Category: Sales Managers

CPG Jargon Buster Master Article

by adminin ACV, Average Items Carried, Brand Manager, CPG, CPG Jargon Buster, decision-making, Explorazor, FMCG, Nielsen, Nielsen Database, sales, Sales Managers, Sales per Million, Total Distribution Points, VelocityLeave a Comment on 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.

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PRODUCT TOUR

The Painful Process of Making a Data-Backed Decision

by adminin Brand Managers, decision-making, sales, Sales Managers

Let’s explore the decision-making process that a business user, say a Sales Manager or a Brand Manager, goes through. The aim would be to identify the challenges they face during this process and explore a very relevant solution for that.

We’ll do this step-wise:

  1. The challenge is presented

Either the business user is actively analyzing a piece of information, looking for solutions, or a challenge presents itself, which s/he starts solving. 

For example, he observes that Total Sales in Region X has shown degrowth.

  1. Possible reasons are explored

Identifying the problem is the first step toward formulating a solution. Total Sales has shown degrowth, the first question that is raised is ‘Why’. For that, the Sales manager will look at whether his primary and secondary sales targets are being achieved or not.  

The Brand Manager, or the Data Manager, as they are called in certain roles, will go a little further to investigate other aspects that might help arrive at the reasons for the degrowth.

Some of the other areas that will be scrutinized are:

a. Market Data

First off, one sees how the market is performing. If my brand is down by 2%, but the entire category is down by 4%, then there’s no real cause for worry. For example, sales of ice cream are bound to go down during the monsoon season. 

Market data would also include the tracking, measurement and evaluation of marketing spends. It also includes surveying competition’s activities and correlating it to the change in sales of our own brand. 

b. Efforts Data

Are my people meeting the wholesalers as they were doing previously? In the case of the pharmaceutical industry, medical representatives meet doctors and provide them with promotional material or, say, medications, and follow a similar course of action with chemists as well. Another sub-component of the Efforts data would be to see if the team is following previously successful strategies or not.

c. Consumer Insights & Brand Health 

Datasets like Kantar provide valuable insights into customer behavior and psyche, how they can be expected to react to a particular promotional strategy, etc. It shares concrete data like Average Trip Size of a customer in a particular store.

Long-term focus areas such brand health, which is quite similar to brand perception, will also be kept a tab on.

3. Proactive or corrective action is undertaken 

Once the reason is pinpointed, managers can then begin setting up and rolling out implementation strategies.  

But before they can do that..

THE ISSUE OF WORKING WITH MULTIPLE DATASETS

Notice that we described the multiple datasets that managers work on in quite some detail. 

This is to bring your focus to the issues concerning working on multiple datasets 

  1. At the very least, time is wasted 
  2. The communication to acquire such datasets is another challenge in itself
  3. Cleansing and merging the datasets is also a painstaking process

By the time the manager gets around to testing assumptions and conducting analysis, much of time has been wasted and the effort that should have gone into analysis and exploration is allocated just readying the dataset for analysis and exploration.

SOLVING THE ISSUE OF WORKING WITH MULTIPLE DATASETS

Explorazor is a data exploration and analysis tool that has been designed to specifically solve this issue for Brand & Sales teams. On Explorazor, managers see a single, integrated view of all their datasets which they can query using simple keywords and obtain data pivots in seconds. It literally puts all of the data under a single roof and makes it available at the fingertips of managers. All of the data would be stored on cloud, accessible via browser.

Of course, Explorazor is not entirely utopian; not every user will obtain access to all the datasets a company possesses. Rather, customized projects will provide access to all relevant datasets that a user needs for his daily, weekly or monthly activities.

For more details, you can visit the Explorazor website, and if you are interested in knowing more in detail, visit Explorazor docs.

  1. Preparing visualizations and presenting the decision

To reiterate, the first three steps in the decision-making process were:

  1. Looking for a piece of information, or a challenge being presented 
  2. Exploration of possible reasons, which includes analyzing multiple datasets
  3. Undertaking proactive or corrective actions

The findings are then finally translated into a narrative to be presented to the management and/or the team. As a manager, you know what’s best for your company, and the all-important task of communicating forward-looking insights impactfully is best left to you. Explorazor seeks to remove the load of tasks that senior managers should not spend, or dare we say, waste their time in. 

To speed up hypothesis testing, provide independence in ad-hoc analysis, and enable managers to spend more and more of their time on tasks that add value to their brands and companies is what Explorazor is built for. 

To understand Explorazor better, contact us at support@vphrase.com and we’ll set up a short Explorazor demo for you. If you can’t find the time for that, we’ll be happy to share a one-pager with you for your reading. Enjoy!

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