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1. General Account and Financial Analysis

2. Sales Analysis

3. Inventory & Warehousing Metrics

4. E-commerce (Onsite Metrics)

5. Physical Store Metrics

6. Merchandising Metrics

7. Pricing Metrics

8. Digital Presence

9. Email Marketing

10. Social Media Engagement

11. Digital Advertising

12. Promotional Analysis

13. Customer Success

14. Shoppers

15. B2B Metrics

16. Human Resources Metrics

17. Delivery & Fulfillment Metrics

18. Manufacturing Metrics

203 metrics for retailers and brands to track

In this post, we will dive into each metric, discuss how to measure it and what it represents.

The importance of each metric differs depending on your company stage so don’t worry if you haven’t been tracking it.

Pick what makes sense for your stage.

To make this easier, we’ve split the metrics into 18 different domains so you can send this out to other team members.

1. General Accounting and Financial Analysis

We will be skipping over the purpose of accounting and focusing on the business goals that drive the underlying rationale behind some of the accounting and financial analysis.

No.

Name

Description

1

Cash in Bank

Amount of money you have tucked away to ensure that you have enough runway to execute on your short to medium term strategies.

This includes hiring new staff, purchasing new software or increasing inventory levels.

2

Net Income

Formula: Sales revenue - All cost.

This is the amount of money you can expect to hit your bank account after different time periods.

3

Operating Income

Formula: Sales Revenue - Operating Expenses

Money leftover after you’ve deducted the expenses required to keep your business running day to day.

4

Gross Profit

Formula: Sales Revenue - Cost of Goods Sold

Amount left after deducting the direct costs associated with providing the good or service

5

Sales Revenues

How much your customer pays you for the goods or service.

6

Other Revenues

Example:

  • You organised a carnival to sell lemonade drinks
  • Carnival fees will be considered “Other Revenues”

7

Cost of Goods Sold

The direct expense relating to producing the good or service.

Example:

  • Item A cost $5. You sell it for $10.
  • The COGS is $5

At times, some forms of shrinkage may be included here to keep the books simple.

8

Operating Expenses

Includes Cost of Goods, Labour, and other day to day expenses (water/ electricity)

9

Non-Operating Expenses

Includes Depreciation, Amortization, Interest rates.

Basically things that you have to pay for but don’t seem to directly contribute to the production or service of your main line of business

10

Gross Profit Margin

Formula: 1- (Cost of Goods Sold/ Sales Revenue)

Ratio to represent how much of incoming cash will be locked up in providing the good or service

11

Operating Profit  Margin

Formula: Operating Income/ Revenue

Similar purpose as gross profit margin but this captures the other overheads associated with running the business

12

Cash Conversion Cycle

Formula: 

Days of inventory outstanding -

Days of sales outstanding + Days payable outstanding

This is a long formula that simply represents how long it takes you to turn cash into product and back to more cash again.

13

Shrinkage

Formula: Inventory on paper- Actual inventory

Any loss inventory due to fraud or damage

14

Estimated Market Share

Formula: Current Sales / Total Addressable Market

Due to the lack of accurate data, most of these are simple estimations. Out of the total addressable market of the people who will and can buy your product or service. How many already have and will continue to do so.

15

Growth Rate

Formula: (Sales at End of Period/ Sales at Start of Period) - 1

Represents the speed at which your organisation is growing.

2. Sales Analysis

No.

Name

Description

1

Sales by Channel

How much sales is each sales channel bringing in?

2

Sales by Supplier

Based on the merchandise supplied by different suppliers, how much sales did that generate?

Represents the financial reliance to individual suppliers.

3

Sales to Date

Represents the cumulative sales from a certain start date to this point.

Commonly used for monitoring the sales progress within a financial period (e.g. a quarter or a month)

4

Average Order Value

Formula: Total Sales / Total No. of Orders

Represents the average amount of money a customer spends per transaction. Depending on the industry, there can be quite a fair bit of fluctuations in these numbers. This represents a huge opportunity to drive these numbers up.

5

Average No. of Products Per Transaction

Formula: Total Quantity of Products Sold / Total No. of Orders

Represents the average number of products a customer purchased per transaction.

6

Average Margin

Formula: Cost of Product / Retail Price

How much is actually earned for every $1 sold.

7

Sales Forecast

NOTE: There are several types of forecast for differing purposes.

For a purely financial forecast, an estimate can be made using future marketing budgets and historical demands as a good estimate.

8

No. of Returns

Total number of exchange request

9

No. of Refunds

Total number of refund request

10

No. of Exchanges

Total number of exchange request

11

Breakdown of Failed Sales

Breakdown the above three based on

  • Reason
  • Frequency
  • Associated cost

Represents what should be tackled first

3. Inventory & Warehousing

No.

Name

Description

1

Inventory Levels

Per product, how many units are there store in warehouse (or the back of the store)

2

Inventory Cost

Formula: Ordering Cost + Carrying Cost + Cost of Deterioration

Represents the cost of managing inventory. Usually a significant percentage of the overall cost structure.

3

Inventory Forecast

NOTE: There are several types of forecast for differing purposes.

For an inventory forecast, a concrete number wouldn’t do much good. You will need a confidence interval.

Example:

With a 95% confidence an inventory level of 100 will meet the demand.

4

Inventory Accuracy Rate

Formula:

(Inventory Level Based on Physical Count / Inventory Level Based on Records) X 100%

Some margin of error should be allowed but you should be alarmed if it is ridiculously off (e.g >7.5%)

5

Days of Supply

Formula:

Inventory levels / Daily Demand

Number of days you can continue to supply the demand without going out of stock

6

Holding Cost

Cost associated with keeping inventory in the warehouse.

Sometimes opportunity cost is included.

7

Safety Stock Percentage

Percentage of extra stock kept just in case of a demand surge or a delay in supply.

8

Safety Stock Cost

Cost associated with keeping this extra inventory in the warehouse.

9

Stock Turnover

Formula:

Cost of goods sold / Average inventory

Represents the number of times inventory is sold over a given period. (Higher the better)

10

Sell-Through Rate

Formula:

Amount received from supplier - Amount sold to customers

Represents the wastage leftover of a particular product line.

11

Receiving Accuracy Rate

Accuracy rate between what receiver records and what was actually delivered.

12

Cost Per Receive

Cost associated with each received (more relevant to large warehouses and deliveries)

13

Picking Accuracy Rate

Formula:

Correct Product Picked / Total No. of Products

A proxy as to how accurate warehouse employees/ robots are at picking and packing the correct merchandise.

14

Lead Time by Supplier

Time taken for a supplier to send the stock to the proper location from the time that the order was placed.

15

Breakdown by Location

Inventory stats broken down by location to see which to optimise first

4. E-Commerce Sites (On-site metrics)

Most of these metrics can be obtained using a free tool- Google Analytics.

No.

Name

Description

1

Total Traffic

Sum total of all traffic to the site

2

Traffic Source

Source of traffic to the site (e.g. Facebook, Instagram, Affiliated Sites)

3

Landing Page

Page that people land on

Proxy as to which pages rank more highly on search engines or is the most linked in by other sites.

4

Bounce Rate

Percentage of visitors who leave the site without any activity on site.

Note: If this number increases too much it might hurt your search ranking because it is a signal that users didn’t find what they were searching for.

5

Pageviews per session

Represents the number of pages visited by visitors per session.

6

Average Time Per Session

Formula: (Total time spent on site from ALL sessions)/ Total number of sessions

There might be some correlation between the increase in average time spent per page but you shouldn’t depend on this metric alone because an increase in average time spent could be due to poor UX that is taking users longer to perform the actions they require.

7

In-Site Search

If you have a search bar in your site, there will be 3 metrics to be optimised:

  1. Time after search
  2. % Search Exits
  3. % Search Refinements

These represent the search intent of users who have already entered your site and are looking for something else.

8

Email Capture Rate

Percentage conversion of visitors who leave their email

Pro tip: Remember to Segment

  • Based on form factor (Email form v Pop-up)
  • Based on offer (Exclusive deals v $5 off first transaction)
  • Based on pages (Main page v Blogs)

9

Peak Traffic Times

Depending on your technical architecture of your site, you might have to scale your servers based on peak traffic times.

If you are running A/ B tests, these traffic times will be when most of the data from your experiments get collected.

10

Device type breakdown

Revenue breakdown based on the device type (Desktop, Mobile, Tablet)

Focus on optimising responsiveness across screen sizes

11

Sales Per Country (State)

Revenue breakdown based on the I.P. address of the user’s device

If you were using a website builder (Shopify or Woocommerce), using their analytics based on the shipping location may be more accurate.

12

Conversion Rates

Formula: (No. of purchasers / No. of site visitors)

Note: The formula above is for the macro conversion but there should be other optimisations between other pages (E.g. Product page to Add to Cart page) as well.

13

Cart Abandonments

Percentage of visitors who have something in their cart but left the site before purchasing.

Note: Try tracking this metric across longer time horizons because there will be instances where shoppers return the next day.

14

Credit Card Errors

Percentage of “purchasers” who have encounters at check out due to credit card errors.

15

Product: Views

No. of times this product SKU was viewed

16

Product: Add to Cart

No. of times this product SKU was added to cart

17

Product: Conversion Rate

Formula: (View)/(Purchased) per product

18

Multi-Channel Funnel

MCF, as known as attribution modeling, attempts to measure the impact of each phase of the shoppers’ journey.

(E.g. Website visit -> Ad on Google -> Ad on Facebook before a purchase)

5. Physical Stores

No.

Name

Description

1

Sales per location

Sum of total sales over a certain time period per location

2

Sales per salesperson

Sum of total sales over a certain time period per sales person

3

Sales per square foot

Sum of total sales over a certain time period per square foot

4

Cost per square foot

Cost of rent & utilities over a certain time period per square foot

5

In-store Traffic

Total foot traffic that enter your store

6

Area Foot Traffic

Foot traffic around the area of your store

7

Area to Store Conversion

Formula: (In-store Traffic / Area Foot Traffic)

Represents the conversion percentage of people walking around outside your store vs those who actually enter your store.

8

In-store Heatmap

A visual representation of which parts of the store has more foot traffic based on number of visitors and time spent

9

In-store Hotspots

A visual representation of which parts of the store has more foot traffic based on time spent

10

Time Spent In-store

Formula: (Total time spent in store from ALL sessions)/ Total number of in-store visits)

11

Peak Periods

Peak periods based on in-store traffic.

Should be used for manpower planning so that conversion rates don’t suffer

12

Average Queue Length

Average time in queue and the number of people waiting in line.

13

In-store Conversion Rates

Formula:  (No. of completed Transactions/ In-Store Traffic)

14

Revenue per Visitor

Formula: (Revenue / Total no. of visitors)

6. Merchandising

No.

Name

Description

1

X- Day New Product Sales

For new products, what was the sales for the first

  • 3 days
  • 7 days
  • 30 days

2

Est. Sales Margin Range

Before pricing the product, an estimation should be made based on historical sales and competitive data to estimate the margin of a product.

3

Sales by Brand

Sales revenue broken down by brand

4

Sales by Category

Sales revenue broken down by categories

5

Sales by Supplier

Sales revenue broken down by suppliers

6

Sales by Product Attribute

Sales revenue broken down by product attributes. Some examples that merchandisers take into account

  • Color
  • Packaging and Unit of measure
  • Material

7

Product Lifecycle

Estimated amount of time before a product “expires” and becomes “obsolete”

  • Fashion: When the next season starts
  • Grocery: Based on the label on the products

8

Quantity of Product Reviews

No. of reviews for a specific product

9

Quality of Product Reviews

Average Quality rating (E.g. 1-5) for a product

10

Supplier Reviews (Quality)

No. of reviews for a specific supplier

11

Supplier Reviews (Quantity)

Average Quality rating (E.g. 1-5) for a supplier

12

Seasonality periods per product

Product attributions and seasonality of these attributes.

  • Season 1: Black, Fur, Wet does well
  • Season 2: White, Wool, Dry does well

13

Product Complements

Which products tend to be purchased together

14

Product Substitutes

Which products tend to be seen as competition to each other

15

Sales per packaging

Depending on the products, some products could be sold in different packages. For example;

  • Coca Cola (1 can, 6 pack, 24 cans)

This can also be analysed as the same product.

16

Recommendation Hit Rate

Percentage of Total number of successful recommendations

17

Upsell Hit Rate

Percentage of recommendations that were upsells

18

Cross-Sell-Rate

Percentage of recommendations that were cross-sells

7. Pricing

No.

Name

Description

1

Historical Pricing

Shows the historical price points across time

2

Sales per price

Formula: Total revenue per historical sales price

3

Elasticity Estimate

Formula: (% Change in Quantity Demand) / (% Change in Price)

4

Competitive Pricing

Table of competitive pricing against yours and the estimated deviation

8. Digital Presence (Inbound, SEO & other unpaid)

No.

Name

Description

1

Site Traffic from Organic

Total site traffic from organic traffic sources

2

Blog Traffic

Total site traffic to blog content

3

Blog Conversion Rate

Formula: 

(Purchases from blog traffic)/ (Total site traffic to blog content)

4

Blog view frequency

How often your blog is visited and revisited

5

Revenue per blog post

Formula:

(Revenue driven from blogging)/ (No. of Blog Post)

6

Average Monthly Impression per content

Formula: 

(Total monthly impressions based on search, social, referral and others) / (Content)

Represents the return on impressions for each new piece of content that is pushed out

7

Common Search Queries

Search terms that lead visitors to your page

8

Page rank on search engines

Rank on search engines (broken down by search terms)

9

Keywords Ranked

Keywords that your site ranks for (broken down by page)

10

Domain Authority

Prediction of how well search engines will rank your site based on its relevance for a specific subject area

9. Email Marketing

No.

Name

Description

1

Email Open Rate

Percentage of emails that get opened

2

Email Click-Through Rate

Based on the content of the emails, percentage of subscribers that click the links within the email

3

No. Of Spam Complaints

Total number of spam complains

4

Unsubscribe Rate

Percentage of subscribers that unsubscribe to your email

5

Device Breakdown

Ratio of Mobile : Desktop : Tablet : Others

Note: Based on where they first opened the email

6

Revenue per subscriber

Formula: (Revenue Generated from email) / (No. of subscribers)

7

Revenue per email

Formula: (Revenue Generated from email) / (No. of emails sent)

10. Social Media Engagement

No.

Name

Description

1

Social Media Fans

No. of followers on each social media platform

2

Social Media Engagements

Note: There are different measures as to what constitutes an engagement depending on the platform

E.g.

Facebook: Like, Share, Comment

Reddit: Like, Share, Comment

Youtube: Thumbs up/ down, Share, Comment

3

Post Type

Total number of post based on type

  • Video
  • Image
  • Image with caption
  • Image with cute animal

4

Performance breakdown by post type

Engagement breakdown based on image type

5

Impression to Website Traffic

Formula: (Website traffic from post) / (Impression per post)

6

Post to Website Traffic

Formula: (Website traffic from post) / (No. of post)

7

Revenue per post

Formula: (Sales driven from post) / (No. of post)

11. Digital Advertising

No.

Name

Description

1

Cost per impression

Formula:

(Ad budget attributed to impressions )/(Total no. of impressions)

2

Cost per click

Formula:

(Ad budget attributed to clicks )/(Total no. of impressions)

3

Customer acquisition cost

Formula:

(Ad budget )/(Total no. of new customers)

4

Affiliate performance

Formula:

(Affiliate-Driven Revenue )/(Total no. of new customers)

5

Campaign performance

Represents how well a particular advertising campaign performed (can be broken down into LOTS of other secondary dimensions)

6

Keyword performance

Represents revenue driven by a particular keyword

12. Promotional Analysis

No.

Name

Description

1

Number of Promotions

Total number of promotions (Segment into active v inactive)

2

Revenue Contribution

Revenue from transactions that have a promotion applied

3

Lift from promotions

Estimated lift from promotion:

Formula: 

(Actual sales with promotion) - (Estimated Baseline without)

4

Breakdown by promotional attributes

Revenue breakdown based on promotional attributes

  • 2 for X
  • $5 off
  • Buy one get one

Which of these are getting you more traffic?

5

Breakdown by product

Revenue breakdown based on product SKUs

6

Breakdown by category

Revenue breakdown based on categories

7

Breakdown by brands

Revenue breakdown based on brands

8

Breakdown by channel

Revenue breakdown based on sales channel

9

Estimated Cannibalisation

Opposite of Lift from promotions if the Lift is negative

13. Customer Support/ Success

No.

Name

Description

1

Average time to first response

Formula: 

(Total time taken before first response)/ (No. of Request)

2

Average resolution time

Formula: 

(Total time taken to resolve all issues)/ (No. of Request)

3

Total Sessions per day

Include EVERYTHING that a customer support rep has to handle

4

Web-chat sessions

Total number of web-chat session and a breakdown of how long they take

5

Social Media chat sessions

Total number of social media-chat session and a breakdown of how long they take

6

Email chat sessions

Total number of email-chat session and a breakdown of how long they take

7

Text- Sessions

Total number of text-chat session and a breakdown of how long they take

8

Overall Channel breakdown

Breakdown of time taken on

  • Web-chat
  • Social media
  • Email
  • Text
  • Other

9

Average number of opened tickets

Opened tickets are issues that are currently worked on at this moment.

10

Average number of resolved issues per day

Formula:

Total number of issues per month / Days in the month

11

Average backlog

Backlog represents the number of unopened issues that the team has yet found the time to resolve

12

Net Promoter Score per case type

Breakdown the NPS based on the problem they faced

  • Delivery delay
  • Damaged product

13

Net Promoter Score per Rep

Breakdown the NPS based on the customer support representative

14

Resolution Time per Rep

Average time taken for a customer support representative to solve an issue

15

Resolution Rate per Rep

Percentage of issues that a customer support representative can solve

16

Average Ramp up Time

Average time taken to go from a complete noob to an average performer

16

No. of session breakdown based on different purposes

Breakdown the main reason why customers are contacting you

17

Sessions resolution time breakdown based on purpose

Based on the above, measure the time taken to resolve those issues.

18

Resolution rate based on purpose

Measure the resolution rate of those issues.

14. Shoppers

No.

Name

Description

1

Historical LTV

Formula: 

(Total sales revenue to date) * (Average margin) per shopper

2

Predictive LTV

Based on churn rate, calculate estimated lifetime value

[ Churn = (1/ LTV) ]

Formula:

Lifetime (in months) * Average sale * Average Margin

3

Cohort Analysis

Cohort analysis breakdowns the transactions that occurred within a month into new and returning customers to see if the number of returning customers is steadily increasing.

4

Lasagna Model

The next level for cohort analysis.

Breakdown the returning cohort into further pieces to see when they first came.

Example: This month is April 2019

  • 30% of returning shoppers came from Mar 2019
  • 25% of returning shoppers came from Feb 2019
  • 25% of returning shoppers came from Jan 2019
  • 20% of returning shoppers came from before 2019

5

New v Returning Ratio

Ideally this ratio should skew towards returning shoppers over time so that you can shift customer acquisition efforts to customer retention.

6

Return Rate against time

Percentage of shoppers who return after the first month, second month, third month…

The goal is to drive these numbers up.

7

Time between Visits

Average time between visits broken down by visit number

Example:

  • Between the 1st and 2nd: 90 days
  • Between the 2nd and 3rd: 100 days
  • Between the 3rd and 4th: 95 days

A decrease in these numbers represent a higher shopper engagement score.

8

Referral Rates

Percentage of current customers who are willing to refer others

9

Net Promoter Score

A measure of how likely a customer is willing to refer your brand to their friends

For a benchmark:

  • Apple’s score is 72
  • Nike’s score 32

10

Customer Satisfaction Test

A measure of the level of satisfaction with a particular service.

Note:

CSAT measure satisfaction levels whilst NPS measures loyalty

11

Customer Acquisition Cost

Total cost associated with acquiring a new customer. Examples of cost that can be included

  • Sales commission
  • Ad budget
  • Cost to create creative
  • Software involved

12

Churn Rate

Percentage of shoppers who leave your service forever

13

Loyalty tier breakdown

Breakdown number of shoppers based on their loyalty tiers

14

No. of points in circulation

If you offer loyalty points as a discounting mechanism, you will want to track the number of points in circulation for accounting purposes.

15

No. of Loyalist

No. of shoppers who fall under “loyalist”

These individuals have

  • An above average NPS score
  • Seem to never churn
  • Will always offer their feedback

Retailers should always have some idea of what market segment they are going after and what can be considered “loyal” in that market.

16

Total No. of Distinct Segments

Measure of how many shoppers segments you have based on their purchasing behaviour.

Not everyone shops the same way.

17

Market Segment Growth

Based on your target shoppers, how fast is the market growing/ Example: If your store sells green tea, how fast is the green tea enthusiast market growing?

15. B2B Sales

No.

Name

Description

1

On Target Earning (OTE)

Amount that a sales rep should expect to take home (as thus how much they should be expected to sell)

2

Average Sales per rep

Formula: (Total B2B Sales) / (No. of reps)

3

Average Sales cycles

Represents the average time taken to close a new deal (from start to finish)

4

Average win rate

Formula: (No. of closed deals) / (No. of initial deals)

5

Overall funnel conversion

Conversion rate from:

  • First contact
  • Meeting / Email
  • Invoice sent
  • Payment made

6

Average deal size

Formula: (Total B2B Sales) / No. of Deals

7

Capacity per rep

Number of calls, emails and meetings a rep can take in a month

8

Average Ramp time

Average time taken to go from a complete noob to an average performer

9

Average Margin per rep

Represents one variable in determining if reps are good enough to close deals without having to offer too large a discount

10

Percentage Hitting Quota

Overall percentage of reps that attain their monthly quota.

Pro Tip:

  • You don’t want this at 100% because it means you guys aren’t stretching enough
  • >80% should be hitting quota

16. Human Resource

No.

Name

Description

1

Revenue per employee

Formula: Total Revenue/ Total number of employees

2

Average time since promotion

Average time since an employee has been promoted

3

Cost per New Hire

Cost (sometimes this could just be the time invested) to hire a new candidate

* Time spent interviewing failed candidates should also be included

4

Performance Appraisal Rating

Rating of performance from managers

5

Peer Appraisal Rating

Rating of performance from peers

6

HR to Employee Ratio

Ratio of HR professionals to Regular Employees

7

Turnover Rate

Average time spent within the organisation before a personal leaves

8

Time to Hire

Average time taken to hire for an unfulfilled position

9

Ramp Time

Average time taken to go from a complete noob to an average performer

17. Delivery and Fulfilment

No.

Name

Description

1

Average Fulfilment Time

Formula: 

(Total time taken to fulfill all orders) / (No. of fulfilments)

2

Overall Delivery cost

Total cost associated with delivering product

3

Delivery cost per unit

Formula: 

(Overall delivery cost) / (Total no. of units)

4

Perfect order rate

Percentage of orders that were delivered perfectly

  • On time
  • Right product
  • No customer complaints

5

No. of returns

Total number of returns

Remember to segment by:

  • Customer segment
  • Location
  • Product
  • Fulfilment centre

These attributes should help you diagnose the problem later

6

Cost of returns

Total cost of returns

7

No. of exchanges

Total number of exchanges

Remember to segment by:

  • Customer segment
  • Location
  • Product
  • Fulfilment centre

These attributes should help you diagnose the problem later

8

Cost of exchanges

Total cost of exchanges

9

No. of backorders

Total number of orders in the backlog left unfulfilled

10

On-time Shipping Rate

Percentage of orders that get fulfilled on time

11

Lull time for trucks

Percentage of time that trucks are not in use

18. Manufacturing

No.

Name

Description

1

Cycle Time

Represents the average time taken to manufacture a single product. From start to finish.

2

Equipment productivity

Represents the percentage uptime that the manufacturing equipment is in use

3

Labour productivity

Represents the percentage uptime that labour is active

4

Yield

Represents the number of products that can be produced each cycle