As Easter draws near, online retailers around the world should be prepared to maximize every dollar they can from the increase of shoppers they’ll have over the holiday.

In 2016, more than 8 in 10 Americans celebrated Easter, according to an NRF survey. Those who celebrated spent an average of $146 per person on planned Easter purchases—a 3.8 increase over the previous years’ spending.

In some locales, Easter is a much larger shopping holiday than it is in the U.S. In the UK last year, planned Easter purchases rose 4.3 percent, when compared to sales in April 2015. Easter shoppers in the UK spend more since the UK declares the Friday before Easter Sunday and the Monday after, bank holidays. Also over Easter, schools in the UK close for two weeks, prompting many families to increase spending not only on traditional Easter goods, but also on travel, sporting goods and DIY projects.

Online retailers whose markets cover areas where Easter celebrations are pronounced can benefit from taking proactive steps to prepare their e-commerce strategy for an influx of customers in the coming months. Here’s what e-commerce companies need to know.

Industries That Should Be Prepared for Easter Shoppers

While all e-commerce retailers will do well to prepare for Easter shoppers this year, it’s more critical in some industries than others. Apparel, sporting goods, travel and home improvement retailers should be prepared for larger-than-average sales numbers this Easter season, as should retailers selling movies, books and magazines.

Personalization: The Key to a Successful E-Commerce Presence

Today, customers shopping online have more opportunities than they could ever hope to redeem. Thousands of online merchants provide products that are similar to or duplicates of one another, and it’s harder than it’s ever been to get noticed online.

Fortunately, e-commerce merchants still have one secret weapon: personalization.

In a world where the possibilities are limitless and customers can have anything they want, whenever they want it, personalization can serve as the added “boost” that helps differentiate one company from another.

Personalize Your Shopping Experience with Smart Recommendations

Today, there are dozens of different solutions for e-commerce retailers who want to make the shopping experience more personal for customers. Tools designed to “learn” from customer behavior and make recommendations based upon it are a great place to start. In addition to providing a more personalized shopping experience, these tools can also do the following things:

  • Boost E-Commerce Sales. Tools that learn from customer behavior can take a great deal of the guesswork out of your merchandising strategies. By automatically adapting to your customers, they make it easier for your company to cycle products according to customer desire, which allows for more (and simpler) e-commerce sales.
  • Create Cross-Sell & Upsell Opportunities. Companies that already have customers on their website over the Easter holiday want to do everything in their power to enhance the order value of each shopper. The right recommendations can provide compelling cross-sell and upsell opportunities. When this is done efficiently, it can help boost a company’s bottom line.
  • Provide Tailored Recommendations. When a tool can learn from a customer’s shopping and browsing behavior, it can display products that are likely to appeal to a given customer. This makes the shopper feel understood by your company, and will lead to repeat sales.

Better Easter Sales Start Here

While many merchants struggle to prepare their sites for sales booms over the Easter holiday, machine learning, cloud-based tools are the perfect place to turn.

Recommendations that are powered by cloud-based machine learning reduce site managers’ legwork and make it easier for companies to deliver a highly personalized, targeted shopping experience to each and every customer, naturally leading to happier shoppers and higher Easter sales.

To learn how you can maximize average order values on a cloud-based, machine learning platform, read the SLI Systems Learning Recommendations™ product brief.