❖ Part of the Coffee Shop Financial Performance series
Measure your baskets to know who you are serving profitably
In this article we’re going to start to draw together ideas from several previous posts so you can work out which customers your coffee shop is serving at a profit.
In the previous post we looked at the profitability of SKUs; but to further our journey towards lifting profitability we need gain an insight into the profitability of your current customers. And the link between your SKUs and your customers is baskets.
You don’t need to have read all the previous articles to be able to make sense of this, but you probably will need to calculate your gross profit by SKU to be able to perform this analysis. If you’re serious about increasing the profitability of your business, taking the time to perform these calculations will be some of the best time you invest this week.
As you’ll know from firsthand experience, some of your customers come in for a coffee daily and, at another extreme, others visit infrequently but when they do they buy coffee for their entire team. Between these variations in visitor frequency and spend lies your ‘average basket’ as well as a selection of ‘typical baskets’.
Let’s start with an average basket as it is easier to calculate. Simply take your revenue for a period and divide it by the number of transactions in that period. This gives you an average spend per transaction.
- A shop takes £1,200 in a day with 170 transactions, that’s
- £1,000 ex VAT
- 170 transactions
- £5.88 average spend per transaction for the day (ex VAT)
Knowing your average spend per transaction is critical. It allows business managers to know how many transactions are commonly required to reach a budget or target, it offers an insight into the resource requirements and the operational intensity that are required to reach that target, and it is a key lever for increasing profitability.
In short, the average spend per transaction is the numerical insight that turns your financial objectives into shop operations — and visa versa. We’ll return to the average basket regularly in the future.
A typical basket identifies groups of SKUs that are commonly purchased together in a single transaction.
Typical baskets are usually harder, much harder, to work out than the average basket — but are worth the hassle. Ideally, like the profitability analysis, you want to be able to rank baskets by gross profit over a time; but accepting that this level of analysis is a stretch too far for the data gathered in most POS systems, crunching the numbers with sales revenue or volume will suffice.
It is worthwhile seeing if your system can either produce this data, or, obviously, if you are not able to produce a report with the gross profit by basket, you can take your top selling baskets as measured by sale volume (the better option) or revenue, and manually calculate the gross profit using the gross profit from the constituent SKUs.
You can, and should, perform the analysis at a number of levels, for example:
- A category level analysis might show that a coffee beverage and a sweet food item to eat in is the most commonly purchased basket in your shop
- A product level analysis might show that two flat whites to go are the most popular products purchased in a single transaction
- A SKU level analysis might show that the majority of transactions that include a baked good with a dietary requirement correlates with the same dietary requirement expressed in the beverage, and that they are consumed on site
Ranking your typical baskets in this way allows you to see which transactions you are frequently providing your customers, how profitable these transactions are, and it’s easier to see whether the gross profit derived from the transaction is sufficient to justify the cost and hassle of serving these particular groups of products — and therefore customers.
Products and Customers
If as an industry we are going to lift the perceived value in the public’s eye of specialty coffee, then we need to know where we are starting from.
Calculating these insights helps business managers to identify:
- What products their current customers value most
- The level of operational intensity required for the profitable operation of the business
- Which ‘baskets’ of SKUs contribute most (and least) to the business’s profitability
- And, therefore, which customers they are severing profitably and (equally importantly) less profitably
In the same way that average spend per transaction is the link between financial objectives and shop operations, the gross profit of your most popular typical baskets is the link between
- the products you offer
- the customers you serve
- and the business’s profitability
To refer back to The Iron Triangle, when various specialty coffee businesses perform this same analysis they will have, comparatively, developed products, operational capacity, and a concept which gives them a positioning leaning towards one of:
- Fast and cheap (but comparatively lower quality)
- Fast and quality (but comparatively more expensive)
- Cheap and quality (but comparatively slower)
Adding and delivering value
Now that you have the tools to perform some analysis on your business, we are in a position to start raising a series of strategic questions, such as:
- What is your business’s current positioning?
- Which positioning does the management think to be the most profitable for the business going forwards?
- How can the business hone it’s current proposition for greater profitability?
- How can the business successfully transition to a new, more profitable, proposition?
Go for it! Make the time to get the insights
Now that you have the tools to perform some analysis on your business, products and customers, you are in a better position to work out where the greatest opportunities are for increasing the profitability of your business.
We’ll start a new series of articles on increase prices and profitability later in the year, but to get the most our of these tips you’ll need to have this data to hand; without it, you’ll be flying blind.
We’ll pick up the conversation in a couple of weeks. In the interim, let us know if you require clarification, have a valuable critique, or are happy to share the insights from your data with us. We’re on all the normal channels.