Adobe Digital Economy Project -- April 2017

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

© 2017 Adobe Systems Incorporated. All Rights Reserved.© 2017 Adobe Systems Incorporated. All Rights Reserved.
Main takeaways: April
2
 The Adobe DEP focuses on the U.K. this month, where the start of Brexit proceedings and the triggering of Article 50 appear to be dampening U.K. consumer
confidence. After a few months of mostly normal economic activity post-vote, the first quarter of 2017 shows a -4.9% YoY decline in spending on select
durables (computers and televisions) compared to the same category in the U.S. (13.9% YoY growth). Travel has remained unaffected, where revenue in
domestic and international flight bookings in 2017Q1 in the U.K. is up 14.0% YoY
 The DPI also shows that consumers in the U.K. are facing higher prices for food, where grocery prices have been rising since last September and are up 1.0%
YoY. Prices for televisions and computers are down YoY but deflation in computers is far from the level in the U.S. in the same category (prices down -0.2% YoY
in the U.K. compared to -3.5% YoY in the U.S.) Price declines for televisions are similar in the U.S. and the U.K.
 In the U.S., topline inflation is down across DPI categories (-0.1% in the all-items index and -0.2% in the all-items less grocery index). This is the first month of
deflation in the DPI following four straight months of inflation. Prices remain down year-over-year in both indexes (-0.6% in the all-items index and -1.3% in
the all-items less grocery index)
 Deflation is driven in April by a drop in prices for flights (down -0.5% MoM), flat prices in grocery (0.0% MoM inflation), and deflation in several durables categories including appliances (-0.5% MoM), computers (-
0.7% MoM), toys (-1.5% MoM), and tablets (-2.1% MoM)
 Grocery inflation in April is near-zero, but slightly positive, keeping grocery prices in the U.S. on track to show YoY inflation. Prices in the category are currently down -0.2% YoY. The largest price increases in the
category MoM included meats and poultry (0.9%), rice and pastas (0.5%), and breakfast foods (0.3%). These rises were offset by price declines in dairy including milk (-0.6%), other dairy (-0.9%), and eggs (-1.9%),
leading to overall unchanged prices
 The April DPI contains state-level inflation data for the third time. The state-level data show that half of U.S. states experienced deflation while half experienced
inflation
 26 of the 51 states and D.C. showed inflation in April, while the remainder showed deflation. State-level price changes depended in April on how prices changed in those states in flights, hotels, or groceries

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:
• $7.50ofevery $10spent online with top 500 U.S.retailers go through Adobe Experience Cloud **
• Adobe Experience Cloud powers:
• 20 ofthe top 30 U.S.employers
• 9 of10largest hotel groups
• 7of10largest airlines
**Latest IR Top 500 Report 2015
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

DPI Coverage of U.S. CPI Categories
9
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. DrugsCurrent DPI
To be added to DPI
Unlikely
Professional
services
Hospital
services

Big data in DPI decreases uncertainty
10
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
11
• 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
12
• 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
13
• 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
14
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)

Limited Economic Impact Immediately Post-Brexit
16
• In the weeks following Brexit, eCommerce activity in
the U.K. was normal
• Adobe Digital Insights (ADI) International Holiday
Report showed 11.0% YoY growth in holiday spending
in the U.K., the strongest in Europe
• ADI Europe Travel Report (forthcoming) shows
domestic and international flight bookings in the U.K.
dropped post-vote but rebounded back and travel
spending has shown strong growth YoY (revenue up
14% YoY in 2017Q1)

As Brexit Proceedings Start, Consumers Pull Back
17
26.4%
15.3%
13.9%
11.3% 11.3%
-4.9%
-10.0%
-5.0%
0.0%
5.0%
10.0%
15.0%
20.0%
25.0%
30.0%
Q32016 Q42016 Q12017
YoY Growth in Computers and TVs by Quarter, U.S. and U.K.
U.S. YoY Growth U.K. YoY Growth
• Consumer spending in computers and TVs, a
measure of consumer confidence, shows declines
YoY in the U.K. Revenue in the category is down
-4.9% YoY in 2017Q1, compared to an increase of
13.9% in the U.S.
• The Office of National Statistics (ONS) reported retail
sales fell -1.4% in 2017Q1, the first quarterly decline
since 2013.
• “This is the first time we’ve seen a quarterly decline
since 2013, and it seems to be a consequence of price
increases across a whole range of sectors.“ – Kate
Davies, ONS Senior Statistician 1
1
Office for National Statistics: Retail Sales in Great Britain: March 2017. Available at:
https://www.ons.gov.uk/businessindustryandtrade/retailindustry/bulletins/retailsales/mar2017

Consumers in the U.K. Continue to Face Higher Food Prices
18
• U.K. shoppers have seen grocery prices on the rise since last
summer, for six straight months, though prices are ticking down
slightly in April. Adobe DPI for the U.K. shows cumulative inflation
for groceries of 1.0% YoY (April 2016 to April 2017) though prices
are down MoM for the first time in six months (down -0.1%
MoM). Prices have been on the rise since September 2016
• U.K. computers and TVs are both showing YoY and MoM
deflation, but deflation in computers is less than steep deflation
for the same category in the U.S.
• Computers in the U.K. saw a -1.5% deflation in April; the category is still
showing -0.2% deflation YoY
• After two straight months of inflation in televisions, computers saw a ---
-3.2% deflation in April, bringing the category to -16.6% YoY

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

Consistent Inflation across the U.S., but prices down YoY
20
• Price changes are split in April : 26 out of 51 states plus D.C. are
showing price rises, while 25 states are showing price declines
• State inflation in April driven by travel and grocery prices:
States that show inflation in April tended to also have inflation in
flights, hotels, or groceries while states showing deflation had
deflation in some or all of those same categories

Travel driving price changes across states
21
Highest inflation by state
Lowest inflation by state
State April MoM Inflation Major Inflation Drivers
Rhode Island 1.0% Hotels**, Flights*
North Dakota 0.8% Flights*, Grocery
Iowa 0.8% Flights*, Hotels**
New York 0.6% Hotels**, Flights*
Connecticut 0.6% Hotels**, Flights*
State April MoM Deflation Major Deflation Drivers
Texas -0.7% Flights*, Grocery
Louisiana -0.8% Hotels**, Flights*
Utah -0.9% Groceries, Computers
Nevada -0.9% Hotels**, Grocery
Arizona -1.4% Hotels**, Flights*
* 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

March 2017 U.S. Recap
22
MoM: February
to March
MoM: February
to March
Difference
(percentage)
Same
Sign?
YoY: Cumulative March
2016-2017
YoY: Cumulative March
2016-2017
Difference
(percentage)
Same
Sign?
DPI CPI DPI vs. CPI DPI vs. CPI DPI CPI DPI vs. CPI DPI vs. CPI
Alcohol -0.2% 0.2% -0.4% No -0.9% 0.5% -1.4% No
Appliances 0.9% 0.1% 0.8% Yes -4.5% -2.8% -1.7% Yes
Auto Parts 0.0% 0.4% -0.4% Yes -1.3% -0.2% -1.1% Yes
Computers 0.9% -1.3% 2.2% No -4.9% -5.5% 0.6% Yes
Flights 3.2% 1.1% 2.1% Yes 5.0% -0.2% 5.2% No
Furniture and bedding -0.5% -0.1% -0.4% Yes -4.2% -1.8% -2.3% Yes
Grocery 0.1% 0.1% 0.0% Yes -0.4% -0.9% 0.5% Yes
Hotels 2.3% 0.0% 2.3% No 3.7% 0.0% 3.7% No
Medical equipment and supplies -0.7% -0.1% -0.6% Yes -1.3% 1.0% -2.3% No
Nonprescription drugs -0.1% 0.6% -0.7% No 0.6% 1.1% -0.5% Yes
Personal care products 0.5% -0.6% 1.1% No -1.3% -1.3% 0.0% Yes
Pet Products -0.1% 0.0% -0.1% No -0.7% -0.3% -0.4% Yes
Sporting goods 0.0% -0.5% 0.5% No -5.2% -1.6% -3.6% Yes
Televisions 0.6% -0.5% 1.1% No -17.5% -18.9% 1.4% Yes
Tools & Home Improvement -0.2% 0.1% -0.3% No -2.2% -0.9% -1.3% Yes
Toys -0.6% -1.3% 0.7% Yes -4.9% -8.3% 3.4% Yes
Weighted Average Inflation* 0.3% 0.0% 0.3% Yes -0.8% -1.1% 0.3% Yes
Weighted Aggregate Inflation, Less
Grocery** 0.5% 0.0% 0.6% No -1.3% -1.4% 0.1% Yes
* Weighted average inflation is calculated using CPI-U relative component weights (2014-2015) across the shared categories in the DPI and the CPI
** 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.

April 2017 U.S. Summary
23
• Main MoM inflation in April:
• International flights, international hotels,
personal care products
• Main MoM deflation in April:
• Tablets, toys, medical equipment and supplies
YoY MoM
Alcohol -0.9% 0.0%
Appliances -3.9% -0.5%
Auto Parts -1.2% 0.0%
Computers -3.5% -0.7%
Electronics -8.9% -0.7%
Flights 6.2% 0.3%
Domestic Flights 5.5% -0.5%
Intl Flights 7.4% 3.1%
Furniture and bedding -3.8% -0.2%
Grocery -0.2% 0.0%
Hotels 2.2% 0.1%
Intl Hotels -1.2% 1.5%
Medical equipment and supplies -2.5% -1.2%
Nonprescription drugs -0.1% -0.1%
Personal care products -1.7% 0.2%
Pet Products 0.8% 0.1%
Sporting goods -5.8% -1.3%
Tablets -15.5% -2.1%
Televisions -15.8% 0.5%
Tools & Home Improvement -2.5% -0.5%
Toys -4.7% -1.5%
Weighted Average Inflation* -0.6% -0.1%
Weighted Aggregate Inflation, Less Grocery** -1.3% -0.2%
* Weighted average inflation is calculated using CPI-U relative component weights (2014-2015) across the shared categories in the DPI and the CPI
** 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
24
• Adobe DPI shows cumulative deflation of -0.9% YoY (April
2016 to April 2017)
• Prices for Beer show cumulative inflation of 2.9% YoY
• Prices for Spirits show cumulative inflation of 0.2% YoY
• Prices for Wine show cumulative deflation of -3.0% YoY
• For April 2017, prices increased 0.0% vs March 2017 MoM
METHODOLOGY:
• The data used reflect transactions for ~120 K products

Appliances
25
2016 to April 2017)
• Main YoY price decreases for Appliances priced between $200
and $400
• For April 2017, prices decreased -0.5% vs March 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
26
2016 to April 2017)
• Main YoY price decreases for Auto Parts priced greater than
$200
METHODOLOGY:
• The data used reflect transactions for ~300 K products

Airfare
27
• Adobe DPI shows cumulative inflation of 6.2% YoY (April
2016 to April 2017)
METHODOLOGY:
• The data used contains transactions for ~370 K flight routes
• Includes associated fees, where applicable

Airfare: domestic
28
2016 to April 2017)
• Largest monthly inflation to South Dakota (14.1% MoM), North
Dakota (12.7% YoY), and West Virginia (8.8% YoY)
• Largest monthly deflation to Colorado (-3.9% MoM), Arizona (-
3.1%) and Oregon (-.3.0%)
• For March 2017, prices decreased 0.5% vs February 2017
MoM
METHODOLOGY:

Airfare: international
29
• Adobe DPI shows cumulative inflation of 7.4% YoY (April 2016
to April 2017)
• Largest price increases for airfare were to South America, with
inflation of 21.6% YoY
• Largest price decreases are for airfare to Europe with deflation of -
3.4% YoY
METHODOLOGY:

Electronics
30
2016 to April 2017)
• Main YoY price decreases for Electronics priced greater than
$1500
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
31
2016 to April 2017)
• Main YoY price decreases for Computers priced between $700
and $1200
• Main YoY price increases for Computers priced between $0 and
$300
METHODOLOGY:

Electronics: televisions
32
2016 to April 2017)
• Main YoY price decreases for Televisions priced greater than
$2000
METHODOLOGY:

Electronics: tablets
33
2016 to April 2017)
• Main YoY price decreases for Tablets priced between $550 and
$900
METHODOLOGY:

Furniture and Bedding
34
2016 to April 2017)
• Main YoY price decreases for Furniture and bedding priced
between $150 and $250
METHODOLOGY:
• Products include interior and exterior furniture, mattresses and other bedding products

Groceries
35
2016 to April 2017)
• Main YoY deflation for eggs (-16.6%), beverages (-1.8%)
and flour (-1.5%)
• Main price increases for meats, poultry (inflation 0.9%
MoM), rice and pasta (0.5% MoM). breakfast (0.3%
inflation MoM)
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
36
METHODOLOGY:
• The data used contains transactions for ~250 K hotel properties
2016 to April 2017)
• Largest inflation in April in Massachusetts (7.6% MoM),
New York (6.0%), Rhode Island (5.5%)
• Largest deflation in April in to Airzona (-16.4%), Florida
(-8.8%), and Washington D.C. (-.5.4%)

Hotels: international
37
METHODOLOGY:
• The data used contains transactions for ~250 K hotel properties
2016 to April 2017)
• Largest price increases were for hotels in North America
(4.0% inflation YoY)
• Largest price decreases were for hotels in Asia (-2.3%
deflation YoY)

Medical Equipment and Supplies
38
2016 to April 2017)
• Main YoY price decreases for Medical equipment and supplies
priced between $45 and $135
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
39
2016 to April 2017)
• Main YoY price decreases for Nonprescription Drugs priced
between $0 and $10
• Main YoY price increases for Nonprescription Drugs priced
between $25 and $40
METHODOLOGY:
• Includes all non-prescription medicines taken by swallowing, applying on your skin (such as topicals), inhaling, as suppositories, or enemas.

Personal care products
40
2016 to April 2017)
• Main YoY price decreases for Personal care products priced
between $10 and $30
• Main YoY price increases for Personal care products priced
greater than $150
METHODOLOGY:
• Includes cosmetics, lotion, hair (shampoo, conditioner) and nail care

Pet products
41
2016 to April 2017)
• Main YoY price decreases for Pet Products priced between $10
and $20
• Main YoY price increases for Pet Products priced between $0
and $10
METHODOLOGY:
• Includes pet food & treats, kitty litter and accessories (leashes, pet beds)

Sporting Goods
42
2016 to April 2017)
• Main YoY price decreases for Sporting Goods priced between
$200 and $350
METHODOLOGY:
• Products include small equipment and accessories (balls, gloves, uniforms) as well as large equipment such as treadmills, weightlifting tools etc.

Tools & Home Improvement
43
2016 to April 2017)
• Main YoY price decreases for Tools & Home Improvement priced
between $140 and $280
METHODOLOGY:

Toys
44
2016 to April 2017)
• Main YoY price decreases for Toys priced between $70 and $200
METHODOLOGY:
• Products include toys, games as well as playground equipment

Job Seeking Index
(JSI)

Online job seeking continues YoY declines
46
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**
US online job seeking is down -18.1% YoY in April

Digital Housing Index
(DHI)

Online housing search grows YoY
48
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 10.0% YoY
in April.

Appendix
49

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 -- April 2017

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