For consumer brands, the holiday season is go time. The high-energy, two-month period that starts on Black Friday and Cyber Monday (BFCM) can account for as much as 19% of a brand’s total annual retail sales, according to the National Retail Federation.
Even as brands have visions of profits dancing in their heads, there’s another side to the holiday season they must consider. Holiday shoppers tend to be the worst when it comes to customer lifetime value (LTV). Too many shoppers will buy once from your brand and then disappear. They might come back next year in some cases. Other times, they’re gone forever.
How do you take one-and-done shoppers and turn them into loyal brand advocates? The answer lies within the treasure trove of commerce data that you collect.
Let’s examine four ways that your commerce data can help you craft the right pre-holiday strategy and drive repeat post-holiday business.
Pre-holiday: Optimize your marketing spend
Proper segmentation drives better personalization during the holiday season.
In light of growing uncertainty over the effectiveness of digital advertising, brands must carefully monitor their marketing spend data in November to see whether they’re on track for success or failure over the holiday season. Your ROI should increase the closer you get to BFCM. If it’s not, you need to adjust fast to optimize your holiday profit margin.
At a high level, you want to monitor the effectiveness of each marketing channel over the holidays. One of the most helpful metrics to track is return on ad spend (ROAS), a barometer of efficiency that shows how much revenue you generate for every marketing dollar spent. Break your ROAS down by channel and watch for any sudden fluctuations or red flags so you can make adjustments in real time.
To see whether your marketing efforts are driving profitability and bringing the right customers to your website, you can go a step further by running a cohort analysis that measures LTV:CAC ratio. This calculation will give you valuable insight into your customer lifecycle so you can identify the ROI for each dollar you spend on customer acquisition.
To do so, you’ll need to create time-based cohorts of “customers from first time of purchase” and compare them year over year. Because the exact dates of BFCM are fluid, we recommend starting by making Black Friday day 0, then counting backward (-1, -2) pre-BF and forward (+1, +2) each day after BF. This also works for performing an LTV:CAC cohort analysis for Christmas sales using Christmas as day 0.
4 ways to use e-commerce data to optimize LTV pre- and post-holiday by Ram Iyer originally published on TechCrunch
