Nielsen Basics
January 19, 2010
Confidential & Proprietary • Copyright © 2010 The Nielsen Company
Today’s Agenda
• NDA
• Scanner basics
• Form groups
• Discuss key readings take-aways
– Segmentation
Foundation of Analysis:
Retail Measurement Data
Slide 2
Confidential & Proprietary
Copyright © 2008 The Nielsen Company
Nielsen Collects Data from
Retailers & Consumers...
Manufacturer
Data
Retailer
Consumer
…& sells / trades data to the
manufacturer & retailer
Foundation of Analysis:
Retail Measurement Data
Slide 3
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Copyright © 2008 The Nielsen Company
Data Collection & Quality
Source of Information
Retailer Sample
Stores
Foundation of Analysis:
Retail Measurement Data
 Consumer sales
 Retail price
Slide 4
Confidential & Proprietary
Copyright © 2008 The Nielsen Company
Data Collection & Quality
Source of Information
Retailer Sample
Stores
ACNielsen’s Field
Auditors
 Consumer sales
 Retail price
 Display presence
 Custom observations(inventory
levels, facings, linear shelf
measurements, etc.)
Foundation of Analysis:
Retail Measurement Data
Slide 5
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Copyright © 2008 The Nielsen Company
Data Collection & Quality
Source of Information
Retailer Sample
Stores
 Consumer sales (audit or scan)
 Retail price
ACNielsen's Field
Auditors
 Display presence
 Custom observations(inventory
ACNielsen’s
Feature Coders
Foundation of Analysis:
Retail Measurement Data
levels, facings, linear shelf
measurements, etc.)
 All retailer print advertising
 Standardized ABC feature coding
Slide 6
Confidential & Proprietary
Copyright © 2008 The Nielsen Company
We Collect Data Across Multiple Outlets ...
Supermarkets
Gas Convenience
Stores
Mass
Merchandisers
Independent
Food Stores
Supercenters
Chain Convenience
Stores
Foundation of Analysis:
Retail Measurement Data
Slide 7
Drug Stores
Confidential & Proprietary
Copyright © 2008 The Nielsen Company
We Use Two Primary Methods to Collect
Raw Data . . .
In-Store Field Audits
Scanning
and
• Retailers provide sales and price data
– scanned purchases
– all UPC-coded items
– each week for every store included in sample
Foundation of Analysis:
Retail Measurement Data
Slide 8
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Copyright © 2008 The Nielsen Company
Foundation of Analysis –
Retail Measurement Data
Confidential & Proprietary • Copyright © 2010 The Nielsen Company
Goal and Objectives
Provide a foundation for understanding some of
the common differences in facts and help
determine the best choice for an analysis.
• Provide an overall approach to analysis of data
• Provide analysis tips for using facts in an analysis
• Determine the best fact to use in a particular situation
Foundation of Analysis:
Retail Measurement Data
Slide 10
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Copyright © 2008 The Nielsen Company
Accurate Data Consists of Four Parts
Periods
When did it occur?
Markets
Where did it happen…
geography, sale territory or Retailer
Products What item(s), brand(s), flavor(s) am I
interested in?
Facts
What type of issue?
Foundation of Analysis:
Retail Measurement Data
Slide 11
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Copyright © 2008 The Nielsen Company
Periods
Foundation of Analysis:
Retail Measurement Data
Slide 12
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Copyright © 2008 The Nielsen Company
Periods
• Monthly (4 wk) and Weekly hard-coded time periods
reside on all Heinz databases
– Monthly data goes back 5 years
– Weekly data goes back 3 years
– We also have stored several years of hard coded 52 week time
periods
• Custom time periods have also been created for your use
(Latest 4, 12, 24, & 52 Wks, Fiscal Quarters, etc.), built off
of the monthly & weekly periods
– When using the custom time periods, be sure to select the correct
ones for the measure you selected
– Monthly time periods should be used for all ACV-based measures
– Weekly time periods must be used for all promotion-based
measures (including ACV by promo type)
Foundation of Analysis:
Retail Measurement Data
Slide 13
Confidential & Proprietary
Copyright © 2008 The Nielsen Company
Markets
Foundation of Analysis:
Retail Measurement Data
Slide 14
Confidential & Proprietary
Copyright © 2008 The Nielsen Company
ACNielsen Total U.S. 52 SCANTRACK Markets
Salt Lake City/Boise
Denver
Omaha
Des Moines
Minneapolis
Indianapolis
Milwaukee
Grand Rapids
St. Louis
Seattle
Chicago
Cincinnati
Syracuse
Buffalo/Rochester
Detroit
Pittsburgh
Columbus
Portland
Cleveland
Albany
Boston
Hartford/
New Haven
New York
Philadelphia
Baltimore
Washington DC
San Francisco
Richmond
Louisville
Raleigh/Durham
Charlotte
Sacramento
Las Vegas
Los Angeles
San Diego
Phoenix
Nashville
Memphis
West Texas/
New Mexico
Oklahoma City/Tulsa
Atlanta
Birmingham
Houston
Jacksonville
New Orleans/Mobile
Little Rock
Dallas
Kansas City
San Antonio
Tampa
• Note: Markets Defined by Nielsen
Foundation of Analysis:
Retail Measurement Data
Orlando
Miami
Slide 15
Confidential & Proprietary
Copyright © 2008 The Nielsen Company
Example: ACNielsen SCANTRACK®
Atlanta - Food
Tennessee
Clay
South Carolina
Towns
Fannin
Whitfield
Murray
Union
Gilmer
White
Lumpkin
Pickens
Chattooga Gordon
Banks
Dawson
Hall
Forsyth
Floyd
Bartow
Fulton
Cherokee
Alabama
Polk
Jackson
Cherokee
Paulding
Cobb
Barrow
Gwinnett
Cleburne
Oconee
Greene
Douglas Fulton
Rockdale
Morgan
Newton
Clayton
Henry
Carroll
Coweta
Randolph
Oglethorpe
Walton
De Kalb
Haralson
Clarke
Putnam
Fayette
Jasper
Spalding
Heard
Hancock
Butts
Baldwin
Lamar
Pike
Troup
Meriwether
Monroe
Jones
Upson
Chambers
Harris
Talbot
Georgia
Maps are a geographic representation at the time of development and may not reflect recent changes. Please refer to the market profile for county listings.
Foundation of Analysis:
Retail Measurement Data
Slide 16
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Copyright © 2008 The Nielsen Company
Trading Areas & Competitive Markets
• Sample/Census Trading Area: counties it includes are
defined by the particular retailer, data reported is for that
retailer’s stores only
• Competitive Markets: all retailers within the trading area
counties that participate in the sample are included in the
data reported, this includes the trading area particular
retailer sales as well
Foundation of Analysis:
Retail Measurement Data
Slide 17
Confidential & Proprietary
Copyright © 2008 The Nielsen Company
Example: Custom SCANTRACK® Trade Area Cub Minneapolis
Minnesota
Sherburne Isanti
Chisago
Anoka
Washington
Wright
Hennepin Ramsey
St. Croix
Carver
Scott
Dakota
Wisconsin
Maps are a geographic representation at the time of development and may not reflect recent changes. Please refer to the market profile for county listings.
Counties within the circle make up the trading area, all participating retailer stores
falling within those counties make up the data reported for Cub Minneapolis
Foundation of Analysis:
Retail Measurement Data
Slide 18
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Copyright © 2008 The Nielsen Company
Products
Foundation of Analysis:
Retail Measurement Data
Slide 23
Confidential & Proprietary
Copyright © 2008 The Nielsen Company
Product Overview
• Industry Subtotals
– Heinz defined aggregates based on how company views the category
– Only available on custom databases
• Hierarchy
– Nielsen defined department, category and brand aggregates across the
grocery store
– Only available on Strategic Planner
• Characteristics
– Ability to filter through all database UPCs based on unique characteristics
of products
– Ex: size, flavor, meat type, container type
– Characteristic availability differs by category
– Uses: UPC level output, need to create custom aggregates based on
product characteristics when not available via Industry Subtotals
– Available on all databases
Foundation of Analysis:
Retail Measurement Data
Slide 24
Confidential & Proprietary
Copyright © 2008 The Nielsen Company
Facts
Foundation of Analysis:
Retail Measurement Data
Slide 25
Confidential & Proprietary
Copyright © 2008 The Nielsen Company
Why is it important to understand
facts?
• There are a tremendous number
of facts
• The difference between similar
facts is important
• The application drives the
correct choice of fact
• There is never any one correct
fact
• There is always a best fact for
the specific application in
question
Foundation of Analysis:
Retail Measurement Data
Slide 26
Confidential & Proprietary
Copyright © 2008 The Nielsen Company
Analytical Thinking
Certain mathematical tools
and calculations can be very
helpful, but...
knowing how to use them,
more so than actually
deriving them, is most
important.
Foundation of Analysis:
Retail Measurement Data
Slide 27
Confidential & Proprietary
Copyright © 2008 The Nielsen Company
Analysis Tip – The Analytic Path
Most issues can be addressed by drilling down this path
Issue
Base Volume
Distribution
Velocity
% ACV
(Breadth)
# of Items
(Depth)
Incremental Volume
Base Price
Promotion
Support
(Quantity)
Promotion
Effectiveness
(Quality)
Competitive
Activity
Level of
Support
Promo Mix
Promo Price
Other Factors
Price Discount
Competitive Activity
Foundation of Analysis:
Retail Measurement Data
Slide 28
Confidential & Proprietary
Copyright © 2008 The Nielsen Company
Analysis Tip – Prioritize Key Issues
To set up a logical flow and to avoid “analysis paralysis”,
start with the higher level trends then work into the
individual drivers
Total Volume
Trends
Base
vs
Incremen
tal
Recommended Level
of Detail
Distribution
Everyday
Pricing
Base
&
Increme
ntal
Drivers
Dependent upon
level of chg
Level of Detail
Trade
Support
Discount
Category
.
Segments
Manufacturers
Competitive Brands
Your Brand
Foundation of Analysis:
Retail Measurement Data
Slide 29
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Copyright © 2008 The Nielsen Company
Volume and Share
Foundation of Analysis:
Retail Measurement Data
Slide 30
Confidential & Proprietary
Copyright © 2008 The Nielsen Company
Sales Volume
• Measures the amount of product sold over a given time
period
• Sales Dollars – Dollar value of total sales
• Sales Units – Total package sales
• Equivalent Unit Sales – Total sales on an equivalized
basis (pounds, cases, servings, etc.)
• Uses
–Tracking
–Ranking
–Share calculations
–Show a brand’s importance to the category
Foundation of Analysis:
Retail Measurement Data
Slide 31
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Copyright © 2008 The Nielsen Company
Share
• Measures the % of sales
that a product accounts
for
• Influenced by two different
measures
–Brand Sales and
Category Sales
Foundation of Analysis:
Retail Measurement Data
Slide 32
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Copyright © 2008 The Nielsen Company
Share Activity
• What do the following sales
scenarios have in common?
–Brand sales flat, category
declines
–Brand sales up, category
flat
–Brand sales up a lot,
category up a little
Foundation of Analysis:
Retail Measurement Data
Slide 33
Confidential & Proprietary
Copyright © 2008 The Nielsen Company
When to Use – Volume and Share
When concerned with…
Use…
Absolute volume;
Absolute volume change
Unit, Dollar, Eq Sales
volume
Comparing performance relative to the
category or segment
Unit, Dollar, Eq Share
Relating volume to profit;
Comparing across different categories
Dollar Sales
Controlling for disparate package sizes
Equivalized Sales
Absolute item movement;
Comparing sales to shipments
Unit Sales
Foundation of Analysis:
Retail Measurement Data
Slide 34
Confidential & Proprietary
Copyright © 2008 The Nielsen Company
When To Use – Volume Benchmarks
Use Benchmarks to compare category and brand
trends
When concerned with…
Use…
Analyzing category growth in a retailer or channel that is growing
significantly.
Example: Category B grew 16% in Kroger last year. However, since
Kroger grew its total $ sales by 22%, Category B is not keeping pace
with its potential growth in Kroger.
ACV growth /
Total $ Ring
Growth
Analyzing mature categories that have not seen significant innovation
Examples: Categories that are considered “staple” items. If population
is growing at 3% a year, a staple category should see growth just by
maintaining its penetration and buying rate.
Population
Growth
Evaluating categories that have restricted shelf space
Examples: Frozen departments, Checkout-aisle racks, coolers
Department
Growth
Macro consumer trends affecting your category and related categories
Examples: Categories affected by Low Carb diets, Convenience,
Trans-fats
Equivalized
Sales
Foundation of Analysis:
Retail Measurement Data
Slide 35
Confidential & Proprietary
Copyright © 2008 The Nielsen Company
Different Ways to Look at Volume
Promoted
Volume
+
Non-Promoted
Volume
TOTAL VOLUME
Baseline
Volume
Foundation of Analysis:
Retail Measurement Data
+
Incremental
Volume
Slide 36
Confidential & Proprietary
Copyright © 2008 The Nielsen Company
The Benefits of Identifying Promoted Vs.
Non-Promoted Volume
• Provides an indication of what percent of a brand’s
volume came from stores with a promotion.
• Provides an indication of what percent of a
manufacturer’s deal was passed on to the consumer by
the retailer.
• Retailers’ trade promotion execution can be observed.
Foundation of Analysis:
Retail Measurement Data
Slide 37
Confidential & Proprietary
Copyright © 2008 The Nielsen Company
Analysis Tip – Promoted Volume
Promoted volume is useful for determining
how deal reliant a brand is
Brand Share Trend
Total Volume Share Promoted Volume Share
19.7
17.5
13.1
11.2
Our Brand
Competitive Brand
Interpretation:
• Our brand receives a higher share of category promoted volume compared to it’s
share of sales
• Our competitor’s promoted volume share is under-indexed relative to it’s market share
Foundation of Analysis:
Retail Measurement Data
Slide 38
Confidential & Proprietary
Copyright © 2008 The Nielsen Company
Baseline Volume
• Normal expected everyday sales in the absence of any
store-level promotion
• A statistically calculated measure NOT adjusted for FSIs,
print, TV and market-level affects
• Uses
–Track the underlying health of a brand and compare it
to its competition
–Analyze merchandising effectiveness in conjunction
with incremental volume
Foundation of Analysis:
Retail Measurement Data
Slide 39
Confidential & Proprietary
Copyright © 2008 The Nielsen Company
Baseline Calculation
170
Unit Sales
75
75
75
75
Display
Week
week 1
week 2
Foundation of Analysis:
Retail Measurement Data
week 3
week 4
Slide 40
week 5
Confidential & Proprietary
Copyright © 2008 The Nielsen Company
Baseline Calculation
170
In Week 4 Baseline estimate would be
75 units based on pre and post week
sales
Unit Sales
75
75
75
75
75
Display
Week
week 1
week 2
Foundation of Analysis:
Retail Measurement Data
week 3
week 4
Slide 41
week 5
Confidential & Proprietary
Copyright © 2008 The Nielsen Company
Baseline Volume Includes Marketplace
Conditions that Affect Sales of a Product
Baseline
10,000,000
8,000,000
6,000,000
4,000,000
2,000,000
0
Category
Trends
Long-Term
Seasonality
Foundation of Analysis:
Retail Measurement Data
Market-Level
Effects
Slide 42
Brand
Trends
Confidential & Proprietary
Copyright © 2008 The Nielsen Company
Reasons for Total/Baseline Volume
Differences
• Total volume below
baseline
– Competitive activity
– Out of stock
– Seasonal/holiday
• Total volume above
baseline
– Promotions or advertising not
captured by regular means
– Market-level influences (e.g.,
battery sales during a
hurricane in Miami)
Foundation of Analysis:
Retail Measurement Data
Slide 43
Confidential & Proprietary
Copyright © 2008 The Nielsen Company
Incremental Volume
• Represents the additional
predicted volume that results
from in-store promotion
• Calculation:
Total Actual Volume Baseline Volume =
Incremental Volume
Foundation of Analysis:
Retail Measurement Data
Slide 44
Confidential & Proprietary
Copyright © 2008 The Nielsen Company
Incremental Volume
170
In Week 4 Incremental volume
would be 95 units
95
Unit Sales
75
75
75
75
75
Display
Week
week 1
week 2
Foundation of Analysis:
Retail Measurement Data
week 3
week 4
Slide 45
week 5
Confidential & Proprietary
Copyright © 2008 The Nielsen Company
How Can Incremental Volume Be Negative?
• If actual sales are less than expected sales
– Out-of-stocks
– Competitive activity
Actual sales are below
estimated Base – Incremental
is negative 15 units
170
Unit Sales
75
75
75
week 1
week 2
Foundation of Analysis:
Retail Measurement Data
60
week 3
75
75
week 4
week 5
Slide 46
Confidential & Proprietary
Copyright © 2008 The Nielsen Company
Analysis Tip - Base and Incremental Volume
Identifying whether a volume change is coming primarily from
base or incremental volume is a good way to start an analysis
Category Volume Trend
Current 12 Weeks vs. Year Ago
37,500
25,000
Total EQ
Base EQ
Incr EQ
12,500
0
(12,500)
(25,000)
Total FDM ex
WM
Food
Drug
Target
K-Mart
Interpretation:
• For the Food and Drug channels, an increase in Incremental EQ volume is not enough
to offset a decline in Base EQ volume.
• Target is showing significant growth, driven by both base and incremental volume.
Foundation of Analysis:
Retail Measurement Data
Slide 47
Confidential & Proprietary
Copyright © 2008 The Nielsen Company
Analysis Tip - Base and Incremental Volume
Base and Incremental trends will determine potential
strategies
Foundation of Analysis:
Retail Measurement Data
Slide 48
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Copyright © 2008 The Nielsen Company
Base Volume = Non-Promoted Volume
Incremental Volume = Promoted Volume
Base vs. Non-Promoted
• Base volume estimates sales in all stores
• Non-Promoted volume is measured only in stores that
did not run a promotion
–Subset of stores
Incremental vs. Promoted
• Incremental volume estimates additional sales due to
promotions
–Volume sold above the base
• Promoted volume measures all volume sold on deal
Foundation of Analysis:
Retail Measurement Data
Slide 49
Confidential & Proprietary
Copyright © 2008 The Nielsen Company
When to Use – Base, Incremental, Promoted,
Non-Promoted Volume
When concerned with…
Use…
Understanding the underlying health and
trends of a brand
Baseline Volume
Measuring the effectiveness and efficiency of
trade promotions
Incremental Volume
Quantifying the importance of promotional
activity to a brand
Promoted Volume
Quantifying the amount of volume sold in
stores that did not provide trade support
Non-Promoted Volume
Foundation of Analysis:
Retail Measurement Data
Slide 50
Confidential & Proprietary
Copyright © 2008 The Nielsen Company
Sales Volume is influenced by
Seasonality
• Consumers value certain
products more (or less) during
the year.
• Examples of seasonality
– Holidays or “event” driven: 4th of July,
Thanksgiving, Cinco de Mayo, Back
to School, etc.
– Seasonal: BBQ sauce and ice cream
during the summer or soup and
crackers in the winter
Foundation of Analysis:
Retail Measurement Data
Slide 51
Confidential & Proprietary
Copyright © 2008 The Nielsen Company
Seasonality Calculation
1. Divide annual base volume by 52 to get expected weekly sales
(in the absence of seasonality and promotion).
2. Divide actual base weekly volume by expected weekly sales
(just calculated in step 1) to derive a seasonality index
Battery Powered Toothbrushes
Seasonality Index
225
200
TOTAL BASELINE-UNITS
175
150
125
100
75
n
Ja
b
Fe
ar
M
A
pr
ay
M
Foundation of Analysis:
Retail Measurement Data
n
Ju
Ju
l
A
ug
Se
p
ct
O
Slide 52
N
ov
D
ec
Confidential & Proprietary
Copyright © 2008 The Nielsen Company
Analysis Tips - Seasonality
• Use Base Volume when calculating seasonality to negate
promotion-driven volume spikes
• Be careful of moving holidays and market level effects
• In a category that has encountered a lot of activity 2 years
of history should be used
• Compare versus the year-ago period rather than a prior
period
• For categories with extreme seasonality look at “on
season” versus “off season” periods
Foundation of Analysis:
Retail Measurement Data
Slide 53
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Copyright © 2008 The Nielsen Company
ACV Distribution and Velocity
Foundation of Analysis:
Retail Measurement Data
Slide 54
Confidential & Proprietary
Copyright © 2008 The Nielsen Company
Understanding the “Whys” to Changes in
Baseline Volume
Baseline sales can be impacted by different market factors.
Baseline Volume
Distribution
% ACV
(Breadth)
# of Items
Carried
(Depth)
* Non-Nielsen measures
Foundation of Analysis:
Retail Measurement Data
Velocity
Base Price
Seasonality
*Advertising Support
*Manuf. Coupons/FSI’s
*Brand Awareness/Image
*Product Quality
*Weather
*Consumer Promotions
*Sampling
Slide 55
Competitive:
Distribution
Price
Merchandising
*Advertising
*Coupons
Confidential & Proprietary
Copyright © 2008 The Nielsen Company
How Is
Distribution
Foundation of Analysis:
Retail Measurement Data
Measured?
Slide 56
Confidential & Proprietary
Copyright © 2008 The Nielsen Company
ACV Distribution
• ACV Distribution is a measure of
a product’s availability
• Can be measured in terms of
breadth and depth
–Breadth: percent of All
Commodity Volume that carries
your brand
–Depth: number sku’s that are
carried in the stores that sell
your brand
Foundation of Analysis:
Retail Measurement Data
Slide 57
Confidential & Proprietary
Copyright © 2008 The Nielsen Company
What is Distribution?
• Distribution is the measure of the availability of a product.
For an individual item, distribution depends on two basic
variables:
– How many stores stock the item?
– How large are those stores?
Foundation of Analysis:
Retail Measurement Data
Slide 58
Confidential & Proprietary
Copyright © 2008 The Nielsen Company
All Commodity Volume $ (ACV)
• An individual store’s/market’s ACV is the dollar volume of
everything the store sold during a period—all the
merchandise that passed over the scanner (or was rung
on the register)
• The sum of the ACVs of all the stores within a given
channel is the ACV for the channel. Likewise, the sum of
the ACVs for all the stores in a market is the ACV for the
market (Market ACV $ fact on database)
Foundation of Analysis:
Retail Measurement Data
Slide 59
Confidential & Proprietary
Copyright © 2008 The Nielsen Company
All Commodity Volume $ (ACV) Explanation
JONES’s
The 7 Food Stores
SMITH’s
In This Market Sell
$300,000 Per Week
A) $36,000 (12%)
SMITH’s
JONES’s
B) $36,000 (12%)
B) $48,000 (16%)
SMITH’s
JONES’s
C) $48,000 (16%)
SMITH’s Grocery Chain
* Has 3 stores in the market
doing $132,000 per week
for a total of 44% of the ACV
Foundation of Analysis:
Retail Measurement Data
A) $60,000 (20%)
JONES’s
C) $36,000 (12%)
D) $36,000 (12%)
JONES’s Grocery Chain
* Has 4 stores in the market
doing $168,000 per week
for a total of 56% of the ACV
Slide 60
Confidential & Proprietary
Copyright © 2008 The Nielsen Company
All Commodity Volume $ (ACV) Explanation
If These 3 Stores
Sold Your
Product This Week,
What Would The
%ACV Be?
SMITH’s
B) $36,000 (12%)
SMITH’s
B) $48,000 (16%)
JONES’s
A) $60,000 (20%)
JONES’s
JONES’s
B) $36,000 (12%)
JONES’s
SMITH’s
C) $48,000 (16%)
Foundation of Analysis:
Retail Measurement Data
B) $36,000 (12%)
D) $36,000 (12%)
Slide 61
Confidential & Proprietary
Copyright © 2008 The Nielsen Company
All Commodity Volume $ (ACV) Explanation
ANSWER:
20% ACV +
16% ACV +
12% ACV = 48% ACV
JONES’s
A) $60,000 (20%)
SMITH’s
B) $48,000 (16%)
JONES’s
D) $36,000 (12%)
Foundation of Analysis:
Retail Measurement Data
Slide 62
Confidential & Proprietary
Copyright © 2008 The Nielsen Company
Breadth of Distribution -- % ACV
A measure of breadth, or reach, indicates how
many consumers have the opportunity to buy the
product
• % ACV Selling serves as a good weighting factor when
measuring distribution.
• All stores are not created equal
• Higher ACV stores serve more consumers
Foundation of Analysis:
Retail Measurement Data
Slide 63
Confidential & Proprietary
Copyright © 2008 The Nielsen Company
% ACV Selling is NOT Distribution
• Real on-shelf distribution is
almost always higher
–Most products do not
sell in every store every
week
–Out-of-stocks can
happen
One other point to remember…
Just because an item is authorized
at Chain Headquarters does not
mean that every store actually
stocks it.
Foundation of Analysis:
Retail Measurement Data
Slide 64
Confidential & Proprietary
Copyright © 2008 The Nielsen Company
Analysis Tip - % ACV Selling
Use 4 Wk
Periods only!
Use longer timeframes to get the
best picture of “distribution”
Brand A
Sales
Week
1
Store A
(40% ACV)
X
Week
2
Week
3
X
X
Store C
(25% ACV)
X
X
60%
60%
40%
4-Week
Total
X
Store B
(35% ACV)
Total
Week
4
X
X
X
35%
100%
Average Weekly % ACV = 48%
Foundation of Analysis:
Retail Measurement Data
Slide 65
Confidential & Proprietary
Copyright © 2008 The Nielsen Company
Analysis Tip - % ACV Selling
In most cases, use the latest period when analyzing %
ACV Selling
• Represents the current state of the business
• Averaging longer time periods may mask more recent trends
% ACV Selling
75
70
67
55
4 wks ending
Apr
4 wks ending
May
Foundation of Analysis:
Retail Measurement Data
4 wks ending
Jun
Slide 66
Latest 12 wks
AVG
Confidential & Proprietary
Copyright © 2008 The Nielsen Company
Depth of Distribution
Use 4 Wk
Periods only!
Depth assesses the variety of different items
being sold
• Cumulative Distribution Points (CDP) or Total
Distribution Points (TDP)
–Measures both the number and size of stores that
carry your brand and the number of sku's each store
carries
• Average Number of Items Handled
–On average, the number of sku's carried in the
stores that sell your brand
Foundation of Analysis:
Retail Measurement Data
Slide 67
Confidential & Proprietary
Copyright © 2008 The Nielsen Company
Cumulative Distribution Points (CDP)
• Also called Total Distribution Points (TDP)
• Calculated by adding the %ACV of each individual sku
%ACV
CDP
BRAND X
98%
295
Flavor 1
Flavor 2
Flavor 3
Flavor 4
95%
90%
80%
30%
95
90
80
30
}
Sum =295
Use 4 Wk
Periods only!
Foundation of Analysis:
Retail Measurement Data
Slide 68
Confidential & Proprietary
Copyright © 2008 The Nielsen Company
Difference from %ACV
CDP shows us that while Brand A and Brand B are both
sold in 100% of the stores in this market, Brand A has
more items available in each of the stores.
Brand A
Brand B
% ACV
CDP
100%
100%
2100
990
%ACV tells us
breadth of
distribution
Foundation of Analysis:
Retail Measurement Data
CDP tells us
depth of
distribution
Slide 69
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Average Number of Items Handled
• Dividing Cumulative Distribution Points by %ACV gives
the Average Number of UPC's Carried within those stores
selling the brand.
–The average store in this market carries 21 upc’s of
Brand A.
% ACV
Brand A
Brand B
100%
100%
Foundation of Analysis:
Retail Measurement Data
CDP
2100
990
AVG #
Items
21.0
9.9
Slide 70
Use 4 Wk
Periods only!
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Analysis Tip – Average Number of Items
Handled
Use Average Number of Items Handled to compute a
Fair Share index comparing share of items to share of
sales
AVG #
Items
Share of
Items
Share of
Sales
Fair Share
Index
Category
57.5
100.0
100.0
Brand A
21.0
36.5
31.0
117
Brand B
9.9
17.2
27.0
64
Interpretation: Brand B’s share of items is underdeveloped
relative to it’s share of sales. Potential to add additional Brand
B items to the shelf
Foundation of Analysis:
Retail Measurement Data
Slide 71
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Analysis Tip – Cumulative Distribution Points
CDP’s may explain volume changes that might not be
seen when looking at % ACV
Distribution Points
% ACV
100
100
100
100
100
100
690
685
693
658
609
584
1
2
3
4
5
6
Period
Interpretation; The brand’s base sales began eroding in period 4,
yet % ACV remained at 100%. However, depth of distribution
declined as the brand lost the equivalent of one item.
Foundation of Analysis:
Retail Measurement Data
Slide 72
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When To Use - ACV facts
When concerned with…
Use…
Breadth of distribution – the
number of stores carrying
your product
Trending overall depth or
quality of distribution over
time
% ACV Selling
How many sku’s are carried
in stores that sell your brand;
Fair Share Analysis –
comparing share of shelf to
share of sales
Average Number of Items
Handled
Foundation of Analysis:
Retail Measurement Data
Cumulative Distribution
Points;
Total Distribution Points
Slide 73
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Velocity
Measures brand strength while controlling for
distribution
• Sales Per Million ACV
–Average sales of a product for every million dollars of
ACV that is scanned
–Comparisons across and within markets
• Sales Per Point
–Average sales of a product for every percentage point
of ACV distribution
–Comparisons within markets only
Foundation of Analysis:
Retail Measurement Data
Slide 74
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Uses of Velocity
• Marketing
– Is my growth distribution driven or velocity driven?
– Velocity driven growth can be long term,
signaling consumers like your product and are
buying more.
– Distribution driven growth can be limited
because soon you will run out of new stores to
carry your product.
• Sales
– Prove your product sells faster than the competition
and deserves shelf space.
Foundation of Analysis:
Retail Measurement Data
Slide 75
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Analysis Tips - Velocity
• When comparing brands with differing numbers of UPC's,
use Sales Per Cumulative Points of Distribution
–Divide sales by CDP
–Brands with a greater number of UPC's will tend to
have stronger turns as more items contribute to overall
sales
• Use caution when tracking Sales Per Point of Distribution
for a new product
–Distribution will be growing as the product gains
distribution in new retailers and markets, resulting in
fluctuating turns
Foundation of Analysis:
Retail Measurement Data
Slide 76
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CDI/BDI MEASURES
Comparison of CDI and BDI identifies product
opportunity or vulnerability by geographic area.
• Category Development Index
– Category volume indexed to the population index
in relation to the United states norm. (TTL US =
100)
• Brand Development Index
– Brand volume indexed to the population index in
relation to the United states norm. (TTL US =
100)
Foundation of Analysis:
Retail Measurement Data
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CDI/BDI MEASURES
Population Development Index—The importance of
product sales compared to the importance of the population
in a market.
% of Total U.S. Population in Chicago:
% of Total U.S. Brand A $ Sales in Chicago:
7%
13%
How to calculate a Development index...
% of Sales: 13%
% of Population: 7% = 1.86, then multiply by 100 to derive an index = 186
This means that for every person in Chicago, Brand A $
sales are almost twice as important as the average market.
Foundation of Analysis:
Retail Measurement Data
Slide 78
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Analysis Tip – CDI/BDI
Use CDI/BDI’s to prioritize market opportunities
Foundation of Analysis:
Retail Measurement Data
Slide 79
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Analysis Tip – CDI/BDI
Calculate an Opportunity Index to further prioritize
markets
How to calculate an Opportunity index...
CDI X 100 = Opportunity Index
BDI
Oppy
CDI
BDI
Index
Chicago
106
95
112
Indianapolis
159
116
137
Interpretation—The brand has a larger opportunity gap in
Indianapolis even though both the category and brand indices are
above 100, compared to Chicago where the category is over 100
and the brand is under 100
Foundation of Analysis:
Retail Measurement Data
Slide 80
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Promotion, Promotion Effectiveness
and Pricing
Foundation of Analysis:
Retail Measurement Data
Slide 81
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Understanding the “Whys” to Changes in
Incremental Volume
Incremental sales can be impacted by different
merchandising factors.
Use 1 Wk
Periods only!
Incremental Volume
Promotion Support
(Quantity
Promotion Effectiveness
(Quality)
Level of Support
• Promotion Mix
• Promotion Price
• Level of Price Discount
• Competitive Conditions in
Promoting Stores
Foundation of Analysis:
Retail Measurement Data
Slide 82
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Promotions
What could cause this spike in sales?
Sales
Week 1
Week 2
Week 3
Foundation of Analysis:
Retail Measurement Data
Week 4
Week 5
Slide 83
Week 6
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Promotion Types
Nielsen measures three types of trade promotions
• Temporary Price Reductions (TPR)
–A 5% discount (or more) off a
product's regular price
• Features
–Print ad placed by the retailer
used to promote a specific
product
• Displays
–Temporary secondary stocking
location for a product
Foundation of Analysis:
Retail Measurement Data
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Features
• Features are retailer print advertisements or other special
printed promotions:
–Ads inserted in Newspapers
–Store Flyers / Circulars
• Nielsen Feature Coders collect and classify all retailer
features from the entire Nielsen store sample.
• The features are classified into A, B, C or Coupon Ads,
based on the size of the ad
• FSIs (Free Standing Inserts) are excluded since they are
manufacturer promotions
Foundation of Analysis:
Retail Measurement Data
Slide 85
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Displays
• Information collected for all Nielsen sample stores every
week
• Three conditions to be considered a display:
–Temporary secondary location
–Special effort by the retailer to attract attention and to
boost sales of the item
–Contain actual merchandise accessible to the
customer.
Foundation of Analysis:
Retail Measurement Data
Slide 86
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Temporary Price Decrease (TPR)
• Consists of those Stores/Weeks where a Price Decrease
of at Least 5% is present, but no Feature Ad, Coupon Ad
or Display accompanies the Price Decrease (TPR)
• Lower price becomes new base price after 7 weeks
Foundation of Analysis:
Retail Measurement Data
Slide 87
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Promotion Conditions
Feature
Display
w/out F&D w/out
Display
Feature
Promotional
Conditions are
mutually exclusive at
the UPC level. A UPC is
either Promoted or Not
Promoted.
Price
Decrease
(TPR)
Foundation of Analysis:
Retail Measurement Data
Slide 88
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Promotion Support
Three ways to view Quantity of trade support
Use 1 Wk
Periods only!
• % ACV Promoted
–% of ACV that sold at least one unit on deal during the
time period
• Store Weeks of Support
–Number of weeks a product is on deal weighted by the
ACV of the stores participating in the promotion
• % Base Support
–How much of a brand's everyday business (baseline
volume) is exposed to a deal
Foundation of Analysis:
Retail Measurement Data
Slide 89
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% ACV Support
Use 1 Wk
Periods only!
Measures the amount of consumer traffic
exposed to a promotion
• How much support did I receive on this event?
• How much of each type of support was received?
• Did the retailer execute as agreed to?
• Did the sales force or broker support and/or merchandise
the promotion as required?
Foundation of Analysis:
Retail Measurement Data
Slide 90
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Store Weeks Support
Measures the quantity of weeks the brand was on
promotion
Week 1
Week 2
Week 3
Week 4
Week 5
Actual %
ACV ANY DSP
20%
100%
60%
30%
50%
260% /100 = 2.6 weeks
Interpretation - Brand received the equivalent of 2.6 weeks of
Display activity in the five-week period
Foundation of Analysis:
Retail Measurement Data
Slide 91
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% Base Support
Measures the % of Base business exposed to
a particular promotion type
• Weights the importance of the store to the brand.
• Gives more credit for an important SKU
• Is additive/combinable across markets, time, products
and retail conditions
Foundation of Analysis:
Retail Measurement Data
Slide 92
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% Base Support Calculation Example
Base Sales
Store 1
10
Store 2
10
Store 3
Store 4
Store 5
25
20
15
Total Base Volume
=
Feature Base Volume =
% Base Support
=
Promotion?
No
Feature
Feature
No
Feature
80
50
50/80 = 63%
Interpretation – 63% of the brand’s base volume was exposed to
a feature during the promotion period
Foundation of Analysis:
Retail Measurement Data
Slide 93
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When To Use – Promotion Support facts
When concerned with…
Use…
Level of trade participation in an % ACV Support
event;
Amount of consumer traffic
exposed to promotions
Duration of support
Store Weeks Support;
Cume Weighted Weeks
How much of a brand’s base
volume was exposed to a
promotion
Foundation of Analysis:
Retail Measurement Data
% Base Support
Slide 94
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Promotion Effectiveness
Measures how much incremental volume each
promotion generated
• Percent Lift
• Promotion Effectiveness Index (PEI)
• Incremental Weeks
• Efficiency
Foundation of Analysis:
Retail Measurement Data
Slide 95
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Promoted Baseline Volume
Promoted
Incremental
Incremental
that is a result
of promotion
Also Known
Promoted Base
as
Subsidized
Base
NonPromoted
Foundation of Analysis:
Retail Measurement Data
Base
Non-Promoted
Base
Slide 96
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Promoted Baseline Volume
170
In Week 4 all the volume is
promoted, but only 95 units
are incremental; 75 units
are subsidized base
95
Unit Sales
75
75
75
75
75
Display
Week
week 1
week 2
Foundation of Analysis:
Retail Measurement Data
week 3
week 4
Slide 97
week 5
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Promotion Efficiency
• Percent of promoted sales that were incremental
Incremental Sales x100
Promoted Sales
• Tells how efficient was the promotion
– What percent was incremental to baseline?
– What percent was subsidized?
• Note: The more subsidized volume that is generated
during a promotion the less efficient that promotion will
be!
Foundation of Analysis:
Retail Measurement Data
Slide 98
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Promotion Effectiveness
Measures how much incremental volume each
promotion generated
• Promotion Effectiveness Index (PEI)
– Indexes Total volume to Base volume
Promoted Sales x 100
Promoted Base Sales
• % Lift
– Similar to PEI but expressed as a
percentage
Promoted Sales x 100 - 100
Promoted Base Sales
• Incremental Weeks
– Similar to Lift but expressed as a number Promoted Sales - 1
Promoted Base Sales
of weeks
Foundation of Analysis:
Retail Measurement Data
Slide 99
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Analysis Tips - Interpreting Promotion
Response
170
PEI
95
Sales indexed at 227 vs. base
during the promotion week
170 x 100 = 227
75
% Lift
The promotion drove a
127% increase in sales
75
Display
Week
170 x 100 - 100 = 127%
75
Incremental Weeks
The promotion generated
1.3 additional weeks of sales
170 - 1 = 1.27
75
Promotion Efficiency
week 4
56% of the promoted volume
was incremental to the brand
Foundation of Analysis:
Retail Measurement Data
95 x 100 = 56%
170
Slide 100
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Analysis Tips – Promotion Effectiveness
• Promotions will yield different results depending on:
–Type of merchandising occurring in the store - ads,
displays, TPR's
–Depth of discount offered to consumers
–Competitive activity
• When reviewing promotion effectiveness, take into
account the size of the brand
–Smaller players, with small base businesses, have a
much easier time generating big lifts
Foundation of Analysis:
Retail Measurement Data
Slide 101
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When to Use – Promotion Effectiveness Facts
When concerned with…
Use…
Measuring the increase in volume
due to promotions;
Determining which promotions
generate the largest incremental
gains
Measuring the ability of a
promotion to minimize subsidizing
existing volume
% Lift;
Promotion
Effectiveness Index
(PEI);
Incremental Weeks
Promotion Efficiency
Foundation of Analysis:
Retail Measurement Data
Slide 102
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Pricing
Nielsen databases track pricing in four ways:
• Average Retail Price
–Weighted price of a product, representing both nonpromoted and promoted prices
• Non-Promo Price
–Average scanned price of a product in stores where
there was no promotion
• Any Promo Price
–Average scanned price of a product in stores where
there was a promotion
• Base Price
–Estimate of the normal, non-discounted price of a
product in a store
Foundation of Analysis:
Retail Measurement Data
Slide 103
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Base Price = Non-Promoted Price
• Non Promoted Price is
based solely on stores
where the item in not being
promoted
• Base Price is based on all
stores, not just nonpromoted stores
Foundation of Analysis:
Retail Measurement Data
Slide 104
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Price Discount
• Measures the difference
between Base Price and
Promoted Price
• The deeper the price
discount the greater the
expectation that consumer
sales will increase
Foundation of Analysis:
Retail Measurement Data
Slide 105
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Average Retail Price - Precautions
• Think when you average across:
– Products: (10, 26 and 51 oz. sizes)
– Markets: (Los Angeles vs. Boston)
– Promotions (display price vs. feature price)
• Aggregate price is one big average… beware!!!
– $2.99 =Average of $1.99 & $3.99
– $2.99=Average of $0.99 & $4.99
– $2.99=Average of $2.98 & $3.00
Foundation of Analysis:
Retail Measurement Data
Slide 106
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Analysis Tips - Pricing
• Analyze price at the SKU level
–Prices at the brand level are an average of all sizes and
multi-pack counts
• Match like items when comparing price to competition
–Select similar-sized competitive items for comparison
–Or use equivalized price
• Use the most recent period to measure base price
–Longer timeframes may mask recent trends
Foundation of Analysis:
Retail Measurement Data
Slide 107
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When to use – Pricing Facts
When concerned with…
Use…
What consumer is paying on average Average Retail
Price
What is the average price for an item No Promo Price
when not on promotion
What the consumer is paying on
promotion/deal
Any Promo Price
Tracking price trends;
Impact of price on baseline volume
Base Price
Magnitude of savings passed on to
the consumer
% Price Discount
Foundation of Analysis:
Retail Measurement Data
Slide 108
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Analysis Tips - Recommendations
If Volume Change is
driven by:
Potential Actions
An increase in Base
Price
• Increase perceived value of product
– Decrease price
– Increase package size
– Increase use of bonus packs, special packs
– Launch a product or package innovation
– Improve communication of product benefits
– Improve product quality
A decrease in Base
Velocity
• Improve advertising
– Weight, Target, Message, Media
• Improve consumer promotion
– Frequency, Values, Types
• Increase shelf presence, change item mix
A decrease in %ACV
• If base velocity is competitive with brands on the shelf, conduct a
distribution drive
• If base velocity is low, improve velocity (see point above) to justify
increased distribution
A decrease in Average
Items Carried
• Introduce new products
• Change item mix
• Address any Out-of-Stock issues
Foundation of Analysis:
Retail Measurement Data
Slide 109
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Analysis Tips - Recommendations
If Volume Change is
driven by:
Potential Actions
An increase in Promoted
Price
• Reduce promoted price
• Implement a price multiples strategy (e.g. 2 for $5)
A decrease in the %ACV
with Quality
Merchandising
• Increase number of stores with features or displays
–Determine which promotion condition works best for each
brand / segment
• Improve event timing / frequency
A decrease in the # of
Promoted Items
A decrease in Promoted
Velocity
A decrease in Promotion
Efficiency
• Identify targets for number of items on feature or display
• Provide consumer incentives for purchase of multiple items
• Improve event timing / frequency
• Coordinate & integrate trade promotion with other mix elements
(e.g., advertising, coupons, consumer events)
• Identify stronger items for promotion
• Develop promotion themes
• Improve event timing / frequency
• Improve Customer Targeting (loyals vs. switchers)
Foundation of Analysis:
Retail Measurement Data
Slide 110
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Thoughts
• Sorensen
– Trade promotion $ focus (p. 18)
– Table I.1 (p. 9)
– Trip types
– Reach,stop,close
– Money, time, angst
– Table 1.1 (p. 26) and 1.2 (32)
– Promoted baseline (p. 31)
– Top category locations (Fig 1.2)
– Danger of focusing on quick trips?
– Tyranny of choice (p. 61)
– Time measures (65)
Foundation of Analysis:
Retail Measurement Data
• Underhill
–
–
–
–
Conversion rate 48% (p. 29)
Importance of shopping time (32)
Confusion index (33)
Transition zone (44)
Slide 111
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Whew!
Foundation of Analysis:
Retail Measurement Data
Slide 112
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