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Copyright @ 2018 Michael Galbreth and Guangzhi ShangPlease do not distribute without permission from authors.
The Impact of Emerging Technologies on
Consumer Returns:Insights from Academia
September 20, 2018
Michael Galbreth Professor and Pilot Corporation ChairHead, Department of Business AnalyticsHaslam College of BusinessUniversity of Tennessee
Copyright @ 2018 Michael Galbreth and Guangzhi ShangPlease do not distribute without permission from authors.
Recent Academic Inquiries
Returns Forecasting
Drivers of Returns
The Returns Experience
Impact of Retail Innovations
Copyright @ 2018 Michael Galbreth and Guangzhi ShangPlease do not distribute without permission from authors.
Recent Academic Inquiries
Returns Forecasting
Drivers of Returns
The Returns Experience
Impact of Retail Innovations
Copyright @ 2018 Michael Galbreth and Guangzhi ShangPlease do not distribute without permission from authors.
Return Forecasting
What we need:
Forecasted returns next
month
What we have:
POS purchase and return
transactions
Shang, McKie, Ferguson & Galbreth (2017)
ID Purchase Date Return Date
xxx Dec-01-2016 N/A
xxx Dec-01-2016 Dec-09-2016
. . . . . . . . .
Thousands oftransactionsper month !
358 returns will come back next month
A single number!
Copyright @ 2018 Michael Galbreth and Guangzhi ShangPlease do not distribute without permission from authors.
Return Forecasting
What we need:
Forecasted returns next
month
What we have:
POS purchase and return
transactions
Shang, McKie, Ferguson & Galbreth (2017)
Transaction-level granularity
Period-level granularity
Aggregate
Aggregate
Predict
Predict
Time-series ORregressionmethods
Classification-styleAND survival methods
Copyright @ 2018 Michael Galbreth and Guangzhi ShangPlease do not distribute without permission from authors.
Implementation Test 1➜ Brick & Mortar channel➜ Consumer electronics➜ Average return rate =
12%
Results➜ Average improvement =
12% reduction in forecast error (RMSE)
Returns Forecasting Shang, McKie, Ferguson & Galbreth (2017)
Audio -30%Auto Parts -9%Cable -12%Computer -19%Imaging -13%Mobile Phone -6%Phone -5%TV -1%TV Box -15%Simple Average -12%
Forecast Error Reduction
Copyright @ 2018 Michael Galbreth and Guangzhi ShangPlease do not distribute without permission from authors.
Implementation Test 2➜ Online channel➜ Jewelry and accessories➜ Average return rate =
8%
Results➜ Average improvement =
18% reduction in forecast error (RMSE)
Returns Forecasting Shang, McKie, Ferguson & Galbreth (2017)
Bracelets -25%Earrings -1%Necklaces -22%Rings -42%Other Accessories -1%Simple Average -18%
Forecast Error Reduction
Copyright @ 2018 Michael Galbreth and Guangzhi ShangPlease do not distribute without permission from authors.
TakeawayPredict-first, aggregate-second
makes return forecasts much more accurate
Why does it increase accuracy?Because it preserves and leverages the
granularity of POS data!
Copyright @ 2018 Michael Galbreth and Guangzhi ShangPlease do not distribute without permission from authors.
Recent Academic Inquiries
Returns Forecasting
Drivers of Returns
The Returns Experience
Impact of Retail Innovations
Copyright @ 2018 Michael Galbreth and Guangzhi ShangPlease do not distribute without permission from authors.
Data: large Brick & Mortar electronics retailer
Return probability decreases with product maturity➜ Longer time on shelf, more WOM and
review info for consumers
What about product variety?➜ less differentiation across products might
increase my regret…however:
➜ more options might help me make a more precise choice…
Drivers of Returns Shang, Ferguson & Galbreth (2018)
Product Maturity Return Probability
Brand New (1st day on shelf) 12.6%
6 month later 11.4%
1 year later 11.3%
Product Variety Return Probability
5 items in same assortment 13.4%
15 items 12.0%
25 items 11.3%
All else equal, both
maturityand varietydecrease the return probability
Copyright @ 2018 Michael Galbreth and Guangzhi ShangPlease do not distribute without permission from authors.
Data: mail-order catalog retailer selling women’s fashion clothing
➜ Color varietyOne more color => 0.7% decrease in return rate
➜ Size varietyOne more size => 0.5% increase in return rate
Drivers of Returns Anderson, Hansen, Simester & Wang (2006)
Copyright @ 2018 Michael Galbreth and Guangzhi ShangPlease do not distribute without permission from authors. Minnema, Bijmolt,
Gensler, & Wiesel (2016)
ValenceAverage rating
VarianceStandard deviation of
rating
VolumeNumber of reviews Purchase
Important emerging influence on retail:
user reviews
Copyright @ 2018 Michael Galbreth and Guangzhi ShangPlease do not distribute without permission from authors. Minnema, Bijmolt,
Gensler, & Wiesel (2016)
ValenceAverage rating
VarianceStandard deviation of
rating
VolumeNumber of reviews PurchaseReturn
A major online European retailer selling electronics and furniture
if rating inflated initially
No Effect
No Effect
if
Copyright @ 2018 Michael Galbreth and Guangzhi ShangPlease do not distribute without permission from authors.
TakeawayProduct maturity and variety are key drivers of returns (and bracketing is an emerging issue in
some categories)
Positive user reviews = fewer returns(but beware of artificially inflated reviews)
A wide variety of user reviews can reduce returns, if consumers find the reviews helpful
Copyright @ 2018 Michael Galbreth and Guangzhi ShangPlease do not distribute without permission from authors.
Recent Academic Inquiries
Returns Forecasting
Drivers of Returns
The Returns Experience
Impact of Retail Innovations
Copyright @ 2018 Michael Galbreth and Guangzhi ShangPlease do not distribute without permission from authors.
THE QUESTION:
“Does customer experience with the product return process affect purchasing patterns following the
return, and if so, how?”*
* Griffis et al. 2012
Copyright @ 2018 Michael Galbreth and Guangzhi ShangPlease do not distribute without permission from authors.
Return Experience Future Transactions
Evidence from Online Retail Data
I love it!no refund needed here!
I’m not happy with this product…
I’ll take a full refund, please!
# of ordersavg. order $basket size
# of ordersavg. order $basket size
Griffis et al.(2012)
less more
less more
PLUS: the faster the refund is processed, the larger all three of these gains become
Copyright @ 2018 Michael Galbreth and Guangzhi ShangPlease do not distribute without permission from authors.
Implication:optimize returns, don’t minimize them!
cost center mentality focuses only here
research supports an effect of returns on this term as well!
Petersen & Kumar (2010)
Copyright @ 2018 Michael Galbreth and Guangzhi ShangPlease do not distribute without permission from authors.
Return Experience Future Transactions
But what if a full refund is not justified?
I’m not happy…I’ll take a full refund,
please!
futurespending
Bower and Maxham(2012)
less more
I’m not happy…I’ll take a full refund,
please!
The product works perfectly, so there
will be a fee
no problem!
futurespending
current
morecurrentless
Copyright @ 2018 Michael Galbreth and Guangzhi ShangPlease do not distribute without permission from authors.
What do shoppers dislike the most?
Source: Narvar Report, June 2017 (consumer survey)
Copyright @ 2018 Michael Galbreth and Guangzhi ShangPlease do not distribute without permission from authors.
immediate retailer benefit
Are exchanges better than returns?Ertekin(2018)
How ‘bout an exchange?
HOWEVER…
Empirical Finding #1:➜ In terms of customer lifetime
value, future purchase behaviormatters more than immediate exchanges
sales pressure during returns process
lower returns satisfaction
fewer future purchases
Don’t lose focus on this!
Empirical Finding #2
plus, sales pressure does not necessarily increase exchange probability!
Copyright @ 2018 Michael Galbreth and Guangzhi ShangPlease do not distribute without permission from authors.
Are exchanges better than returns?Ertekin(2018)
How ‘bout an exchange?
So What is the Solution?
highly competent returns desk staff
higher returns satisfaction
more future purchases
Empirical Finding #3
plus, exchange probability increases!
Copyright @ 2018 Michael Galbreth and Guangzhi ShangPlease do not distribute without permission from authors.
Takeawayfull refunds, while costly, can
drive future revenues(the optimal return rate is not zero!)
restocking fees can deter abuse, but they can also lead to feelings of unfairness, regret, and
lost future business
Investments in highly competent returns desk staff might be justified
Copyright @ 2018 Michael Galbreth and Guangzhi ShangPlease do not distribute without permission from authors.
Recent Academic Inquiries
Returns Forecasting
Drivers of Returns
The Returns Experience
Impact of Retail Innovations
Copyright @ 2018 Michael Galbreth and Guangzhi ShangPlease do not distribute without permission from authors.
A CHALLENGE FOR ONLINE RETAILERS:
How do we overcome the lack of an ability for customers to truly assess the “look and feel” of a
product before purchase?
Copyright @ 2018 Michael Galbreth and Guangzhi ShangPlease do not distribute without permission from authors.
POTENTIAL SOLUTION:IMPROVED ONLINE VISUAL TOOLS
3 common approaches:
De et al.(2013)
1. color swatches
2. zoom functionality
3. alternative photos (models, angles)
no evidence of a relationship
between viewing different colors and
return rates
Some (weak) evidence: using zoom leads to
LOWER return rates
(factual information)
Strongest empirical result:
alternative photos lead to HIGHER return
rates
“impression-based” information
unrealistic expectations?
Copyright @ 2018 Michael Galbreth and Guangzhi ShangPlease do not distribute without permission from authors.
POTENTIAL SOLUTION:VIRTUAL FITTING ROOMS
Customer creates a “virtual model” by providing body measurements, skin tone, and hairstyle.
Does it work? Based on a randomized field experiment:
conversion rate
order size
Gallino and Moreno(2017)
$
$$$
return rate
10-16% increase!
1-2% increase!
>5% decrease!
Net Result: 13.5% profit increase from the virtual fitting tech
Copyright @ 2018 Michael Galbreth and Guangzhi ShangPlease do not distribute without permission from authors.
POTENTIAL SOLUTION:VIRTUAL FITTING – emerging tech
Copyright @ 2018 Michael Galbreth and Guangzhi ShangPlease do not distribute without permission from authors.
TakeawayZoom technology and other sources of factual
info seem to reduce returns. But beware of impression-based info!
There is evidence that virtual fitting rooms are very effective at reducing returns (along with
other benefits)
Copyright @ 2018 Michael Galbreth and Guangzhi ShangPlease do not distribute without permission from authors.
Thanks!Any questions?
Michael Galbreth University of Tennessee
Copyright @ 2018 Michael Galbreth and Guangzhi ShangPlease do not distribute without permission from authors.
Anderson, Hansen, Simester, Wang (2006) How are demand and returns related? Theory and empirical evidence. Working paper.
Bower, Maxham (2012) Return shipping policies of online retailers: normative assumptions and the long-term consequences of fee and free returns. Journal of Marketing, 76(5).
De, Hu, Raman (2013) Product-Oriented Web Technologies andProduct Returns: An Exploratory Study. Information Systems Research, 24(4).
Ertekin, N. (2018) Immediate and Long‐Term Benefits of In‐Store Return Experience. Production & Operations Management, 27(1).
Gallino, Moreno (2017) The value of fit information in online retail: evidence from a randomized field experiment. Manufacturing & Service Operations Management, 20(4).
Griffis, Rao, Goldsby, Niranjan (2012) The customer consequences of returns in online retailing: An empirical analysis. Journal of Operations Management, 30(4).
Cited Academic Studies
Copyright @ 2018 Michael Galbreth and Guangzhi ShangPlease do not distribute without permission from authors.
Minnema, A., Bijmolt, T. H., Gensler, S., & Wiesel, T. (2016) To keep or not to keep: Effects of online customer reviews on product returns. Journal of Retailing, 92(3).
Petersen & Kumar (2010) Can product returns make you money? MIT Sloan Management Review, 51(3).
Shang, McKie, Ferguson, Galbreth (2017) Using transactions data to improve consumer returns forecasting. Working paper.
Shang, Ferguson, Galbreth (2018) Where should I focus my return reduction efforts? Data-driven guidance for retailers. Decision Sciences, in press.
Cited Studies