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Cyber Monday Is Not Extinct - It Has Evolved

Cyber Monday Is Not Extinct - It Has Evolved

E-commerce site operators should take advantage of technology that enables them to better serve their customers' needs from the moment they enter the site. One way to achieve that is through automated social behavioral software, which tracks user behavior and recommends products based on that data, writes Rolf Elmer, CEO of Avail Intelligence.

Cyber Monday, once considered the No. 1 shopping day for e-commerce and retail Web sites, has become the official kickoff to the holiday season and a key marketing event for the online community. As with any economic marker, it is vulnerable to credit crunches and significant financial tide changes.

Just as weather predictions help us to plan accordingly, knowing what to expect from holiday shoppers during the highest selling season of the year enables online merchants to prepare properly. However, similar to mother nature, consumers are a self-guiding force and declarations of what may be, cannot guarantee what the outcome will be.

What can be accurately assessed is that people will turn to online sources to buy clothes, books, music and more for family and friends in preparation of the coming holiday season, as evidenced by the record-setting online shopping spree witnessed in 2007. This means that e-commerce professionals must not only aim to provide consumers with what they are seeking in terms of the hottest products and coolest gifts, but must also offer a rich shopping experience to stay competitive.

Make the Most of It

With only a handful of high-sales seasons per year, it is critical that online marketing professionals capitalize on these spikes. The run-up to a high traffic season is the ideal time for online retailers to implement a new e-commerce optimization and personalization technology platform. Deploying a system specifically designed to increase conversion rates and revenue prior to an increase in visitors enables e-commerce professionals to maximize their sites' value and marketing efforts.

There are three main strategies for online merchandising: top-seller approach, deployment of rules-based segmentation, and integration of automated predictive social behavioral recommendations. The top-seller tactic, akin to mass marketing, is built on the dated "bullet theory." This one-size fits all approach assumes that 20 percent of a site's products (the best sellers) will make up 80 percent of the sales to all customers. It also presumes that consumers do not require the promotion of specific products and services based on their needs and preferences. Unfortunately, this strategy often results in missing the "long tail" effect and reveals to consumers that they are not being treated as individuals.

Rules-based segmentation divides consumers into categories based on various statistics, creating "business rules" for how each group should be marketed to. For example, a rule might state: "Promote products x, y and z to women under 30, arriving after 3 p.m. to the women's clothing section." The benefit of this approach is that visitors are treated in differentiated ways. However, it is limited to a manageable number of segments and therefore cannot provide a truly personalized experience for each shopper.

Lastly, the level of personalization offered by an automated social behavioral architecture enables e-commerce sites to leverage information about each visitor to provide customized recommendations. Click patterns, searches conducted and products purchased are all implicit actions performed by consumers. In conjunction, explicit actions, such as, basket content, click stream and collaborative search results from every interaction point are also gathered and stored. Through intelligent sorting of this data set, the system provides customers with personalized, real-time suggestions, assisting them in finding the products, services and promotions that best fit their needs.

Make a Connection

Consumers are looking for rich experiences that allow them to feel connected to the sites where they shop. The real-time mining of the collective behavioral data of an entire community of visitors enables customized recommendations to be presented. A system expressly designed to automatically promote the most relevant products to each visitor engenders a feeling of trust on the side of the consumer. In turn, a site with this technology can expect to see increased conversion rates and uplifts in revenue-per-visit.

To ensure a successful deployment of behavioral merchandising software, e-commerce executives should consider integrating a system that includes the following key attributes:

  • Intelligent mining of large data sets -- Offers real-time, automated predictive suggestions
  • Landing page optimization -- Directs consumers to the landing page of the product being searched, versus the homepage to the entire site
  • Behaviorally driven recommendations -- Generated by peers, not marketing professionals, these are the most respected and trusted by consumers
  • A/B testing -- Illustrates the conversion rates of consumers and the overall effectiveness of the software. More advanced systems use these results to identify sales uplift for only those transactions directly affected by the technology
  • Dual delivery systems -- Provides technology as a hosted Software as a Service or as co-located servers residing behind the retailers' firewalls
  • Full automation -- Requires no manual administration after setup

For newer retailers, this technology can be easily added to the schematics before the Web site is launched. Allocating funds for this technology and working with a provider early on will ensure the site goes live with the merchandising optimization technology embedded. The professional teams of more mature e-commerce sites will also find that integrating this technology is a simple, seamless process that entails working closely with a vendor to ensure all preparatory steps have been completed and that component is tied to the proper functionality. Be sure to select a vendor that offers on-site support at the beginning of the process.

Online visitor traffic to e-commerce sites fluctuates for many reasons. At times it is merely due to the natural ebb and flow of annual sales cycles. Some predictions state that the current economic climate may result in shoppers spending less this holiday season. Regardless of the reasons, if online retailers are not generating enough sales revenue from site visitors, they can arm themselves with technology expressly designed to convert Web browsers into buyers. Social behavioral merchandising architectures offer the best protection against dips in traffic, and a leg-up on competition during the holiday spike, as they optimize each customer interaction, resulting in increased loyalty and ultimately conversion rates.


Dr. Rolf Elmér is CEO of Avail Intelligence, which helps e-commerce sites maximize the value of visitor traffic.


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