3 Ways Analytics Will Improve Your Homebrew

Updated: Oct 29, 2019

If you're a homebrewer and not using analytics, you’re missing out. It’s a tool that is available to brewers of any level or experience and doesn’t require a lot of work to make a difference.


What Is Analytics Anyway?


Analytics involves gathering data and translating that data into something useful



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Think of yourself as a detective. You gather clues (data points) and put them together to formulate a conclusion to the mystery. The more clues you have, the more accurate your solution will be. Brewers can use this concept to help them brew better beer, and it’s easy!


Here’s 3 Ways Analytics Will Improve Your Homebrew:

1. Reference Previous Batch Data

2. Find Trends

3. Make Adjustments



Reference Previous Batch Data

We compare EVERYTHING. It’s how we assign value to something. This beer isn’t too sweet, like the last batch…So I think it’s better. If you start recording data about your beer and brewing, you’ll always have something objective to compare future batches to. How can you know if your beer is improving if you have nothing from the past to compare it to?

Say you brew a batch of pale ale, and it turns out just ok. You slap on your game face, go back to the drawing board, and whip up a second batch of the same beer. But you’re only human, and naturally will have a tendency to call the second batch better, simply due to the extra effort you put in. But is it REALLY better? Comparing data about different batches takes the bias out of the situation.




Data comes in many forms, and it can describe different things. Objective data, things like temperature, time, and specific gravity, is typically represented by numbers, perfect for doing calculations. But what about more subjective things like taste? Keep it simple – scale of 1 to 10. Translating your data into numbers makes visualizing the data easier down the road.



Find Trends

Analytics typically involves visualizing data. It’s far easier to gather insights from a badass line chart than a table with hundreds of numbers endlessly marching down the columns. Visualizing data with graphics makes it child’s play to recognize patterns. It’s like Sesame Street, people, “One of these things is not like the other!” Each recipe you brew will have a characteristic “look”, for example, the graph produced by plotting specific gravity over the primary fermentation. If you brew the same way each time, with the same recipe and same ingredients, you’ll likely have very similar graph shapes. But what if one day, on the fourth iteration of your favorite recipe, the graph shape deviates from its typical shape? Probably should peak under the hood and check that out, ‘cause something is up.



Brewing better beer is accomplished by making connections between the data and end results. For example, after looking at your temperature chart over the span of your fermentation, you noticed there was a pretty sharp temperature swing on the fourth day. Your beer is done fermenting, it has a much higher final gravity then previous batches of the same recipe. It’s possible there’s a correlation between the temperature swing you noticed in the data and the low attenuation. Finding these correlations between data and outcomes helps you answer the

question, “why did this happen?”



Make Adjustments

Tracking data in real time allows you to keep a finger on the pulse of your beer. Critical metrics, such as final gravity, attenuation, and alcohol content are affected by controllable factors, such as temperature. If you are tracking your beer’s fermentation data every day during fermentation, you will be able to prevent problems before they happen. You notice a temperature swing in the chart? Adjust your fermenter temp. The gravity curve leveled out two days early? Maybe you should pitch more yeast, or kick up the temp a few degrees. Without objective data, you are brewing with one eye closed, and may not make a needed adjustment.



With objective data to back you up, you can be confident in any adjustments you make. You’re not basing your adjustments off guesswork, rather, you’re interpreting solid data and using that as credible evidence to make a change.




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Cheers Y’all!




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Arithmech Analytics

New Orleans, LA

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