Retailers prepare for holiday season with Hadoop

Using Clickstream data to understand and serve holiday shoppers

x_0_0_0_14041029_300The approaching winter means one thing for many retailers and their customers: the holiday shopping season. This is the time when many stores make the bulk of their profits for the year, and it is also when many consumers throw caution to the wind and spend a little more on that special gift to put a smile on their loved one’s face.

According to a recent survey by McCann, the average American plans to spend $667 purchasing gifts this year. However, where many individuals are asking for new clothes, toys and tech gear, retailers are asking for big data. This information can greatly benefit a retailer’s ability to not only prepare for the upcoming shopping season, but to effectively target consumers and bring its preferred shoppers through the establishments’ doors.

Big data illuminates shoppers’ habits

Within recent years, the holiday shopping season has seen great changes. Due to an increase in online shopping and specials being offered earlier, consumers are now utilizing different channels to shop and are doing so earlier than they have in the past.

Although the buzz surrounding Cyber Monday has been increasing lately, McCann research shows that the majority of shoppers still believe they plan to do more shopping in stores than online. However, the margin here was thin, as 51 percent of survey respondents said they will spend more in stores on Black Friday than on the Web.

These figures held true for almost every demographic except women over the age of 35, according to the survey. Women in this age bracket stated that this year, they plan to spend more online than in stores.

Utilizing this information, retailers can tailor advertising efforts and specials to target these individuals. For example, online advertisements pertaining to Cyber Monday – sometimes referred to Cyber ‘Mom’-day – can be geared toward women shopping for their children, husbands and other individuals on their list. In addition, in-store ads can broaden their appeal to engage vast numbers of shoppers from all walks of life who are planning to spend more in stores. In this way, advertisements are more personal and shoppers may feel an increased connection with the retailer, thereby increasing the likelihood that they will spend money on the company’s website or in its stores. SmartData Collective contributor Roman Vladimirov also pointed out that if retailers fail to target shoppers on an individual level, it could hurt their holiday bottom line this season.

Optimizing big data during the holiday season

In order to prepare for the upcoming holiday rush, retailers are utilizing the insights provided by big data analysis to improve their efforts across the board. One industry-wide utilization of big data analysis is to enhance the specials being offered to appeal to certain age groups and demographics. For example, by analyzing the shopping habits of certain individuals, organizations can provide discounts for these shoppers on the platforms they are most likely to utilize. For example, because big data shows that most women will spend the majority of their holiday budget online, retailers can offer discounts on toys, men’s items and the other gifts that these shoppers will most likely be buying. Along the same lines, in-store specials can focus more on women’s items, as two-thirds of men stated they plan to spend more in stores than online.

Big box giant Macy’s is a well-known user of big data to improve its customers’ holiday shopping experience. The retailer recently told Forbes that its analytics have revealed that it needs to be specific and strategic when it comes to customer engagement. Macy’s told the source that “our customer wants what she wants, when she wants it.” In this way, the retailer is utilizing big data to target customers and fulfill this demand.

Retailers looking to better prepare for the holiday season with big data analysis can utilize Apache Hadoop. The platform provides analytics tools for organizations to create a unique system to gain insight from their big data.

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