CPG Jargon Buster Master Article

Hello, and welcome to the knowledge hub that is the CPG Jargon Buster Master Article!

Here you will find direct links to many relevant jargon/concepts in the CPG Industry. Each term is explained in brief below, with a link to the detailed blog at the end of it. 

We keep adding more jargon as we write about them, so be sure to bookmark this page and keep learning! We’re also creating a FANTASTIC CPG-specific product for optimal and super-easy data exploration – you might want to check Explorazor out!

Till now, we have covered 

  1. ACV

ACV stands for All Commodity Volume. It is used in the calculation of %ACV (obviously, but the term ‘ACV’ is often used interchangeably with %ACV, so one needs to be mindful of that). 

ACV is nothing but the total monetary sales of a store. Assessing the ACV of a retailer helps suppliers know which outlet presents the best sales potential based on its business health. 

Learn how to calculate ACV using Nielsen data and how ACV relates to %ACV 

Read more: What is ACV in CPG?


  1. %ACV 

A more comprehensive blog than the ACV blog above, %ACV, or %ACV Distribution, helps managers understand the quality of their distribution networks. You might wonder why a product is not selling well in a region despite being apparently well-distributed there. A deep analysis of metrics such as %ACV will help you resolve that. 

Read the blog to understand how to calculate %ACV, and the 5 points to consider when performing the calculations:

Read more: What is %ACV?


  1. Velocity

Velocity is another metric to study distribution. Velocity factors the rate at which products move off the store shelves once they are placed there. 

Managers can take charge of sales by utilizing velocity fully, and understanding the two major velocity measures – Sales per Point of Distribution (SPPD) and Sales per Million. Refer to the blog to learn what these measures are, with examples to help. As Sales per Million is a complex concept we’ve also explained it separately in another blog:

Read more: ALL About Velocity / Sales Rate in CPG


  1. Average Items Carried

This is the average number of items that a retailer carries – be it of a segment, brand, category, etc. For example, suppose that Brand X has 5 products/items under its name. Average items Carried would be from a retailer’s perspective – he could be carrying 2 products, or 2.5 products, or 4 products of Brand X, on average. 

AIC is one of the 2 components of Total Distribution Points (TDP), the other being %ACV Distribution. The blog explains the relationship between AIC and %ACV with respect to TDP (Total Distribution Points), using examples to simplify. 

Learn why AIC and %ACV are called the width and depth in distribution, and how to calculate AIC in Excel:

Read more: What is ‘Average Items Carried’ and How Does it relate to %ACV?


  1. Total Distribution Points – Basics

Total Distribution Points, or Total Points of Distribution, is again a distribution measure, considering both %ACV and Average items Carried to produce a TDP score that helps Brand Managers understand things like product distribution and store health, and base their future strategies accordingly. 

There’s also a method for managers to know whether their brand is being represented in a fair manner on the retailer’s shelf, using TDP. Learn how to calculate TDP and the special case of TDP if %ACV is 95 or above:

Read More: Basics of Total Distribution Points (TDP) in CPG


  1. Sales per Million

How do you compare two markets where one is many times larger than the other? Does a manager simply say “It’s a smaller market, thus sales are less” and be done with it? Shouldn’t s/he investigate if the products in the smaller market are moving as fast as they are in the larger market? 

Sales per million helps compare across markets, while controlling for distribution. It accounts for the varying Market ACVs and stabilizes them, so managers can find how each product is doing in each market, regardless of market size.

Learn how to calculate Sales per Million with a cross-market comparison example following it:

Read More: Sales per Million 


  1. Panel Data Measures

Nielsen and IRI provide the numbers for these 4 measures, and even those who do not use Nielsen/IRI need to have an understanding of household-level analysis using these 4 measures.

Here are the one-line introductions:

  1. Household Penetration

How many households are buying my product?

  1. Buying Rate

How much is each household buying?

Purchase Frequency and Purchase Size are sub-components of Buying Rate.

  1. Purchase Frequency (Trips per Buyer)

(For each household) How often do they buy my product? 

  1. Purchase Size (Sales per Trip)

(For each household) How much do they buy at one time?

These 4 measures in table format can be used by managers to understand the consumer dynamics that drive the total sales for their product.

Understand these 4 measures in detail, and how they relate to sales:

Read More: Panel Data Measures


  1. Market Basket Analysis

Market Basket Analysis (MBA) is a powerful data mining technique used in the CPG industry to analyze customer purchase behavior and identify relationships between products.

Learn how Market Basket Analysis can help you gain valuable insights into consumer behavior in the CPG industry.

Read more on: Market Basket Analysis


  1. Point of Sale

The consumer packaged goods (CPG) industry is a highly competitive market, and companies need to make informed decisions to stay ahead.

One tool that CPG companies use to make data-driven decisions is Point of Sale (POS) data.

Learn how CPG and Pharma companies optimize their performance using Point of Sale


  1. Customer Segmentation

Customer segmentation, is a technique that helps you divide your audience into distinct groups based on their characteristics, behavior, or preferences.

By doing so, enterprises can tailor your strategies to each segment’s specific needs, improving your chances of success.

Read more on: Customer Segmentation


  1. Price Elasticity of Demand

Price elasticity of demand is calculated by dividing the percentage change in the quantity demanded of a product by the percentage change in the price of that product. 

The resulting number is a measure of how sensitive the quantity of the product demanded is to changes in its price. 

The formula for calculation Price of Elasticity is:

Price Elasticity of Demand = (% Change in Quantity Demanded) / (% Change in Price)

Check out our blog on how CPG companies take decision on the basis of Price Elasticity.

Take an Interactive Product Tour of Explorazor Today!

ALL About Velocity / Sales Rate in CPG

Blog snapshot:

What is velocity, and why is it important to focus on this measure? After learning about ACV and %ACV in our CPG Jargon Buster Series, let’s have a look at what velocity is, its relation to sales and distribution, how to calculate it, and what the two major velocity measures are:

WHAT IS VELOCITY?

While distribution tells you how well your product is distributed in the market, or how widely available it is, velocity tells you well it sells once it is on the shelf. Velocity is the measure you want to look at when judging which product is the best-selling or most preferred by consumers, not distribution.

VELOCITY’S RELATION TO SALES AND DISTRIBUTION

When velocity and distribution are combined, one arrives at retail sales. Thus, 

Sales = Velocity x Distribution.

CALCULATING VELOCITY

The formula to calculate velocity is derived as:

Velocity = Sales ÷ Distribution.

TAKING CHARGE OF SALES THROUGH VELOCITY

It is generally considered that distribution is in the hands of the distributor, and the manufacturer can always follow up with the distributor for better product availability across geographical areas. However, if the product is not moving off the shelf, meaning that velocity is low, then the manufacturer has greater control over being able to change that. 

Let’s understand this through an example, for greater clarity. Suppose 2 products, A and B, are sold equally in a market of 100 stores. Product A has good distribution but low velocity while product B is vice versa. 

The table is as follows:

Market of 100 storesSales =Distribution (x)Velocity
(units)(stores)(units/store)
Product A 600060100
Product B600010060

We see that although distribution for product A is not very impressive, the velocity, or the speed at which the product is selling in these stores, equalizes the sales of Product B, which, although present in all 100 stores, only manages to sell as much as Product A.

In the case of Product B, the manufacturer must have a closer look at his pricing and promotional strategies. Why are people not preferring the product even when it’s available to them in the outlet? Are my competitors outdoing me in those areas, or is their product quality better, or better suited to the audience I am trying to capture? Questions like these need to be raised and answered asap.

Tools like Explorazor and its root-cause analysis function can help a lot here.

TWO MAJOR VELOCITY MEASURES:

The example we described above was one of ‘Sales per Store’. This, however, is not and should not be used in real-world scenarios as store sizes differ, which leads to biases when estimating velocity.

When looking at sales for a single retailer or within a single market, we go with the first velocity measure – Sales Per Point of Distribution, or SPPD.

  1. SPPD = Sales ÷  %ACV Distribution

SPPD is great for understanding where the root cause of a problem lies – is it in the distribution, or the velocity? Let’s understand this further with an example:

Mumbai Market
DistributionVelocity
Brand Sales (in Rupees)%ACV DistributionSPPD
Product 16500080812
Product 295000751267
Product 370000154667
Product 480000204000

Above is an item level report for an individual market. We see that Products 1 and 2, although impressively distributed, but have poor velocity. The opposite holds true for Products 3 and 4 – %ACV is poor, while velocity is great. 

Note that SPPD works only for one market, be it at the retailer level, the channel, market, or the national level. When comparing across markets, SPPD doesn’t work. Also note that a 100% or close to 100% market distribution will mean that velocity and sales will almost be the same, so managers can overlook velocity in favour of focusing on sales only.

  1. Sales per Million 

In a cross-market comparison, certain markets are naturally bigger than others. In other words, the ACV of a Large Market, call it Market L, is bigger than the ACV of a smaller market, Market S.  

This is where Sales per million comes in, because it accounts for the ACV of each individual market in the denominator. 

Sales per Million is calculated as: 

Sales 

÷ 

%ACV distribution X (Market’s ACV ÷ 10,00,000)

Note that ‘Sales ÷ %ACV Distribution’ is nothing but the formula for SPPD. Market ACV, as explained above, has to be taken in the denominator to account for the size difference in ACV.

Regarding the ‘in millions’, Market ACVs are large numbers, and we simply ease our calculations by denoting them in millions.

Let’s compare Mumbai, a bigger market, to Pune, which is 3 times smaller:

Mumbai vs Pune market comparison with respect to Sales per Million
Mumbai vs Pune market comparison

Clearly, Pune’s numbers are lesser than Mumbai’s because of the size discrepancy. In comes Sales per Million to level that out.

Example of how we calculated Sales per Million (in the below table) using information from the above table:

For Product 1, Mumbai –

Sales = 65,000

%ACV Distribution = 80

Market ACV Size = 120 million

Sales per Million 

= 65000 ÷ [(80/100) x (120 million / 1 million) 

= 65000 ÷ [0.80 x (120)]

= 677

Similarly for all.

Mumbai vs Pune Velocity comparison in perspective of Sales per Million

Notice that Pune’s sales compared to Mumbai

  • For Product 1, is almost equal
  • For Product 2, not far off
  • For Products 3 and 4, is miserably low

Without the Sales per Million calculation, Pune as a whole would have been swept under the rug under the guise of ‘It’s a small city, hence our products don’t do well there’. But conducting the above analysis clearly demonstrates that Products 3 and 4 need a lot of attention if they are to sell in Pune. 

Some Notes: 

  1. Sales per Million can be used within 1 market as well, if you want to keep your velocity measures uniform throughout. SPPD is easier to use than Sales per Million, hence people prefer that too
  2. Velocity is uber-important. Hope we didn’t fail to convey that!

Take an Interactive Product Tour of Explorazor today!

Modeling Basic FMCG KPIs in Excel

This blog will introduce you to how Brand Managers model basic FMCG KPIs in Excel.

There are a lot of articles that touch upon the life of a Brand Manager and the various responsibilities they shoulder. Here we will put a microscope on just one of the numerous calculations that Brand Managers undertake, and learn how they find business improvement areas through data analysis.

If you are a Brand Manager, we recommend you skip to the end of this blog to ‘Basic FMCG Modeling Made Easy’ or read ‘Complementing Excel – How Brand Managers can Simplify Data Exploration and Analysis’.

Let us understand how to obtain Gross Margin, Net Margin, and Operational Profit. Arriving at these numbers helps Brand Managers analyze where they are losing their margin – is it at the production level, is it the cost of sales and marketing, or is it the head office costs? Brand Managers thus have a sense of direction to initiate further data exploration and make optimal, data-driven decisions.

Let’s begin:

Part 1 – Obtaining Net Margin

  1. Unit Gross Margin 

Unit Gross Margin Depends on two things – 

  1. The average price we are getting from the middlemen, or if we are directly selling to the customers, from them 
  2. Subtracting the unit production cost from this average price 

So Unit Gross Margin = Avg product price (say Rs. 70) minus its production cost (say Rs. 40) = Rs. 30

Note: The unit production cost is again dependent on two things – 

a. The total fixed cost divided by the total quantity produced, plus 

b. The unit variable cost

There are further sub-calculations in each component. For example, Total Fixed Cost (FC) includes salaries to be paid, which is typically generated as: taking the number of full-time employees or full-time equivalents (FTE), setting an average salary per FTE, and assuming some social securities as a percentage of the salary. The salary excludes the bonus earned by the employee.

  1. Gross Margin 

Once we have the unit gross margin and the total number of products sold, we get the Gross Margin easily enough.

Gross Margin = Unit Gross Margin x Total Products Sold

The Gross Margin will be calculated for various channels we are selling through, and a year-on-year, or month-on-month record will be maintained too.

As you can see, such calculations require Brand Managers to be detail-oriented, organized, knowledgeable and possess a deft hand at Excel.  

  1. Sales and Marketing Costs 

Obtaining the Gross Margin has covered the Production Cost. We have yet to factor in the sales and marketing costs, so let’s do that. Sales and marketing costs depend on the size of a brand’s market share. A bigger market share means we are selling more, which means that the costs attached to sales and marketing per unit is lesser. 

Marketing elements would include –

  • Social Media
  • TV ads (computed as the number of campaigns multiplied by the cost of 1 campaign)
  • Outdoor campaigns
  • Loyalty programs
  • Market research
  • Mailing

Components of cost of sales would be –

  • Salaries
  • External services (cars, phones, fuel, etc)
  • Materials & Energy
  • Other related services

These would be calculated for both retail chains where we supply directly as well as for the traditional stores that we reach via wholesalers.

  1. Net Margin

Part 2 – Obtaining Operational Profit

Deducting Head Office costs from the Net Margin gives us the Operational Profit. Head Office costs include –

  • Salaries
  • Material and Utilities
  • Maintenance
  • Rent (for offices and warehouses)
  • Depreciation and amortization of assets

Part 3 – Zooming Out

Converting all numbers into percentages for easier visual view, the final output would be like this:

Basic FMCG Modeling Made Easy

The above KPI modeling and profit calculation require a Brand Manager to continuously switch between multiple tabs and insert various formulae to get the figures. The same process can be augmented through Explorazor, our data exploration tool. 

Explorazor combines and hosts all datasets, for example, market research, internal sales, Nielsen data, etc. in an integrated manner. Brand Managers thus obtain a single view of the entire dataset. From there, they can extract data cuts instantly through a simple search function of using column names as keywords.  

Explorazor also allows 

  • Visualizing pivots as charts
  • Pinning the charts to a pinboard, and 
  • Downloading them as CSV files

Moreover, all data resides on servers and is accessible via a browser. Laptops are thus relieved from the burden of processing huge datasets. Brand Managers are further liberated when their reliance on BI teams is reduced. The acceleration of ad-hoc exploration is experienced immediately with Explorazor.

Explorazor is built for large enterprises, with single sign-on, row and column level security, data encryption, and on-cloud and on-premise availability.

Do you want to see other features added to Explorazor? Write to us at sales@vphrase.com. If you want to see the product in action, take an interactive Product Tour.

6 Challenges Faced by Brand Managers when Marketing and Selling FMCG Products

The aim of this blog is to help readers understand and appreciate the various challenges that Brand Managers in the FMCG industry tackle on a daily basis when marketing and/or selling FMCG products. Let’s start with a quick introduction, followed by a swift overview of the challenges:

Investopedia defines FMCG as follows:
“Fast-moving consumer goods are products that sell quickly at relatively low cost. These goods are also called consumer packaged goods. FMCGs have a short shelf life because of
– High consumer demand (e.g., soft drinks and confections) or
– Because they are perishable (e.g., meat, dairy products, and baked goods)
These goods are purchased frequently, consumed rapidly, priced low, and sold in large quantities. They also have a high turnover when they’re on the shelf at the store.”

6 Common Challenges Brand Managers Face When Marketing and/or Selling FMCG Branded Products

  1. How to Create Brand Architecture and Establish Brand Awareness

Brand awareness choices are hard, and each carries its own pros and cons. An example of an initial decision to be made is to either go for an umbrella branding (think LG) or brand each product separately. The Brand Architecture (the science of how brands and sub-brands in a company’s portfolio are related to each other) of P&G pits Tide and Ariel against each other in the market, while both are in-house brands. The advantage of umbrella branding is that the brand credibility overflows from one product to the other – if you trust an LG refrigerator, why not go for an LG air conditioner. The con applies in the same way; if you didn’t like the fridge, you’ll wave the AC goodbye as well.

Branding each product separately involves more capital raising each brand off the ground. There is no parent brand to fire them up and boost their brand reputation. However, one is open to exploring new target markets and experimenting with the price range – there is no need to stick to any previous approach since the connection between the brand and the parent company is not established in the minds of the masses. 

The challenges go much, much deeper than this, and there are many other ways to create a brand architecture, but we hope you got an overview of the tough Brand Architecture choice that Brand Managers make even before proceeding with multi-channel online and offline promotion for Brand Awareness. 

  1. How to Establish Reach

Reach simply means if the product is available everywhere, at all times. Building great brands has to be complemented with a robust logistical infrastructure if the product is to contribute significantly to company revenue consistently. 

Brand Managers work on huge datasets, conducting complex data analysis to set up the distribution flow while managing costs, and optimizing them wherever possible. A BM in a food-producing company will look at 

  1. The total number of warehouses
  2. The total area of each warehouse 
  3. The number of trucks available to carry the goods to the destination
  4. The holding capacity of each truck and its expected fuel usage
  5. The wages of the drivers and the cost of fuel 
  6. Truck maintenance cost 
  7. Other factors such as optimal routes and seasonality also come into play. Bear in mind that most of these calculations are derived through exhaustive data exploration; only some are readily available 

Once the numerical values are achieved, Brand Managers proceed to identify cost and process inefficiencies and look at ways to plug them. 

As Dwight D. Eisenhower, the 34th president of the United States of America, underlining the importance of reach, once said, “You will not find it difficult to prove that battles, campaigns, and even wars have been won or lost primarily because of logistics.”

3. How to Manage Price 

Pricing is a sensitive issue. Underprice, and bottom lines go for a toss. Set too high a margin for the product, and you won’t be able to penetrate into new markets or sustain in the existing ones. 

Pricing in FMCG depends on multiple factors, some of which are explained:

a) The demand for the product in the market and the customer’s willingness to pay for a particular product. The demand/willingness-to-pay price curve helps locate the optimal price peak w.r.t to quantity and w.r.t revenue generation as well. The customer’s willingness to pay is usually based on the price perception a customer has of the product

b) Existing market price – that of competition. This is one of the safest approaches to take when launching a new product in the market, for obvious reasons

c) The approach of the company also plays a part. Apple uses a price skimming strategy where it initially charges high but adopts lower prices as competition, say Samsung Galaxy, begins to enter the market. Conversely, we see streaming platforms adopt a price penetration strategy in the Indian market over the past few years, where they charged super-low prices for a wide library of content, and built upwards from there.

d) Managing price across channels is yet another challenge for Brand Managers today. The same product competes against different competitors on different channels, with customer behavior and expectation varying channel-wise too. Determining channel markups and avoiding price conflicts are subject to deep data analysis and exploration.

4. How to Manage Customer Experience and Promotional Strategies across Channels

Just like pricing, channel-wise CX and strategy management are heavily impacted by channels. Retail stores offer a completely different experience to the same customer as compared to a D-Mart or Reliance Smart. Smart cross-channel strategies are important to create a consistent brand experience for the customer, no matter where s/he chooses to interact with the product. Brand Managers create a budget and undertake a marketing campaign covering social media, website, paid ads, and more. It’s the whole marketing exercise that Brand Managers are responsible for.

Such cross-channel strategies go beyond simple brand awareness and product value communication; there are multiple upselling and cross-selling opportunities that need to be exploited.

5. How to Manage Product Life Cycle

Product Life Cycle is understood as the series of stages that a product goes through, right from being introduced to the consumer till it is discontinued. These stages are broadly classified as Introduction, Growth, Maturity, and Decline. Various models such as the Product Life Cycle curve and the BCG Matrix Model are used for product planning and control. Especially in FMCG where products are sold quickly and at lower costs, with limited and continuous distribution, is it very important to understand the stage at which the product lies in its life cycle, and devise a value-creation model for consumers that simultaneously generates revenue for the brand/s.

6. How (and whether) to Diversify Existing Brands

Capsule Case Study: In 2001, ITC found itself in a precarious position when the Government of India introduced stringent measures to curb the usage of cigarettes among the masses. This included the prohibition of the sale of tobacco products to individuals below 18 years and a ban on media advertising. Even surrogate advertising was banned. To diversify from cigarettes, ITC invested a whopping  Rs. 5 billion in non-tobacco-related businesses in 2001, including Branded Packaged Food, Greeting Cards & Gifts, and Lifestyle Retailing. 

A point to note is that ITC’s diversification strategies were operational since the 1970s, and the events in 2001 proved to be an immediate catalyst for ITC’s diversification approach. As the case stands, ITC’s revenue in Q1 2023 in the non-cigarette FMCG segment was Rs. 4,458.71 crore, a sharp rise from Rs. 3,731.40 crores just a year ago. 

Brand Managers play an instrumental role in such change management strategies. This comes from exhaustive data exploration, analyses, hypotheses testing, and an understanding of ground-level realities. From primarily cigarettes to juice, biscuits, noodles and what-have-you, Brand Managers at ITC made sure that diversification strategies led ITC to not just survive, but thrive against many odds. 

Conclusion

There are many other challenges faced by Brand Managers, like managing seasonal demands, improving the efficiency of marketing activities, handling Target Audience lifecycle, looking for ways to spread beyond original Target Groups, and more. Each of these activities demands that Brand Managers have a pragmatic outlook and well-honed data analytical skills. 

We at Explorazor are making the lives of Brand Managers easy by allowing them to obtain one-stop access to their data. On Explorazor, Brand Managers can work on an integrated and standardized dataset that helps extract data cuts in seconds, allowing hypotheses testing at a much faster rate than what BMs are currently accustomed to. The time spent switching between tabs, sheets, and pivots is effectively eliminated, laptops process data much faster, and what’s more, everything is downloadable as CSV for further analysis. There are many other advantages for Brand Managers and Insights teams as well.

If You Want to Brighten a Brand Manager’s Day

Try our Interactive Product Tour.