Today, let's dive deep into how data, both aggregated (summed or grouped data) and granular (detailed data), can help give different view points on the same set of raw data.

Imagine this: you're striving to understand your taproom pricing strategy and price performance to see if you have the opportunity to make smart adjustments. Let’s see how different levels of analysis can play a part when reviewing historical data.

In this example, we are looking at our average price of a draft at a high level and can see the average is $7.58 and has gone up $6.87 to $7.62 over the last several months.

Great! At a high-level things are looking pretty good. But let’s keep drilling down and see if we can find any additional insights.


Now let’s look at it by Beer and Location.

Cool – this starts to show us some new insights that we didn’t get at the highest level. We can see a spread between different beers and that we generally charge more at our restaurant vs taproom.
I think often times breweries will stop here in their analysis but lets dive deeper…


What if we looked at every transaction to see if they were all right at that average or if we have a spread or some outliers.

Yeow – that’s a lot to take in all at once, lets focus in on a single beer, WIPA- C in this case, and find some insights.

At this very granular level (+ some aggregation), we can get to some new insights:
- 80% of our sales are at ‘normal’ price of $9 for restaurant and 8% for taproom
- 13% are at happy hour $1 off at taproom
- 7% of sales are at an unusually low price including 3% less than $1
- If we can get that 7% up to an expected price we’d raise the ASP for this beer by about $0.50 a pint or 6.5%

To sum it up here are some things to consider when it comes to aggregated vs granular analysis

Aggregated Data: A Birds-eye Brew

Benefits:
- Spotting Sales Trends: By looking at overall monthly or yearly sales, aggregated data helps taprooms understand peak sales periods, enabling better inventory and staffing management.
- Efficient Decision-making: With aggregated data, it's easier to present and discuss sales performance with stakeholders, as it provides a concise overview without delving into every transaction.
- Budgeting and Forecasting: An overarching view of sales can guide financial planning and budgeting decisions.

Drawbacks:
- Loss of Specificity: While you know stouts sold well last winter, aggregated data might not reveal which specific stout variant was the top seller.
- Missed Micro-Trends: Some short-lived sales spikes (like a one-day event) might get diluted when data is viewed on a larger timeframe.


Granular Data: Into the Beer's Bubbles

Benefits:
- Individual Sale Analysis: Understanding sales at a transactional level helps pinpoint performance trends.
- Dynamic Sales Strategy: Granular insights might reveal that a certain beer sells better on weekends or during happy hours, enabling dynamic pricing or promotions.
- Detailed Customer Insights: By examining individual receipts or sales, taprooms can identify patterns, like if customers tend to pair a certain beer with a specific snack, paving the way for bundled promotions.

Drawbacks:
- Potential Data Overwhelm: Examining every sale can be cumbersome, especially for taprooms with high transactions.
- Analysis Paralysis: Too much detail can lead to indecision if not interpreted correctly.
- Time-Consuming: Sifting through granular data demands more time, tools, and expertise.

As we’ve seen there are benefits and drawbacks to the various types of analysis. It is best to use a combined approach to get the full picture of what you are analyzing. And while trying to build this out in excel probably wouldn’t be feasible, modern analytics tools make this all possible!