Come earnings season, there are no shortages of corporate excuses for missed financial targets. Companies have been known to blame shifting holidays, stormy weather and other acts of God. Yes, they even blame it on the rain.
While some excuses are legitimate – after all, five feet of snow really will keep consumers at home – companies cannot afford to let such happenings cloud their view of what’s really driving sales.
For example, if sales plummet after a price increase, was the revenue decline due to the pricing or the Nor’easter that blew through town? If attendance is up but you didn’t lower prices, what explains the spike? How do you strip out these effects to measure the true impact of your pricing and promotional strategies?
Answering these questions is critical not only to measuring the impact of pricing on demand, but also to maximizing your revenue and profits. This is the key to a successful Revenue Management Strategy.
Some good places to start are to:
- Identify Key Drivers of Your Sales – analyze your consumers and look at their behavior for various purchases. Are more purchases being made because of changes in your guest mix? Did major weather events, locally or in your source markets, impact purchase behavior? Have your media strategies opened new markets to drive demand? Have investments in guest experiences driven organic demand growth? Dig deep to find out what is truly driving your sales and start by explaining their impact on demand before trying to measure the impact of price.
- Find Sustainable Data Sources – get creative, and don’t be afraid of new data sources. Not all data is captured centrally, but that doesn’t mean the data doesn’t exist. Obtain sample data to test your hypothesis (for example: ask your Marketing department for their media schedule, then download sample weather data from the National Oceanic and Atmospheric Administration (NOAA)). Once you know the key drivers, work with internal and external teams to establish repeatable and sustainable processes to update this data. This will be critical to your analytics and pricing strategy in the long run.
- Create Statistical and Predictive Models — create a model to normalize historical demand to be consumed by your core analytical models. You are now ready to measure true customer price responsiveness, measure and explain the exact impact last week’s weather had on demand and most importantly, predict how customers will respond to your price/pricing strategy or any of these key drivers in the future so you can optimize your company’s actions in response.
Your company can’t afford to offer fake excuses.