Predictive Modeling Brings Holiday Cheer To Retailers
December 4, 2014
Black Friday — the Super Bowl of the retail industry — has come and gone, but holiday shopping is just getting started. November and December combined are two crucial and competitive months for retailers — and the good news is that the National Retail Federation expects sales during that period to increase 4.1% year over year, bringing total sales to $616.9 billion and dwarfing the 3.1% increase during the same time last year.
One way retailers can make the most out of the holiday shopping season is to ensure their company is up-to-date with the latest analytics technology. Making customers happy — and, in turn, making them buy — is imperative to a successful and cheerful holiday season. Luckily, data about social media sentiment, call center feedback, survey responses, buyer behavior, sales and more, hold clues as to what’s needed for a successful season — from the right marketing campaigns to the best product mixes and everything in between.
Of course, there are different levels of retail analytics to this end. The most basic type is a simple volume assessment of your data, which is the process of counting the number of occurrences of issues and taking action as the volume and importance increases. The next type is change analysis — that is, looking at the rate of change in the data, including spikes, and then determining the next best action based on dramatic increases. However, the most effective and advanced analytics — and those that have the most impact on holiday shopping season success — uses all data sources for predictive modeling.
Through the use of retail analytics for predictive modeling, companies can clearly see and understand how sentiment, emotion and actions have changed; determine what is influencing that change; and make the adjustments necessary in real time. This can occur at both a trend level and an individual level.
With that in mind, let’s take a look at four specific ways that this advanced level of retail analytics can be integrated in retailers’ marketing initiatives this holiday season.
The rest of the blog post, including the four ways that retailers can use advanced analytics and predictive modeling to increase sales, can be viewed at Retail TouchPoints.