The 2017 holiday season was the strongest in nearly a decade for America’s retailers. From Thanksgiving through Christmas Eve, nearly three-fourths of the selling days showed positive year-over-year growth, with specialty apparel, jewelry and furniture racking up solid performances. This strong performance offers an opportunity for retailers to stay connected to their customers and continue the momentum in the new year through the use of holiday data. It takes a combination of the right messaging and marketing campaigns, powered by the deliberate use of data.
Black Friday Gives Way to Super Saturdays
The five Saturdays during the holiday season averaged 20 percent year-over-year growth and accounted for 40 percent of the total year-over-year growth. The last full weekend before Christmas saw the strongest sales of the season, a change from prior years when the Saturday immediately before Christmas showed the strongest sales.
What lessons can retailers take away from the 2017 season, and how can they keep customers engaged and extend the shopping spirit? A well thought-out data analytics strategy is the first step to developing the insights that will build long-term customer loyalty and drive sales.
Purchase Patterns and Buying Behavior
Through inventory management systems, retailers know what they’re selling, including where and when. But to get closer to ideal one-to-one relationships with customers, they need to know who is buying which products, and when. While fresh data from the holiday season is a start, it should extend beyond to deliver a full-year view. An ability to combine and analyze data will help retailers understand purchase patterns and behaviors, which then can drive more relevant marketing programs, brand messages, rewards and in-store experiences.
Retailers can extract more value from the data about purchase patterns and behaviors by combining it with the voice of the customer. Then, predictive analytics can help retailers understand where and when their customers need them most. Anticipating a customer’s needs is critical, especially after the holidays when they may suffer from shopping fatigue or find their discretionary dollars competing for attention with vacation planning or home improvements. This type of predictive modeling drives engagement, retains customers and keeps them shopping year-round.
While data forms a strong foundation to build customer relationships, the experience can strengthen the brand’s affinity with the shopper. For example, creating special “best customer” events and offers based on how a customer likes to shop can go a long way in keeping them engaged during any season. With consumer confidence high and a stack of gift cards to spend, consumers may feel it’s the perfect time to treat themselves. Retailers that focus on making people feel good about themselves during this post-holiday time — and beyond — will be successful in getting customers shopping online and in stores.
Looking Ahead to 2018
Retailers that adopt this data-centric approach will be better positioned for the 2018 holiday season, which will bring new opportunities and challenges. With the holiday season starting Nov. 1, retailers have the opportunity to build a strategy that captures early shoppers and build momentum up through the extra weekend leading into Christmas 2018.
Online purchasing continues to make inroads on growth, yet in-store opportunities still exist, particularly as shoppers get closer to the actual holiday. Retailers must know who their full-price and discount customers are, as well as their preferred channels and shopping day preferences. Furthermore, they must capitalize on ways to drive sales during the “valleys” to sustain momentum in between the “peaks.”
Convenience and experience are rapidly becoming as valuable a commodity as money, and brands that stay focused on what’s most important to the customer will move in the right direction in 2018 and beyond.
Mike Schmidt is the head of Alliance Data’s Analytics & Insights Institute with more than 20 years of experience in the retail space. He is an expert in using data-driven insights to inform marketing decisions, developing custom statistical models to fit the needs of retail brands, and evaluating each stage of the customer journey. Schmidt provides strategic insights to retail brands, as well as sales and customer reporting, and credit sales and application forecasting.
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