Adobe Digital Economy Project - March 2017

© 2017 Adobe Systems Incorporated. All Rights Reserved.

ADOBE DIGITAL ECONOMY PROJECTMARCH 2017 UPDATE

© 2017 Adobe Systems Incorporated. All Rights Reserved.© 2017 Adobe Systems Incorporated. All Rights Reserved.

Main takeaways: March

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The Adobe DPI shows March as the fourth consecutive month of inflation in the U.S. across DPI categories (0.3 percent in the all-items index and 0.5 percent in the all-items less grocery index). This is the first time in the 40-month history of the DEP to show four or more consecutive months of inflation. The all-items inflation figure is, however, lower in March than in February (0.4% in the all-items index in February) and prices in the U.S. remain down -0.7% YoY, led by year-over-year price declines in grocery and durable goods

Monthly inflation in March is driven by price increases in non-durable goods and select durable goods: Prices are up for flights (3.2% MoM), domestic hotels (2.3% MoM), computers (0.9% MoM), appliances (0.9% MoM), and groceries (0.1% MoM)

Grocery inflation in March is small but represents the largest category of spending in the DPI. Price increases in the category in March are driven by price increases in cheese and related products (0.8% MoM), sugar and sweets (0.6% MoM), fats and oils (0.4% MoM), and meats (0.3% MoM)

Historically the DPI shows price increases for flights and hotels in March, but inflation this month is higher than expected for both categories

The March DPI contains state-level inflation data for the second time. The state-level data show that inflation is consistent and affecting nearly all states 35 of the 51 states and D.C. are showing 4 straight months of inflation. Only four states (West Virginia, Delaware, Ohio, and Louisiana) show MoM deflation in March. However, prices remain down year-over-

year: 47 out of 51 states and D.C. have lower prices compared to March 2016.

Differences in inflation across states were smaller in March than differences in February because of a small but uniform rise in grocery prices that affected all states similarly. The states with the highest inflation also had high inflation in flights and hotels

The Adobe DPI for the U.K. shows cumulative inflation for groceries of 1.3% YoY (March 2016 to March 2017) with a sixth-straight month of inflation (0.1% MoM) Prices for computers (down -0.5% MoM) and televisions (down -1.5% MoM) are down month over month following a short period of inflation in both categories. Prices in both categories remain down year-

over-year.


Adobe Digital Insights Background

Based on analysis of aggregated and anonymous data from Adobe Marketing Cloud:• Adobe Analytics and Adobe Mobile Services

Thousands of brands worldwide including two thirds of Fortune 50 companies rely on Adobe Marketing Cloud:• $7.50 of every $10 spent online with top 500 U.S. retailers go through Adobe Marketing Cloud **• Adobe Marketing Cloud powers:

• 20 of the top 30 U.S. employers• 9 of 10 largest hotel groups• 7 of 10 largest airlines

** Latest IR Top 500 Report 2015

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AdobeAnalytics

AdobeMobile Services


Economist Advisors

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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.

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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 Marketing Cloud **• Based on analysis 1 billion website visits and 100k products sold online

ONS: Consumer Price Index Adobe: Digital Price IndexQuantities Sold No YesProducts/quantities updated Annually Daily

Number of Products 180,000 100k(currently covered categories)

Data Collection Frequency Monthly DailyData Availability Monthly DailyOffline Prices Yes NoLong history Yes NoAll categories of spending Yes No

** Latest IR U.K. Top 500 Report 2015


Methodology – U.S.

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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 Marketing 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 YesProducts/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 DailyData Availability Monthly Monthly DailyOffline Prices Yes Yes NoLong history Yes Yes NoAll categories of spending Yes Yes NoIndex Type Laspeyeres Fisher Ideal Fisher Ideal

** Latest IR Top 500 Report 2015


DPI Coverage of U.S. CPI Categories

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DPI Category February 2017 DPI WeightsAll-Items All-Items Minus Groceries

Grocery 54.00% N/AFurniture 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

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DPI CPIAppliances 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

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• 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

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• 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

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• 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

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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(DPI)


Consistent Inflation across the U.S., but prices down YoY

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• Consistent inflation is occurring everywhere across the U.S: 35 out of the 51 states and D.C. showed 4 straight months of inflation

• Regional prices and consumer preferences are less significant in March: Monthly inflation in March was more uniform than previous months due to a small but uniform rise in grocery prices across states

• Prices are still down compared to March 2016: 47 out of 51 states and D.C. are showing YoY deflation compared to March 2016


Travel driving price changes across states

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Highest inflation by state

Lowest inflation by state

State March MoM Inflation Major Inflation Drivers

Massachusetts 0.8% Flights*, Hotels**

Alaska 0.8% Flights*, Hotels**

Washington 0.8% Flights*, Hotels**

Illinois 0.6% Hotels**, Flights*

New York 0.6% Hotels**, Flights*

State March MoM Inflation Major Deflation Drivers

Florida 0.0% Hotels**, Alcohol

Louisiana -0.1% Flights*, Hotels**

Ohio -0.1% Alcohol, Toys

Delaware -0.1% Alcohol, Appliances

West Virginia -0.2% Alcohol, Medical Equipment

* 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


Adobe DPI Findings in the United Kingdom

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• Adobe DPI for the U.K. shows cumulative inflation for groceries of 1.3% YoY (March 2016 to March 2017), with a sixth-straight month of inflation and (0.1% MoM inflation)

• U.K. computers and television inflation have diverged in recent months, though both saw MoM inflation in January

• Computers in the U.K. saw a -0.5% deflation in March; the category is still showing -0.2% deflation YoY

• After two straight months of inflation in televisions, computers saw a ----1.5% deflation in March, bringing the category to -15.7% YoY


February 2017 U.S. Recap

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MoM: January to February

MoM: January to February

Difference (percentage)

Same Sign?

YoY: Cumulative February 2016-2017

YoY: Cumulative February 2016-2017

Difference (percentage)

Same Sign?

DPI CPI DPI vs. CPI DPI vs. CPI DPI CPI DPI vs. CPI DPI vs. CPIAlcohol 0.3% -0.1% 0.4% No 0.3% 0.1% 0.2% YesAppliances -1.3% 0.8% -2.1% No -4.5% -3.8% -0.7% YesAuto Parts -0.2% 0.2% -0.4% No -1.3% -0.9% -0.4% YesComputers -0.6% -0.2% -0.4% Yes -7.9% -4.2% -3.7% YesFlights 5.3% 4.2% 1.1% Yes 3.7% -1.3% 5.0% NoFurniture and bedding -1.1% -0.1% -1.0% Yes -3.6% -1.4% -2.2% YesGrocery 0.4% 0.2% 0.2% Yes -1.0% -1.7% 0.7% YesHotels 2.9% 4.3% -1.4% Yes 3.2% 1.3% 1.9% YesMedical equipment and supplies -0.3% 0.8% -1.1% No -1.0% 0.1% -1.1% NoNonprescription drugs 0.3% 0.1% 0.2% Yes 0.3% 0.3% 0.0% YesPersonal care products -0.6% 0.1% -0.7% No -3.6% -0.8% -2.8% YesPet Products -0.1% -0.2% 0.1% Yes -0.1% -0.2% 0.1% YesSporting goods -0.9% 0.2% -1.1% No -6.1% -1.2% -4.9% YesTelevisions -1.0% 1.4% -2.4% No -19.1% -20.1% 1.0% YesTools & Home Improvement -0.1% 0.0% -0.1% No -2.0% -0.8% -1.2% YesToys -1.8% 0.2% -2.0% No -7.1% -7.9% 0.8% YesWeighted Average Inflation* 0.4% 0.5% -0.2% Yes -1.3% -1.3% 0.0% YesWeighted Aggregate Inflation, Less Grocery** 0.4% 0.8% -0.2% Yes -1.6% 0.0% -1.5% 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. *** New categories introduced in this month’s Adobe DPI


March 2017 U.S. Summary

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• Main MoM inflation in March:• Flights, hotels, computers, appliances

• Main MoM deflation in March:• Tablets, medical equipment and supplies, toys

YoY MoM

Alcohol -0.9% -0.2%Appliances -4.5% 0.9%Auto Parts -1.3% 0.0%Computers -4.9% 0.9%Electronics -9.2% 0.2%Flights 5.0% 3.2%Domestic Flights 4.8% 3.1%Intl Flights 4.7% 3.6%Furniture and bedding -4.2% -0.5%Grocery -0.4% 0.1%Domestic Hotels 3.7% 2.3%Intl Hotels -1.4% 1.0%Medical Equipment and Supplies -1.3% -0.7%Nonprescription Drugs 0.6% -0.1%Personal Care Products -1.3% 0.5%Pet Products -0.7% -0.1%Sporting Goods -5.2% 0.0%Tablet -15.7% -2.5%Televisions -17.5% 0.6%Tools & Home Improvement -2.2% -0.2%Toys -4.9% -0.6%

Weighted Average Inflation* -0.7% 0.3%Weighted Aggregate Inflation, Less Grocery** -1.1% 0.5%

* 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. *** New categories introduced in this month’s Adobe DPI


Alcohol

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• Adobe DPI shows cumulative deflation of -0.9% YoY (March 2016 to March 2017)

• Prices for Beer show cumulative inflation of 3.4% YoY • Prices for Spirits show cumulative inflation of 0.4% YoY • Prices for Wine show cumulative deflation of -3.2% YoY

• For March 2017, prices decreased -0.2% vs February 2017 MoM

METHODOLOGY:

• The data used reflect transactions for ~120 K products


Appliances

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• Main YoY price decreases for Appliances priced between $200 and $400

• For March 2017, prices increased 0.9% vs February 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

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• Main YoY price decreases for Auto Parts priced greater than $200


METHODOLOGY:

• The data used reflect transactions for ~300 K products


Airfare

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• Adobe DPI shows cumulative inflation of 5.0% YoY (March 2016 to March 2017)


METHODOLOGY:

• The data used contains transactions for ~370 K flight routes• Includes associated fees, where applicable


Airfare: domestic

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METHODOLOGY:



Airfare: international

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• Largest price increases for airfare were to South America, with inflation of 19.2% YoY

• Largest price decreases are for airfare to Europe with deflation of -6.2% YoY


METHODOLOGY:



Electronics

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• 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, printers etc..


Electronics: computers

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• Main YoY price decreases for Computers priced between $700 and $1200

• Main YoY price increases for Computers priced between $0 and $300


METHODOLOGY:

• The data used contains transactions for ~63 K products• Products span across dozens of different categories such as televisions, laptops, Blu-ray players, desktops, tablets, wearables, headphones, video games, printers etc..


Electronics: televisions

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• Main YoY price decreases for Televisions priced greater than $2000


METHODOLOGY:



Electronics: tablets

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• Main YoY price decreases for Tablets priced between $350 and $550


METHODOLOGY:



Furniture and Bedding

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• Main YoY price decreases for Furniture and bedding priced between $150 and $250


METHODOLOGY:

• The data used contains transactions for ~173 K products• Products include interior and exterior furniture, mattresses and other bedding products


Groceries

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• Main YoY deflation for eggs (-20.6%), beverages (-2.8%) and sugar and sweets (-1.8%)


• Main price increases for cheese (inflation 0.8% MoM), sugar and sweets (0.6% MoM). Fats and oils (0.4% inflation MoM) and meat products (0.3% inflation MoM) also contributed to the rise in grocery prices in March

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

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METHODOLOGY:

• The data used contains transactions for ~250 K hotel properties• Includes associated fees, where applicable




Hotels: international

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METHODOLOGY:

• The data used contains transactions for ~250 K hotel properties• Includes associated fees, where applicable


• Largest price increases were for hotels in South America (4.1% inflation YoY)

• Largest price decreases were for hotels in Asia (-1.5 deflation YoY)



Medical Equipment and Supplies

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• Main YoY price decreases for medical equipment and supplies priced between $45 and $135

• Main YoY price increases for medical equipment and supplies priced greater than $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

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• 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:

• The data used contains transactions for ~16 K products• Includes all non-prescription medicines taken by swallowing, applying on your skin (such as topicals), inhaling, as suppositories, or enemas.


Personal care products

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• 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:

• The data used contains transactions for ~110 K products• Includes cosmetics, lotion, hair (shampoo, conditioner) and nail care


Pet products

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• 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:

• The data used contains transactions for ~70 K products• Includes pet food & treats, kitty litter and accessories (leashes, pet beds)


Sporting Goods

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• Main YoY price decreases for Sporting Goods priced between $200 and $350


METHODOLOGY:

• The data used contains transactions for ~300 K products• Products include small equipment and accessories (balls, gloves, uniforms) as well as large equipment such as treadmills, weightlifting tools etc.


Tools & Home Improvement

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• Main YoY price decreases for Tools & Home Improvement priced greater than $600


METHODOLOGY:

• The data used contains transactions for ~225 K products


Toys

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• Main YoY price decreases for Toys priced between $70 and $200


METHODOLOGY:

• The data used contains transactions for ~249 K products• Products include toys, games as well as playground equipment


Job Seeking Index(JSI)


Online job seeking continues YoY declines

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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 Marketing Cloud powers 20 of the top 30 U.S. employers**

US online job seeking is down -19.3% YoY in March


Digital Housing Index(DHI)


Online housing search grows YoY

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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 13.0% YoY in February.


Appendix

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Inflation rates by price ranges, cont’d (tablets)

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• 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



Inflation rates by price ranges, cont’d (televisions)

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• 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



Inflation rates by price ranges, cont’d (televisions)

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• 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



Digital Price Index: Fisher Ideal Price Index

∑𝑖𝑖=1𝑛𝑛 𝑃𝑃𝑖𝑖𝑖𝑖𝑈𝑈𝑖𝑖𝑖𝑖−1∑𝑖𝑖=1𝑛𝑛 𝑃𝑃𝑖𝑖𝑖𝑖−1𝑈𝑈𝑖𝑖𝑖𝑖−1

∗∑𝑖𝑖=1𝑛𝑛 𝑃𝑃𝑖𝑖𝑖𝑖𝑈𝑈𝑖𝑖𝑖𝑖∑𝑖𝑖=1𝑛𝑛 𝑃𝑃𝑖𝑖𝑖𝑖−1𝑈𝑈𝑖𝑖𝑖𝑖

• 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.

𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹 𝜋𝜋𝑖𝑖 =


Methodology Comparison: Fisher, Laspeyres and Paasche


Economy & Finance

Adobe Digital Economy Project - March 2017