The most recent round of Chinese tariffs is likely to result in price hikes for customers. Here's what retailers can do to maintain steady sales and preserve customer relationships.
The new round of tariffs on a whopping $200 billion worth of Chinese imports took effect in September, and much to the chagrin of American retailers, no waivers or removals were allowed. Electronics and clothing are both among the items affected by the tariffs, indicating that retailers may be facing an especially difficult holiday season this year.
The National Retail Federation has warned that the tariff war between the U.S. and China could soon lead to a rise in the prices of day-to-day goods, particularly if the two countries are not able to come to an agreement in the next few months. The tariffs are predicted to jump from 10 to 25 percent if a resolution isn’t reached by January.
While retailers are doing their best to mitigate the damage to consumers, the vast majority of companies are not able to quickly or easily reroute their supply chains or change their sourcing. While many retailers have absorbed price hikes thus far, razor-thin margins are making it increasingly difficult to continue that approach. With no resolution in sight, it appears that the tariffs will soon mean higher prices for American consumers.
Although there’s nothing simple, easy, or comfortable about raising prices for customers, the smart use of customer data can make the process much smoother and can help to preserve customer relationships for the future. Here are three ways retailers can use their customer data to prepare for price hikes in the coming months.
Three Ways to Put Your Customer Data to Work
Customer data allows retailers to gain a better understanding of their customers’ buying habits, product affinities, and preferred price points. In turn, that data can be used to create more personalized customer experiences and target individuals with precise product recommendations, messaging, and discounts. In anticipation of coming price hikes, customer data is even more vital to cement customer loyalty and avoid product waste.
- Personalization: Knowing your customer well and personalizing communication can help secure loyalty — after all, customer loyalty isn’t always or exclusively tied to low prices. While customers are less brand-loyal than ever before, they are experience-loyal. If your brand can offer an improved customer experience to counterbalance price hikes, you can save face with price-sensitive customers.
In addition, you can use customer data to identify big spenders who are likely to maintain their purchasing habits even if prices increase; roll out the red carpet for these customers to maximize their customer lifetime value (CLV). Retailers may even consider sending an email (or postcards by mail!) explaining the reasons for the price hike and apologizing for the inconvenience. A little honest, human communication can go a long way.
- Price Sensitivity and Product Affinities: With a forward-thinking approach to product and price preferences, retailers can forecast and plan for a decrease in demand for certain products. If a product is set to go up in price, data-savvy retailers can accurately predict which customer segments will stop buying that product, and which ones will continue to purchase it at a higher price point.
Depending on the relative value and loyalty of those customer segments, retailers can determine how to maximize communications in order to minimize damage to those relationships. That may mean providing suggestions for other products within a customer’s price range based on known cross-product affinities, or marketing the products that have gone up in price more heavily to customers who tend to make more expensive purchases.
- Planning Inventory: If you haven’t planned for the tariffs and your customer base tends to be price-sensitive, it could lead to an oversupply of inventory. In these cases, retailers will be forced to make deep discounts to clear inventory, which will further eat into profit margins.
To avoid this scenario, it pays to get smarter about planning and merchandising. Good customer segmentation data and predictive analytics can help you avoid blanket assumptions that lead to excess inventory and the requisite deep discounts that go with it.
Of course, it’s impossible to predict with total certainty how tariffs are going to affect your sales. If prices for a certain item are increasing industry-wide, even your more price-sensitive customers may continue to buy from you. Above all, retailers need to remain agile and react to customer data in real time, even in an uncertain retail landscape.