adobe digital economy project - january 2017

© 2016 Adobe Systems Incorporated. All Rights Reserved.

ADOBE DIGITAL ECONOMY PROJECTJANUARY 2017 UPDATE

© 2016 Adobe Systems Incorporated. All Rights Reserved.© 2016 Adobe Systems Incorporated. All Rights Reserved.

Main takeaways: January

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The Adobe DPI adds two new categories this month: Personal care products (cosmetics, lotion, hair, nail care and more): 1.1% MoM inflation, -3.0% YoY deflation

Pet products (pet food & treats, kitty litter, accessories like leashes and pet beds, and more) 1.1% MoM inflation, 0.2% YoY inflation

Early signals from 2017 suggests that inflation is on the rise. Weighted average inflation across the Adobe DPI categories shows 0.5% MoM inflation

Many categories show strong MoM inflation after the holiday season, including tablets (6.4% MoM inflation), toys (3.4% MoM), and alcohol (2.6% MoM)

The Adobe DPI generally shows MoM increases in January after holiday sales end, though 2017 increases were higher on average. While the same number of categories showed MoM inflation in January for 2016 and 2017, the DPI categories that had price increases showed more inflation MoM on average in January 2017 (1.74%) compared to January 2016 (1.57%) Tablets (6.4% MoM inflation in January 2017), televisions (1.1%), auto parts (0.8%), furniture and bedding (0.6%), sporting goods (1.2%), pet products (1.2%), and toys (3.4%) have higher MoM inflation rates this

year than last year

The DPI shows international travel is more affordable in January: international flight prices are down -5.0% MoM (though up 1.5% YoY), and international hotels show near-zero inflation (0.1% MoM and down -1.4% YoY)

Trade from and travel to Mexico shows signs of inflation YoY, but prices for travel are down steeply since November Auto parts, a category that is significantly made up of imports from Mexico, shows a 0.8% MoM inflation but -1.4% YoY deflation

Travel into Mexico’s largest airport, Mexico City International (MEX) shows 4.0% YoY inflation (compared to 1.5% YoY inflation for international flights) but prices are down significantly since November 2016. Flight prices to MEX show deflation of -19.0% between November 2016 and January 2017.

In the U.K. prices are rising but still showing deflation YoY: grocery prices are up for the 4th month in a row (0.2% MoM inflation, -0.8% YoY deflation). Computers are up 1.6% in January (-2.5% deflation YoY), while televisions in the U.K. saw 0.6% MoM inflation (-21.1% YoY deflation)


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

The youngest member of the cabinet of President Obama

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

© 2016 Adobe Systems Incorporated. All Rights Reserved.© 2016 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


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)


Digital Price Index Findings(DPI)


Adobe DPI Findings in the United Kingdom

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• Adobe DPI for the U.K. shows cumulative deflation for groceries of -0.8% YoY (January 2016 to January 2017), with a fourth-straight month of inflation (0.2% 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 1.6% inflation in January; the category is still showing -2.5% deflation YoY

• Televisions in the U.K. saw 0.6% MoM inflation; the category is still showing -21.1% deflation YoY


December 2016 U.S. Recap

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MoM: November to

December

MoM: November to

DecemberDifference

(percentage)Same Sign?

YoY: Cumulative December 2015-2016

YoY: Cumulative December 2015-2016

Difference (percentage)

Same Sign?

DPI CPI DPI vs. CPI DPI vs. CPI DPI CPI DPI vs. CPI DPI vs. CPIAlcohol -2.1% -0.1% -2.0% Yes 0.5% 0.9% -0.4% YesAppliances 6.0% -0.4% 6.4% No -4.6% -4.5% -0.1% YesAuto Parts -0.1% 0.6% -0.7% No -1.8% -1.0% -0.8% YesComputers 1.2% -0.5% 1.7% No -6.5% -5.8% -0.8% YesFlights -0.7% -3.4% 2.7% Yes 3.3% -4.9% 8.2% NoFurniture and bedding 1.7% -0.1% 1.8% No -3.8% -2.9% -0.9% YesGrocery 0.5% -0.2% 0.7% No -0.7% -2.0% 1.2% YesHotels -1.6% -2.3% 0.7% Yes 4.1% 3.3% 0.8% YesMedical equipment and supplies -0.2% 0.1% -0.3% No -1.4% 0.3% -1.7% NoNonprescription Drugs 0.4% 0.1% 0.3% Yes -0.2% -0.7% 0.5% YesPersonal Care Products*** 1.1% 0.2% 0.9% Yes -2.3% -0.4% -1.9% YesPet Products*** 2.0% 0.0% 2.1% No 0.0% 0.6% -0.6% YesSporting Goods 2.1% -0.2% 2.3% No -5.7% -1.5% -4.1% YesTelevisions 7.8% -3.5% 11.3% No -19.8% -24.5% 4.7% YesTools & Home Improvement 0.7% 0.1% 0.6% Yes -2.1% -0.5% -1.6% YesToys 2.7% -1.4% 4.1% No -6.9% -8.9% 1.9% YesWeighted Average Inflation* 0.6% -0.4% 1.0% No -1.2% -1.9% 0.7% YesWeighted Aggregate Inflation, Less Grocery** 0.8% -0.7% 1.5% No -1.7% -1.8% 0.2% 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


January 2017 U.S. Summary

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• Main MoM deflation in January:• International flights, domestic flights,

Computers

• Main MoM inflation in January:• Tablets, toys, domestic hotels, alcohol,

YoY MoM

Alcohol -0.1% 2.6%Appliances -5.1% 1.7%Auto Parts -1.4% 0.8%Computers -8.0% -0.5%Electronics -9.8% 1.0%Flights 1.1% -3.5%Domestic Flights -0.7% -2.9%Intl Flights 1.5% -5.0%Furniture and bedding -3.5% 0.6%Grocery -1.2% 0.1%Domestic Hotels 3.1% 4.3%Intl Hotels -1.4% 0.1%Medical Equipment and Supplies -1.5% 0.1%Nonprescription Drugs 0.0% -0.1%Personal Care Products -3.0% 1.1%Pet Products 0.2% 1.1%Sporting Goods -5.4% 1.2%Tablet -13.0% 6.4%Televisions -19.5% 1.1%Tools & Home Improvement -1.9% 0.6%Toys -6.7% 3.4%

Weighted Average Inflation* -1.5% 0.5%Weighted Aggregate Inflation, Less Grocery** -1.9% 0.9%

* 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 -0.1% YoY (January 2016 to January 2017)

• Prices for Beer show cumulative inflation of 2.5% YoY • Prices for Spirits show cumulative inflation of 1.0% YoY • Prices for Wine show cumulative deflation of -1.7% YoY

• For January 2017, prices increased 2.6% vs December 2016 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


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 1.1% YoY (January 2016 to January 2017)

• For January 2017, prices decreased -3.5% vs December 2016 MoM

METHODOLOGY:

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


Airfare: domestic

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• Largest price increases in airfare were to Kansas, with YoY inflation of 9.1%

• Other large price increases for airfare were to Ohio, with YoY inflation of 6.1%

• Other significant price decreases for airfare are to Colorado, with YoY deflation of -4.4%

• Largest price decreases are to airfare to Minnesota, with YoY deflation of -5.2%


METHODOLOGY:



Airfare: international

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• Largest price increases for airfare were to South America, with inflation of 17.6% YoY

• Other price inflation for airfare include Oceania, with inflation of 2.2% 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 $1200 and $1600

• 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 $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, mattresses and other bedding products


Groceries

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• Main YoY deflation for eggs (-21.4%), beverages (-3.2%) and cheese (-2.6%)


• Main price increases for bakery products (+2.1%)

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


• Prices for hotels in Nevada show the highest inflation among states measured at 14.1% YoY

• Prices for hotels in North Dakota show the highest deflation among states measured at -4.4% YoY



Hotels: international

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METHODOLOGY:

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


• Largest prices increases are for hotels in Oceania, with 7.5% YoY inflation

• Largest price decreases are for hotels in Asia, with YoY deflation of -1.9%



Medical Equipment and Supplies

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• 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

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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 $15 and $25


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


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

• Main YoY price decreases for Pet products priced between $10 and $20


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 $40 and $100


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 $200 and $300


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 14.5% YoY in January


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 9.6% YoY in January.


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

adobe digital economy project - january 2017

Economy & Finance