CASE STUDY: REVENUE MANAGEMENT Imagine you own a pub. Would you rather increase prices after 10pm or bundle beer and shot at a favorable price? Your ultimate KPI in revenue management is revenue per available capacity. In a restaurant business your capacity is calculated as all seats per hour. You should understand the main drivers behind this KPI (revenue per seat hour); -average spend per customer -average duration of a customer visit -available capacity (opening hours, available tables/seats) In my case I set out the following framework to improve revenue management in a restaurant business: Note that I neglected the duration of a customer visit. While in airline or hotel industry the duration is given (room per night), in restaurant business the customer visit duration is quite unpredictable. Also, restaurant staff has limited options to manage customer visit duration without a reputation damage. STEP 1: Set your sales & price strategy The key question in revenue management is, how do you want to position your business. Premium or affordable. Small and cosy, or large and open to everyone. Not all pub/restaurant models are viable. With a set of critical success factors in mind, you will have a better idea of your operational model and possibilities to improve revenues. Main drivers are restaurant premises, skills, and competition. Restaurant business is lot about location. To get a better understanding how your venue fits in the world of restaurant business, go and visit competitors in your vicinity. Have a meal or beer. Look out for service, pricing, atmosphere, type of guests. Take someone with you. First, it doesn't look weird to be on your own and spy around, second you'll have a second opinion. The picture below is a random example unrelated to this case study. STEP 2: Know your customer value For the sake of revenue management you can define customer groups on 2 dimensions: money spent and time spent. Resulting segmentation (4 quadrants) will lead us to specific measures for each group of customers. Basically you want to prefer customers who spend (a lot of) money over little time. The most attractive customers are tourists and customers who come for an event (quiz night, nearby concert or theater). Although their spending power is uncertain, they stay limited time and free up space for next customer. Walk-in customers are highly unpredictable. You may keep some tables unavailable (reserved for larger groups or returning customers). If they turn out to be big spenders, offer them better seats or give them sweetener (an extra shot or drink). Your walk-in business can also turn into cheap tippers, i.e. customers who spend 2 hours over 1 coffee. You do not want them in your business. First ask if they are interested in a special savings deal (i.e. 2 drinks for 1). If so, they are definitely cheap tippers. Make them go. Make it quick. Ask (politely) to bring a bill, ask (politely) to change their seats. Bug them regularly if they want to order. Loyal customers represent recurring revenues (meaningful forecasting), at least in first months. Their spending power decreases over time. Worse, they become cheap tippers. No capacity should be assigned long term exclusively to loyal customers. STEP 3: Analyse historical sales to forecast revenues The goal is to understand dynamics behind revenues, i.e. what business hours, days, weeks are the strongest, what products sell the most, in what extent does temperature have an impact on revenues, etc. With the facts in your hand, you can look ahead and plan your capacity, events, pricing, or even change your operating model. In my case, I exported all available transaction data from a cash machine. In total I analysed 133 business days, 2067 transactions, 4031 items sold. 1) AVERAGE EXPECTED SALES Average (median) daily revenues are EUR 970 /day with a 95% probability of not exceeding EUR 2.290 / day. Average (median) weekend revenues are EUR 2650 /weekend (FriSun) with a 95% chance of not exceeding EUR 3.980 / weekend. This shows us quite significant revenue spread. On one hand it is difficult to make accurate revenue forecasts, on the other hand there is still a revenue upside if things go well. So if you want to boost your revenues with an event, you know your (current) limits. 2) SEASONALITY HOUR: peak time starts at 7pm and culminates at 11pm. Party drinkers stay longer and although smaller group, they generate same revenue as first group of customers who leave at 11pm. DAY: strongest days are Saturday and Sunday, weakest day is Tuesday WEEK: Last 2 weeks in a month are significantly stronger (pay cheque effect). MONTH: Unfortunately, I didn’t have enough data to look at monthly seasonality. Takeaway: Plan pub events for the 1st and 2nd week of a month! Plan pub events on Tuesdays and Mondays! Sales after 1am drop dramatically! Do not stay late open take rest instead. Look out for products that sell well in peak periods – price them up! Bundle products/ do Sell offs or special deals in off-peak periods! 3) PRODUCT SEASONALITY People drink different beverages in different hours, on different days. This is an opportunity to push/endorse products with higher margins, bundle outperforming products with low margins and high margin products. Coffee time: 12am – 3pm Lemonades time: 4pm – 7pm Get drunk time: 8pm – 1am Takeaway: Special offer: 5 beers for a price of 4 until 20:00 Special offer: small beer & spirit for a price of EUR 4 until 20:00. 4) CORRELATION WITH TEMPERATURE Outside temperature does influence sales only a little. In our model, the correlation between sales and temperature was insignificant. Factors like weekday, pay cheque effect, and business hour was far more important when predicting sales. Looking at the product sales however; whiskey and wine are "celsius-resistant", while beer, lemonades and softdrinks are slightly positively correlated with the heat.
