The way you're scheduling staff is hurting your sales
The idea of scheduling staff to traffic is an old idea, but it’s an important one. It also just makes sense. You want to have your store labor applied to when shoppers are actually visiting the store. So why are so many retailers not doing this properly?
If you’re like most retailers, you schedule labor based on sales budgets, and sales transactions — using transaction counts as a proxy for actual store traffic.
In this short video example, you can see the incredible difference it can make when you schedule to traffic and not transactions:
In the chart below you can see what the retailer’s sales transaction counts looked like compared to labor. It looks like this retailer did a good job of scheduling. More labor during the busiest hours between noon and 4 PM and then less labor in the evening makes sense.
But this is another example of how sales transaction data alone can lead you down the wrong path
In the chart below, look at actual store traffic shown here in the blue bars and the corresponding conversion rates. That is the percentage of visitors who actually made a purchase during these hours. These are indicated in the yellow dots.
- Using store traffic and conversion insights paints a completely different picture of what’s going on in this store – and it’s not all good.
- It’s clear from this chart that there’s a big conversion drop at 5 PM and it carries through the evening hours right to the store close.
- It’s clear that this store is missing sales opportunities. Conversion rate sags are a telltale sign that sales opportunities are being missed and labor scheduling very well may have a lot to do with it.
- Comparing traffic and conversion with the labor schedule, you can clearly see when we compare how labor hours were scheduled relative to actual store traffic and conversion rates.
- As the amount of labor goes down, we see a commensurate drop in the conversion rate. It’s worth noting that store traffic is still actually pretty high from 5PM to closing, but the transaction counts couldn’t pick up on the signal.
Do you have questions about how traffic data might help you staff better?
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