Adobe Digital Economy Project -- November 2017

© 2017 Adobe Systems Incorporated. All Rights Reserved.
ADOBE DIGITAL ECONOMY PROJECT
NOVEMBER 2017 UPDATE

© 2017 Adobe Systems Incorporated. All Rights Reserved.© 2017 Adobe Systems Incorporated. All Rights Reserved.
Main Takeaways: November
2
 In the U.S., topline inflation is down in November across DPI categories for the first time after two months of inflation (-0.9% in the all-items index and -1.1% in
the all-items less grocery index). Prices are slightly up in the year-over-year in the all-items index (0.3%) and down for the all-items less grocery index (-1.1%).
 In November, monthly deflation was driven by consumer products, consistent with the holiday shopping season: televisions (-9.4%), tablets (-6.9%), and
appliances (-7.1%).
 In the midst of the holiday travel booking season all flights showed 1.7% MoM inflation, while domestic flights increased 1.3% MoM. Consistent with typical
travel patterns, international and domestic hotels showed month-over-month deflation (-1.1% and -4.6%, respectively).
 In grocery, deflation in November (-0.5%) was driven by beverages materials including coffee and tea (-1.6%), ice cream and related products (-1.5%), fats and
oils (-1.0%).
 Across the pond, consumers in the U.K. are facing continued price rises in grocery prices., where food prices are up 0.4% MoM in November resulting in a 3.8%
year-over-year for the twelve months ending in November
 Contrary to last month where almost all states showed inflation, all states in November showed deflation consistent with nationwide holiday discounts

Adobe Digital Insights Background
Based on analysis ofaggregated and anonymous data from Adobe Experience Cloud:
• Adobe Analytics and Adobe Mobile Services
Thousands of brands worldwide including two thirds of Fortune 50 companies rely on Adobe
Experience Cloud:
• Adobe Experience Cloud powers:
• 20 ofthe top 30 U.S.employers
• 9 of10largest hotel groups
• 7of10largest airlines
3
Adobe
Analytics
Adobe
Mobile Services

Economist Advisors
4
Austan Goolsbee, University of Chicago
 Robert P. Gwinn Professor of Economics at The University of Chicago's Booth School of Business
 Formerly served as President Obama’s Chairman of the Council of Economic Advisers
 Served as the youngest member of President Obama’s cabinet
Pete Klenow, Stanford University
 Professor, Department of Economics, Stanford University
 Currently Visiting Scholar, Federal Reserve Bank of San Francisco
 Member of editorial boards for Econometrica, American Economic Review, Quarterly Journal of Economics and others

© 2017 Adobe Systems Incorporated. All Rights Reserved.© 2017 Adobe Systems Incorporated. All Rights Reserved. 5
Digital Price Index
(DPI)
Job Seeking Index
(JSI)
Digital Housing Index
(DHI)

Digital Price Index Methodology
(DPI)

Methodology – U.K.
7
Based on analysis of aggregated and anonymous data
• Fisher Ideal Price Index
• $6 of every $10 spent online with top 100 European retailers go through Adobe Experience Cloud **
• Based on analysis 1 billion website visits and 100k products sold online
ONS: Consumer Price Index Adobe: Digital Price Index
Quantities Sold No Yes
Products/quantities updated Annually Daily
Number of Products 180,000
100k
(currently covered categories)
Data Collection Frequency Monthly Daily
Data Availability Monthly Daily
Offline Prices Yes No
Long history Yes No
All categories of spending Yes No
** Latest IR U.K. Top 500 Report 2015

Methodology – U.S.
8
Based on analysis of aggregated and anonymous data
• Fisher Ideal Price Index
• Adobe measures 80% of all online transactions from top 100 U.S. retailers **
• $7.50 of every $10 spent online with top 500 U.S. retailers go through Adobe Experience Cloud **
• Based on analysis of 15 billion website visits and 2.2 million products sold online
BLS: Consumer Price Index
BEA: Personal Consumption
Expenditures
Adobe: Digital Price Index
Quantities Sold No No Yes
Products/quantities updated Every 2 years Monthly Daily
Number of Products 83 thousand (all categories) 83 thousand (all categories)
2.5 million
(currently covered categories)
Data Collection Frequency Bi-Monthly Monthly Daily
Data Availability Monthly Monthly Daily
Offline Prices Yes Yes No
Long history Yes Yes No
All categories of spending Yes Yes No
Index Type Laspeyeres Fisher Ideal Fisher Ideal
** Latest IR Top 500 Report 2015

Big data in DPI decreases uncertainty
9
DPI CPI
Appliances 0.15% 0.46%
Airfare 0.08% 0.51%
Computers 0.28% 0.49%
Furniture and bedding 0.07% 0.31%
Grocery 0.10% 0.12%
Hotels: domestic 0.04% 2.30%
Medical equipment and supplies 0.20% 0.39%
Nonprescription Drugs 0.18% 0.47%
Sporting Goods 0.12% 0.31%
Televisions 0.24% 0.60%
Toys 0.25% 0.59%

Inflation rates by price ranges
10
• Televisions have seen higher-ticket items
deflate faster than lower-ticket items in 2015
• For computers, mid-range models priced
between $700 and $1,200 showed the
highest deflation last year
*Price bins are determined based on the price the product had when originally launched
(first price).

The Importance of detail: Black Friday discount comparisons
11
• DPI captures the effect of major discount holidays
like Black Friday and Cyber Monday because it
measures quantities and does so in real-time
• Prices online for Televisions dropped later in
November 2016 than in 2015, with more discounts
during the Black Friday week (Monday 11/21 through
Cyber Monday), which accounted for more than half
of all Televisions units purchased between
November and December
• Television prices then increased more in December
2016 than they did in December 2015, a sign that
retailers were able to capitalize on later shopping

Measuring rapidly shifting consumer preferences
12
• Electronics see an average of 77% of online
spend on new* products**
• 17% of monthly online spend for groceries
on new products
* Products that have been available for 1 year or less
** A product is defined as an item for purchase which has an unique identifier (such as a SKU)

State-by-state inflation: examples of sources of variance
13
1. Different baskets across states
• Consumers in western states buy more on organic fruits and vegetables than other regions
• Consumers in southern states buy more meats, poultry and fish than other regions
2. Different shopping attitudes, preferences across states
• Consumers in states with lower median incomes tend to shop more on heavy-promotion days
3. Different prices for same products across states
• Price-only variances across states tend to be bigger in groceries and smaller in consumer electronics

Digital Price Index Findings, U.K.
(DPI)

U.K. Food Prices Up Over 3.5% year-over-year
15
• U.K. grocery prices recorded another month of inflation in
November, the seventh month in a row after a one-month
reprieve from rising food prices in April. The Adobe DPI for the
U.K. shows cumulative inflation for groceries of 3.8% YoY
(November 2016 to November 2017). Prices are up 0.4% MoM.
Prices have been on the rise since October 2016.
• In the U.K. computers and televisions both recorded deflation in
November, reflective of holiday discounts.
• Computers in the U.K. saw a -2.7% deflation in November and as a
result the category is showing a -1.4% deflation YoY.
• Televisions recorded significant deflation in November due to holiday
sales: TVs in the U.K. saw a -7.1% deflation in November, bringing the
category to -20.1% YoY.

Digital Price Index Findings, U.S.
(DPI)

Nationwide deflation in November
17
• All states show deflation in November: consistent with a
national downturn in prices for the holiday season, all states
showed deflation in November

Variation in prices for travel across states drives regional changes
18
Lowest deflation
Highest deflation by state
State Oct. MoM Inflation Major Inflation Drivers
Florida -0.3% Televisions, Appliances
Nebraska -0.6% Televisions, Computers
Hawaii -0.7% Televisions, Appliances
Alaska -0.7% Televisions, Appliances
Washington -0.7% Televisions, Appliances
State
Oct. MoM
Inflation/Deflation Major Deflation Drivers
Maine -1.4% Hotels**, Televisions
Ohio -1.5% Televisions, Computers
South Dakota -1.5% Televisions, Computers
Wyoming -1.6% Televisions, Computers
Vermont -1.7% Hotels**, Computers
* Flight prices are determined by the state of flight origin
** Hotel prices reflect hotel properties in a given state
*** New categories introduced in this month’s Adobe DPI

October 2017 U.S. Recap
19
MoM:
September to
October
MoM:
September to
October
Difference
(percentage)
Same
Sign?
YoY: Cumulative October
2016-2017
YoY: Cumulative October
2016-2017
Difference
(percentage)
Same
Sign?
DPI CPI DPI vs. CPI DPI vs. CPI DPI CPI DPI vs. CPI DPI vs. CPI
Alcohol 0.7% 0.4% 0.3% Yes 3.0% 1.2% -0.5% Yes
Appliances 1.0% -0.6% 1.6% No -2.6% -1.3% -1.3% Yes
Apparel 0.7% 1.1% -0.4% Yes -5.3% -0.5% -4.7% Yes
Auto Parts 0.2% -0.7% 0.9% No 1.5% -0.5% 2.0% No
Computers -0.3% 0.2% -0.5% No -4.4% -3.2% -1.2% Yes
Flights 3.0% 3.1% -0.1% Yes 3.8% 12.6% -8.8% Yes
Furniture and bedding 0.3% -0.4% 0.7% No -5.6% -1.3% -4.3% Yes
Grocery 0.7% 0.2% 0.5% Yes 2.0% 0.6% 1.4% Yes
Hotels -2.1% -0.6% -1.5% Yes 3.4% 3.8% -0.4% Yes
Jewelry 0.6% -0.1% 0.7% No -4.2% 3.3% -7.5% No
Medical equipment and supplies 0.1% -0.2% 0.3% No -0.1% 0.4% -0.5% No
Nonprescription drugs 0.6% 0.2% 0.4% Yes 1.9% 0.4% 1.5% Yes
Personal care products 0.2% 0.1% 0.1% Yes 0.1% -0.7% 0.8% No
Pet Products 1.3% 0.1% 1.2% Yes 1.2% -0.7% 1.9% No
Sporting goods 0.5% -0.1% 0.6% No -2.4% -2.1% -0.3% Yes
Televisions -1.6% -2.6% 1.0% Yes -11.7% -10.3% -1.4% Yes
Tools & Home Improvement 0.4% 0.5% -0.1% Yes -0.6% -0.8% 0.2% Yes
Toys -1.1% 0.0% -1.1% No -3.9% -8.0% 4.1% Yes
Weighted Average Inflation* 0.5% 0.3% 0.2% Yes -0.1% 0.4% -0.6% No
Weighted Aggregate Inflation, Less
Grocery** 0.5% 0.5% 0.0% Yes -1.8% 0.3% -2.1% No
* Weighted average inflation is calculated using CPI-U relative component weights (2014-2015) across the shared categories in the DPI and the CPI, less apparel
** Grocery is a large component of the current CPI weights, so changes in grocery prices drive the majority of weighted average inflation. As we add more categories (like housing, auto etc.), these
aggregate numbers will change
*** New category addition to DEP this month
*** New categories introduced in this month’s Adobe DPI

November 2017 U.S. Summary
20
• Main MoM inflation in November:
• Int’l flights, domestic flights, pet products
• Main MoM deflation in November :
• Televisions, appliances, tablets
YoY MoM
Alcohol 4.7% 0.2%
Apparel -4.6% -0.4%
Appliances -3.0% -7.1%
Auto Parts 1.5% -0.8%
Computers -5.4% -3.1%
Electronics -4.8% -4.4%
Flights 3.8% 1.7%
Domestic Flights 3.2% 1.3%
Intl Flights 6.4% 3.3%
Furniture and bedding -4.5% -1.3%
Grocery 2.0% -0.5%
Domestic Hotels 3.3% -4.6%
Intl Hotels 6.3% -1.1%
Jewelry -5.5% -2.8%
Medical Equipment and Supplies -2.0% -1.1%
Nonprescription Drugs 2.0% 0.1%
Personal Care Products 2.4% -0.2%
Pet Products 3.4% 0.5%
Sporting Goods -1.1% -3.2%
Tablet -15.3% -6.9%
Televisions -8.1% -9.4%
Tools & Home Improvement -0.3% -1.0%
Toys -3.4% -4.0%
Weighted Average Inflation* 0.3% -0.9%
Weighted Aggregate Inflation, Less Grocery** -1.1% -1.1%
* Weighted average inflation is calculated using CPI-U relative component weights (2014-2015) across the shared categories in the DPI and the CPI, less apparel
** Grocery is a large component of the current CPI weights, so changes in grocery prices drive the majority of weighted average inflation. As we add more categories (like housing, auto etc.), these aggregate
numbers will change

Alcohol
21
• Adobe DPI shows cumulative inflation of 4.7% YoY
(November 2016 to November 2017)
• Prices for Beer show cumulative inflation of 1.4% YoY
• Prices for Spirits show cumulative inflation of 2.7% YoY
• Prices for Wine show cumulative inflation of 5.2% YoY
• For November 2017, prices increased 0.2% vs October 2017
MoM
METHODOLOGY:
• The data used reflect transactions for ~120 K products
4.7%

Apparel
22
• Adobe DPI shows cumulative deflation of -4.6% YoY
• For November 2017, prices decreased -0.4% vs November
2017 MoM
METHODOLOGY:
• The data used contains transactions for ~1.5 m products
• Products include clothes for women, men, boys, girls, infants, and footwear

Appliances
23
• Main YoY price decreases for Appliances priced between $200
and $400
• For November 2017, prices decreased -7.1% vs October 2017
MoM
METHODOLOGY:
• The data used contains transactions for ~110 K products
• Products include large appliances such as fridges, ovens, washers, dryers as well as smaller appliances such as vacuums, mixers, blenders etc.

Auto Parts
24
• Main YoY price increases for Auto Parts priced between $110 and
$140
• For November 2017, prices decreased -0.8% vs October
2017 MoM
METHODOLOGY:
• The data used reflect transactions for ~300 K products

Airfare
25
MoM
METHODOLOGY:
• The data used contains transactions for ~370 K flight routes
• Includes associated fees, where applicable

Airfare: domestic
26
• Largest monthly inflation for flights to and from Alaska (9.0%),
Washington (4.5%), and Colorado (3.4%)
MoM
METHODOLOGY:

Airfare: international
27
• Adobe DPI shows cumulative inflation of 6.4% YoY (November
2016 to November 2017)
• Largest monthly inflation for flights to and from South America
(7.3%), Asia (4.6%) and Africa (1.7%)
MoM
METHODOLOGY:

Electronics
28
• Main YoY price decreases for Electronics priced greater than
$1500
• For November 2017, prices decreased -4.4% vs. October
2017 MoM
METHODOLOGY:
• The data used contains transactions for ~1 M products
• Products span across dozens of diﬀerent categories such as televisions, laptops, Blu-ray players, desktops, tablets, wearables, headphones, video games,printersetc..

Electronics: computers
29
• Main YoY price decreases for Computers priced between $1200
and $1600
• Main YoY price increases for Computers priced between $0 and
$300
MoM
METHODOLOGY:

Electronics: televisions
30
• Main YoY price decreases for Televisions priced greater than
$2000
• Main YoY price increases for Televisions priced between $0 and
$300
MoM
METHODOLOGY:

Electronics: tablets
31
• Main YoY price decreases for Tablets priced between $550 and
$900
2017 MoM
METHODOLOGY:

Furniture and Bedding
32
• Main YoY price decreases for Furniture and bedding priced
between $100 and $150
MoM
METHODOLOGY:
• Products include interior and exterior furniture, and mattresses

Groceries
33
2017 MoM
• Main MoM inflation in beverages materials including
coffee and tea (-1.6%), ice cream and related products (-
1.5%), fats and oils (-1.0%).
METHODOLOGY:
• Our dataset covers an estimated 30-40% of all online grocery purchases. It contains transactions for ~195k products
• The mix of grocery products bought online is not the same as oﬄine – the top category for online shopping is drinks (nonalcoholic), while for oﬄine shopping it is meat

Hotels: domestic
34
METHODOLOGY:
• The data used contains transactions for ~250 K hotel properties
• Largest inflation in October in Florida (6.5%), Arizona
(4.7%), Louisiana (4.5%)
• Largest deflation in November in Massachusetts (-
16.0%), Vermont (-12.5%), and D.C. (-11.8%)
2017 MoM

Hotels: international
35
METHODOLOGY:
• The data used contains transactions for ~250 K hotel properties
• Largest price decreases were for hotels in North America
(4.5% deflation MoM)
• Largest price increases were for hotels in South America (-
1.7% inflation MoM)
MoM

Jewelry
36
METHODOLOGY:
• The data used contains transactions for ~300K products
• Includes men’s and women’s rings, necklaces, watches, bracelets, earrings, etc.
MoM

Medical Equipment and Supplies
37
• Main YoY price decreases for Medical equipment and supplies
priced greater than $135
• Main YoY price increases for Medical equipment and supplies
priced between $0 and $10
MoM
METHODOLOGY:
• The data used contains transactions for ~6,000 products
• Includes supportive and convalescent equipment, dressings and first aid kits, and medical equipment for general use

Nonprescription drugs
38
• Main YoY price decreases for Nonprescription Drugs priced
greater than $40
• Main YoY price increases for Nonprescription Drugs priced
between $0 and $10
MoM
METHODOLOGY:
• Includes all non-prescription medicines taken by swallowing, applying on your skin (such as topicals), inhaling, as suppositories, or enemas.

Personal care products
39
• Main YoY price increases for Personal care products priced
between $0 and $10
2017 MoM
METHODOLOGY:
• Includes cosmetics, lotion, hair (shampoo, conditioner) and nail care

Pet products
40
• Main YoY price increases for Pet Products priced between $0
and $10
MoM
METHODOLOGY:
• Includes pet food & treats, kitty litter and accessories (leashes, pet beds)

Sporting Goods
41
• Main YoY price decreases for Sporting Goods priced between
$100 and $200
• Main YoY price increases for Sporting Goods priced greater than
$350
MoM
METHODOLOGY:
• Products include small equipment and accessories (balls, gloves, uniforms) as well as large equipment such as treadmills, weightlifting tools etc.

Tools & Home Improvement
42
• Main YoY price decreases for Tools & Home Improvement priced
between $140 and $280
• Main YoY price increases for Tools & Home Improvement priced
between $0 and $50
MoM
METHODOLOGY:

Toys
43
• Main YoY price decreases for Toys priced between $70 and $200
2017 MoM
METHODOLOGY:
• Products include toys, games as well as playground equipment

Job Seeking Index
(JSI)

Online job seeking continues YoY declines
45
METHODOLOGY:
• Based on analysis of aggregated and anonymous data from more than 1 billion visits to U.S. employment-search websites and top employer career pages
• Adobe Experience Cloud powers 20 of the top 30 U.S. employers**
U.S. online job seeking is down -17.7% YoY in November.

Digital Housing Index
(DHI)

Online housing search grows YoY
47
METHODOLOGY:
• Based on analysis of aggregated and anonymous data from more than 2 billion visits to U.S. housing search websites
Online search for purchases and rentals is up 11.3% YoY
in November.

Appendix
48

DPI Coverage of U.S. CPI Categories
49
DPI Category
February 2017 DPI Weights
All-Items All-Items Minus Groceries
Grocery 54.00% N/A
Furniture and bedding 5.16% 11.22%
Hotels 4.99% 10.85%
Personal care products 4.79% 10.40%
Tools & Home Improvement 4.61% 10.03%
Flights 4.27% 9.27%
Pet Products 4.01% 8.72%
Alcohol 3.99% 8.68%
Sporting goods 2.95% 6.40%
Auto Parts 2.62% 5.71%
Nonprescription drugs 2.45% 5.33%
Toys 2.00% 4.35%
Computers 1.87% 4.07%
Appliances 1.21% 2.63%
Televisions 0.66% 1.44%
Medical equipment and supplies 0.41% 0.89%
Shelter
Food Away
From Home
Vehicles Apparel
Electricity,
gas etc.
Grocery
Furniture
Lodging
Personal Care
Np. Drugs
To be added to DPI
Professional
services
Hospital
services
Current DPI
Unlikely

Inflation rates by price ranges, cont’d (tablets)
50
• Tablets have seen higher-ticket items deflate
faster than lower-ticket items
• The greatest price decrease and increase in
November and December were for tablets
priced between $350 and $600
(first price).

Inflation rates by price ranges, cont’d (televisions)
51
• The highest priced televisions have have
seen faster deflation than lower priced items
• The greatest price decrease in November
and increase in December were for TVs
priced between $600 and $1,000
(first price).

Inflation rates by price ranges, cont’d (televisions)
52
• Mid-range computers have seen faster
deflation than lower and higher priced
models
• The greatest price decrease in November
were for mid range computers between
$700 and $1,200 while the greatest price
increase in December were for lower priced
models between $300 and $700
(first price).

Digital Price Index: Fisher Ideal Price Index
∑𝑖𝑖=1
𝑛𝑛
𝑃𝑃𝑖𝑖𝑖𝑖 𝑈𝑈𝑖𝑖𝑖𝑖−1
∑𝑖𝑖=1
𝑛𝑛
𝑃𝑃𝑖𝑖𝑖𝑖−1 𝑈𝑈𝑖𝑖𝑖𝑖−1
∗
∑𝑖𝑖=1
𝑛𝑛
𝑃𝑃𝑖𝑖𝑖𝑖 𝑈𝑈𝑖𝑖𝑖𝑖
∑𝑖𝑖=1
𝑛𝑛
𝑃𝑃𝑖𝑖𝑖𝑖−1 𝑈𝑈𝑖𝑖𝑖𝑖
• The Fisher Ideal Price Index uses quantities purchased on the current period (month) and a previous period
(previous month) to determine actual consumer’s preferences. Instead of assuming that consumers
preferences for what goods to buy are constant over a certain number of years, it is able to account for the fact
that they are constantly changing what they buy.
𝐹𝐹𝐹𝐹𝐹𝐹 𝐹𝐹𝐹𝐹𝐹 𝜋𝜋𝑡𝑡 =

Methodology Comparison: Fisher, Laspeyres and Paasche

Adobe Digital Economy Project -- November 2017

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