Report.

1. RETAIL 2025
How will Immersive Technology affect Global Retail by 2025?
Final Paper
Urban Economy URP6042
at the
University of Florida
Bryan Dentici
December 1st, 2019

2. Introduction
The retail industry has gone through revolutionary change in recent years due to the exponential
growth of e-commerce. Online retail has grown 300% between 2000 and 2018. During that same
period, department store sales have dropped almost 50% according to the U.S. Commerce
department. In 2019, the total market share of “non-store” online U.S. retail sales were higher than
general merchandise sales for the first time in history (CNBC 2019). The “Retail Apocalypse” is the
name given to the phenomena which started in 2010. It has also affected employment as the sector
has lost nearly 200,000 jobs since the start of 2017 (CNN 2019). Most of those jobs were from
traditional department stores and clothing stores.
The “Retail Apocalypse” will cause brands to change their value proposition to consumers because of
changing expectations. Surviving retailers will need to enhance the customer experience with new
technologies as the behavioral habits of consumers have been heavily influenced by the digital age.
The retail transformation will also change the nature of urban development and real estate as the
trend is now to build smaller stores in urban settings. The desirability of communities will be affected
because proximity to retailers will no longer be relevant due to store closures. Industrial real estate is
hot because of e-commerce and warehouses are being located close to urban areas where
customers live.
Consumers have much more leverage these days with user-generated content in the form of reviews.
In an article on Retail Touch Points in 2012, it states that Millennials trust the opinion of strangers in
user-generated content much more than the recommendations of the people they know. 86 percent
of Millennials indicated that user-generated content is a good indicator of the quality of a brand,
service or product (Retail Touch Points 2012).
Time value is now at a premium. Brick-and-mortar retailers can no longer afford to cost consumers
valuable time during the in-store shopping experience. This could be in the form of fitting rooms,
checkout lines, parking spaces and store location. An estimated 75,000 stores that sell clothing,
electronics and furniture will close by 2026, when online shopping is expected to make up 25 percent
of retail sales (Washington Post 2019).
Most of the items that could be bought in the store are also sold online, where consumer reviews are
widely available, and alternatives are just a click away. Many retailers have already released online
apps to keep up, but the online arena is currently being dominated by Amazon. According to Statista,
global visitor traffic to Amazon was 2.65 billion visits (combined mobile and desktop) in July 2019. By
comparison, Walmart was at 353 million during the same time period (Similar Web 2019).
So, how will brick-and-mortar retailers compete going forward? If they haven’t already, they will need
to join the e-commerce playing field as soon as possible and add value in ways the online-only
players cannot. This means in-store deals, events, and other unique perks. The in-store deals must
be better than the online deals. The biggest adaptation will be to make sure the consumers who do
visit stores have an enjoyable experience. This involves implementing new technology. There are
also sensory experiences in store that cannot be had online.
Before brick-and-mortar stores can give consumers sensory experiences, retailers need to utilize
technology to better their operations. This means real-time inventory management, efficient payment
systems, personalized customer service supplemented by machine learning and integrating mobile
technology with the in-store experience. To bring in consumers, retailers need to understand the
modern consumer and be in sync with the current consumer culture. During the past 15 to 20 years,
we have had 10x more innovations then the previous 140 years. Because of this extreme change,

3. many legacy retailers have experienced a disconnect with today’s consumer, which is vastly different
than in the past. According to Business 2 Community, “only 20% of brands are prepared to meet the
demands of today’s modern consumer” (Business 2 Community 2019). Millennial (and even
Generation Z) consumers are more diverse and they are (and will be) under greater financial
pressure (Visual Capitalist 2019). We’re in an on-demand culture and some call this the “Amazon
effect”. The modern consumer demands things like data security, constant customer support and
relevant experiences based on their culture. They want personalization, strong brand purpose and
price transparency. Brand loyalty does not exist like it did in the past. Access to information means
that research before a purchase is likely. Also, the modern Millennial consumer will be accepting of
giving personal data if the brand is transparent with them.
The main form of this technology I will focus on is Augmented Reality. I will also touch a bit on the
development of new payment systems for in-store retailers. Artificial Intelligence is a big part of both
these new retail technologies. These new technologies can be leveraged to reach the customer and
facilitate a positive retail experience.
A big question at the source of all my research is, “Is it inevitable that online shopping will continue to
grow so that brick-and-mortar stores will eventually serve mainly as showrooms?” Is this why some
retailers are moving towards smaller spaces? This may be the case. The sooner retailers
understand this, the better.
Implications
In 2017 alone, retailers closed a record 102 million square feet of space and then proceeded to break
that record in 2018 with an additional 155 million square feet, according to CoStar. Sears filed for
bankruptcy in 2018 and closed 3,500 stores (USA Today 2019). As of November of 2019, they will
only have 182 stores left. This year (2019), closings are at a record level with more than 9,300 store
closings due to the “retail apocalypse”.
Fortunately, it’s not all bad news. The retail industry is anything but dead. Total retail sales (including
ecommerce) has been rising. The six-year range, from Q4 in 2015 to Q2 in 2018 has grown 4.1%
and continues (Wolf Street 2019).

4. Another surprising fact is that the total number of retail establishments has been increasing because
of new chain stores and restaurant openings. These openings have filled the gap from the many
store closings reported in the media. Grocery stores and supermarkets have seen the most growth in
sales, but restaurants and drinking establishments will soon pass them. Even though these
restaurants are not classified as retail in the Bureau of Labor Statistics data, these establishments
attract shoppers and enhance the retail experience (CNU 2019).
So, what strategies are these new retailers going for in the digital age?
Established retailers are focusing on urban locations with smaller “micro” stores. Some of these
retailers include Target, Ikea, and Nordstrom. These smaller locations are designed to complement,
synergize the experience across digital and physical channels. Inventory is minimized and these
“micro” stores are located closer to where customers live and work (Forbes 2018). Retailers are
essentially reengineering their value proposition.
First Target opening in Manhattan in 2016 New Target in downtown Denver in 2017
Another substantial implication is the deskilling of thousands of jobs. Sears alone has cut out
250,000 jobs since 2004. Macy’s no longer has a dedicated cashier as the department store now has
a “stock” person that handles the entire floor. This term “stock” was used in a 2017 article in a
research finding from the Work in Progress journal. It’s no longer enough to have a positive attitude

5. or person charm as a salesperson in the retail industry. At Target, selling was “routinized” as
transactions were judged on the speed of processing, not on the quality of service.
While the retail sales sector is losing jobs, warehouse and distribution jobs are exploding. According
to CBRE, the growth of e-commerce forecasted demand for 452,000 warehouse and distribution jobs
in 2018 and 2019. The Inland Empire in California is #1 on this list, adding 41,300 jobs since 2013
(CBRE 2018). This is a growth rate of 48.6% during that period. Warehouses are being developed in
areas that are both close to customers and in areas to find labor. From 2011 to 2015, the warehouse
and distribution sector has seen a 66% increase in workers. Although, this isn’t enough. Since 2000,
employment in warehousing has risen 90%, while the average employment growth was at 12%
(Supply Chain Dive 2017).
In the real estate industry, mixed-use developments are becoming one of, if not the most popular
product type for developers. Mixed-use developments have made up a large portion of the record
high $1.26 trillion in construction spending in 2017 (National Real Estate Investor 2017). These
developments include multifamily, office, retail and restaurants (which were mentioned earlier).
These days, it’s about using land efficiently in urban areas. The growth of mixed-use development
goes along with the shifting of consumer expectations towards the concept of “convenience”. The
digital age has caused society to expect instant gratification. This lifestyle change is the key driver.
Residents now crave “walkable” communities with vibrance.
The History of Retail Innovations
To fully understand the context of a generational “disconnect”, I will briefly go over the history of retail
innovations. Many people who grew up during these times are tasked with reaching the modern
consumer. By going over the past, we can get a better picture of how much of a challenge it has
been to keep up with innovation in the 21st century.
Retail advertising
The history of retail goes back thousands of years. In 800 BC, ancient Greece had the Agora in the
city center where people came to shop and socialize (Big Commerce 2019). “Mom and pop” shops
have been around since the 1800’s and the first shopping mall was outdoors in Kansas City in 1922.
It wasn’t until 1956 when the first indoor mall opened in Edina, Minnesota. Fast forward to today,
roughly 60 years later, and the indoor shopping mall is becoming extinct.
In the early days of retail, advertising was all about the physical branding. Signage and packaging
were the only ways to differentiate for retailers. Then came the traveling salesmen and direct mail
catalogs. TV advertising began with a Bulova watch commercial on July 1st, 1941. It was a 10-
second ad that 2,000 people viewed. TV advertising evolved as color, cable channels, and increased
distribution made this advertising channel a monster. In 1955, TV advertising reached $1 billion in
spending. In 1977, revenues rose to $7.5 billion (Oracle 2019).
In 1984, Apple released a commercial spot during the Super Bowl that convinced the world that
television advertising was a very effect way to reach consumers. The commercial spot was named
“1984” and was directed by Ridley Scott (acclaimed director of Alien, Blade Runner, Gladiator, etc.).
Consumers would go on to purchase $155 million worth of Macintosh computers within the three
months after the Super Bowl (Business Insider 2014).

6. (“1984” Apple TV spot during the Super Bowl based off of George Orwell’s novel Nineteen Eighty-Four, which was set in a
dystopian future controlled by “Big Brother”)
Television was much more concentrated before the internet age. When advertisers spent money on
TV spots, they could be sure it was reaching a large amount of people. Today, people use a wide
range of media channels to get their content. It’s not even close to being comparable. The
landscape is extremely fragmented.
The touch points between consumers and businesses are everywhere in the digital age. It follows
consumers in their hand, pocket or purse, at home, at work and in the car. According to Salesforce,
70% of customers say connected processes are very important to winning their business. They judge
a company based on their experience as a whole and they expect consistency across channels
(Salesforce 2019). Below is a breakdown of how Baby Boomers, Gen Xers, Millennials, and Gen
Zers prefer to communicate with companies. Note the discrepancy of preference on mobile apps.

7. Cash Registers
The way a consumer purchases a product is vital. The cash register was created over 140 years ago
and it was hardly updated since then, relatively speaking.
The cash register was invented in 1878 by an Ohio saloon owner named James Ritty (Thought Co.
2019). He received a patent and tried to manufacture the invention, but his company was a failure.
John H. Patterson bought Ritty’s patent and the company that sold the cash register. He improved it
by adding a paper role to record the transactions. He named his company the National Cash
Register Company. NCR was founded in 1884 and is now a public company with assets of $8.451
billion as of September 30th, 2019 (YCharts 2019). The cash register would continue to go through
improvements the following years as an electric motor was added in 1906 by businessman Charles F.
Kettering.
Ritty’s cash register had a large dial that was used to count the inputs along with keys labeled in five
cent increments from 5 to 95 cents and dollar amounts from 1 to $9. It had no cash drawer. The
“clock”, or dial, recorded the sales. The outer circle showed cents and the inner circle showed
dollars. The 2nd iteration of the machine did not have a dial, but an indicator with adding wheels
mounting in the back of the machines. Neither of these first two machines were put on the market.
(1st
machine with round dial) (2nd
machine with indicator. First patent for a cash register. 1879)
After the patents and register were bought by Kettering, the NCR continued to develop the cash
register in the early 20th century. A cash drawer was added along with the electric motor and paper
rolls. By the 1940’s, the cash register was a must in every retail store (eats 365 Pos 2019).
I focus on the cash register as a proxy to demonstrate the rate of innovation. The cash register in the
late 1800’s was roughly the same as it was in the 1980’s. See below.

8. On the left is a cash register from 1894 and on the right is a cash register from 1980. Both are from the National Cash
Register company.
The cash register was the main payment facilitator until the credit card became popular and electronic
payment terminals were introduced in the 1970’s. The POS system wasn’t changed until computer
software was introduced I the 1980’s and 1990’s. Although today, almost all of us have our own POS
system and cash register in our pockets.
Our computers and mobile devices currently account for almost 12.4% of total retail in the United
States (Statista 2019). The digital payment method we use today, combined with consumer credit is
noteworthy in that our integration to a cashless society began decades ago. Only in the past 10 or so
years has it been exponentialized by digital payments.

9. Consumer Credit
The idea of consumer credit goes all the way back to 1914 when Western Union issued a metal plate
to employees instead of a traditional paycheck. This plate was a “closed-loop” system and could only
be used at company-owned stores (Be Business Ed 2019). In 1946, a banker named John Biggins
pioneered a program with the “charg-it” card program. These cards could be spent only at local
merchants who then forwarded an invoice to Biggins. These cards could not be taken out of town
and the users had to bank with Biggins (NX Gen 2019). Overall, retail was a cash industry until the
first credit card was created by Diners Club in 1950. Although, this card required the entire balance
to be paid off each month (Credit Karma 2019). In 1951, Diners Club had 20,000 cardholders. Bank
of America offered the first general-purpose “revolving credit” card in 1958. American Express
introduced the first plastic card in 1959, which replaced cardboard and celluloid (Credit Cards 2017).
(Dinners Club card 1950) (American Express plastic card 1959)
Credit card processing required a massive amount of paper. Paper-based systems eventually
became too tedious to handle the large volume of customers. In the 1970s, National BankAmericard
and Interbank Card Association released the first electronic online authorization systems (Be
Business Ed 2019). This was when point of sale technology and cash registers finally met the
computer (Vend 2019). In 1970, a magnetic stripe was added to credit cards. This magnetic strip
was invented by an IBM engineer, which contained information needed to validate payment. This
included the cardholder name, number, authorization code and expiration date. In order to read the
magnetic strips, the first electronic payment terminal was created in 1973 (Mobile Transaction 2019).
The system linked merchants to the Visa data center in California. The first patented chip card was
created by a French inventor Roland Moreno in 1975. This utilized a microprocessor that was first
used in calling cards and then in bank cards in 1985. The first electronic card machine was launched
by Visa in 1979 (Mobile Transaction 2019).
The wireless card was first invented by a Norwegian company in 1997 and this led to restaurants
adopting WiFi terminals that allowed customers to pay at their table rather than going to the till
(Mobile Transaction 2019). Today, mobile wallets have begun to grow, but these digital payments
can be traced back to 1997 as Coca Cola released vending machines in Finland that allowed
customers to pay for purchases with text messages (Sociable 2019). By 2003, 95 million consumers
used a mobile device to make a purchase. Google was the first to launch a mobile wallet in 2011.
Apple wasn’t far behind with the “Passbook”, which focused on boarding passes, tickets and
coupons. Apple Pay was then announced in 2014 (Tech Bullion 2016).
Payment systems are a major source of innovation for the retail industry as cash is slowly becoming
obsolete. These systems are the intermediator in the process between consumer and merchant. A

10. cashless society allows easier transfer of currency while traveling, it equates to lower crime because
of the lack of tangible money to steal, and it saves consumers time costs of handling and depositing
the cash.
It’s estimated that in 2020, 90% of smartphone users will have made a payment with their phone.
Currently, there are 265.9 million smartphone users in the U.S. alone (Statista 2019). In the world,
there are 2.71 billion smart phone users (Tech Jury 2019). The smartphone is the main tool used by
the retail industry in its’ integration of new technology. This is also a big part of my research on the
effect of Augmented Reality.
Research & Methodology
I wanted to get an idea how the retail landscape will look by the year 2025. We’re current on the
brink of the Fourth Industrial Revolution and consumers behavior has changed. In addition, the
Millennial generation is becoming the most studied generation in history because of its place in the
center of the digital age.
I designed a survey to get some input directly from consumers when it comes to new retail
technologies current under development. I also wanted to get a sense of shopping habits and
preferences.
For AR to be effective, consumers will have to adopt it. The questions I formulated were designed to
ask consumers how (if at all) they would use this AR technology. At the end of the survey, I asked if
a new “frictionless” payment system would affect their shopping habits. The nature of the AR
technology is a mobile application that could be used on a phone or a laptop/desktop computer. It
would allow consumers to see the retail product in full 3D AR and put the product on themselves
(clothing, shoes, jewelry, purse, wallet, etc.) or in the context of their home (furniture, stereo
equipment, décor, etc.).
I also asked about a “Virtual” AR fitting room that would allow the customer to try different colors or
styles on themselves without needing to use the actual fitting room. This technology uses advanced
body scanners with a live feed that superimposes the 3D model or picture over the customer.

11. In my research, the value of time was a big consideration. In this on-demand culture, time has a
higher cost than it ever did. My thought was that if a retailer could save a customer costs on time, it
would lessen barriers to purchases in a brick-and-mortar store. This would then translate to profits.
In my survey, I mainly focused on clothing retailers. The reason for this is that people still have a
reason to go to stores to try on clothes. Also, some people buy clothes online and some people
don’t. It’s a category that can still be shifted one way or another. If technology gets to the point
where it becomes unnecessary to try clothing on at the outlet, consumers will start buying more
clothing through e-commerce. On the other hand, if retailers add value to the in-store experience,
this may be enough to keep consumers walking through the door.
These are some of the questions I asked:
• How would an Augmented Reality (AR) phone/computer app affect your shopping habits
for clothing (including accessories)?
• How would an Augmented Reality "virtual" fitting room in-store affect your use of a real fitting room
while shopping for clothes (including accessories)?
• How would an Augmented Reality "virtual" fitting room in-store affect your shopping habits?
• Imagine a new "seamless" payment technology was implemented in all retail stores which
allowed instant (no lines) checkout. How would this affect your shopping habits?
I have three main research questions I wanted to answer from this survey. The first is:
1. What demographics will make use of & benefit from AR technology in the retail
industry?
a. How will they use AR technology in the retail industry?
My survey was not restricted to the Millennial demographic. I also had a broad spectrum of
respondents from different parts of the world due to my past travels and connections. This included
Hong Kong, Barcelona, London, Thailand, Toronto, and from US cities such as Austin, Denver,
Portland, New York and Los Angeles, along with the largest portion being from Florida. The age
distribution was from 18 to 64 years old, with the largest age range being from 18 to 25.
I differentiated the uses of AR technology by asking about store visits and online purchases. Also,
the mobile AR app and the in-store “Virtual” fitting room assumes the customer will either go to the
store, buy from the mobile app, or a combination of both.

12. The second question was:
2. What type of products will benefit the most from Augmented Reality (AR) technology?
I focused mainly on the clothing and apparel industry, but there was a section where I listed a range
of products and asked if they would buy the product without seeing it. The matrix question is below.
I also asked the females if they would buy beauty products (makeup) on AR technology.
The third question was:
3. How much more profit can be made by using AR & artificial intelligence payment
systems?
A few of the questions I asked were regarding the additional number of visits to stores if the use of
AR was available. I also asked about increased spending due to the technologies:
• With both the mobile and in-store Augmented Reality technologies available, how would this affect
your total clothing (including accessories) spending per month?
The survey was created to get an approximation of how much more revenue a retailer can receive in
only one industry, which was clothing & apparel. I wanted to find out if AR technology combined with
other strategies could change the economic outlook for these retailers. My intention was not to get
robust quantitative data, so I used ranges of spending amounts and the number of visits.
The main methods I used for statistical analysis was cross-tabulation and correlation. I segmented
different demographics based on patterns I discovered. I used the 0.70 level as an indicator that the
correlation coefficient was significant. As for negative correlation, I used the level -0.50, but this was
only to show patterns in the data. I did not pay attention to data that was correlated with some of the
information because even though I recoded all the questions, not all had ordinal levels. Most of the
questions had ordinal answers, but many did not. There were a couple questions that called for
percentages, but these questions used as a range.
Results
I was able to get 50 respondents total (27 males and 23 females). This was done through the
University of Florida’s Qualtrics software account. There were no incentives offered to survey
participants, so it was difficult to get a large sample size. I think for the objective of this research, 50
survey respondents gave a good indication of consumer behavior.
When doing a correlation with the full sample, I noticed the most significant patterns with the age
range of 18-25 and 26-34, the Millennial age range. Although, this could have been because a larger
portion of my sample was within this range. The first segmentation I focused on was Millennial
females age 18-34.

13. I found there was a correlation with these three survey questions:
• How would an AR "virtual" fitting room in-store affect your use of a real fitting room while
shopping for clothes (including accessories)?
• How would an AR "virtual" fitting room in-store affect your shopping habits?
• With both the mobile and in-store AR technologies available, how would this affect your total
clothing (including accessories) spending per month?
• There was also a negative correlation with relationship status and a willingness to buy jeans off
mobile AR.
From this, I came to the following four theories:
• The more visits to the store, the more likely they were to buy makeup on mobile AR
• The more they were in a relationship, the less likely they were to buy jeans off the mobile AR
app.
• An AR fitting room will have effect on overall shopping habits
• The more an AR fitting room affects shopping habits, the more AR technology overall will
increase spending
Next, I segmented Millennial males age 18-34. I only found one interesting insight with this
demographic and I had to make the connection through two correlations.
• There was a correlation between the frequency of visits and average spending, but then there
was also a correlation between visits and status.
My theory is that spending on clothing increases with more store visits, but as males 18-34 are in a
relationship, the visits increase because of the influence of the partner. Could Millennial spending for
males be indirectly related to female store visits? This makes sense, but to what extent?
This goes along with my analysis of males over 34 years old. I found a high negative correlation with
store visits and marital status (-0.80).
Now, we come to males over 34 years old: I found a couple interesting correlations here.

14. • There was a negative correlation between frequency of visits and relationship status.
• There was also a correlation between age and the willingness to buy jeans from an AR mobile
app without trying them on in the store.
My theories are as follows:
• Men over 34 visit the store less when they are in a relationship.
• As men over 34 get older, they are more willing to buy jeans on the mobile AR app.
The theory that men over 34 visit the store less when they are in a relationship is significant because I
coded the marital status questions to equate with a “level” of relationship. The key here was the
choice of “Single but cohabitating with a significant other”. This gives another level to the correlation.
The significance of males over age 34 being willing to buy jeans off the mobile AR app is that jeans
were the item least likely to be bought through AR without seeing them in person (trying them on).
So again, men over 34 do not go to the store when they are in a relationship. But with men 34 and
under, the frequency of visits goes up with relationship status. This is an interesting insight in that
there may be a behavioral difference between different ages of males in relationships. Men under 34

15. may be subject to more influence by their significant other than males over 34. If this is true, could
advertising narrow this demographic with more personalized focus on females and males under 34
who are in a relationship? This could involve several different strategies.
The last demographic segment I separated was both males and females outside of the U.S. This
would include Barcelona, London, Hong Kong and Toronto.
I found some correlations with different questions and products, but they mostly involve the females
because of the willingness to buy beauty products on the mobile AR app, which wasn’t displayed to
male respondents. The following two questions were correlated.
• How would an Augmented Reality (AR) phone/computer app affect your shopping habits
for clothing (including accessories)?
• Would you buy beauty products (including makeup) on an Augmented Reality (AR)
phone/computer app?
Also, the following products were correlated with the willingness to buy beauty products on the mobile AR
app:
Shoes
Sunglasses
Furniture

16. From these correlations, I discovered that woman outside of the U.S. would be more willing to buy
makeup or beauty products if they were influenced by AR technology. Also, if the females were willing to
buy makeup on AR, they were also willing to buy shoes, sunglasses, and furniture on mobile AR only.
Both the males and females outside of the U.S. would be willing to buy home electronics on the mobile
AR app if their shopping habits were influenced by AR technology.
When it comes to the retailers, I did a crosstabulation of the products asked about on the survey and I
found that overall, home electronics (TV, stereo, etc.) were the most popular item to buy from mobile AR.
The least popular was jeans. The following is the ranking.
1. Home Electronics (TV, Stereo, etc.)
2. (Tied) Bag (wallet, purse) & Home Décor
3. (Tied) Jewelry & Sunglasses
4. Furniture
5. Shoes
6. Jeans
The other insights from the questions are the following:
• The effect of the mobile AR app on clothing purchases.
o 44% of the respondents would buy more clothes on the app and go to the store less.
o 6% of the respondents would buy more clothes on both app and in-store.
• Beauty products on the mobile AR app
o 47.80% of female respondents would maybe buy beauty products on the mobile AR app.
o 30.40% of female respondents said yes, they would buy beauty products on the mobile AR
app.
• AR “virtual” fitting room.
o 32% of respondents to use the fitting room slightly less.
o 12% of respondents to use the fitting room much less.
o 6% wouldn’t need to use the fitting room at all if they had access to a “virtual” fitting room.
• AR’s total effect on clothing purchases.
o 24.00% Would spend $20-$50 more per month on clothing
o 18% Would spend $51-$100 more per month on clothing
o 2% Would spend $101-$200 more per month on clothing
o 2% Would spend $201-300 more per month on clothing
• New payment technology
o 51% Maybe would go shopping once or twice more per week.
o 6% Would go shopping 3-4 times more per week.

17. Conclusions & Limitations of Research
This research had a relatively small sample size so there is a larger margin of error. I was unaware of
how many respondents I could get when working on the survey. I am also not that familiar with in-depth
statistical analysis, so other methods could have possibly been utilized.
Also, the survey had limited coverage on the effect of new “frictionless” payment systems. More research
on this technology could be beneficial for retailers.
From this small survey, it’s apparent that many respondents would buy more clothes on the app and go to
the store less. This goes into the idea that brick-and-mortar stores will need to be smaller and may only
serve as a showroom for the products sold online. The trend is going towards a larger majority of retail
products being sold online with the assistance of augmented reality technologies.
From this survey, Millennial females aged 18-34 would benefit the most when it comes to clothing retailers
and AR technology. An interesting finding is that Millennial males in relationships may indirectly be
influenced to make more store visits and increase spending. On the other hand, men over 34 decrease
visits to the store when they are in a relationship. In addition, they are also more willing to purchase jeans
on mobile AR. Female survey respondents located outside of the U.S. would be more willing than
females in the U.S. to buy more of the products online, including beauty products.
Electronics (TV, home stereo equipment, etc.) would be the retail category that would benefit the most,
according to this research. Augmented Reality’s total affect may result in an average of $50 to $100 per
month in additional revenue for clothing (and accessories) retailers.
When it comes to “frictionless” payment technologies, respondents may visit stores 1-2 times per week.
This is in reference to all retail categories. I expected this to be a little higher when considering grocery
store visits and smaller CVS or Walgreens type stores. When pondering this more, long lines seem to
matter less and less, unless it’s while shopping during a Holiday like “Black Friday”.
Again, this research was very limited in size and scope. The research deserves much more in-depth
analysis and time dedicated to it. Retailers would benefit from getting additional information on customer
preferences when AR technology is used, especially when it comes to “hedonistic” spending habits or
“impulse” buying. There also could have been additional statistical methods used that might have
revealed additional discoveries. In judging how accurate these insights were, it remains to be seen.
Future research can also focus on other ways in which AR can be utilized, which includes in-store
entertainment. My preliminary research showed that the “luxury” retail and the real estate sectors are
currently using “Virtual Reality” in very interesting ways. More research could be valuable in this area.
Augmented Reality is already being utilized by retailers like Ikea, Sephora, Nordstrom and Nike. It’s only
a matter of time before more retailers adopt it. As artificial intelligence advances with more complex
machine learning ability, retailers will benefit, but only if they reevaluate their “legacy” strategies from the
past and adapt to the digital age of retail.

18. Sources
Joshi, Naveen. Forbes. “Retailers Have A Lot to Gain from AR and VR”. October 1, 2019.
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