Adobe Digital Economy Project -- July 2017

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

© 2017 Adobe Systems Incorporated. All Rights Reserved.© 2017 Adobe Systems Incorporated. All Rights Reserved.
Main Takeaways: July
2
 In the U.S., topline inflation is down across DPI categories for the fourth month in a row (-0.3% in the all-items index and -0.8% in the all-items less grocery
index). This is the fourth month of deflation in the DPI following four straight months of inflation. Prices remain down year-over-year in the all-items index
(-0.7%) and down for the all-items less grocery index (-2.0%)
 The Adobe DPI for July now includes jewelry, a category which includes men’s and women’s rings, necklaces, watches, and other accessories. The category is
up 0.4% in July, consistent with seasonal price changes for this category in the past. Year-over-year, prices are down -1.9% from July 2016.
 Inflation in July in the U.S. affected travelers purchasing hotels domestically, where inflation is 0.6% month over month. Other categories showing inflation
include auto parts (0.7%) and groceries (0.4%).
 In July, deflation was concentrated in domestic flights (-5.4% MoM) and tablets (-3.2% MoM), and apparel (-1.5%). The sharp decline in flight prices is consistent
with the monthly seasonality of the summer travel season as domestic flight prices tend to drop in July.
 In grocery, inflation in July was driven by staples: in July MoM inflation was highest in dairy products other than cheese and milk (1.5%), breakfast cereals
(0.9%), and cheese and related products (0.8%).
 Across the pond, consumers in the U.K. are facing continued price rises in grocery prices., where food prices are up 0.2% MoM in July and up 2.5% year-over-
year for the twelve months ending in July.
 Twenty states in the U.S. show inflation in July, while 31 states and D.C. show deflation. Price declines for flights across states drove deflation for states that
showed overall price declines, while price increases for hotels drove inflation for those states that showed price increases.

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

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 Nearly Two Percent Year-Over-Year
15
• U.K. grocery prices show inflation again in July, the third month in
a row after a one-month reprieve from rising food prices in April.
Adobe DPI for the U.K. shows cumulative inflation for groceries of
2.5% YoY (July 2016 to July 2017). Prices are up 0.2% MoM. Prices
have been on the rise since September 2016
• U.K. computers and televisions show YoY deflation through June
2017; prices have been declining in both categories since February.
• Computers in the U.K. saw a -10% deflation in July and as a result the
category is showing a -0.3% deflation YoY.
• Televisions continue to deflate in July, TVs in the U.K. saw a -0.8%
deflation in July, bringing the category to -16.9% YoY.

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

Slower inflation and deflation in June
17
• Price changes lean towards deflation in July: 31 out of 50 states
plus D.C. are showing price declines, while only 20 states are
showing price increases

Hotel Prices Driving Inflation, Flights Driving Deflation
18
Highest inflation by state
Lowest inflation by state
State July MoM Inflation Major Inflation Drivers
Wyoming 1.1% Hotels**, Alcohol
Maine 0.6% Hotels**, Medical Equipment and Supplies
Vermont 0.6% Alcohol, Computers
Montana 0.5% Hotels**, Grocery
New York 0.4% Hotels**, Auto Parts
State July MoM Deflation Major Deflation Drivers
Colorado -0.4% Flights*, Computers
Mississippi -0.4% Flights*, Computers
Illinois -0.6% Flights*, Computers
South Carolina -0.6% Computers, Flights*
Alaska -0.8% Hotels***, Alcohol
* 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

June 2017 U.S. Recap
19
MoM: April to
June
MoM: April to
June
Difference
(percentage)
Same
Sign?
YoY: Cumulative June
2016-2017
YoY: Cumulative June
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% -0.4% 0.2% Yes -1.6% 0.1% -0.3% No
Appliances -1.6% -1.1% -0.5% Yes -4.1% -3.4% -0.7% Yes
Apparel -1.8% -1.5% -0.3% Yes -4.1% -0.6% -3.4% Yes
Auto Parts 0.5% 0.1% 0.4% Yes -0.4% -0.2% -0.1% Yes
Computers 0.3% 0.5% -0.2% Yes -2.0% -4.3% 2.3% Yes
Flights -0.6% -1.4% 0.8% Yes 3.6% -4.4% 8.0% No
Furniture and bedding -0.6% 0.0% -0.6% No -4.3% -0.8% -3.5% Yes
Grocery 0.3% -0.3% 0.6% No 0.3% -0.1% 0.4% No
Hotels 0.9% 1.1% -0.2% Yes 5.0% -0.5% 5.6% No
Jewelry*** -0.8% -2.0% 1.2% Yes -4.1% 1.4% -5.5% No
Medical equipment and supplies 0.9% -0.3% 1.2% No -0.4% -0.1% -0.3% Yes
Nonprescription drugs 0.6% 0.0% 0.6% No 1.0% 1.3% -0.3% Yes
Personal care products 0.0% 0.3% -0.3% Yes -0.9% -0.6% -0.3% Yes
Pet Products 0.0% -0.3% 0.3% Yes 0.5% -0.8% 1.3% No
Sporting goods -0.4% -0.1% -0.3% Yes -5.6% -2.0% -3.6% Yes
Televisions -0.2% 2.7% -2.9% No -13.2% -11.4% -1.8% Yes
Tools & Home Improvement -0.3% -0.3% 0.0% Yes -1.0% -0.3% -0.7% Yes
Toys -0.1% -1.1% 1.0% Yes -6.1% -9.0% 3.0% Yes
Weighted Average Inflation* -0.2% -0.4% 0.2% Yes -0.9% -0.7% -0.2% Yes
Weighted Aggregate Inflation, Less
Grocery** -0.6% -0.6% 0.0% Yes -1.9% -1.2% -0.7% Yes
* 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

July 2017 U.S. Summary
20
• Main MoM inflation in July:
• Auto parts, domestic hotels, groceries, and
jewelry
• Main MoM deflation in July:
• Int’l flights, domestic flights, tablets
YoY MoM
Alcohol -1.4% 0.0%
Apparel -4.4% -1.5%
Appliances -2.6% -0.9%
Auto Parts 0.2% 0.7%
Computers -2.2% -1.4%
Electronics -6.8% -0.9%
Flights 2.9% -4.2%
Domestic Flights 2.4% -5.4%
Intl Flights 5.7% 0.0%
Furniture and bedding -5.1% -1.0%
Grocery 1.0% 0.4%
Domestic Hotels 3.2% 0.6%
Intl Hotels 4.7% 0.1%
Jewelry*** -1.9% 0.4%
Medical Equipment and Supplies -1.4% -0.5%
Nonprescription Drugs 1.0% 0.3%
Personal Care Products -0.3% 0.2%
Pet Products 1.2% -0.1%
Sporting Goods -5.0% 0.1%
Tablet -17.0% -3.2%
Televisions -13.0% -2.0%
Tools & Home Improvement -1.4% 0.2%
Toys -5.6% -0.8%
Weighted Average Inflation* -0.7% -0.3%
Weighted Aggregate Inflation, Less Grocery** -2.0% -0.8%
* 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 product category added to the DEP this month

Alcohol
21
• Adobe DPI shows cumulative deflation of -1.4% YoY (July
2016 to July 2017)
• Prices for Beer show cumulative inflation of 2.8% YoY
• Prices for Spirits show cumulative inflation of 4.2% YoY
• Prices for Wine show cumulative deflation of -4.3% YoY
• For July 2017, prices increased 0.0% vs June 2017 MoM
METHODOLOGY:
• The data used reflect transactions for ~120 K products

Apparel
22
2016 to July 2017)
• For July 2017, prices decreased -1.5% vs June 2017 MoM
METHODOLOGY:
• The data used contains transactions for ~1.5 m products
• Products include clothes for women’s, men’s, boys, girls, infants, and footwear

Appliances
23
2016 to July 2017)
• Main YoY price decreases for Appliances priced between $200
and $400
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
• Adobe DPI shows cumulative inflation of 0.2% YoY (July
2016 to July 2017)
• Main YoY price decreases for Auto Parts priced between $0 and
$70
• Main YoY price increases for Auto Parts priced between $140
and $200
METHODOLOGY:
• The data used reflect transactions for ~300 K products

Airfare
25
2016 to July 2017)
METHODOLOGY:
• The data used contains transactions for ~370 K flight routes
• Includes associated fees, where applicable

Airfare: domestic
26
2016 to July 2017)
• Largest monthly deflation for flights to and from Illinois (-10.7%),
Colorado (-10.3%), and California (-7.1%)
METHODOLOGY:

Airfare: international
27
• Adobe DPI shows cumulative inflation of 5.7% YoY (July 2016 to
July 2017)
• Largest price increases for airfare were to Africa, with inflation of
22.9% YoY
METHODOLOGY:

Electronics
28
2016 to July 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
29
2016 to July 2017)
• Main YoY price decreases for Computers priced between $1200
and $1600
• Main YoY price increases for Computers priced between $0 and
$300
METHODOLOGY:

Electronics: televisions
30
2016 to July 2017)
• Main YoY price decreases for Televisions priced greater than
$2000
• Main YoY price increases for Televisions priced between $0 and
$300
METHODOLOGY:

Electronics: tablets
31
2016 to July 2017)
• Main YoY price decreases for Tablets priced between $550 and
$900
METHODOLOGY:

Furniture and Bedding
32
2016 to July 2017)
• Main YoY price decreases for Furniture and bedding priced
between $250 and $750
METHODOLOGY:
• Products include interior and exterior furniture, mattresses and other bedding products

Groceries
33
2016 to July 2017)
• Main MoM inflation in other dairy products (1.5%),
breakfast cereals (0.7%), and cheese and related
products (0.6%)
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
2016 to July 2017)
• Largest inflation in July to Maine (7.7%), Nevada
(6.0%), Wyoming (3.7%)
• Largest deflation in July to Nebraska (-5.8%), D.C. (-
5.1%), and Alaska (-4.2%)

Hotels: international
35
METHODOLOGY:
• Adobe DPI shows cumulative inflation of 4.7% YoY (July 2016
to July 2017)
• Largest price increases were for hotels in Africa (1.6%
inflation MoM)
• Largest price decreases were for hotels in South America
(-0.7% deflation YoY)

Jewelry
36
METHODOLOGY:
• Adobe DPI shows cumulative deflation of -1.9% YoY (July 2016
to July 2017)

Medical Equipment and Supplies
37
2016 to July 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
38
2016 to July 2017)
• Main YoY price decreases for Nonprescription Drugs priced
greater than $40
• Main YoY price increases for Nonprescription Drugs priced
between $0 and $10
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
2016 to July 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
40
2016 to July 2017)
• Main YoY price decreases for Pet Products priced greater than
$80
• 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
41
2016 to July 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
42
2016 to July 2017)
• Main YoY price decreases for Tools & Home Improvement priced
greater than $600
METHODOLOGY:

Toys
43
2016 to July 2017)
• Main YoY price decreases for Toys priced between $0 and $30
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 -17.4% YoY in July

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 10.8% YoY
in July

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 -- July 2017

Recomendados

Recomendados

Más contenido relacionado

La actualidad más candente

La actualidad más candente (20)

Similar a Adobe Digital Economy Project -- July 2017

Similar a Adobe Digital Economy Project -- July 2017 (15)

Más de Adobe

Más de Adobe (20)

Último

Último (20)

Adobe Digital Economy Project -- July 2017