%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Print eBook Print eBook Print eBook Print eBook
Kindle Owner Amazon (non Kindle) Target Walmart
% of Units Purchase
Nov-10
Feb-11
Shopper’s Marketing—Competing for Footsteps
Awareness
• Out of Department placement
• Events
• Fixture Signage
• Media Category Advertising
• Online influence
Discovery
• Clear recommendations and brand (author)
awareness
• Repeat visits—tell them what’s coming
• Develop new authors in Mass Merchant channel
• Consistent and directed merchandising
• Wayfinding
Value
• Everyday Low Price
• Price Cuts
• Competitive pricing
Book Buyer Conversion
LHE
Improving the In-Store Experience Leads to Double Digit Sales Increases
Way Finding
Price Message
30% increase in kids sales 5 – 12%
increase in overall sales
Promote out of the Department—Increased Awareness Leads to conversions
-25%
-20%
-15%
-10%
-5%
0%
5%
10%
15%
20%
25%
2/27 3/13 3/27 4/10 4/24 5/8 5/22 6/5 6/19 7/3 7/17 7/31 8/14 8/28 9/11 9/25 10/9 10/23 11/6 11/20 12/4 12/18 1/1 1/15 1/29 2/12 2/26 3/12
% C
hang
e in
$ S
ales
Test Group Control Group
Lift During Promotion
Pre Promotion
Post Promotion Sustained Sales
Emerging Growth Brand Equity Authors
Lora Leigh Nicholas Sparks David Baldacci
Kressley Cole Kristin Hannah Janet Evanovich
Monica McCarty Linda Lael Miller John Grisham
Karen Marie Moning Lee Child Debbie Macomber
Elin Hilderbrand Robyn Carr Nora Roberts
Lori Wilde Susan Mallery Charlaine Harris
Lara Adrian Vince Flynn James Patterson
Lori Foster Harlan Coben Danielle Steel
Kerrelyn Sparks Cathy Maxwell Sandra Brown
Larissa Ione Mary Higgins Clark
Tracy Anne Warren Michael Connelly
Clive Cussler
With limited retail space, and full-face merchandising, Mass Merchants can drive large sales volumes on emerging and growth authors
LHEXX% Average Bookscan
Marketshare
XX% Average Bookscan
Marketshare
Buyer Selections, Book Club Picks and Spotlight Author programs are helping readers discover new authors
• Wayfinding is necessary for mass merchants to attract bookstore shoppers
• Mass merchants are more successful in breaking out new authors in mass or trade
• Test programs have shown an average 16% increase in sales over control group LHE
Organize the Data so it Becomes Useable 313544612.9914.9522121022214
413544612.9914.9529181112920
513544612.9914.9545182724531
1213544612.9914.95211011332112
1313544612.9914.9510554104
1813544612.9914.95154115158
1913544612.9914.95341618123422
2413544612.9914.954473724422
2613544612.9914.9548123614828
4313544612.9914.9528121622816
4413544612.9914.9513499139
4813544612.9914.95271611442715
5213544612.9914.95141135146
5513544612.9914.951798121712
5713544612.9914.9513943138
6113544612.9914.9546739664630
6413544612.9914.9532302793221
6713544612.9914.952191202114
6813544612.9914.95179821711
6913544612.9914.9552242815232
7513544612.9914.95871183
7613544612.9914.9535102523525
7813544612.9914.9540103014025
7913544612.9914.9546262024628
8013544612.9914.95201010332015
8213544612.9914.9542162644231
8313544612.9914.952161552113
8413544612.9914.9517512121711
8513544612.9914.9546123424628
8613544612.9914.9537181913730
9013544612.9914.95131032138
9213544612.9914.9511569119
9313544612.9914.95271314442717
9513544612.9914.95642563
9613544612.9914.95361125123619
10013544612.9914.953425933421
10713544612.9914.9534628663420
10813544612.9914.9545936794527
11113544612.9914.951551001511
12013544612.9914.9511742119
13713544612.9914.954383514328
13913544612.9914.9528101812816
14413544612.9914.9528111702818
14513544612.9914.9517980179
14613544612.9914.9542271504223
14713544612.9914.952071302010
15113544612.9914.9543271604326
15213544612.9914.954083204028
313544612.9914.9522121022214
413544612.9914.9529181112920
513544612.9914.9545182724531
1213544612.9914.95211011332112
1313544612.9914.9510554104
1813544612.9914.95154115158
1913544612.9914.95341618123422
2413544612.9914.954473724422
2613544612.9914.9548123614828
4313544612.9914.9528121622816
4413544612.9914.9513499139
4813544612.9914.95271611442715
5213544612.9914.95141135146
5513544612.9914.951798121712
5713544612.9914.9513943138
6113544612.9914.9546739664630
6413544612.9914.9532302793221
6713544612.9914.952191202114
6813544612.9914.95179821711
6913544612.9914.9552242815232
7513544612.9914.95871183
7613544612.9914.9535102523525
7813544612.9914.9540103014025
7913544612.9914.9546262024628
8013544612.9914.95201010332015
8213544612.9914.9542162644231
8313544612.9914.952161552113
8413544612.9914.9517512121711
8513544612.9914.9546123424628
8613544612.9914.9537181913730
9013544612.9914.95131032138
9213544612.9914.9511569119
9313544612.9914.95271314442717
9513544612.9914.95642563
9613544612.9914.95361125123619
10013544612.9914.953425933421
10713544612.9914.9534628663420
10813544612.9914.9545936794527
11113544612.9914.951551001511
12013544612.9914.9511742119
13713544612.9914.954383514328
13913544612.9914.9528101812816
14413544612.9914.9528111702818
14513544612.9914.9517980179
14613544612.9914.9542271504223
14713544612.9914.952071302010
15113544612.9914.9543271604326
15213544612.9914.954083204028
1 DAYS DATA FEED IS AS HIGH AS
6 STACKED EMPIRE STATE BUILDINGS
120,000 EXCEL ROWS OF DATA10,000 ft. high
313544612.9914.9522121022214
413544612.9914.9529181112920
513544612.9914.9545182724531
1213544612.9914.95211011332112
1313544612.9914.9510554104
1813544612.9914.95154115158
1913544612.9914.95341618123422
2413544612.9914.954473724422
2613544612.9914.9548123614828
4313544612.9914.9528121622816
4413544612.9914.9513499139
4813544612.9914.95271611442715
5213544612.9914.95141135146
5513544612.9914.951798121712
5713544612.9914.9513943138
6113544612.9914.9546739664630
6413544612.9914.9532302793221
6713544612.9914.952191202114
6813544612.9914.95179821711
6913544612.9914.9552242815232
7513544612.9914.95871183
7613544612.9914.9535102523525
7813544612.9914.9540103014025
7913544612.9914.9546262024628
8013544612.9914.95201010332015
8213544612.9914.9542162644231
8313544612.9914.952161552113
8413544612.9914.9517512121711
8513544612.9914.9546123424628
8613544612.9914.9537181913730
9013544612.9914.95131032138
9213544612.9914.9511569119
9313544612.9914.95271314442717
9513544612.9914.95642563
9613544612.9914.95361125123619
10013544612.9914.953425933421
10713544612.9914.9534628663420
10813544612.9914.9545936794527
11113544612.9914.951551001511
12013544612.9914.9511742119
13713544612.9914.954383514328
13913544612.9914.9528101812816
14413544612.9914.9528111702818
14513544612.9914.9517980179
14613544612.9914.9542271504223
14713544612.9914.952071302010
15113544612.9914.9543271604326
15213544612.9914.954083204028
313544612.9914.9522121022214
413544612.9914.9529181112920
513544612.9914.9545182724531
1213544612.9914.95211011332112
1313544612.9914.9510554104
1813544612.9914.95154115158
1913544612.9914.95341618123422
2413544612.9914.954473724422
2613544612.9914.9548123614828
4313544612.9914.9528121622816
4413544612.9914.9513499139
4813544612.9914.95271611442715
5213544612.9914.95141135146
5513544612.9914.951798121712
5713544612.9914.9513943138
6113544612.9914.9546739664630
6413544612.9914.9532302793221
6713544612.9914.952191202114
6813544612.9914.95179821711
6913544612.9914.9552242815232
7513544612.9914.95871183
7613544612.9914.9535102523525
7813544612.9914.9540103014025
7913544612.9914.9546262024628
8013544612.9914.95201010332015
8213544612.9914.9542162644231
8313544612.9914.952161552113
8413544612.9914.9517512121711
8513544612.9914.9546123424628
8613544612.9914.9537181913730
9013544612.9914.95131032138
9213544612.9914.9511569119
9313544612.9914.95271314442717
9513544612.9914.95642563
9613544612.9914.95361125123619
10013544612.9914.953425933421
10713544612.9914.9534628663420
10813544612.9914.9545936794527
11113544612.9914.951551001511
12013544612.9914.9511742119
13713544612.9914.954383514328
13913544612.9914.9528101812816
14413544612.9914.9528111702818
14513544612.9914.9517980179
14613544612.9914.9542271504223
14713544612.9914.952071302010
15113544612.9914.9543271604326
15213544612.9914.954083204028 313544612.9914.9522121022214
413544612.9914.9529181112920
513544612.9914.9545182724531
1213544612.9914.95211011332112
1313544612.9914.9510554104
1813544612.9914.95154115158
1913544612.9914.95341618123422
2413544612.9914.954473724422
2613544612.9914.9548123614828
4313544612.9914.9528121622816
4413544612.9914.9513499139
4813544612.9914.95271611442715
5213544612.9914.95141135146
5513544612.9914.951798121712
5713544612.9914.9513943138
6113544612.9914.9546739664630
6413544612.9914.9532302793221
6713544612.9914.952191202114
6813544612.9914.95179821711
6913544612.9914.9552242815232
7513544612.9914.95871183
7613544612.9914.9535102523525
7813544612.9914.9540103014025
7913544612.9914.9546262024628
8013544612.9914.95201010332015
8213544612.9914.9542162644231
8313544612.9914.952161552113
8413544612.9914.9517512121711
8513544612.9914.9546123424628
8613544612.9914.9537181913730
9013544612.9914.95131032138
9213544612.9914.9511569119
9313544612.9914.95271314442717
9513544612.9914.95642563
9613544612.9914.95361125123619
10013544612.9914.953425933421
10713544612.9914.9534628663420
10813544612.9914.9545936794527
11113544612.9914.951551001511
12013544612.9914.9511742119
13713544612.9914.954383514328
13913544612.9914.9528101812816
14413544612.9914.9528111702818
14513544612.9914.9517980179
14613544612.9914.9542271504223
14713544612.9914.952071302010
15113544612.9914.9543271604326
15213544612.9914.954083204028 1 WEEKS DATA FEED IS AS HIGH AS
3 STACKED MT. EVEREST
830,000 EXCEL ROWS OF DATA70,000 ft. high
LHE
Assign Attributes to the Data
Onix Coding to Capture “Title DNA” (get it right the first time!)Sorted data relates to space productivity and category trends
“Control Tower” makes sure data tables are populated correctly
Regression and Correlation Analysis is a powerful tool to spot trends (you can run multiple regressions by loading the Data Analysis Add-On for Excel)
LHE
Customer Relationship Management
• Non-linear Regression—new data points create new demand outcomes that feed the supply chain
• Systems Communication—retailer demand forecasts need to drive print quantities so stock is available at the right time
• Returns—If we’re all making analytical decisions based on the same demand forecasts can we get rid of the old returns model?
LHE
The Future of Books in Big Box Retail (If past events are any indication)
LHE
1. Books will Remain an Important Margin Category for Retailers• Consolidation with electronics and media
52% 51% 48% 45% 41% 36% 33% 29%23%
1% 3% 5% 8% 12% 18% 25% 29% 36%
34% 35% 38% 40% 41% 40% 36% 36% 33%
13% 11% 9% 7% 6% 6% 7% 6% 8%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
2002 2003 2004 2005 2006 2007 2008 2009 2010
Unit (Physical Album) Market Share
Chain Outlets Non Traditional (On-Line) Mass Merchants Independents
Despite tremendous unit growth, the Digital Music Industry represents only 39% of the dollar sales. Digital Unit Growth has hit a Plateau 7 years after the iTunes launch. Mass Merchants are still a significant portion of Physical Album Sales
$11.3 $11.5 $10.5
$9.4 $7.5
$5.5 $4.3
$0.1 $0.2 $0.9
$1.6
$2.4
$2.6
$2.7
$-
$2.0
$4.0
$6.0
$8.0
$10.0
$12.0
$14.0
Year of iTunes
Year 1 after
iTunes
Year 2 after
iTunes
Year 3 after
iTunes
Year 4 after
iTunes
Year 5 after
iTunes
Year 6 after
iTunes
Sale
s $
(Bill
ions
)
Dollars
Physical CD (Full + Single) Download (Full + Single + Mobile)
Digital only 39% $ share
RIAA & Nielsen SoundScan
LHE
The Future of Books in Big Box Retail (If the past is any indication)
LHE
1. Books will Remain an Important Margin Category for Retailers• Consolidation with electronics and media
2. Juvenile Space will Increase Significantly Leading into Fall• Category is growing YOY and Returns are Decreasing• Mass Merchants have a very high market share in Young Reader and Young
Adult categories• Mass Merchants will continue to dominate share of novelty, movie tie-in
and event driven publishing events
LHE
As Adult Categories Continue to Shift Toward eBooks More merchandise space is Devoted to Juvenile
40.1%36.1% 36.0% 36.8% 36.4% 36.0% 35.7% 35.3% 35.0%
9.1%9.7% 9.8% 9.3% 8.9% 8.4% 8.0% 7.6% 7.2%
31.8%31.8% 31.1% 31.0% 30.7% 30.4% 30.1% 29.8% 29.5%
16.0%16.7% 17.5% 19.4% 20.3% 21.4% 22.4% 23.5% 24.7%
3.1% 5.7% 5.6% 3.5% 3.7% 3.8% 3.8% 3.8% 3.6%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
2007 2008 2009 2010 2011e 2012e 2013e 2014e 2015e
% o
f $ S
ales
Hardcover Mass Market Paperback Trade Paperback Kids YA
Historical – BookScan + non reporting chains, $’s extrapolatedProjection – Levy estimate
LHELHE
The Future of Books in Big Box Retail (If the past is any indication)
LHE
1. Books will Remain an Important Margin Category for Retailers• Consolidation with electronics and media• Some space loss, but not retailer profits
2. Juvenile Space will Increase Significantly as Endcap Space for AdultFiction Shrinks• Category is growing YOY and Returns are Decreasing
3. Market consolidation has historically been good for Big Box retailers when they can show a value
LHE
Similar to music, video, and greeting cards Mass Merchants can get a bigger piece of a shrinking pie by 2015
62.9% 60.5% 58.0%53.7%
46.7%41.1%
35.7%30.4%
25.2%
16.0% 17.6% 20.1%24.0%
31.9%36.7%
40.4%44.4%
48.8%
18.7% 19.5% 19.6% 19.9% 19.3% 20.0% 21.7% 23.0% 23.8%
2.5% 2.4% 2.3% 2.4% 2.1% 2.2% 2.2% 2.2% 2.1%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
2007 2008 2009 2010 2011e 2012e 2013e 2014e 2015e
% o
f $ S
ales
Retail (Bookstores) On-Line Mass Merchants / Clubs Specialty / Grocery / Drug
Historical – BookScan + non reporting chains, $’s extrapolatedProjection – Levy estimate
56.3%50.2% 54.5% 54.3% 53.1% 54.8% 54.7% 51.2%
25.6%31.9% 22.9% 25.6%
21.8%25.0% 22.6%
24.5%
16.1% 15.9%20.0% 17.9%
22.1%17.8% 19.9% 21.3%
2.0% 1.9% 2.6% 2.2% 3.0% 2.4% 2.7% 3.0%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
LY TY LY TY LY TY LY TY
January February March April
Retail (Bookstores) On-Line Mass Merchants / Clubs Specialty / Grocery / Drug
Excluding the Borders Liquidation, Recent Mass Merchant Market Shares are Close to Prior Year
Relatively Unchanged
Impact of Borders Liquidation
Based on market shifts we estimate print books will still be over $5.5 billion in 2015
$10,923 $10,963 $10,884 $10,024
$8,520 $7,668
$6,902 $6,211
$5,590
$96 $161 $323
$862
$1,768 $2,599
$3,171 $3,488
$3,662
0.9% 1.5%2.9%
7.9%
39.6%
0.0%
5.0%
10.0%
15.0%
20.0%
25.0%
30.0%
35.0%
40.0%
45.0%
$-
$2,000
$4,000
$6,000
$8,000
$10,000
$12,000
2007 2008 2009 2010 2011e 2012e 2013e 2014e 2015e
eBoo
k M
arke
t Sh
are
Boo
k Sa
les
(mill
ions
)
Total Market Print (Trade Channel) Total Market eBooks eBook Market Share
PrintBooks
eBooks
2010 to 2015 -44% +324%
Historical – AAP & BookScan (Trade Channel excludes Scholarly, K-12, University Press)
Projection – Levy estimate
Print Books$5.5 Billion
LHE
LHELHE
The Future of Books in Big Box Retail (If the past is any indication)
LHE
1. Books will Remain an Important Margin Category for Retailers• Consolidation with electronics and media• Some space loss, but not retailer profits
2. Juvenile Space will Increase Significantly as Endcap Space for AdultFiction Shrinks• Category is growing YOY and Returns are Decreasing
3. Market consolidation has historically been good for Big Box retailers when they can show a value
4. Economics of book retailing need to adapt to a new value benchmark
We must abandon the archaic business models of the past (push strategy) and adopt compatible demand planning and
analytics tools (pull strategy)