The Golden Quarter's Hidden Margin Game: Getting Gifting Right

Every golden quarter, retailers place the same high-stakes bet. How much gifting stock is enough? Gift packs sit at the sharpest edge of this trade-off. If you underforecast, you’ll watch peak season revenue walk out the door; if you overforecast, January becomes a season of clearance rails, heavy discounting and eroded margin.

However, optimal forecasting isn’t the only challenge — or advantage — retailers have. The retailers pulling ahead this year are also looking beyond the initial sale. They're using gifting as the on-ramp to understanding which gift purchases convert into basket add-ons, and which shoppers come back.

Therefore, for retailers it’s not only about getting golden quarter forecasting right, but turning a one-off gift buyer into a repeat customer. That’s the real prize. Using the purchase to engage both the buyer and person receiving the gift and, from that, drive repeat sales after Christmas.

Ultimately, it’s about nailing both aspects. The retailers leading the field are using artificial intelligence and automation to help human teams accurately forecast demand and understand which gift purchases lead to basket add-ons and encourage customers to return after Christmas.

Forecasting Demand Without Sacrificing Availability or Margin

Forecasting demand is an essential activity to ensure retailers have an optimal amount of products available both online and in-store. It’s the balance between holding enough stock to avoid missed sales but not too much stock that ties up capital and risks becoming obsolete when the season ends.

The trouble is many retailers still rely on spreadsheets for this process, making it incredibly difficult, sometimes impossible, to monitor the range of constantly changing variables that can impact demand for products. It’s a hard balance to strike, one that requires a dynamic and real-time approach provided by AI.

AI can analyze real-time and historical data to identify patterns and highlight where the stock opportunities and risks are. By collecting and processing this data (inventory, sales, market trends, availability, external supply chain factors), the AI can forecast demand and suggest optimal stock levels for every product at every location. This specificity and tailored approach is what then enables retailers to engage the customer and entice them to make repeat purchases.

Identifying and Maximizing Repeat Sales Opportunities

What might seem like a one-off transition is in fact crucial for encouraging repeat purchases. If the price is right to secure the sale and the right additional product is recommended at the first time of asking, a customer will be more likely to make another purchase.

By connecting and analyzing inventory, purchasing and customer data, AI can help retailers to identify these repeat sales opportunities; it can tell them what product prices, suggestions and add-ons successfully landed with which customers and at what locations. Not only does this data provide immediate value, but it can also inform retailers’ strategies long after the golden quarter around pricing and add-ons, providing longer-term revenue gains.

Crucially, this insight is valuable for any new customers making a purchase. By understanding the purchasing habits for different customer segments and at different locations, retailers can make better predictions around what products and add-ons a new customer might be interested in and then find the optimal price needed to land a purchase.

For example, AI could assess a product’s previous sales performance, a store’s inventory, and transaction data and combine this with real-time demand signals, like what Christmas products are trending, to suggest optimal prices and relevant add-ons. It’s these live demand signals and competitive dynamics, which traditional pricing models can fail to account for, that can give retailers a crucial edge.

Thinking Beyond the Golden Quarter

As the golden quarter begins, companies will be focused on maximizing revenue from their gifting products. To do this, their focus might, primarily, be on ensuring they have enough stock to match increased demand and the sales that come with this. However, guided by AI insights, the increase in sales also presents retailers with an opportunity to turn one-off purchases into repeat purchases and build more longer-term customer relationships.

That’s why the real measure of golden quarter success extends beyond December revenue.

Catherine Frame is director of retail solutions at UiPath, a leader in business orchestration and automation.