Nordstrom started modestly in 1901 as a small shoe store in
Seattle, and has since expanded to over 225 stores doing over $10 billion in
annual sales across the country. “The art of retailing has changed dramatically
over the last century and retailers today are concerned with understanding
customer behavior and preferences both in the physical world and online.
Today’s customers expect a unified, relevant experience across all
touch-points: online, in-store, and on mobile devices.” (Shellman
& Von Lehman, 2013) For example, with catalogs in the 80’s, consumers expected
to have a very different experience from their brick-n-mortar store experience. Today, online and offline experiences need to
be consistent with the same pricing, same inventory availability, same promotions,
and same return policies, and to make online experiences relevant, big data
analytics is required.
Data Collection &
Analytics
Recognizing
that their future growth will be online, Nordstrom has committed over $1
billion to e-commerce and big data over the next five years. The goal is to
determine which products to promote to whom, when, and via which channel. An
immense amount of data is collected from their website, point of sale, “2
million likes on Facebook, 4.5 million followers on Pinterest and 300.000
followers on Twitter. In addition they generate vast amounts of data from their
Fashion Rewards Program as customers that want to enjoy the large amounts of
benefits provided in this program will have to use a Nordstrom credit card that
tracks shopper spending and reward points.” (Rijmenam, 2013)
Nordstrom
has even gone so far as to try and track customers in their brick-n-mortar
stores to gain insights. In 2012 with full disclosure, Nordstrom test marketed
a system that tracked customers as they entered and shopped in their
Dallas-Fort Worth store. In essence, Nordstrom tried to apply google analytics
to a physical retail location based on customer cell phone wi-fi signals. Needless
to say, it was not well received and soon discontinued.
Nordstrom
also has an innovation lab comprised of techies, designers, entrepreneurs,
statisticians, researchers, and artists who continually experiment with the
future of retailing. One of their experiments with developing an app can be
seen here: http://www.youtube.com/watch?v=szr0ezLyQHY&feature=youtu.be
The goal of the Nordstrom Data Lab is to
create products that rely on a wide spectrum of data resources from within the
company and social media to reinforce a unified face to their customers. This
includes emulating aspects of the customer-centric store experience on the web,
and applying novel data analyses to augment and enhance the in-store
experience. Three examples of unique systems they are using include:
·
A recommender system powered by the collective
fashion expertise of personal stylists
·
Engaging, interactive visualizations powered by
d3.js
·
Clothing color trend visualizer (Shellman & Von Lehman, 2013)
Nordstrom also uses data analytics as part of their rigorous
customer segmentation process. Promoting the right products to the right
customers is an important piece of their branding strategy. “Statistical tools
help marketers make sense of their customer segments to deliver personalized messaging.”
(Puri, 2013)
Mobile
is definitely Nordstrom’s fastest growing platform in terms of traffic. Although this traffic is conducting product
research rather than product purchases, the retailer is satisfied with results.
Remembering the retailer’s goal of engagement across touchpoints, this platform
makes its contribution. “According to Jill Murray, senior digital
analyst at Nordstrom Direct, the company puts in a lot of time to track these
mobile consumers through their experience to further understand their behavior.”
(Borison, 2013) Through regression and sentiment analysis,
the retailer ties together what the customer’s intent actually was (research or
purchase) and then follows their path all the way to the store.
“Nordstrom is trying to
enhance its analytics to really be able to address the omnichannel experience
and measure across all of the different channels. To do so, Nordstrom
integrates a wide variety of data using Coremetrics, Teradata, Foresee,
OpinionLab, reviews and ratings. The retailer also uses multi-varient testing
and A/B testing to experiment with new features and innovations.” (Borison,
2013)
Results
Nordstrom
uses analytics across channels as their shoppers often move across channels:
from mobile and online research to in store-purchase. Analytics captures data
from purchasers and is used to make recommendations to future purchasers. For
example, customers are offered various options when viewing a product for other
items to complete a look, and/or similar products to the one they are currently
viewing based on historical data. They can look through trending items or
best-selling items. The website also offers advanced search engine capabilities
which evolved from traffic flow data.
Nordstrom
is also able to acknowledge specific shoppers when they first enter the
website. Customers can be targeted with specific interests and recommendations.
The website is able to record previously viewed merchandise when a customer is
signed into an account. It can locate a customer's profile in the database, and
then display the customer's past purchases and offer new product suggestions
while the customer is still visiting the site. The customers' account page will
also provide them with a history of their past orders. Product pages now
also include social media icons to simplify sharing with friends.
Nordstrom recently
invested in a new gift e-retailer, Wantful.com, and opened a co-branded online
store with the company. “Wantful made last year’s Hot
100, an annual list from Internet Retailer that showcases innovative
e-retailers and cutting-edge e-commerce capabilities. Shoppers using
Wantful—and the new venture, The Nordstrom Gift Collection by Wantful—go online
and enter personal data about the gift recipient. That data includes the
occasion (such as a birthday), gender, relationship to the person (friend,
son), spending limit and lifestyle preferences. The service then returns
product recommendations. The recipient then chooses the gifts he wants.” (Rueter, 2013) This new
relationship is consistent with Nordstrom’s commitment to using data to unify
the shoppers experience across platforms. It’s also a smart move for the brand
to use their current customers as a way to reach new customers. Most recently,
Nordstrom has used Pinterest analytics to capture ‘most pinned’ items to then
highlight those particular items in stores with Pinterest signage. This is yet
another example of how the brand uses data analytics to tie the customers
experience together.
Conclusion
Nordstrom
is clearly an old company that is embracing new technologies. One prevailing
characteristic that Nordstrom maintains is the brands quest for innovation and customer
data and then implementation of the analytics to improve and unify the customer’s
experience across platforms. They strive to understand the customer’s journey
beyond just the touch points. (Borison, 2013)
References:
Borison, R. (2013, November 1). Nordstrom exec:
Mobile Web not as sticky as apps. Retrieved December 7, 2013, from Mobile
Marketer: http://www.mobilemarketer.com/cms/news/content/16507.html
Giannopoulos, N. (2013, October 29). Nordstrom Gets
Real with Decision Making. Retrieved December 7, 2013, from RIS: Retail
Information News:
http://risnews.edgl.com/retail-news/Nordstrom-Gets-Real-with-Decision-Making89135
Puri, R. (2013, July 10). How Online Retailers Use
Predictive Analytics To Improve Your Shopping Experience. Retrieved
December 7, 2013, from SAP Business Inovation:
http://blogs.sap.com/innovation/analytics/how-online-retailers-use-predictive-analytics-to-improve-your-shopping-experience-0108060
Rijmenam, M. v. (2013, August 26). How Fashion
Retailer Nordstrom Drives Innovation With Big Data Experiments. Retrieved
December 7, 2013, from Smart Data Collective:
http://smartdatacollective.com/bigdatastartups/140826/how-fashion-retailer-nordstrom-drives-innovation-big-data-experiments
Rueter, T. (2013, June 25). Nordstrom buys itself
an e-commerce gift. Retrieved December 7, 2013, from Internet Retailer:
http://www.internetretailer.com/2013/06/25/nordstrom-buys-itself-e-commerce-gift
Shellman, E., & Von Lehman, D. (. (2013, October
30). How Nordstrom Utilizes Human Intelligence to Blend Brick-and-Mortar
with Online Commerce. Retrieved December 7, 2013, from Strata Conference:
http://strataconf.com/stratany2013/public/schedule/detail/30707
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