The holiday season is always one of the busiest times of the year for online retailers. In 2012, the Black Friday weekend hit a record $59.1 billion, up from $52.4 billion last year in United States. For the first time in history, online retail e-commerce spending on November 23rd, Black Friday — topped $1 billion last year, according to market research firm comScore. The company says, online retail purchases totaled $13.7 billion in the United States during the first 23 days of the holiday shopping season. Approx. 57 million Americans visited online retail sites on Black Friday.
Last Year, Amazon Ranked #1 among Online Retailers on Black Friday followed by Walmart, Best Buy, Target and Apple. Among the Product Categories, Digital Content & Subscriptions Category, saw a staggering 29% YOY change in the traffic while, Toys category saw a lift of 27% YOY. According to Holiday Shoppers, Product Pricing, Free Shipping, Product Availability and Merchant’s Reputation were among the most important influencers in their buying decision.
During the Black Friday Weekend, the biggest challenge before the Retailers and Brands is to determine, what Products and Categories they should be promoting via Search and Navigation to drive incremental revenue, boost the average basket size and order value of their online consumers without compromising on their profit margins.
One way to achieve the required balance is through product recommendation strategy, which helps clears merchandise without incurring losses. Product recommendation strategy also creates visibility for products, helping customers find products easily and thereby allowing them to engage better on the website. This strategy to create visibility is of great advantage during festive seasons when customers land on the website with clear intent to purchase and will result in conversion when presented with the right products. However, considering the cost and effort involved in adopting the product recommendation strategy, it’s crucial for the merchandising team to answer a few basic questions such as:-
Answering the above questions will help the team utilize the website real estate wisely and maximize revenue generation. But, how can we identify such products and be assured that such products have the possibility to sell more, if promoted? This is where predictive analytics comes to play a key role and helps us identify such products using a few statistical techniques.
Predictive analytics team at Nabler has helped clients find answers for such business problems through data modeling procedures. One such approach taken by the predictive analytics team was to identify the products to be promoted on a client’s website during Black Friday with the clear objective of maximizing the revenue generation. Since customers expect heavy discounts on Black Friday, the client was interested provide appropriate discounts to gain advantage over its competitors and to lure customers to the website. The team applied multi-level segmentation techniques to segment products based on the purchase behavior of the customers. A few statistical tests were used to finalize on high value segments within the data clusters. The tests also proved with statistical significance that, the products within the high value segments will lead to high sales when promoted vigorously. The team made conscious choice to avoid skewness in the list of products due to either high value products (expensive products which sell less) or high volume products (cheaper products which sell more). The reason was to maintain the equilibrium of the brand and thereby appeal to all level of customers looking for products ranging from a few dollars to few thousand dollars. The team provided a list of products to the clients with the details of the lift in revenue which can be expected for every incremental product view.
Although, product recommendations were primarily introduced to clear inventory, its current day application is to boost cross-selling and up-selling of products. The cross-sell and up-sell strategies help create visibility for new and unfamiliar products among the customers. Solutions for cross-sell and up-sell strategies can be provided through techniques such as market basket and product pairing methods. At Nabler, our focus has always been to maximize revenue and get better ROI on such product recommendations. We are aware that such critical models need to be dynamic and hence we have also taken measures to automate the models with the recommendation engine running at the backend providing dynamic product suggestions to the customers based on attributes such as purchase behavior, similarity between products, cost relevancy etc. No matter what your strategy is, to maximize revenue or to increase customer satisfaction through suggesting the right products or to promote new products or increase ROI of product recommendations, Nabler can provide the precise solution to help you achieve your goal with less effort and high accuracy. How about you let us help you with your Black Friday and Christmas season promotions?