Thank you for your interest in
modern analytics

Below you will find information on:

1. Basic process on how we transform data into actionable insights
2. Examples of several different demand related analytics

Process to Transform Data into Analytics

Put your Raw Data to Work!

The process to convert raw data into actionable analytics might seem intimidating at first, but the process is pretty straight-forward once you understand the main steps. 
And this process can be easily modified to fit any business no matter the size or complexity.  

  • Date Extraction: Export raw data out of source systems on schedule
  • Data Transformation: Combine, modify, and enhance raw data for analytics
  • Analytics: Publish analytics on accessible cloud site for consumption
Data to Analytics Process jpg

Brewery Analytics Examples

Gain Data-Driven Insights to Take Meaningful Actions!

Below you will experience four purpose-built examples of brewery analytics; each will provide different levels of insights into your business.  They use real (but slightly modified) data from Taproom  and Wholesale transactions systems (Square and Quickbooks respectively, but these would interact just as well with data from any other systems), so you can envision how they would work for your brewery.
Please view the video on each for a deeper understanding.

  • Demand Performance: Quickly see how key demand metrics are performing compared to prior periods and get high level insights to Beers and Customers
  • Beer Insights: visibility to demand trends and performance, see who is buying, and the relationship between revenue and cost
  • Customer Insights: complete understanding of customer performance, what are they buying, how they relate to their peers
  • Taproom Insights: visibility to taproom performance, beers/customer/employee trends, what has been on tap and overlap of styles

Demand Performance

How are we performing across our business, anything that needs to be looked at further?


High level and insightful analytics to overall demand for brewery using combined taproom and wholesale data.

Use this to see business performance across periods and what segments are doing well or need more focus

Quickly find opportunities to take advantage of or risks to mitigate

Sales Dashboard jpg
Beer Summary jpg
Customer Summar jpg

Beer Insights

What do we sell,  how doe we sell it, who is buying it, and how much money are we making on each beer?

Detailed performance analytics for flagship and individual beers.

Use this to understand performance of each beer and deep dive metrics to find actionable insights. 

Flagship Comparison jpg
Beer Deep Dive jpg

Customer Insights

Who buys our beer, what are they buying, how profitable are we when we sell to them?

High-level overview of different customer segments and detailed performance analytics for individual customers.

Use this to understand all the customers we sell to and deep-dive individual customers to gain actionable insights

Customer Portfolio jpg
Customer Deep Dive jpg

Taproom Insights

What are we selling in the taproom, what are the recent trends, how is our coverage by beer style?

Understand previous day and recent demand trends in taproom and see how our tap coverage has been over time.

Use this to understand taproom how the taproom is operating and how we have done with the various beers on tap.

Taproom Metrics jpg
Taproom Density jpg

Additional Information

Pricing Model

Our pricing model is flexible to allow us to add value at any investment level; starting at around $1,000 for a year.

The main components are as follows and the pricing varies based on the complexity and capabilities:  

  • ​Process to Extract Data out of Source Systems
  • ​Clean, Combine, and Enhance data to prepare a Tableau Datasource 
  • ​Create and Deploy Analytics on Tableau Cloud
  • ​Tableau User Licensing
  • ​Tableau Cloud Admin

We also offer Analytics Assessment / Strategy Development and Team Enablement and Training to help build a holistic analytics program 

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email: jeremy@centralcoast-analytics.com