At Efficient Frontier, we love to tease out patterns and use data to inform decisions. One pattern we’ve noticed is that the Average Order Value (AOV), or the average dollar amount spent for each customer order, tends to drop for retailers during the peak Christmas shopping season. One theory to explain this unlikely phenomenon is that consumers who purchase gifts for others tend to buy less expensive items than if they were shopping for themselves. We can also surmise that certain people only become customers during certain seasons, so the mix of customers changes.
The graph below shows the AOV trend for two groups of clients. Group A contains retailers that skew toward romantic and sentimental items commonly gifted during Christmas or Valentine’s Day. Group B contains retailers that tend to sell more practical wares that are not typically considered romantic. We can see from the graph that both groups dip in AOV during the Christmas shopping season. However, Group A also dips to mid-December levels beginning around the third week of January. Group B also takes a slight dip beginning on the 1st of February, just before Valentine’s Day.
That’s not to say that order volume doesn’t play a role. It most certainly does, though the volume trends are not quite the same.
Besides the obvious fact that not all retailers have the same seasonality trends, we can see some similarities that arise across the board. So why does any of this matter?
Whereas Christmas has a well-defined holiday shopping “season” (beginning on Black Friday), other holidays, such as Valentine’s Day, don’t have such clearly defined shopping seasons. A change in AOV can indicate a change in the mix of customers. To capitalize on this, retailers can tailor ad copy towards customers who are seeking to purchase gifts.
Also, since only Group B showed a spike during Thanksgiving when there were a lot of deals, this suggests that retailers should experiment with NOT discounting romantic goods by much.
In addition to ad copy changes, campaigns need to be set up to capture the increase in demand. This means dynamically changing budgets and bids with the appropriate spend mix on high and low AOV campaigns. All of this could help maximize conversions from customers who are planning to buy gifts during the holiday season.
Based on this data, we also recommend that retailers:
- Use historic data to anticipate demand, and pace budgets accordingly
- Experiment with pricing on less time-sensitive but essential retail goods, which show a high degree of elasticity. “Romantic” goods are time-sensitive, and do not usually capture additional demand from low pricing during the high season
- Align your campaigns in a cross-channel fashion. Use Facebook for upper-funnel optimization to generate demand early on in your holiday campaign, and get aggressive on search to capture lower-funnel intent late in the campaign
Ultimately, it all boils down to predictive modeling and proactive account management. In order to maximize your ROI, you need best-of-breed adaptive learning algorithms to place the right bids at the right times. You also need a world-class team to provide human insights and provide the right creative elements.