SlideShare a Scribd company logo
1 of 13
Download to read offline
5 Data Points You Need to Know
We know that understanding what data points are the most important
to your bottom line can sometimes be the hardest part of analyzing
data. That’s why we’re highlighting the top five data points you need
to be checking on a regular basis.
Click through to get a better understanding of the data that can make
you more money.
BEST SELLERS
Best sellers refer to the quantity sold of a product. It can be calculated
using the ROI equation.
•	 Using data to track which items are your best sellers is a way to measure
success of certain products
•	 Knowing which items are your best sellers will help you to know what you
need to order more of
ROI =
Profit During Sales Period
Inventory Cost Over Sales Period
WORST SELLERS
Worst sellers also refer to the quantity sold of a product. You can also use
the ROI equation to calculate which products had the least amount of units
sold over a certain period of time.
•	 Tracking your worst sellers will indicate the merchandise that you might
want to consider discontinuing
•	 If it isn’t making you money, it’s taking up space for inventory that will be
profitable
SALESPERSON ANALYSIS
Salesperson analysis provides key information about your employees,
indicating who has the most and fewest sales, both overall and per hour
•	 Knowing which employees are your best performing salespeople will
help you make smart staffing decisions
•	 It also helps you know which employees need a little more coaching
to meet their sales quota
PEAK SALES TIMES
Tracking your peak sales times will help you staff your employees accordingly
•	 Make sure you are not wasting money on your employees during slower
periods by overstaffing
•	 Capitalize on your peak hours by scheduling your best performing
salespeople
CUSTOMER DATA
Collecting customer data, like purchase history, demographics, and customer
birthdays, will help you create segmented marketing campaigns
•	 This helps you target specific customers and personalize your customer
experience
•	 Use your data to identify your most reliable customers and offer incentives
and loyalty programs to motivate them to come back in
ricssoftware.com
800.654.3123
@ricssoftware
LEARN MORE ABOUT USING YOUR DATA:
RICSSOFTWARE.COM
OR
CLICK HERE ▷

More Related Content

Viewers also liked

10 A/B Testing Mistakes that Make Your Wallet Cry
10 A/B Testing Mistakes that Make Your Wallet Cry10 A/B Testing Mistakes that Make Your Wallet Cry
10 A/B Testing Mistakes that Make Your Wallet CryConvert.com
 
This Isn't 'Big Data.' It's Just Bad Data.
This Isn't 'Big Data.' It's Just Bad Data.This Isn't 'Big Data.' It's Just Bad Data.
This Isn't 'Big Data.' It's Just Bad Data.Peter Orszag
 
Data Science, Machine Learning and Neural Networks
Data Science, Machine Learning and Neural NetworksData Science, Machine Learning and Neural Networks
Data Science, Machine Learning and Neural NetworksBICA Labs
 
Introduction to Data Science
Introduction to Data ScienceIntroduction to Data Science
Introduction to Data ScienceCaserta
 
A Statistician's View on Big Data and Data Science (Version 1)
A Statistician's View on Big Data and Data Science (Version 1)A Statistician's View on Big Data and Data Science (Version 1)
A Statistician's View on Big Data and Data Science (Version 1)Prof. Dr. Diego Kuonen
 
Myths and Mathemagical Superpowers of Data Scientists
Myths and Mathemagical Superpowers of Data ScientistsMyths and Mathemagical Superpowers of Data Scientists
Myths and Mathemagical Superpowers of Data ScientistsDavid Pittman
 
Big Data [sorry] & Data Science: What Does a Data Scientist Do?
Big Data [sorry] & Data Science: What Does a Data Scientist Do?Big Data [sorry] & Data Science: What Does a Data Scientist Do?
Big Data [sorry] & Data Science: What Does a Data Scientist Do?Data Science London
 
Working With Big Data
Working With Big DataWorking With Big Data
Working With Big DataSeth Familian
 

Viewers also liked (9)

10 A/B Testing Mistakes that Make Your Wallet Cry
10 A/B Testing Mistakes that Make Your Wallet Cry10 A/B Testing Mistakes that Make Your Wallet Cry
10 A/B Testing Mistakes that Make Your Wallet Cry
 
Determine Your Data Strategy
Determine Your Data StrategyDetermine Your Data Strategy
Determine Your Data Strategy
 
This Isn't 'Big Data.' It's Just Bad Data.
This Isn't 'Big Data.' It's Just Bad Data.This Isn't 'Big Data.' It's Just Bad Data.
This Isn't 'Big Data.' It's Just Bad Data.
 
Data Science, Machine Learning and Neural Networks
Data Science, Machine Learning and Neural NetworksData Science, Machine Learning and Neural Networks
Data Science, Machine Learning and Neural Networks
 
Introduction to Data Science
Introduction to Data ScienceIntroduction to Data Science
Introduction to Data Science
 
A Statistician's View on Big Data and Data Science (Version 1)
A Statistician's View on Big Data and Data Science (Version 1)A Statistician's View on Big Data and Data Science (Version 1)
A Statistician's View on Big Data and Data Science (Version 1)
 
Myths and Mathemagical Superpowers of Data Scientists
Myths and Mathemagical Superpowers of Data ScientistsMyths and Mathemagical Superpowers of Data Scientists
Myths and Mathemagical Superpowers of Data Scientists
 
Big Data [sorry] & Data Science: What Does a Data Scientist Do?
Big Data [sorry] & Data Science: What Does a Data Scientist Do?Big Data [sorry] & Data Science: What Does a Data Scientist Do?
Big Data [sorry] & Data Science: What Does a Data Scientist Do?
 
Working With Big Data
Working With Big DataWorking With Big Data
Working With Big Data
 

Recently uploaded

Cash Is Still King: ATM market research '2023
Cash Is Still King: ATM market research '2023Cash Is Still King: ATM market research '2023
Cash Is Still King: ATM market research '2023Vladislav Solodkiy
 
Mapping the pubmed data under different suptopics using NLP.pptx
Mapping the pubmed data under different suptopics using NLP.pptxMapping the pubmed data under different suptopics using NLP.pptx
Mapping the pubmed data under different suptopics using NLP.pptxVenkatasubramani13
 
Master's Thesis - Data Science - Presentation
Master's Thesis - Data Science - PresentationMaster's Thesis - Data Science - Presentation
Master's Thesis - Data Science - PresentationGiorgio Carbone
 
Elements of language learning - an analysis of how different elements of lang...
Elements of language learning - an analysis of how different elements of lang...Elements of language learning - an analysis of how different elements of lang...
Elements of language learning - an analysis of how different elements of lang...PrithaVashisht1
 
Persuasive E-commerce, Our Biased Brain @ Bikkeldag 2024
Persuasive E-commerce, Our Biased Brain @ Bikkeldag 2024Persuasive E-commerce, Our Biased Brain @ Bikkeldag 2024
Persuasive E-commerce, Our Biased Brain @ Bikkeldag 2024Guido X Jansen
 
TINJUAN PEMROSESAN TRANSAKSI DAN ERP.pptx
TINJUAN PEMROSESAN TRANSAKSI DAN ERP.pptxTINJUAN PEMROSESAN TRANSAKSI DAN ERP.pptx
TINJUAN PEMROSESAN TRANSAKSI DAN ERP.pptxDwiAyuSitiHartinah
 
Rock Songs common codes and conventions.pptx
Rock Songs common codes and conventions.pptxRock Songs common codes and conventions.pptx
Rock Songs common codes and conventions.pptxFinatron037
 
The Universal GTM - how we design GTM and dataLayer
The Universal GTM - how we design GTM and dataLayerThe Universal GTM - how we design GTM and dataLayer
The Universal GTM - how we design GTM and dataLayerPavel Šabatka
 
Strategic CX: A Deep Dive into Voice of the Customer Insights for Clarity
Strategic CX: A Deep Dive into Voice of the Customer Insights for ClarityStrategic CX: A Deep Dive into Voice of the Customer Insights for Clarity
Strategic CX: A Deep Dive into Voice of the Customer Insights for ClarityAggregage
 
Virtuosoft SmartSync Product Introduction
Virtuosoft SmartSync Product IntroductionVirtuosoft SmartSync Product Introduction
Virtuosoft SmartSync Product Introductionsanjaymuralee1
 
5 Ds to Define Data Archiving Best Practices
5 Ds to Define Data Archiving Best Practices5 Ds to Define Data Archiving Best Practices
5 Ds to Define Data Archiving Best PracticesDataArchiva
 
How is Real-Time Analytics Different from Traditional OLAP?
How is Real-Time Analytics Different from Traditional OLAP?How is Real-Time Analytics Different from Traditional OLAP?
How is Real-Time Analytics Different from Traditional OLAP?sonikadigital1
 
CI, CD -Tools to integrate without manual intervention
CI, CD -Tools to integrate without manual interventionCI, CD -Tools to integrate without manual intervention
CI, CD -Tools to integrate without manual interventionajayrajaganeshkayala
 
CCS336-Cloud-Services-Management-Lecture-Notes-1.pptx
CCS336-Cloud-Services-Management-Lecture-Notes-1.pptxCCS336-Cloud-Services-Management-Lecture-Notes-1.pptx
CCS336-Cloud-Services-Management-Lecture-Notes-1.pptxdhiyaneswaranv1
 
Optimal Decision Making - Cost Reduction in Logistics
Optimal Decision Making - Cost Reduction in LogisticsOptimal Decision Making - Cost Reduction in Logistics
Optimal Decision Making - Cost Reduction in LogisticsThinkInnovation
 
ChistaDATA Real-Time DATA Analytics Infrastructure
ChistaDATA Real-Time DATA Analytics InfrastructureChistaDATA Real-Time DATA Analytics Infrastructure
ChistaDATA Real-Time DATA Analytics Infrastructuresonikadigital1
 

Recently uploaded (16)

Cash Is Still King: ATM market research '2023
Cash Is Still King: ATM market research '2023Cash Is Still King: ATM market research '2023
Cash Is Still King: ATM market research '2023
 
Mapping the pubmed data under different suptopics using NLP.pptx
Mapping the pubmed data under different suptopics using NLP.pptxMapping the pubmed data under different suptopics using NLP.pptx
Mapping the pubmed data under different suptopics using NLP.pptx
 
Master's Thesis - Data Science - Presentation
Master's Thesis - Data Science - PresentationMaster's Thesis - Data Science - Presentation
Master's Thesis - Data Science - Presentation
 
Elements of language learning - an analysis of how different elements of lang...
Elements of language learning - an analysis of how different elements of lang...Elements of language learning - an analysis of how different elements of lang...
Elements of language learning - an analysis of how different elements of lang...
 
Persuasive E-commerce, Our Biased Brain @ Bikkeldag 2024
Persuasive E-commerce, Our Biased Brain @ Bikkeldag 2024Persuasive E-commerce, Our Biased Brain @ Bikkeldag 2024
Persuasive E-commerce, Our Biased Brain @ Bikkeldag 2024
 
TINJUAN PEMROSESAN TRANSAKSI DAN ERP.pptx
TINJUAN PEMROSESAN TRANSAKSI DAN ERP.pptxTINJUAN PEMROSESAN TRANSAKSI DAN ERP.pptx
TINJUAN PEMROSESAN TRANSAKSI DAN ERP.pptx
 
Rock Songs common codes and conventions.pptx
Rock Songs common codes and conventions.pptxRock Songs common codes and conventions.pptx
Rock Songs common codes and conventions.pptx
 
The Universal GTM - how we design GTM and dataLayer
The Universal GTM - how we design GTM and dataLayerThe Universal GTM - how we design GTM and dataLayer
The Universal GTM - how we design GTM and dataLayer
 
Strategic CX: A Deep Dive into Voice of the Customer Insights for Clarity
Strategic CX: A Deep Dive into Voice of the Customer Insights for ClarityStrategic CX: A Deep Dive into Voice of the Customer Insights for Clarity
Strategic CX: A Deep Dive into Voice of the Customer Insights for Clarity
 
Virtuosoft SmartSync Product Introduction
Virtuosoft SmartSync Product IntroductionVirtuosoft SmartSync Product Introduction
Virtuosoft SmartSync Product Introduction
 
5 Ds to Define Data Archiving Best Practices
5 Ds to Define Data Archiving Best Practices5 Ds to Define Data Archiving Best Practices
5 Ds to Define Data Archiving Best Practices
 
How is Real-Time Analytics Different from Traditional OLAP?
How is Real-Time Analytics Different from Traditional OLAP?How is Real-Time Analytics Different from Traditional OLAP?
How is Real-Time Analytics Different from Traditional OLAP?
 
CI, CD -Tools to integrate without manual intervention
CI, CD -Tools to integrate without manual interventionCI, CD -Tools to integrate without manual intervention
CI, CD -Tools to integrate without manual intervention
 
CCS336-Cloud-Services-Management-Lecture-Notes-1.pptx
CCS336-Cloud-Services-Management-Lecture-Notes-1.pptxCCS336-Cloud-Services-Management-Lecture-Notes-1.pptx
CCS336-Cloud-Services-Management-Lecture-Notes-1.pptx
 
Optimal Decision Making - Cost Reduction in Logistics
Optimal Decision Making - Cost Reduction in LogisticsOptimal Decision Making - Cost Reduction in Logistics
Optimal Decision Making - Cost Reduction in Logistics
 
ChistaDATA Real-Time DATA Analytics Infrastructure
ChistaDATA Real-Time DATA Analytics InfrastructureChistaDATA Real-Time DATA Analytics Infrastructure
ChistaDATA Real-Time DATA Analytics Infrastructure
 

5 Data Points You Need to Know

  • 2. We know that understanding what data points are the most important to your bottom line can sometimes be the hardest part of analyzing data. That’s why we’re highlighting the top five data points you need to be checking on a regular basis. Click through to get a better understanding of the data that can make you more money.
  • 4. Best sellers refer to the quantity sold of a product. It can be calculated using the ROI equation. • Using data to track which items are your best sellers is a way to measure success of certain products • Knowing which items are your best sellers will help you to know what you need to order more of ROI = Profit During Sales Period Inventory Cost Over Sales Period
  • 6. Worst sellers also refer to the quantity sold of a product. You can also use the ROI equation to calculate which products had the least amount of units sold over a certain period of time. • Tracking your worst sellers will indicate the merchandise that you might want to consider discontinuing • If it isn’t making you money, it’s taking up space for inventory that will be profitable
  • 8. Salesperson analysis provides key information about your employees, indicating who has the most and fewest sales, both overall and per hour • Knowing which employees are your best performing salespeople will help you make smart staffing decisions • It also helps you know which employees need a little more coaching to meet their sales quota
  • 10. Tracking your peak sales times will help you staff your employees accordingly • Make sure you are not wasting money on your employees during slower periods by overstaffing • Capitalize on your peak hours by scheduling your best performing salespeople
  • 12. Collecting customer data, like purchase history, demographics, and customer birthdays, will help you create segmented marketing campaigns • This helps you target specific customers and personalize your customer experience • Use your data to identify your most reliable customers and offer incentives and loyalty programs to motivate them to come back in
  • 13. ricssoftware.com 800.654.3123 @ricssoftware LEARN MORE ABOUT USING YOUR DATA: RICSSOFTWARE.COM OR CLICK HERE ▷