CPCA & CPCM Exams Flashcards
Get Certified
Originally published by ECR sub-committee in US late 1980s
8 Step Category Management Process
Distinctly - measurable and manageable grouping of products that are interrelated and substitutable
Category
Collaborative effort between trading partners (retailers and manufacturers) to optimize the development of total category volume and profit
Category Management Process
Assigned to categories that are high impulse purchases and low volume generators for retailer
Convenience Role
Assigned to most important categories for the retailer. Typically targeted to categories with large dollar sales, high household penetration, high purchase frequency
Destination Role
Category Management was formally defined in the US as a result of this joint industry project
ECR (Efficient Consumer Response)
1) Definition
2) Role
3) Assessment
4) Score Card
5) Strategies
6) Tactics
7) Implementation
8) Review
8 Steps in the Category Management Process
Most influential trading partner in Category Management
Retailer
Assigned to categories that are part of the customer’s regular shopping pattern once they have entered the store. Assigned to categories with high household penetration
Routine Role
Assigned to categories that are available at specific times of year or are more predominant at certain times of the year
Seasonal Role
The focal point of category management
Shopper
Total store sales for a store or group of stores
ACV (All-Commodity Volume)
Total cost of the products paid by Retailer to prepare them for sale in the store
COGS (Cost Of Goods Sold)
Manufacturer ships products directly to retail stores
DSD (Direct Store Delivery)
Pricing strategy where there is an everyday low price with little to no feature pricing
EDLP (Every Day Low Price)
An inventory profitability measure commonly used by retailers
GMROI (Gross Margin Return On Investment)
Measurable value that organizations use to evaluate overall success at reaching targets
KPI (Key Performance Indicators)
When the product has no stock left on the shelf, resulting in lost sales and upset shoppers
OOS (Out Of Stock)
A shelving schematic
POG (Planogram)
In-store merchandising materials used to catch shoppers’ attention
POP (Point of Purchase)
Retailers front-end cash register that scans products purchased and stores the information in a database
POS (Point Of Sale)
Tool that captures strengths, weaknesses, opportunities, and threats that tie in with results of a category or business review
SWOT (Strength, Weakness, Opportunity, Threat)
Price of an item that is reduced from it’s everyday regular price, usually some type of promotion
TPR (Temporary Price Reduction)
Retail industry scenario driven by growth of new store formats, new ways to increase consumer spending through new categories and services, new items beyond typical assortment with a channel, and to meet a changing shopper
Blurred Channel
Channel with typically lower operating expenses and less overhead (with primarily large size offerings) so prices are generally lower
Club Channel
Channel that offer low prices on certain items and in some categories with a wide variety of merchandise but a limited assortment. Attracts all income levels with their $1 price points
Dollar Stores
Walmart was one of the first retailers to launch this initiative to create a value proposition for shoppers
EDLP (Every Day Low Price)
Channel with typically higher operating expenses than other channels, resulting in lower margins and/or higher prices than other channels
Grocery Channel
A shopper’s primary concerns that drive their shopper purchase decisions
Quality, Value, Convenience
The phenomenon when a product is segmented and transformed into niche products in order to offer Shoppers more apparent choices to drive up the sales of the product
SKU/Item Proliferation (Rapid Increase In Numbers)
A solution for Retailers to address differences related to size, geography, and Shopper needs
Store Clustering
The most important retail in-store factors that are affected by increased product assortment
Variety, placement, and space
A price that reflects units sold with and without any type of discount
Average Price
Retail pricing strategy to balance lower margins required on more price-sensitive products with higher margin prodcts to achieve category margin objectives
Blended Margin Strategy
((Non-promoted price - promoted price) / Non-promoted price)*100
Level Of Discount
Products whose sales are not affected with an increase in price have this
Low Elasticity
A price that reflects the average product price in retail stores when any merchandising condition (including feature, display, price reduction) was in effect
Promoted price
EDLP, High/Low, Frequent shopper pricing, Hybrid Pricing
Retail Pricing Strategies
The most valuable data source to help Retailers set item level pricing
Weekly point of sales data
Modelled or estimated sales results based on algorithms
Baseline and Incremental sales
The normal expected sales volume in the absence of any promotion
Baseline sales
Establishes if there is a relationship between unit sales and price
Correlation analysis
The retail practice of marketing or displaying products from different categories together to generate additional revenue for the store
Cross Merchandising
Key drivers of incremental sales volume
Display, TPR, Promotions
An analysis that compares $ share to tactical shares for a given product group (e.g. share of shelf, share of items,share of promotion, share of display)
Fair Share Analysis
The activity referred to when a product is promoted in a weekly newspaper or in store circular or flyer
A feature or promotion
A measure used to indicate an increase in product sales volume due to some type of tactical activity
Lift
Refers to sales generated during the presence of any type of promotional activity (feature, display, TPR)
Promoted Sales
Lift, incremental sales, subsidized volume, profit
Promotional Effectiveness Measures
Quantifies the impact of pricing changes on volume
Regression analysis
The difference between incremental sales and promoted sales
Subsidized volume
A measure used to assess product availability in retail outlets based on weighted distribution of stores
ACV Distribution
The opposite effect of incremental contribution
Cannibalization
A combination of several metrics, such as dollar sales and unit sales, which provide an overview of a product’s true impact on a category
Combined performance index
Sales growth strategy where a retailer operates in one or only a few segments of the larger market, following a niche strategy with one brand
Concentrated market coverage strategy
Sales growth strategy where several niche markets or population segments are targeted with different products for each niche or segment
Differentiated Market Coverage Strategy
Helps to define which products to carry in assortment analysis and rules out products that are not substitutable
Focus Market
Numerically identifies the benefit of adding a particular item to a particular category assortment based on cannibalization
Incremental contribution
Gives a visual representation of SKU rationalization using market coverage results based on cumulative % of sales plotted on a line chart. On average, 20% of category items generate 80% of category sales
Pareto Analysis
Assortment changes should be incorporated into these once the changes have been approved
Planograms
First to market, market coverage objectives, broad assortment, private label strategy
Retail Assortment Strategies
The process of identifying poor performance items that should be deleted from the product assortment to improve category sales
SKU Rationalization
A measure used to assess product availability in retail outlets based on the number of retail outlets (store count) that carry an item
% stores carrying
A sales growth strategy where a retailer ignores segmentation variables and go after the whole market with one brand
Undifferentiated market coverage strategy
Includes promotional in-store and circular activity gathered by field staff used to compile syndicated scanner data
Audit data
The two data sources that comprise syndicated scanner data
Audit data and scanner data
The projected sales in a given time period that would have sold without any type of promotion
Baseline sales
Product distribution, new items, regular price, shelf space
Baseline sales drivers
An analytic approach that starts at a topline level (e.g. total category, total market) and then drill down into lower levels (e.g. segments, channels, different time periods)
Drilling down
Display, flyer/promotion activity, TPR or price reductions
Incremental sales drivers
Region of the USA that has the lowest syndicated data coverage versus other regions
Northwest Region
The most important source of data used in category management
Retail scanned data
Item $ sales / distribution (weighted or % of stores carrying). Equalizes sales between items with different levels of distribution and highlights distribution opportunities
Sales per point of distribution
( Distribution target x $ SPPD for Item A) - $ sales for Item A
Sales per point of distribution opportunity gap
Point-of-sale data gathered from Retailers used to compile syndicated scanner data
Scanner Data
Total product group category $ share / # of items in product group. Calculates the average productivity across product groups.
Share per SKU or share per item
Sales data compiled across multiple Retailers across a variety of distribution channels
Syndicated Scanner Data
Areas to drill into to get a better understanding of data results
Time, product, geography, and measures
Baseline Sales + Incremental Sales
Total Sales
How much the consumer spends on their total basket when a particular product is included in their purchase
Average Basket Ring or Market Basket Analysis
Purchase frequency x $ per Purchase
Buying Rate Formula
An important shopper group to understand because they represent a small % of buyers but usually make up a majority of the sales volume
Heavy Buyers
The percentage of households that purchased a product group (brand or category)
Household Penetration
Loss of volume to other channels or retailers
Leakage
A shopper group that usually doesn’t purchase as much ($) or as frequently as Heavy Buyers
Light Buyers
Product loyalty, retailer loyalty, consumer purchase behavior, consumer demographics
Panel data can measure…
Total product group buyers / total category buyers
Penetration formula
The number of times the product group has been purchased over the time period
Purchase Frequency
Measures how a product group satisfies a consumer’s category needs. Also referred to as product loyalty
Share of Requirements or Share of Wallet
Gathered from statistically reliable panels of consuming households that scan or record their purchases and for which they are compensated
Syndicated Panel Data
of Buyers x $ Spent Per Household
Total Sales Formula
An activity where data is checked for discrepancies and errors before starting retail point of sale data analysis
Data Cleansing
- Calculate the change in sales between the base and test period for both the control store and test store groups
- Compare changes in the test store group to the control store group
Steps to Analyze In-Store Test
A grouping of stores with similar characteristics based on the customers’ demographics, lifestyle, and other factors.
Store Clustering
A common product link between retail POS data and syndicated POS data that excludes store brand/private label items that are not reported in syndicated data
UPC Code
A method to more accurately identify overhead costs when they are not tied to direct labor
ABC (Activity-Based Costing)
Calculated by summing up the total of all category sales within a geography (market, channel, or retailer)
ACV (All-Commodity Volume)
Goods Available For Sale - Ending Inventory
Costs of Goods Sold
A comparison between the % of households in specific demographics in a region vs a specific store. Identifies stores which skew high in certain demographic profiles
Demand Index
($ Sales / ACV Distribution) x (ACV Distribution Target - ACV Distribution)
Dollar Opportunity Gap Formula
Annual Profit / Average Inventory Cost
GMROI Formula
Beginning Inventory + Cost of Goods Purchased
Goods Available for Sale
(Retail Price - Cost) / Retail Price
Gross Margin %
Total units per year / (# of facings * units per facing)
Inventory Turns Formula
Annual Cost of Goods Sold / Average Inventory Level
Inventory Turns Formula
(Retail Price - Unit Cost) / Unit Cost
Markup % Formula
A comparison between the % ACV sales in a specific product group within a market and the % of households within a market
Product Demand Index (Market)
Total # of trips / # of buying households
Purchase Frequency Formula
A comparison between a store’s sales with the chain’s average sales
Sales Index
Store Sales / Store ACV $
Sales Index Formula
Brand $ Sales / Category $ Sales
Share of Category Sales Formula
Measures the extent to which a product satisfies a consumer’s requirements in a category
“Share of Requirements” or “Share of Wallet”
Data source that can be used to create demographic profiles for products and retailers, measure product demand by store and zip code, and identify leisure activities for target consumers
Geodemographic data
Data source that includes information collected by consumers who scan their purchases and are then compiled into syndicated data source
Household Panel Data
Information collected by observing consumers while they shop followed by asking them a defined set of questions
In-store Shopper Research
Provides the information about other products that are purchased at the same time as a specific category
Market basket analysis
Research that includes in-depth surveys, focus groups, observational, video monitoring, and ethnographic research
Qualitative and quantitative research
Internal sales data collected by retailers through their scanned sales systems
Retailer Point-of-Sale Data
Data source that is gathered from the transactions of multiple retailers that is compiled into a database to create market data
Syndicated scanner data
analyzes the changing views of a single group of consumers, making it an effective tool for market research. Provides ongoing research surveys, often conducted online, through a series of questions to a representative sample of consumers
Tracking studies
A common identifier across the data sets
MOST important requirement to allow you to analyze across multiple data sets
The 3 Dimensions along which Data Cube describes market facts for a specific data measure
Product, Geography, Time Period
The BEST analysis that you can perform through purchase frequency and shopping basket information in retail point of sale data
Shopper Insight Analysis
Retail measurement data (scanned sales data) that is “rolled up” to include and reflect channel and market data
Syndicated Scanner Data
Measures the percentage of category buyers lost to other stores
Buyer conversion analysis
The loss of $ volume in a category stemming from a retailer’s current shopper purchasing the same category in a competitive retailer
Category leakage
Information is gathered from a panel of consumers who record their purchases over a period of time and compiled into this data source
Consumer panel data
Represent a small percentage of buyers but usually make up a majority of the sales volume
Heavy buyers
Measures the % of dollars a retailer is capturing in a category, and the percentage it’s losing to competition
Leakage analysis
Assesses the size and contents of a shopper’s total purchases to identify affinities or related purchases over time
Market basket analysis
Total # of trips / # of buying households
Purchase Frequency Formula
Is the most important source of data used in category management work
Retailer scanned sales data
Brand $ sales / category $ sales
Share of category sales formula
A measure that is based on shopper’s perceived deals
% sold on deal
A measure that is based on the actual volume sold on a temporary price reduction
% sold on TPR
The foundational data element used to organize and measure product performance in household panels. They are the common product field that ties panel data together
UPC Codes
An area surrounding a store based on the distance a consumer is willing to drive for a type of product that the store can effectively reach and potentially influence
Consumer trade area or market area
A comparison between the % of households in specific demographics in a region vs a specific store. Identifies stores which skew high in certain demographic profiles at any level of product grouping
Demand Index
Analyzing the way consumer behavior and lifestyle interact
Most important element of demographic behavioral data analysis
A comparison between the % ACV sales in a specific product group within a market and the % of households within a market
Product Demand Index (Market)
A comparison between a store’s sales with the chain’s average sales
Sales Index
Store Sales / Store ACV $
Sales Index Formula
Attributes that can affect differences across stores and should be considered by retailers when clustering their stores
Store size, geography and climate, consumer purchase behavior and consumer demographics
Store volume (units and dollars), Shopper demographics, consumer purchase behavior, Geography/location
Attributes customarily used to create store clusters
The MOST important reason for category managers to use store level data in their category analysis
Compare store performance across a banner
A retail scanned sales data component that allows retailers to track organic growth in their business (or all stores excluding new store openings)
Comp Stores
($ Sales / ACV distribution) x (ACV distribution target - ACV distribution)
Dollar Opportunity Gap Formula
The measurement that can be MOST influenced by ghost inventory, visual out of stocks, and location of store inventory in the store
In Stock/Out of Stock
Look at sales before ad during the test period for both the control and test stores, and then you need to compare the results of each for the best analysis
In-Store test results analysis
Includes information on Dollar and Unit sales, profit, transactional, basket and time aggregates
Retail Scanned Sales Data
$ Sales / ACV distribution
Sales per Point of Distribution Formula
BEST approach to take when choosing stores for an in-store test
Selecting test stores that are similar to the control stores
Analytics available in retailer scanned sales data
Trends, sales and profit analysis, shopper insights
Best tool to help design a shelf layout that maximize shopper friendliness based on shopper needs
Consumer decision tree
Indicates how many days of stock is available before it runs out
Days of supply
Do I need to have an item in each segment of a category?
How many different items do I need to satisfy a particular shopper demand?
How can I optimize volume in key segments?
Can I reduce the number of items in a given segment thereby reducing my inventory costs without risking a loss in overall category demand?
Important considerations when establishing a planogram based on a consumer decision tree
Total units per year / (# of facings x units per facing)
Inventory turns
The process through which, once a new planogram is implemented by a retailer, the category management team conducts a direct comparison between the metrics for the past planogram and the new one, and then continues to make comparisons over time as new sales data is collected
Post-reset tracking
Balance between minimizing days of supply and maximizing stock availability
Space management inventory objective
The MOST important factors that retailers need to consider when determining product assortment and considering how it affects the shelf
Variety of items and shelf capacity
Transactional data analysis, inventory balancing, seasonality evaluation
Analytics enabled through retailer’s POS data
A way for retailers to test out new ideas without committing to all stores in a real world environment
Control store test
A means to check for and clean out discrepancies and errors in item level data before analysis is completed
Data Cleansing
Calculate the sales between the pre-test and test periods for both the control store group and the test store group. Then calculate and compare the changes between time periods for both test and control store groups.
Procedure for analyzing results of an in-store test
Increased resource capacity requirements, Increased data storage requirements, increased analytical horsepower / computer capability, Increased access to detailed demographics psychographics
Requirements to establish effective retail store clusters
The grouping of stores based on similar characteristics or attributes beyond geography including store size and more importantly shopper characteristics
Store Clustering
- Reach
- Response
- Quality
- Frequency
4 BEST drivers to consider when assessing display performance
- Display
- Feature
- Feature and display
- Price Reduction
4 primary merchandising conditions that can influence promotional results
- Define the problem
- Determine the reasons for the problem
- Determine the underlying conditions that give rise to the reason for the problem
- Design a solution
- Implement the solution
- Evaluate the success of the solution
6 Steps of Root Cause Analytics
Pricing term that identifies the true cost (and therefore profitability) of each activity in the sales of a product
Activity Based Costing (ABC)
Calculated by summing up the total of all category sales within a geography (market, channel, or retailer), to get a “Total ACV” number
ACV (All-Commodity Volume)
Estimated product sales expected to generate during a non-promoted week
Base sales
A root cause analysis technique used to record the actions and conditions for a given consequence to occur
Causal factor tree
To help identify, explore, and display possible causes realted to a problem or condition. They help to look for relationships between actions or events such that one or more are the result of the other or others
Cause and effect diagram
Consider the strengths and weaknesses of each data resource, use relative comparisons vs absolute comparisons, use the appropriate time periods for evaluation
Considerations when combining data resources
Give an external perspective of the total market that consumers are shopping in. Shoppers shop the entire market - not within a specific channel. By looking at the bigger perspective it helps retailers better understand their strengths and opportunities
External retail benchmarks
Share of features by product group / dollar share by product group within a category
Fair share of features
Product sales that would not have sold without the promotion
Incremental sales
Indicates if the retailer’s category share is higher or lower than it’s ACV share, but doesn’t imply over - or under - development
Index vs ACV
A process designed for use in investigating and categorizing the root causes o events that involves data collection, cause charting, root cause identification and recommendation generation and implementation and helps identify what, how and why something happened, thus preventing recurrence
Root cause analytics
Define the problem
Step #1 of Root Cause Analytics
Determine the reasons for the problem
Step #2 of Root Cause Analytics
Determine the underlying conditions that give rise to the reason for the problem
Step #3 of Root Cause Analytics
Design a solution
Step #4 of Root Cause Analytics
Implement the solution
Step #5 of Root Cause Analytics
Evaluate the success of the solution
Step #6 of Root Cause Analytics
Should identify areas of opportunity (including potential volume) that takes you from “what is” to “what could be”. Should include dimensions like: category trends, economic trends, category tactics, and competitive activity
Category health assessment
Should consider each one of these perspectives: Consumer, Category, Company, Competition
Category review
Traffic building, transaction building, turf defending, excitement creating, image enhancing, cash genera and profit generating
Category strategies
An approach to analyzing large amounts of data with focus on the correct business issues, opportunities and hypotheses starting at a big perspective and then moving to more detailed information
Data drilldown
An approach to help you to understand where your tactical support is category share across brands and segments
Fair Share Analysis
A strategy that will help to build sales because more buyers will purchase the category at a specific Retailer
Improve buyer conversion
An approach that helps to identify the $ volume potential based on benchmarks within a category
Opportunity gap analysis
An approach that helps to determine the best regular or TPR price for a specific item
Regression analysis
Goods Available For Sale - Ending Inventory
Cost of Goods Sold
An efficient system that allows products to flow faster and with less handling expenses because the product does not have to be put away in the warehouse
Cross Docking
Measure on the retailer income statement that captures items like merchandise inventory among others
Current assets
Annual cost of Goods Sold / Average Inventory Level
Goods available for sale
Sales - Cost of Goods Sold (COGS)
Gross Margin $ Formula
(Retail price - Cost) / Retail Price
Gross Margin % Formula
This doesn’t always equate to high gross margin $ generations
High gross margin %
Annual cost of Goods sold / Average Inventory Level
Inventory Turns formula
1 - (Reduced Price / Original Price)
Markdown % formula
(Retail Price - Unit Cost) / Unit Cost
Markup % formula
Measure on the retailer income statement that includes items as “employee costs, warehouse and store costs” among others
Operating Expenses
Measure on the retailer income statement that captures items like cash discounts from manufacturers among others
Other Income
Measure on the retailer income statement that should be evaluated based on budgets, sales from year ago or other previous period, etc.
Sales
Measure on the retail income statement that is subtracted from sales and is the lost sales from an external event (e.g. theft)
Shrink
A method to more accurately identify overhead costs when they are not tied to direct labor
Activity Based Costing (ABC)
A measure used to assess product availability in retail outlets based on weighted distribution of stores
ACV distribution
The intorduction of a new product in an existing brand but in a new/different category
Brand extension
When a new item causes switching from one item to another or one category to another, it cannibalizes other volume
Cannibalization
Annual Profit / Average Inventory Cost
GMROI Formula
Numerically identifies the benefit of adding a particular item to a particular category assortment based on cannibalization
Incremental Contribution
Is the best data source to understand purchase frequency across items for a Shopper
Loyalty card data
Helps determine the target number of items to carry in a category
Pareto Curve analysis
The introduction of a new product in an existing brand and existing category with new/different features (e.g. a different size)
Product line extension
First to market, market coverage objectives, broad assortment, private label strategy
Retail assortment strategies
1st step in the Category Management Process
Definition
2nd step in the Category Management Process
Role
3rd step in the Category Management Process
Assessment
4th step in the Category Management Process
Score Card
5th step in the Category Management Process
Strategies
6th step in the Category Management Process
Tactics
7th step in the Category Management Process
Implementation
8th step in the Category Management Process
Review
