Adobe Digital Economy Project -- November 2017

© 2017 Adobe Systems Incorporated. All Rights Reserved.

ADOBE DIGITAL ECONOMY PROJECTNOVEMBER 2017 UPDATE

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

Main Takeaways: November

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

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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 Experience 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 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 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


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, U.K.(DPI)


U.K. Food Prices Up Over 3.5% year-over-year

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• 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

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• 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

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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

StateOct. 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

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MoM: September to

October

MoM: September to

OctoberDifference

(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. CPIAlcohol 0.7% 0.4% 0.3% Yes 3.0% 1.2% -0.5% YesAppliances 1.0% -0.6% 1.6% No -2.6% -1.3% -1.3% YesApparel 0.7% 1.1% -0.4% Yes -5.3% -0.5% -4.7% YesAuto Parts 0.2% -0.7% 0.9% No 1.5% -0.5% 2.0% NoComputers -0.3% 0.2% -0.5% No -4.4% -3.2% -1.2% YesFlights 3.0% 3.1% -0.1% Yes 3.8% 12.6% -8.8% YesFurniture and bedding 0.3% -0.4% 0.7% No -5.6% -1.3% -4.3% YesGrocery 0.7% 0.2% 0.5% Yes 2.0% 0.6% 1.4% YesHotels -2.1% -0.6% -1.5% Yes 3.4% 3.8% -0.4% YesJewelry 0.6% -0.1% 0.7% No -4.2% 3.3% -7.5% NoMedical equipment and supplies 0.1% -0.2% 0.3% No -0.1% 0.4% -0.5% NoNonprescription drugs 0.6% 0.2% 0.4% Yes 1.9% 0.4% 1.5% YesPersonal care products 0.2% 0.1% 0.1% Yes 0.1% -0.7% 0.8% NoPet Products 1.3% 0.1% 1.2% Yes 1.2% -0.7% 1.9% NoSporting goods 0.5% -0.1% 0.6% No -2.4% -2.1% -0.3% YesTelevisions -1.6% -2.6% 1.0% Yes -11.7% -10.3% -1.4% YesTools & Home Improvement 0.4% 0.5% -0.1% Yes -0.6% -0.8% 0.2% YesToys -1.1% 0.0% -1.1% No -3.9% -8.0% 4.1% YesWeighted Average Inflation* 0.5% 0.3% 0.2% Yes -0.1% 0.4% -0.6% NoWeighted 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

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• 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

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• 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

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• Adobe DPI shows cumulative deflation of -4.6% YoY (November 2016 to November 2017)

• 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

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• 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

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• Main YoY price increases for Auto Parts priced between $110 and $140


METHODOLOGY:

• The data used reflect transactions for ~300 K products


Airfare

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METHODOLOGY:

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


Airfare: domestic

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• Largest monthly inflation for flights to and from Alaska (9.0%), Washington (4.5%), and Colorado (3.4%)


METHODOLOGY:



Airfare: international

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• Largest monthly inflation for flights to and from South America (7.3%), Asia (4.6%) and Africa (1.7%)


METHODOLOGY:



Electronics

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• 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, printers etc..


Electronics: computers

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• Main YoY price decreases for Computers priced between $1200 and $1600

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


METHODOLOGY:

• The data used contains transactions for ~63 K products


Electronics: televisions

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

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


METHODOLOGY:



Electronics: tablets

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• Main YoY price decreases for Tablets priced between $550 and $900


METHODOLOGY:



Furniture and Bedding

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• Main YoY price decreases for Furniture and bedding priced between $100 and $150


METHODOLOGY:

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


Groceries

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• 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

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METHODOLOGY:

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


• 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%)



Hotels: international

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METHODOLOGY:

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


• 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)



Jewelry

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METHODOLOGY:

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




Medical Equipment and Supplies

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• 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


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 greater than $40

• Main YoY price increases for Nonprescription Drugs priced between $0 and $10


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 increases for Personal care products priced between $0 and $10


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 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 $100 and $200

• Main YoY price increases for Sporting Goods priced greater than $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 between $140 and $280

• Main YoY price increases for Tools & Home Improvement priced between $0 and $50


METHODOLOGY:



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 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

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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 11.3% YoY in November.


Appendix

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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. Drugs

To be added to DPI

Professional services

Hospital services

Current DPI

Unlikely


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


Adobe Digital Economy Project -- November 2017

Economy & Finance