Excel Analytics for Dummies

Factotum

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Joined
May 14, 2015
Messages
118
Can anyone point me to a good resource for learning how to do some basic analytics in Excel? What I'm trying to learn how to do is look at all the operating and maintenance costs of hundreds of facilities and determine which ones cost the least/most overall. Also to look for cases where a property manager might be under-performing, overspending, incorrectly coding transactions, or downright stealing from the company.

I'm trying to look at everything at an individual facility/property level. I have the following criteria that could factor into the costs to operate the facility:
  1. Geographic location (by state)
  2. Type of building (Floor Plan A vs Floor Plan B.... vs. Floor Plan X)
  3. Avg number of customers using the building per week
  4. Size of building in square feet
  5. The year the facility was built

Criteria 1-2 allow me to compare apples to apples since heating costs in Canada will be significantly higher than in Mexico.
With criteria 3-5, I would expect a direct correlation: more people, bigger building, older facility = higher operating costs

The problem is that I just don't know how to effectively analyze all these criteria together. Any ideas where I could start learning how to address this? Thanks!
 

Excel Facts

Does the VLOOKUP table have to be sorted?
No! when you are using an exact match, the VLOOKUP table can be in any order. Best-selling items at the top is actually the best.
maybe:
Customer Analytics For Dummies - Amazon
or
Customer Analytics For Dummies - Dummies.com

Part I: Getting Started with Customer Analytics.............. 5
Chapter 1: Introducing Customer Analytics...................................................................7
Chapter 2: Embracing the Science and Art of Metrics.................................................15
Chapter 3: Planning a Customer Analytics Initiative....................................................31
Part II: Identifying Your Customers.............................. 41
Chapter 4: Segmenting Customers.................................................................................43
Chapter 5: Creating Customer Personas........................................................................61
Chapter 6: Determining Customer Lifetime Value........................................................75
Part III: Analytics for the Customer Journey................. 85
Chapter 7: Mapping the Customer Journey..................................................................87
Chapter 8: Determining Brand Awareness and Attitudes..........................................103
Chapter 9: Measuring Customer Attitudes..................................................................113
Chapter 10: Quantifying the Consideration and Purchase Phases...........................133
Chapter 11: Tracking Post-Purchase Behavior...........................................................151
Chapter 12: Measuring Customer Loyalty...................................................................163
Part IV: Analytics for Product Development................ 185
Chapter 13: Developing Products That Customers Want..........................................187
Chapter 14: Gaining Insights through a Usability Study............................................207
Chapter 15: Measuring Findability and Navigation....................................................231
Chapter 16: Considering the Ethics of Customer Analytics......................................249
Part V: The Part of Tens............................................ 255
Chapter 17: Ten Customer Metrics You Should Collect............................................257
Chapter 18: Ten Methods to Improve the Customer Experience.............................263
Chapter 19: Ten Common Analytic Mistakes..............................................................267
Chapter 20: Ten Methods for Identifying Customer Needs.......................................271
Appendix: Predicting with Customer Analytics............ 277
 
Last edited:
Upvote 0
Powerpivot would be a good way and there is tons of YouTube vids om creating data models and the accompaning pivot tables.
 
Upvote 0

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