Research Realism:

by Jenny on November 21, 2016 Comments Off on Research Realism:

The holiday shopping season [November-December] is a big opportunity for brands and retailers around the world. According to, in 2015 the average U.S. consumer spent over $805 during this two month period. In 2016, the amount spent-per-shopper is estimated to be nearly $940; a 4% increase from last year.

With so many companies vying for the attention of consumers by way of sales and discounts, how does one manage to stand out from the rest? Cue the entrance of Big Data.

Top industry consultants are suggesting half of all holiday shoppers plan to buy online this season, and two-thirds of those who don’t will browse online before making in-store purchases. The result is a flood of online shopping data which companies like Amazon are using to offer the right product – for the best price – at the most appropriate time.

Without supporting data, multi-channel marketing is like running in the dark; you’re in motion but there’s no way to know if it’s the right direction. Differing segments of online shoppers have unique preferences and habits that must be accounted for when planning targeted marketing campaigns.

Amazon allocates considerable resources toward its data scientists producing algorithmic systems to help processes complex data sets. When considering a multitude of attributes such as products viewed, items purchased, devices used, time of visit, length of stay and many more, even the most experienced analytic teams need help producing actionable insights.

Through this unique approach, Amazon is able to leverage its consumer data in deciding on featured items, discount levels and a global marketing approach. These targeted techniques have proven to increase return on investment and strengthen confidence in multi-channel sales strategies.

While the benefits of these efforts are attractive to any company hoping to capitalize on holiday shopping trends, without effective data collection, storage and analytics the reliability and confidence in resulting insights will be extremely low. This is where many research projects fail, and when the ultimate objective is not achieved it’s common to see consumer research disregarded as ineffective. This is an ill-advised move considering how the top brands and retailers around the world continue to find success using Big Data to guide their strategic decision making.

We recently found a great article further outlining Amazon’s approach to the holiday shopping season and how Big Data can be applied throughout the entire year:

“Even beyond Black Friday and Cyber Monday, data science is powering dynamic pricing on retailers’ websites. The data models being used to optimize pricing, which can be adjusted to compensate for the significant behavioral changes of consumers during the holidays, are active throughout the year. Statistics vary, but McKinsey & Company has estimated that retailers using big data analytics could boost their operating margins by up to 60 percent. So it’s little wonder that retail giants with the resources to do so are powering their pricing with data science.”


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Jenny Dinnen is President of Sales and Marketing at MacKenzie Corporation. Driven to maximize customer's value and exceed expectations, Jenny carries a can-do attitude wherever she goes. She maintains open communication channels with both her clients and her staff to ensure all goals and objectives are being met in an expeditious manner. Jenny is a big-picture thinker who leads MacKenzie in developing strategies for growth while maintaining a focus on the core services that have made the company a success. Basically, when something needs to get done, go see Jenny. Before joining MacKenzie, Jenny worked at HD Supply as a Marketing Manager and Household Auto Finance in their marketing department. Jenny received her undergrad degree in Marketing from the University of Colorado (Boulder) and her MBA from the University of Redlands.

JennyResearch Realism: