WHITE PAPER Outlook for the Apparel Industry Post-Covid 19

WHITE PAPER

Outlook for the Apparel Industry Post-Covid 19

Copyright © 2020 PreciseTarget. All rights reserved.

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Table of Contents:1. Introduction

2. Retail Market Assessment

3. Comparing Retail to Other Consumer Segments

4. Channel Disruption Analysis

5. Lemonade from Lemons: Expect a Marketing Innovation Wave

6. Behavioral Change Roadmap

7. Recommendations

8. How Brands Use PreciseTarget Data


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About the AuthorRobert McGovern is the founder of PreciseTarget and sometimes refers to himself as Chief of Curiosity. Rob’s

passion is solving difficult computer science problems. At PreciseTarget, he is helping brands overcome their

“sparse customer data” problem. He started PreciseTarget based on his realization that many companies were

selling data based on observations -- like when a consumer clicks on a product -- but that no company had

ever tried to understand why consumers purchase a product or a brand. This led him to create a machine

learning system to profile the buying tastes of a consumer based on their prior

purchases. He forged partnerships with the largest retail and wholesale brands

and is the trusted keeper of over 5 billion SKU-level retail transactions used to

train the machine learning system.

The company has developed an innovative way to combine the machine

knowledge of hundreds of brands with an architecture that completely

pseudonymizes the identity of the consumer. The company is one of the first to

architect a system to be CCPA compliant from the ground-up, creating machine

knowledge, rather than yet another data set designed to exploit consumer

privacy. This architecture has led to the company to being trusted with billions

of SKU-level transactions and to be a behind-the-scenes data partner to the

largest brands.

In his first experience as an entrepreneur Rob developed the Internet’s first online job service. He was frustrated

that jobs were hidden and inaccessible and created Careerbuilder.com to liberate the hidden job information people

desperately needed. The company grew to be the largest job service in the industry with over 25 million users per

month, had a successful IPO, and helped over 100 million people upgrade their careers. When the DotCom bubble

burst, he took the company private and ultimately sold it for $440 Million in a private company acquisition.

When he’s not solving computer science problems he’s a published author, an airplane pilot, a 6,000 mile-per-year

cyclist, an advocate for the disadvantaged, a bicycle builder, a gardener, and a mentor to aspiring entrepreneurs.


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This research brief was written for PreciseTarget’s

customers to help them assess and plan for the rapidly

evolving pandemic era. America’s retailers and wholesale

brands are facing unprecedented risk and disruption

from a double blow: an accelerating transition from in-

store to online, often referred to as the retail apocalypse,

combined with the Covid-19 pandemic, the greatest

pandemic since the Spanish Flu of 1918.

Our goal is to provide insight, background research, and

predictions for the soft goods

sector. At our core we are a

data science company and

we’ve applied our expertise to

the challenge of predicting what

comes next for retail. We’ve

sourced high quality data to augment our research and

to develop an analytical understanding of the disrupted

state of retail. We’ve cited our sources in this report

and have conscientiously assigned probabilities to our

predictions as a service to the reader.

As a technology company PreciseTarget lives in a world

of high-speed technology disruption. Our programming

approaches, databases, and methodologies are

constantly disrupted by the next innovation. Frequently

it is at the moment that we’ve gained mastery of the

incumbent technology that it becomes obsolete and

is surpassed by the next big thing. We have applied

our institutional experience in adapting to sudden and

unplanned changes to this problem. We believe the

COVID disruption will be unparalleled, although we have

not succumbed to pessimism. We see a future where

there will be successful post-pandemic brands,

many of whom emerged as leaders during the recession.

Their success will almost certainly be attributable to

constructive actions taken during the disruption period.

It is uniquely American for disruptions to catalyze the

creation of new brands, new business models, and

new methodologies. Google began gathering steam

during the DotCom recession. Advertisers rapidly shifted

their spending away from traditional media, like radio

and newspapers, to this new oddly named thing called

Google. Total advertising

spending in the US didn’t

decrease during the

DotCom recession. In fact,

it accelerated as you’ll see

later in this report. The ad

budgets just shifted to being spent on a new medium.

The Trade Desk, Instagram, LiveRamp, MediaMath, and

Pinterest were all founded during the Great Recession

which took place between December 2007 and June

2009. If you’ve ever considered being an entrepreneur,

now might be a good time to start your company.

We’re certain this recession will have winners; they’ll

be the innovative brands that make lemonade from the

pandemic lemons.

Introduction1We’re certain this recession will have winners; they’ll be the innovative brands that make lemonade from the pandemic lemons.

We see a future where there will be successful post-pandemic brands, many of whom emerged as leaders during the recession. Their success will almost certainly be attributable to constructive actions taken during the disruption period.


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The music industry has gone through many disruptive

waves, each one described in dire terms. In fact, the

descriptions are not too different from the way the press

talks about the retail apocalypse. Before the so-called

end of music, shopping malls featured record stores.

When the cassette tape cape along the experts were

sure it would kill music. The fear was everyone would

make illegal copies thus, hollowing out the industry’s

profits. Somehow the world switched to cassette

tapes and the Rolling Stones didn’t lose their jobs or

their yachts. Next the cassette tape had a target on its

back, and the Music CD appeared as a major disrupter.

Best Buy rapidly devoted 30% of its floor space to

merchandising CD’s. It was the next big thing, until it

was ‘killed’ by Apple iTunes. The pundits crowed that

iTunes was surely going to kill music. You could now

buy one song for 99 cents, rather than the whole album

for $12.00, so people we’re going to spend far less

on music. The headlines declared that the bands and

record companies would go broke. Can you picture

Steve Jobs in his office watching music sales skyrocket

higher, far larger than CD sales? Every technology has its

day, and iTunes was taking its turn as the next big thing.

Progress and disruption continue, and now it’s the era

where Pandora and Spotify disrupt Apple with streaming

music.

What was the end-result of all this catastrophic music

disruption? People listen to more music now than ever -

38 minutes per day - more than just doing it differently.

We’re quite certain people will wear clothing and shoes

after the pandemic. And, we’re confident the sweatpants

and slippers featured in the Zoom wardrobe will be a

short-term fashion trend. People will continue to wear

clothes and their desire to express themselves with

fashion hasn’t gone away; they’re just going to do it

differently. After the 9/11 tragedy, people adapted by

buying shoes that were easy to remove, carry-on gear

that was TSA friendly, and toiletries conforming to the

new TSA guidelines. We’ll see a similar adaptation

phenomenon happen as shoppers develop new

behaviors following the pandemic.

People will continue to wear clothes and their desire to express themselves with fashion hasn’t gone away; they’re just going to do it differently.


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Retail Market Assessment

The COVID-19 period marks the third major recession

since 2000. The first came in 2001 and is often

referred to as the DotCom recession. The emergence

of the Internet enabled the creation of hundreds of

thousands of companies. Investor euphoria was part of

the phenomenon, which included stock prices being

irrationally bid up. This had the effect of creating paper

wealth, and paper billionaires, which was too good

to last. Around the year 2000, investors found their

bearings and the inflated stock

values melted like a snowman.

The economic freefall was further

amplified by the 9/11 terrorist

event which happened during the

DotCom recession.

The second recession, referred to as the Great

Recession, was caused by the mortgage and banking

meltdown of 2008. From a historical perspective

the Great Recession was second only to the Great

Depression of the 1930’s in its severity and reach.

During the Great Recession the markets discovered that

many (or most) of the mortgages recently written were

based on artificially inflated home values. This, combined

with counter-party risk, meaning that Wall Street had

structured securities which enabled investors to make

leveraged bets. When the market crashed there was

a double whammy; banks were holding illiquid loans

secured by undervalued assets, and they had lent

money to investors/gamblers who were betting things

would go higher. The crash was more of an implosion,

pulling the banks, homeowners, and related companies

into the vortex. Recovering from the Great Recession

required rebuilding our entire banking system and

rewriting the laws about what banks can and can’t do.

The current recession, which may someday be referred

to as the Virus Recession, started in March of 2020. It’s

uncertain how long it will last, although we believe the

recession will catalyze structural changes to the retail

sector. In this research we studied the 2001 and 2008

recessions, including detailed analysis of the soft goods

sector. We conducted

our research using high-

quality data from multiple

sources including the

Federal Reserve Bank,

which tracks monthly

retail sales data in virtually

every category. The Fed collects this data to make

forecasts about employment and economic activity.

Our Fundamental Question: What Happens to

Soft Goods in a Recession?

We began our research with this base-level question.

(Readers note: for the purposes of this research we

combined apparel and footwear into one category.) Our

research data includes monthly apparel sales for the

USA, combining online and in-store sales. We added

related data sets with the goal of making predictions

about the expected velocity of apparel spending in the

coming quarters. Our research included dissecting other

consumer categories to gain a greater understanding

of consumer spending before, during, and after a

recession.

The current recession, which may someday be referred to as the Virus Recession, started in March of 2020. It’s uncertain how long it will last, although we believe the recession will catalyze structural changes to the retail sector.

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Analysis of Soft Goods Spending During the

DotCom Recession

In Figures 1 and 2 we plotted US Apparel sales in

millions of dollars for the time period of the DotCom

recession, which lasted from January 2000 to December

of 2001. In order to determine the impact that changes

in consumer wealth have on apparel sales we added

two stock indexes as comparison points: the Wilshire

5000 stock index, which is a weighted index of all stocks

traded in the US, and the NASDAQ Composite stock

index, which provides an index focused on high growth

companies. Our ultimate goal was to determine if there

is a correlation between apparel sales and American

wealth, using the price of US equities as a proxy for

consumer wealth.

Our analysis illustrated there is was no correlation

between sales of apparel and the stock markets during

and after the DotCom recession. During this period

apparel sales suffered a modest setback, with sales

down 6.2%, which took 14 months to recover to their

pre-recession levels. In contrast, the Wilshire Index

declined 39.87% and took 66 months to recover. In the

same period the Nasdaq lost 69% of its value and took

over 160 months to recover. The loss in shareholder

wealth appeared to have no impact on consumer

purchase of apparel products. In fact, apparel sales

showed a steady upward growth trend as the markets

continued to fall lower.

Analyzing the Great Recession

We conducted the same analysis on the Great

Recession, comparing apparel sales to the major stock

indexes. In this analysis we saw slight correlation,

although on a percentage basis the stock market losses

were far greater than the loss of apparel sales. During

this period apparel sales were down 11.7% and took

29 months to recover to pre-recession sales levels. In

contrast, the Wilshire index was down 48%, and took 55

months to recover. The Nasdaq performed only slightly

better, down 46% taking 42 months to recover.

The loss in shareholder wealth had no noticeable impact on consumer purchases of apparel products. In fact, apparel sales showed a steady upward growth trend as the markets continued to fall lower.

Apparel vs. Major Stock Indexes Great RecessionFigure 1

Figure 2

Apparel vs. Major Stock Indexes Dotcom Recession


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Does High Unemployment Effect Apparel Sales?

We next examined the effect of job losses on apparel

sales. The nightly news programs are regularly

prognosticating that job losses will lead to a downturn

in retail sales. While these seems logical, as data

scientists we launched a research project to understand

the degree of correlation between apparel sales and

employment rates. In our research we overlaid two data

sets: monthly apparel sales from 2000 to 2020 along

with the monthly unemployment rates for the period.

Our goal was to quantify the effects of unemployment

on apparel sales. When people lose their jobs, do they

spend less on apparel? If so, for how long?

In Figure 3 we have combined both the unemployment

rate, as depicted on the right-side Y-axis, and apparel

sales, depicted on the left Y-axis, in millions of dollars.

Additionally, we overlaid both the DotCom and Great

Recessions on the graph, which reveals the apparel and

the unemployment rates before, during, and after the

recessions.

Stock market: Down 48% for 55 months. Apparel: Down 11.7% for 27 Months.

Apparel sales continued on a slow and steady growth path, irrespective of the ebbs and flows of the unemployment rate as the economy churned through its cycles.

The two recessions provide convincing evidence that increases and decreases in the unemployment rate have no measurable effect on apparel sales

Surprisingly, this analysis showed no correlation

between apparel sales and employment rates. Apparel

sales continued on a slow and steady growth path,

irrespective of the ebbs and flows of the unemployment

rate as the economy churned through its cycles. Apparel

sales grew during periods of highest unemployment,

and no noticeable growth acceleration occurred when

the unemployment rate fell. In fact, during that period,

the economy achieved its all-time low of 3.5% in 2019,

which had no effect on the rate of apparel sales. The two

recessions provide convincing evidence that increases

and decreases in the unemployment rate have a

negligible effect on apparel sales.

Figure 3


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Comparison of Apparel to Other Consumer Categories

We next turned our attention to other categories. Our

research goal was to better understand consumer

spending during and after a recession, with the goal of

developing predictions about the present recession. We

isolated this analysis to the Great Recession given our

belief that the Virus Recession could be equally severe.

We selected a span of consumer categories ranging

from relatively low-cost products, like cosmetics, to very

high-priced products including automobiles and home

improvement. In our analysis we compared the monthly

sales of apparel products to other categories. In each

comparison we outlined the depth of the sales decrease

for the category along with the allotted time until the

category recovered.

3Apparel vs. Restaurant Spending

Apparel vs. Automobile

Figure 4

Figure 6

Figure 7

Apparel vs. Electronics and Appliances

Electronics and Appliances-Depth of Recession: -16.7% reduction in sales-Time to Recover:84 Months

Apparel-Depth of Recession: -11.7% reduction in sales-Time to Recover: 29 Months

Automobiles-Depth of Recession: -43.7% reduction in sales-Time to Recover: 75 Months



Full Service Restaurants-Depth of Recession: -12.3% reduction in sales-Time to Recover: 31 Months

Figure 5Apparel vs. Furniture and Home Goods


Furniture and Home goods-Depth of Recession: -23.23% reduction in sales-Time to Recover: 101 Months


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Apparel vs. Cosmetics SpendingWe anticipate consumer spending will recover in a matter of a few quarters, with a much higher, and likely permanent, shift to online buying.

Recovery Outlook:

In making our predictions we analyzed the recovery

of the major consumer categories in the previous

recessions. We then weighted our analysis based on the

unique circumstances of the pandemic. For example,

while apparel sales and luxury hotel sales were closely

correlated in the previous recessions we extended the

projected hotel recovery based on expected changes in

consumer travel.

We are projecting that the apparel recovery will be similar

to what we experienced in the Great Recession. We

anticipate consumer spending will recover in a matter of

a few quarters, with a much higher, and likely permanent,

shift to online buying.

Figure10

Figure11


Cosmetics and Beauty-Depth of Recession: -.56% reduction in sales-Time to Recover: 7 months

Post Recession Elapsed Months

PreciseTarget Projections on Recovery by Category

Apparel vs. Luxury Hotel SpendingFigure 9


Luxury Hotels-Depth of Recession: -14% reduction in sales-Time to Recover: 28 Months

Apparel vs. Home Improvement SpendingFigure 8


Home Improvement Construction-Depth of Recession: -54% reduction in sales-Time to Recover: 115 Months


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Wholesale/Retail Channel Disruption

Prior to the pandemic America’s retail environment

had been progressively shifting to a higher online

mix. According to Internet Retailer, ecommerce grew

from 6.4% of total retail in 2000 to 16% in 2016. We

anticipate that this progressive migration will shift to a

step-change, where online becomes 30 to 40% of retail

in the 2021/2022 period.

For the past 10 years the hot topic in retail has

been supply chains. They’re a biproduct of offshore

manufacturing, now integral to how we create and

operate retail companies. In our minds Walmart and

Target are supply chains that happen to have retail

stores. Disrupt one link in the chain with a storm or

warehouse fire and you have the catastrophic effects of

the proverbial butterfly flapping its wings.

There’s another chain we rarely speak about that’s being

massively disrupted in retail. It’s equally important, and

the pandemic’s flapping wings are resulting in a wave of

bankruptcies and liquidations. It’s the distribution chain. It

begins when the product is dropped-shipped and flows

from wholesaler, to retailer, to consumer. There’s an

adage in warfare that amateurs focus on strategy while

the pros focus on logistics. If an enemy severs your

army’s supply chain, you can lose your troops. Similarly,

if you cut a link in the retail distribution chain you can

lose your retail enterprise. The bankruptcy courts are

presently swamped with the casualties of today’s

fractured chain.

When the pandemic struck in March of 2020 the timing

couldn’t have been worse for apparel and footwear

retailers. They had just completed stocking the shelves

for the spring season. The traditional fashion season

is 14 weeks - 98 days of do-or-die, profit or bust.

Consumers won’t be interested in bathing suits in the

fall and the creditors want to be paid back the money

funding your inventory. Put yourself in the shoes of a

department store chain. Five of the largest have already

filed for liquidation. The department stores had just

completed stocking for the spring season with billions in

merchandise. They were forced to shut down all stores

and furlough employees. The problem is exacerbated by

the consumer’s understandable fear about the safety of

stores and malls.

We believe the department store channel will suffer the

greatest impact. 100% of the major department store

brands, including JC Penney, Macy’s, Neiman Marcus,

and Nordstrom, have signaled major store closures.

From a planning perspective we are advising our clients

to expect a 30 to 50% reduction in department store

fronts, and a 20 to 40% reduction in revenue of the

department store channel. By necessity, the wholesale

brands must pivot to a much higher mix of direct-to-

consumer.

There’s another chain we rarely speak about that’s being massively disrupted in retail. It’s equally important, and the pandemic’s flapping wings are resulting in a wave of bankruptcies and liquidations. It’s the distribution chain.

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Laypeople think of ecommerce as a form of life

preserver. If only it were that easy. It would be a 9.9

on the difficulty scale to suddenly build an online

audience sufficiently large to grow your sales from 10%

ecommerce to 100%. Under the best of circumstances,

it would take world class team of digital experts 24 to 36

months, and enormous amounts of capital. As Warren

Buffet says, you only find out who is swimming naked

when the tide goes out. The tide is out in retail.

The stores are over-stocked, the malls are empty, consumers are afraid, and the banks are nervous. What

does that mean for 2020? Here are five predictions on what you’ll see as the year unfolds:

1. 2020 Will Set New Records for Discounting: There’s an epic glut of inventory that must be

cleared. There are exacerbating factors like store closures, diminished demand for professional attire due to

sheltering at home, and consumer uncertainty. T.J. Maxx is also overstocked, so the final link in the distribution

chain might not be there for you.

2. Expect to See a 30-50% Reduction in Store Fronts: The pandemic is accelerating the inevitable.

We’re moving to a higher mix of online sales.

3. Wholesale Brands Will Pivot to Direct-to-Consumer: Pre-pandemic, most wholesalers earned

only 5-9% of revenues from selling directly to consumers. In the new reality, we predict that the survivors will be

30% direct within one year, and 40% within two years.

4. Data skills will be the critical success factor: When we assess the winners and losers, the

winners will be the brands staffed with digital expertise possessing sophisticated data strategies. We’re advising

our clients to hire digital staff in preparation for tomorrow’s retail world. They’ll have more data scientists than

merchandisers.

5. Amazon won’t be the Savior: Don’t expect your faves to appear on Amazon. Over the past 36

months Amazon has created over 175 knock-off apparel and footwear brands that compete directly with

the mainstream brands, at dramatically lower prices. The current is flowing the other direction; Nike, IKEA,

Birkenstock, Vans, Ralph Lauren, Patagonia, and The North Face are among the brands no longer selling

directly on Amazon. Expect this trend to continue as Amazon likely becomes one of your major competitors.

We are advising our clients to be cautious in outsourcing the pandemic problem to their media agencies. Our

believe is that the imperative will be to reformulate a retail business and its channel model. We are facing an

unprecedented channel disruption whose implications will be core to any wholesaler or retailer’s future success.

Any brand who wishes to control their own future should be wary of delegating this problem elsewhere and

hoping it will gradually go away.

It would be a 9.9 on the difficulty scale to suddenly build an online audience sufficiently large to grow your sales from 10% ecommerce to 100%.


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Lemonade from Lemons: Expect a Marketing Innovation Wave

During the last two recessions, advertising spending by

retail and wholesale brands increased significantly during

the recession. We are predicting that a similar surge in

advertising will take place in the second half of 2020.

We have been monitoring brand spending and Web site

visits which confirm this expected increase.

In prior recessions, advertisers shifted their spending to

new methods and services. The Trade Desk, LiveRamp,

MediaMath, and Pinterest are integral players in the

relatively new Ad-tech ecosystem, and all were founded

during the Great Recession. While it may feel counter-

intuitive to start a new business during a period of major

economic disruption, the entrepreneurs behind these

companies would tell you it’s an ideal time for a start-up.

During the Great Recession, marketers were forced to

look for more cost-effective ways to advertise, making

the invention of programmatic advertising well-timed

for the era. Going further back, during the DotCom

recession, a new player hit its stride. Google introduced

their pay-per-click advertising model, the first ad venue

that charged customers only if someone clicked on the

advertiser’s ad.

During the DotCom economic downturn advertisers

were hungry for advertising that would deliver the most

value for their constrained budgets. The end result was

ad dollars rapidly rotating out of less accountable TV and

newspaper advertising and into Google’s higher value

click-based ads.

It’s difficult to predict what comes next in technology,

although it’s safe to bet the future will be more digital.

Marc Andreesen, the founder of Netscape, and now

one of the most influential venture capitalists in Silicon

Valley, is known for saying “software is eating the world.”

His point is that virtually everything in our lives is now

controlled by software and algorithms. It is certain that

people will continue to wear apparel and footwear after

the pandemic. Over the past decade the advertising

industry has reformulated itself into something we now

call “Programmatic Advertising.” Translation: software ate

the advertising industry. Gone are the days when clever

mad men (and women) came up with catchy slogans

and tag lines. Instead, powerful algorithms control the

placement and viewing of most advertisements.

It is certain that people will continue to wear apparel and footwear after the pandemic. The more important issue is how shopping behaviors will change.

5Figure12

Figure13

The Trade Desk

Media Math

LiveRamp

Pinterest

Ad Spending by Media Type


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We’re advising our clients to expect the following in the next chapter of retail:

• Programmatic advertising will become a core element of nearly every brand’s media mix: We expect to see brands add balance to their advertising mix. Brands will be dividing their dollars among three media: Search, Social, and Programmatic.

• Migration to In-House Programmatic Advertising: We’re forecasting an acceleration in the trend to move programmatic advertising in-house. Much of the work previously done by advertising agencies will be done in-house by the brands. Brands now realize the importance of building institutional knowledge in house.

• Personalization, Version 2: We expect to see the next wave of personalization in retail. Many of our clients are focused on improving email personalization and upgrading their loyalty programs to better reward loyal customers. Younger customers aren’t opposed to their data being used to personalize music on Spotify or to create a personal Amazon shopping experience. We frequently see apparel brands who send the same email to every customer in their CRM. That practice will need to change rapidly for sellers to remain competitive.

• Sophisticated customer targeting: A key measure of targeting efficiency is an ecommerce site’s bounce rate. This is the number of site visitors who look at only one page and leave. Very few brands have bounce rates below 50%. This means 50% of the brand’s advertising dollars are most likely wasted on customers who won’t engage. Targeting the right customer, as defined by someone who will love your products, will be key for the surviving companies.

• The Invisible Omnichannel: For the past 20 years retailers have institutionalized the notion of the “omnichannel” to describe their various distribution channels: In-store, online, wholesale, Instagram, and the other ways of selling to customers. The problem is that this is largely an internal organization concept. The conflict is customers don’t see themselves as belonging to any one of your omnichannels. In fact, you’re a uni-channel in their minds. They view “Nordstrom” as one entity. Sometimes he or she visits in-store, sometimes on the Nordstrom web site, sometimes the mobile app, and sometimes at a Nordstrom Rack. The consumer wants all purchases, regardless of where the sale took place, instore or online, to be visible in your app or on your web site. The notion of an omnichannel may have helped create organizational structure and territories in a retailer, although it delivered negative benefits to a customer. Home Depot is one of the first companies to seamlessly integrate in-store purchases with their mobile app. If you make a purchase in a store you’ll see that purchase, and receipt, appear in their mobile app. It’s the Home Depot uni-channel to its customers.


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Behavioral Change Roadmap

Americans will define a new normal for life after the

pandemic. There was a time when a man’s preferences

included laced-up shoes, although that changed after

the new normal of post-9/11 travel. He may have

changed his shoes taste to slip-on shoes to speed

passage through TSA. We’ve developed new behaviors

and habits in the new normal of post 9/11 travel. The

goal now is to align your brand with realities of new

behavioral norms of the post-pandemic.

Elisabeth Kubler-Ross was a Swiss psychiatrist who

studied human behaviors following the death of a

loved one. Ultimately her research was extended to

the change-management domain and has become an

important way sociologists, industrial psychologists, and

behaviorists model consumer behavioral change. Our

research indicates that in August of 2020 consumers are

entering the acceptance phase of the model, where the

consumer acknowledges the effects of the pandemic will

permanently change life.

The next phase of the model is the experimentation

phase, where consumers begin to try and experiment

with new things to help them adapt. For example, there

were many consumers who had no interest in Apple Pay

prior to the pandemic but are now experimenting with

this safer contactless payment technique. Many people

had never used their computer’s video camera, and are

now running daily experiments to determine what looks

best on the Zoom camera screen.

6 Figure14


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• Working Remotely Becomes More Popular: Prior to the pandemic 3.5% of America’s professional workforce worked from home. We estimate that this could grow to 15 to 20%. Impact: shift in fashion styles to more casual attire.

• Business Travel is Permanently Reduced: We are predicting that business travel will reduce 25 to 30%. Impact: reduced purchasing on business attire and accessories.

• Reduction in Entertainment and Sporting Events: We believe it is highly unlikely Americans will be attending events with large audiences for the foreseeable future. The New York times surveyed 550 epidemiologists about their expected behavioral changes. 40% said they wouldn’t visit a gym, attend church, or go to a wedding until mid-2021. And, 64% said they wouldn’t consider attending a sporting event, concert, or play for at least one year. Impact: reduced sales of fanwear and high fashion.

• On-sale and Promotions in Q3 and Q4: The glut of inventory caused by store shut-downs will ultimately need to be cleared. We are advising our customers to combine on-sale pricing with a sophisticated targeting strategy. Rather than using discounting to simply clear inventory, we advise using targeted advertising combined with promotional pricing to acquire your best new customer. This is the customer who has a taste for your products, worthy of an investment to create a long-term relationship. We’ve developed a special targeting data-set focused on helping brands target the right customers for acquisition. Impact: lower profits balanced with higher customer acquisition.

• Protective Health Measures Become Part of the Shopping Experience: We believe consumer ratings will begin to include comments about consumer safety. One of our employees has observed that his neighborhood grocery store sanitizes the self-check-out after each customer. Contactless payment will become expected and we anticipate stores will add other safety features to create confidence in the shopping experience. The Gordon Haskett Advisory Group recently reported that 70% of consumers are unwilling to shop in-store, illustrating the long path to recovery of in-store shopping. Impact: Consumers will reward stores and brands for providing a safe shopping experience.

We believe brands will see the following consumer behavioral changes in the coming quarters:


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Recommendations for Our ClientsWe’re living in unprecedented times. Consumer behaviors and shopping habits will change dramatically, which will create the new normal for the way consumers purchase soft goods. Brands must make important decisions in the coming quarters. We’ve created the following eight recommendations based on our research, and our unique vantage point. We have developed over 2,700 brand targeting models, using over 5 billion first-party retail transactions. Our DNA is about learning why consumers make decisions and have devoted this perspective to the following recommendations.

1. Prepare your company for the expected Q3 and Q4 promotions frenzy • We advise customers to use promotional and clearance pricing as an element of new customer acquisition rather than simply for inventory clearance. Targeting a customer with potentially high LTV should be the cornerstone of a deal targeting strategy. • We expect significant competition for share-of-wallet given it’s largely a zero-sum game. • We have created special targeting audiences, for nearly every apparel and footwear category to help our clients target the right consumers

2. For the balance of 2020, focus on online sales of Apparel and Cosmetics categories• We’re skeptical that in-store shopping will recover in 2020. We’ll see the combined effects of governments continuing to delay (and sometimes reverse their decisions) and a general reluctance of consumers to be exposed to the virus. • Our surveillance data of web site traffic to apparel and footwear categories align with our expectations of a relatively fast recovery for online apparel sales

3. Redouble your efforts to improve targeted and personalized emails to your client base. Consumers will be responsive to email promotions if the offer has high relevance• A troublesome trend we’re observing is brands increasing email frequency without a focus on creating offers and content that are relevant to the customer. The net result of un-targeted emails will be degradation of your email lists.

4. Upgrade your programmatic advertising strategy• We’re seeing price increases on Facebook and Instagram which we expect to continue for the balance of the year.• Programmatic advertising can expand your reach, diversify your media mix, and provide hedging to Facebook’s increasing ad prices.• There are new abilities to create custom programmatic audiences targeting current and previous customers• Consider bringing programmatic advertising in house. This may be a business function that’s too important to outsource to an agency.

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5. Remain mindful that price is an element of a consumer’s taste in your targeting efforts• A consumer you identify as a Charter Club customer may become a Ralph Lauren prospect when Polo products are on-sale. Price is an important driver, and brand re-purchase rates usually lower during sales. • We recommend targeting customers based on their product tastes rather than on previous brand purchases. Our data indicates consumers are generally brand indifferent, while generally very consistent in staying within their demonstrated tastes. When our taste data is used for targeting it almost always outperforms brand re- purchase campaigns.

6. Hiring and Staffing will be critical elements of a brands survival strategy• Now is the time to add digital marketing expertise. It’s critical to add staff with intimate knowledge of the programmatic advertising ecosystem.

7. Pivot your omnichannel strategy to be more customer centric• Consumers don’t think of themselves as a mobile, online, or in-store customer. They’re largely indifferent to where a purchase is made, and simply view themselves as one of your customers. • They expect you to treat them as one customer, regardless of their switching between direct channels. The most advanced retailers are instantly adding an in-store purchase to a mobile app using the credit card account number as a pseudo customer identifier.

8. Make your mobile app part of the shopping experience, not a mobile version of your store• Millennials and GenZ are now a larger population than Baby Boomers and Gen X’ers. If you survey them on what they want while shopping in a store, they won’t say helpful sales clerks. Instead, they’ll say they want a powerful mobile app, and to be left alone. They want to be empowered with information, not the target of a sales person.• Sephora has set an excellent standard for integrating its mobile app into the in-store experience. When a shopper sees a cosmetic product in the store, she can do a virtual try-on of the product using the app. The consumer has previously loaded her photo into the app, and Sephora enables her to overlay any of their products on the consumer’s image.• Home Depot has done impressive work adding in-store navigation to their app. If you search for a product using their app, it’ll tell you the precise aisle and shelf location of the product, and how many remain in-stock. They aren’t worried about customers ‘showrooming’, rather they’re interested in helping the consumer navigate their massive stores.


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About PreciseTarget: Data for BrandsPreciseTarget is a behind-the-scenes data provider to wholesale and retail brands. We’ve done extensive research and development in consumer decision making, leading us to learn that a consumer’s personal taste is a key decision diver. What is taste? It’s the collection of product attributes that are integral to the decision process of whether or not to buy a product. Price, brand, fabric, color, size, style, fit and many other attributes determine whether a product makes it into your closet.

We’re a machine learning company, which means we use machines to learn about a consumer’s taste. Retailers and brands have trusted us with over 5 billion SKU-level transactions. They’ve also provided us with the meta-data about the purchased products, which are the attributes of the product. Our machine learning is looking at the attributes of the product a person likes, in order to arrive at the machine knowledge, the person likes slim jeans between $60 and $70, or sub $50 running shoes in bright colors. This large data set has enabled our machine learning system to create taste profiles of 99% of US adults in virtually every soft goods category. Our consumer taste profiles are often used to enrich a brand’s CRM system.

Our customers use our data to target new customers for acquisition, or to gain insight about their current customers. When a brand targets a consumer based on their product tastes it will almost always out-perform brand re-purchase campaigns, demographics-based targeting, and look-alike campaigns. Our insights data is designed to solve the sparse customer data problem. Brands typically know very little about their customers, often someone who has only purchased one or two items. We ‘append’ our data to their customer file, which means we enrich a brand’s customer file with valuable new information.

We have two families of data products:

Targeting Audiences: We have off-the-shelf audiences to enable brands to target customers for acquisition: The data is available in the advertising ecosystem, making it off-the-shelf and available immediately.

Brand Taste Audiences: audiences of people who over-index for specific brands. (Typical audience sizes: 4 to 10 million customers)

Product Taste Audiences: people who over index for price tiers of products. Examples: low-priced running shoes or high-priced women’s outwear categories

Retailer Taste Audiences: people who score highly for the products of a retailer

On-Sale Audiences: people who are likely to make a purchase in a category during a sale

Individualized Insight on Customers: • We have taste profiles on over 99% of the US adult population • Customers enrich their CRM’s, CDP, or data lakes with our profile information • We have a sophisticated method, using a trusted exchange partner, to pass our data to a brand without us every knowing the customers in the file.

Our products are available for testing, and for small to large scale deployments. Your PreciseTarget solutions team is available to help you test and learn how we can be additive to your strategy.

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Sources:

U.S. Census Bureau, Advance Retail Sales: retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/RSCCAS, July 23, 2020.

Zenith Advertising Expenditure Forecasts. (December 2019)www.zenithmedia.com

“MID-YEAR 2018 RIAA MUSIC REVENUES REPORT.” September 20, 2018. Accessed December 16, 2018. https://www.riaa.com/wp-content/uploads/2018/09/RIAA-Mid-Year-2018-Revenue-Report.pdf.

Mcann, Zenith, BLS, @BenedictEvans

This research document, including the information contained herein, has been compiled for informational purposes only and does not constitute an offer to sell any product or service. The document relies on data and insights from a wide range of sources, including public and private companies, market research firms, and government agencies. We cite specific sources where data are public; the presentation is also informed by non-public information and insights. We disclaim any and all warranties, express or implied, with respect to the presentation. No presentation content should be construed as professional advice of any kind.

WHITE PAPER Outlook for the Apparel Industry Post-Covid 19

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