Retailers Hope Big Data Drives Big Holiday Sales

Retailers Hope Big Data Drives Big Holiday Sales

Summary: Pentaho's Chief Technology Evangelist opines on the role of Big Data Analytics in this year's holiday retail sales season.

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TOPICS: Big Data
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Ian Fyfe Photo

This guest post comes from Ian Fyfe, Pentaho's Chief Technology Evangelist, responsible for driving adoption of Pentaho's big data analytics technologies and providing input on high-level product strategy and roadmap development. 

 

"Black Friday" and "Cyber Monday" have come to signify the two major holiday shopping events of the year.  But what many people may not realize is that this period signifies the approximate date on the calendar when many retail businesses move from operating in the red and start to actually make a profit for the entire year. So, performance during this period right up until the New Year holiday is critical to the annual bottom line. The secret weapon used by this season’s winning retailers is "Big Data analytics."

So what's happening with Big Data and the retail market?  Web sites, GPS-enabled tablet devices and smart phones, and embedded sensors -- all increasingly connected using mobile technology -- are generating massive amounts of data about consumer behavior.  For the first time, it is also both technically and economically viable to store and analyze this data to reveal new insights and patterns.  Big Data-savvy retailers are collecting and mining this data to target customers on a more personal and direct level, especially during this critical holiday season.

How are retailers using Big Data this year?  Analytics that can handle enormous volumes of diverse data are being deployed to perform closed-loop analysis on a wide-range of activities, including effectiveness of marketing campaigns, customer on-line buying behavior, performance of sales promotions, social-commerce and inventory optimization.

For example, Big Data analytics make it possible for retailers to directly correlate consumer Web activity with promotions and marketing campaigns, and track resulting sales transactions.  And as a result, retailers can monitor and tweak promotions and campaigns in near real-time to maximize spend, increase profitability and generate revenue during this short, but critical period of time.  They do this by quickly slicing and dicing terabytes of data, including millions of daily emails, every click on Web sites, and every ecommerce and brick and mortar transaction.

These advanced analytics enable retailers to perform deep, precise customer segmentation by demographics, such as age and income, and psychographics such as interest and lifestyle profiles -- segments which are then used to drive highly optimized and personalized offers and campaigns. 

The need for time-sensitive Big Data analytics is leading to the rise of the latest trend of "self-service" Big Data analytics. Data analysts are able to answer their own business questions using Big Data sources in minutes, without needing to wait weeks or even months for their IT department to provide them the data -- too little, too late. This is especially essential when organizations are using the latest and most cost-effective Big Data platforms such as Hadoop, which while immensely powerful, can’t be accessed using traditional SQL-based methods and tools.

An example of Big Data analytics in action is BeachMint, an online seller of high fashion jewelry, clothing and shoes.  BeachMint is an extremely savvy social commerce company with personality driven sites that generate massive amounts of data.  BeachMint tracks all this data, including every click on its Web properties, every click-through on its marketing emails, and every record of each sales transaction. For BeachMint, Big Data analytics has been a game changer for customer acquisition, as they now have easy access to analysis that enables effective cross-selling opportunities and a sophisticated referral engine.

I confidently predict that this year's biggest retail winners will be the ones that have placed a bet to be early innovators in leveraging Big Data analytics to optimize revenue during this holiday.

This post's thumbnail photo credit: FutUndBeidl

Topic: Big Data

Andrew Brust

About Andrew Brust

Andrew J. Brust has worked in the software industry for 25 years as a developer, consultant, entrepreneur and CTO, specializing in application development, databases and business intelligence technology.

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  • Adding Social Media Data to the mix

    Big Data analytics leveraging data compiled by tracking customer activity and reactions to marketing campaigns has indeed an enormous potential.
    Understanding what people are doing when they're not interacting with your organization can significantly increase the richness (and complexity) of the analysis, yielding even better results: better customer experience, higher loyalty, more effective offerings, etc..
    The question is, how to enrich your Big Data analytic process with Social Media Data?
    How to effectively link your customer's enterprise data with their social media profiles?
    agcarletto