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Confidential & Proprietary Copyright 2008 The Nielsen Company

Nielsen Training

Katz Graduate School of Business

January 16, 2009

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Confidential & ProprietaryCopyright 2008 The Nielsen Company

Foundation of Analysis:Retail Measurement Data

Slide 2

Agenda

Overview of NielsenData CollectionFoundation of Analysis

4 Dimensions Overview of terms,

definitions

Nitro training /demonstration

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Company Overview

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Slide 4

We are the worlds leading providerof marketingand media information, leading publisher of

business-to-business magazines and e-media and

leading producer of trade shows and conferences.

We harness the power of our informationand theexpertise of our people to help businesses of all kindsdiscover their growth opportunities through betterunderstanding of consumers, markets and industrytrends.

Who We Are

What We Do

Why We Do ItWere in business to serve businessand aim toprovide our clients with superior service and value, togrow our business profitably, and to deliver superiorreturns to our shareholders.

The World Leader in UnderstandingConsumer Behavior

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Slide 5

Nielsen Global ReachServices in over 100 countr ies

TheAmericas

Schaumburg, I ll inois

Europe, Middle East and AfricaWavre, Belgium

AsiaPacificHong Kong,

China

World HQNew York, NY

ACNielsen Presence

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Slide 6

Provides millions of people around theworld with business and professional

intelligence

Market leader with premium brands

New York (USA)

42,000 employees worldwide

$4.3 billion (2005)

Quick FactsThe Nielsen Company

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Slide 7

Our History

Founded in 1923: Arthur C. Nielsen, Sr.

Pioneered retail, media measurement disciplines

Developed concept of market share

Developed original television & radio ratings business:

Nielsen Families

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Slide 8

Our Assets & Brands are Leveraged toSupport and Grow our Partners

businesses

Client

Bus iness

Partner
http://www.tdlinx.com/http://www.claritas.com/

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Nielsen Client Partners

Many of the Worlds Best-Known Brands

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Data Collection & QualitySource of Scanning Information

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Slide 12

A Look at the Consumer PackagedGoods [CPG] Industry

Consumer

Manufacturer

Retailer

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Slide 13

Nielsen Collects Data fromRetailers & Consumers...

Consumer

Manufacturer

Retailer

Data

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Slide 14

Nielsen Collects Data fromRetailers & Consumers...

& sells / trades data to the

manufacturer & retailer

Consumer

Manufacturer

Retailer

Data

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Slide 15

Data Collection & QualitySource of Information

Consumer sales Retail price

Retailer SampleStores

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Slide 16


Consumer sales Retail price


ACNielsens Field

Auditors

Display presence Custom observations(inventory

levels, facings, linear shelfmeasurements, etc.)

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Slide 17



ACNielsen's FieldAuditors

ACNielsens

Feature Coders

Consumer sales (audit or scan) Retail price

All retailer print advertising Standardized ABC feature coding

Display presence Custom observations(inventory

levels, facings, linear shelfmeasurements, etc.)

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Slide 18

We Collect Data Across Multiple Outlets ...

Drug Stores

Gas ConvenienceStores

IndependentFood Stores

Supermarkets Mass

Merchandisers

Chain ConvenienceStores

Supercenters

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Slide 19

We Use Two Primary Methods to CollectRaw Data . . .

Scanning

and

In-Store Field Audits

Retailers provide salesand pricedata scanned purchases all UPC-coded items each week for every store included in sample

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Foundation of AnalysisRetail Measurement Data

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Slide 21

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

Provide a foundation for understanding some ofthe common differences in facts and helpdetermine the best choice for an analysis.

Goal and Objectives

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Slide 22

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 Iinterested in?

Facts What type of issue?

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Slide 23

Periods

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Slide 24

Periods

Monthly (4 wk) and Weekly hard-coded time periodsreside on all Heinz databasesMonthly data goes back 5 yearsWeekly data goes back 3 yearsWe 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 offof the monthly & weekly periodsWhen 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)

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Slide 25

Markets

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Slide 26

4 Regions & 9 Divisions for Census

Pacific

Mountain

West South

Central

West North

CentralEast North

Central

New

England

Mid-

Atlantic

South

Atlantic

East South

Central

West

Central

East

South

26

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Slide 27

West Pacific

California Oregon Washington

Mountain Arizona Colorado Idaho Montana

Nevada New Mexico Utah Wyoming

East New England

Connecticut Maine Massachusetts New Hampshire Rhode Island Vermont

Mid Atlantic

Pennsylvania New Jersey New York

Census Regions & Divisions

Central West North Central

Iowa Kansas Minnesota Missouri Nebraska North Dakota South Dakota

East North Central

Illinois Indiana Michigan Ohio Wisconsin

South West South Central

Arkansas Louisiana Oklahoma Texas

East South Central Alabama Kentucky Mississippi

Tennessee South Atlantic

Delaware Florida Georgia Maryland North Carolina South Carolina Virginia West Virginia

27

Note: Markets Defined by US Government

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Slide 28

ACNielsen Total U.S. 52 SCANTRACK Markets

Portland

Seattle

Sacramento

San Francisco

Los Angeles

Salt Lake City/Boise Denver

PhoenixLas Vegas

San Diego West Texas/

New MexicoOklahoma City/Tulsa

San Antonio

Dallas

Houston

Omaha Des Moines Minneapolis

TampaKansas City

Little Rock

Memphis

New Orleans/Mobile

Birmingham

Grand Rapids

Milwaukee

St. Louis

Chicago

Cleveland

Detroit

Indianapolis

Cincinnati

ColumbusPittsburgh

Buffalo/Rochester

Nashville

Miami

Atlanta

Orlando

Louisville

Charlotte

Jacksonville

Richmond

Raleigh/Durham

Washington DC

Baltimore

Philadelphia

Hartford/New Haven

New York

Boston

Syracuse

Albany

Note: Markets Defined by Nielsen

E l ACNi l SCANTRACK

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Slide 29

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.

Example: ACNielsen SCANTRACK

Atlanta - Food

Whitfield

MurrayGilmer

Fannin Union

Towns

White

Clay

Lumpkin

DawsonPickensGordon

BartowFloyd

Chattooga

Cherokee

Cleburne

Polk

Carroll

HeardRandolph

Chambers

Harris

Troup

Meriwether

CowetaFayette

Clayton

Henry

Spalding

Pike

Upson

Lamar

MonroeJones

Baldwin

Hancock

PutnamJasper

Morgan

Greene

OglethorpeClarke

Oconee

Walton

Gwinnett

Rockdale

Newton

De Kalb

Fulton

Fulton

Douglas

PauldingCobb

CherokeeForsyth

Hall

Banks

Jackson

Barrow

Haralson

Butts

Talbot

Alabama

Tennessee

South Carolina

Georgia

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Slide 30

_______________________________________________ ATLANTA __________________________________________________________|

Supermarket Composition and | Claritas EstimatesNSUS Sample Representation | as of January 1,2004as of Mar04 | % US

Number NSUS | TOTAL POPULATION 5,905,600 2.0%Over Sample | TOTAL HOUSEHOLDS 2,163,200 2.0%$2MM Cooperation | EFFECTIVE BUYING INCOME($000) 119,291,928 2.2%

|____________________________________________________________________

Major Retail Chains |KROGER 143 YES | ACNielsen Type Food StoresPUBLIX 135 YES | ACNielsen Control EstimatesINGLES 70 YES | as of December 31,2001SAVE RITE 43 YES | Number % US ACV ($000) % USBI LO 17 YES | TOTAL FOOD STORES 2,592 1.6% $ 9,258,802 1.9%FOOD LION 13 YES |QUALITY FOODS 12 NO | STORES $4MM AND OVER 555 7,892,907

WAYFIELD FOODS 12 NO | STORES $2MM AND OVER 623 8,103,955|____________________________________________________________________|| Market by County

Wholesaler Representation | CHAMBERS AL CHEROKEE AL CLEBURNE AL RANDOLPH ALSUPERVALU YES | BALDWIN GA BANKS GA BARROW GA BARTOW GAPIGGLY WIGGLY ALABAMA DIS YES | BUTTS GA CARROLL GA CHATTOOGA GA CHEROKEE GA

MERCHANTS DISTRIBUTORS YES | CLARKE GA CLAYTON GA COBB GA COWETA GAMITCHELL GROCERY YES | DAWSON GA DE KALB GA DOUGLAS GA FANNIN GAASSOC WHOLESALE GROCERS YES | FAYETTE GA FLOYD GA FORSYTH GA FULTON GA

| GILMER GA GORDON GA GREENE GA GWINNETT GA| HALL GA HANCOCK GA HARALSON GA HARRIS GA

Wholesaler Information from | HEARD GA HENRY GA JACKSON GA JASPER GA

Trade Dimensions' Store File | JONES GA LAMAR GA LUMPKIN GA MERIWETHER GA| MONROE GA MORGAN GA MURRAY GA NEWTON GA| OCONEE GA OGLETHORPE GA PAULDING GA PICKENS GA| PIKE GA POLK GA PUTNAM GA ROCKDALE GA| SPALDING GA TALBOT GA TOWNS GA TROUP GA| UNION GA UPSON GA WALTON GA WHITE GA| WHITFIELD GA CLAY NC||| COPYRIGHT 2004 A.C. NIELSEN COMPANY 04/12/04

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Slide 31

Trading Areas & Competitive Markets

Sample/Census Trading Area: counties it includes aredefined by the particular retailer, data reported is for thatretailers stores only

Competitive Markets: all retailers within the trading areacounties that participate in the sample are included in thedata reported, this includes the trading area particularretailer sales as well

E l C t SCANTRACK T d A

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Slide 32

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.

Example: Custom SCANTRACKTrade Area -Cub Minneapolis

St. Croix

Wright

Sherburne IsantiChisago

Anoka

Hennepin

Carver

Scott Dakota

Ramsey

Washington

Minnesota

Wisconsin

Counties within the circle make up the trading area, all participating retailer storesfalling within those counties make up the data reported for Cub Minneapolis

CUB TWIN CITIES TRADING AREA

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Slide 33

________________________________________CUB TWIN CITIES TRADING AREA________________________________________________|

Supermarket Composition and | Claritas EstimatesNSUS Sample Representation | as of January 1,2003as of Jan04 | % US

Number NSUS | TOTAL POPULATION 3,021,600 1.1%Over Sample | TOTAL HOUSEHOLDS 1,161,800 1.1%$2MM Cooperation | EFFECTIVE BUYING INCOME($000) 73,989,445 1.3%

|____________________________________________________________________

Major Retail Chains |CUB FOODS 48 YES | ACNielsen Type Food StoresRAINBOW (ROUNDY'S) 31 YES | ACNielsen Control EstimatesBYERLYS 11 NO | as of December 31,2001

| Number % US ACV ($000) % US| TOTAL FOOD STORES 881 0.5% $ 5,124,729 1.1%|

Wholesaler Representation | STORES $4MM AND OVER 214 4,569,714SUPERVALU YES | STORES $2MM AND OVER 252 4,679,638

NASH FINCH YES |____________________________________________________________________|| Market by County

Wholesaler Information from | ANOKA MN CARVER MN CHISAGO MN DAKOTA MNTrade Dimensions' Store File | HENNEPIN MN ISANTI MN RAMSEY MN SCOTT MN

| SHERBURNE MN WASHINGTON MN WRIGHT MN ST CROIX WI||| COPYRIGHT 2004 A.C. NIELSEN COMPANY 01/23/04

Comp Market data is composed of the Major Retail Chains thatcooperate in the sample in these counties. They include only Rainbowand Cub Foods for the Minneapolis Cub Comp Market

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Slide 45

Products

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Slide 46

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 thegrocery store

Only available on Strategic Planner

Characteristics

Ability to filter through all database UPCs based on unique characteristicsof products

Ex: size, flavor, meat type, container type

Characteristic availability differs by category

Uses: UPC level output, need to create custom aggregates based onproduct characteristics when not available via Industry Subtotals

Available on all databases

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Slide 47

Facts

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Slide 48

There are a tremendous numberof facts

The difference between similarfacts 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 inquestion

Why is it important to understandfacts?

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Slide 49

Analytical Thinking

Certain mathematical toolsand calculations can be veryhelpful, but...

knowing how to use them,more so than actuallyderiving them, is mostimportant.

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Slide 50

Numbers tell you little bythemselves.

Usually you look atnumbers in terms of other

reference points Or you combine them with

other information to form aconclusion, answerquestions, set objectives,make plans, etc.

So, What Do I Do With the Numbers?

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Slide 51

Analysis TipThe Analytic PathMost issues can be addressed by drilling down this path

Issue

Base Volume Incremental Volume

Distribution Velocity

% ACV(Breadth)

# of Items(Depth)

Base Price

CompetitiveActivity

Other Factors

PromotionSupport

(Quantity)

PromotionEffectiveness

(Quality)

Level ofSupport

Promo Mix

Promo Price

Price Discount

Competitive Activity

A l i Ti P i iti K I

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Slide 52

Analysis TipPrioritize Key Issues

To set up a logical flow and to avoid analysis paralysis,

start with the higher level trends then work into theindividual drivers

Level of Detail

Category

. Segments

Manufacturers

Competitive Brands

Your Brand

DistributionEverydayPricing

TradeSupportDiscount

Total VolumeTrends

Basevs

Incremental

Base&

Incremental

DriversRecommended Level

of DetailDependent upon

level of chg

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Slide 53

Volume and Share

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Slide 54

Sales Volume

Measures the amount of product sold over a given timeperiod

Sales DollarsDollar value of total sales Sales UnitsTotal package sales Equivalent Unit SalesTotal sales on an equivalized

basis (pounds, cases, servings, etc.)

UsesTrackingRankingShare calculationsShow a brands importance to the category

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Slide 55

Share

Measures the % of salesthat a product accountsfor

Influenced by two different

measuresBrand Sales and

Category Sales

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Slide 56

What do the following salesscenarios have in common?Brand sales flat, category

declinesBrand sales up, category

flatBrand sales up a lot,

category up a little

Share Activity

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Slide 57

When to UseVolume and Share

When concerned with UseAbsolute volume;Absolute volume change

Unit, Dollar, Eq Salesvolume

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

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Slide 58

When concerned with Use

Analyzing category growth in a retailer or channel that is growingsignificantly.

Example: Category B grew 16% in Kroger last year. However, sinceKroger grew its total $ sales by 22%, Category B is not keeping pace

with its potential growth in Kroger.

ACV growth /Total $ RingGrowth

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 bymaintaining its penetration and buying rate.

PopulationGrowth

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

EquivalizedSales

When To UseVolume Benchmarks

Use Benchmarks to compare category and brandtrends

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Slide 59

Different Ways to Look at Volume

TOTAL VOLUME

+PromotedVolume

Non-PromotedVolume

+BaselineVolume

IncrementalVolume

Th B fi f Id if i P d V

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Slide 60

The Benefits of Identifying Promoted Vs.Non-Promoted Volume

Provides an indication of what percent of a brandsvolume came from stores with a promotion.

Provides an indication of what percent of a

manufacturers deal was passed on to the consumer bythe retailer.

Retailers trade promotion execution can be observed.

A l i Ti P d V l

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Slide 61

Analysis TipPromoted Volume

Promoted volume is useful for determining

how deal reliant a brand is

Interpretation: Our brand receives a higher share of category promoted volume compared to its

share of sales Our competitors promoted volume share is under-indexed relative to its market share

Brand Share Trend

17.5

13.1

19.7

11.2

Our Brand Competitive Brand

Total Volume Share Promoted Volume Share

B li V l

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Slide 62

Baseline Volume

Normal expectedeveryday sales in the absence of anystore-level promotion

A statistically calculated measureNOT adjusted for FSIs,print, TV and market-level affects

UsesTrack the underlying health of a brand and compare it

to its competition

Analyze merchandising effectiveness in conjunctionwith incremental volume

Baseline Calc lation

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Slide 63

Baseline Calculation

week 1 week 2 week 3 week 4 week 5

170

Unit Sales

75 75 75 75

DisplayWeek


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Slide 64


170


Unit Sales

75 75 75 75

In Week 4 Baseline estimate would be75 units based on pre and post weeksales

75

DisplayWeek

B li V l I l d M k t l

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Slide 65

Baseline Volume Includes MarketplaceConditions that Affect Sales of a Product

0

2,000,000

4,000,000

6,000,000

8,000,000

10,000,000

CategoryTrends Long-Term

SeasonalityMarket-Level

Effects

BrandTrends

Baseline

R f T t l/B li V l

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Slide 66

Total volume belowbaselineCompetitive activityOut of stockSeasonal/holiday

Total volume abovebaselinePromotions or advertising not

captured by regular meansMarket-level influences (e.g.,

battery sales during ahurricane in Miami)

Reasons for Total/Baseline VolumeDifferences

I t l V l

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Slide 67

Incremental Volume

Represents the additionalpredicted volume that resultsfrom in-store promotion

Calculation:Total Actual Volume -Baseline Volume =Incremental Volume

Incremental Volume

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Slide 68

Incremental Volume

Unit Sales

In Week 4 Incremental volumewould be 95 units

170


75

DisplayWeek

95

75 75 75 75

How Can Incremental Volume Be Negative?

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Slide 69

How Can Incremental Volume Be Negative?

If actual sales are less than expected sales

Out-of-stocksCompetitive activity


Unit Sales

75 75

75

75

Actual sales are belowestimated BaseIncrementalis negative 15 units

75

170

60

Analysis Tip Base and Incremental Volume

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Slide 70

Analysis Tip - Base and Incremental Volume

Category Volume TrendCurrent 12 Weeks vs. Year Ago

(25,000)

(12,500)

0

12,500

25,000

37,500

Total FDM ex

WM

Food Drug Target K-Mart

Total EQ Base EQ Incr EQ

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.

Identifying whether a volume change is coming primarily frombase or incremental volume is a good way to start an analysis

Analysis Tip Base and Incremental Volume

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Slide 71

Analysis Tip - Base and Incremental Volume

Base and Incremental trends will determine potentialstrategies

Base Volume = Non Promoted Volume

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Slide 72

Base Volume =Non-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 promotionSubset of stores

Incremental vs. Promoted Incremental volume estimates additional sales due to

promotionsVolume sold above the base

Promoted volume measures all volume sold on deal

Incremental Volume =Promoted Volume

When to Use Base Incremental Promoted

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Slide 73


Understanding the underlying health andtrends of a brand

Baseline Volume

Measuring the effectiveness and efficiency oftrade promotions Incremental Volume

Quantifying the importance of promotionalactivity to a brand

Promoted Volume

Quantifying the amount of volume sold in

stores that did not provide trade support

Non-Promoted Volume

When to UseBase, Incremental, Promoted,Non-Promoted Volume

Sales Volume is influenced by

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Slide 74

Sales Volume is influenced bySeasonality

Consumers value certainproducts more (or less) duringthe year.

Examples of seasonalityHolidays or event driven: 4th of July,Thanksgiving, Cinco de Mayo, Backto School, etc.

Seasonal: BBQ sauce and ice creamduring the summer or soup andcrackers in the winter

Seasonality Calculation

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Slide 75

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

75

100

125

150

175

200

225

Jan

Feb

Mar Ap

rMa

yJu

nJu

lAu

gSe

pOc

tNo

vDe

c

Se

asonality

Index

TOTAL BASELINE-UNITS

Analysis Tips Seasonality

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Slide 76

Analysis Tips - Seasonality

Use Base Volume when calculating seasonality to negatepromotion-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

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Slide 77

ACV Distribution and Velocity

Understanding the Whys to Changes in

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Slide 78

Velocity

Baseline Volume

Distribution

Base PriceSeasonality*Advertising Support*Manuf. Coupons/FSIs

*Brand Awareness/Image*Product Quality*Weather*Consumer Promotions*Sampling

Competitive:DistributionPriceMerchandising

*Advertising*Coupons

% ACV(Breadth)

# of ItemsCarried(Depth)

* Non-Nielsen measures

Baseline sales can be impacted by different market factors.

Understanding the Whys to Changes inBaseline Volume

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Slide 79

How Is Distr ibut ion Measured?

ACV Distribution

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Slide 80

ACV Distribution

ACV Distribution is a measure ofa products availability

Can be measured in terms of

breadth and depthBreadth: percent of All

Commodity Volume that carriesyour brand

Depth: number skus that are

carried in the stores that sellyour brand

What is Distribution?

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Slide 81

What is Distribution?

Distribution is the measure of the availability of a product.For an individual item, distribution depends on two basicvariables:

How many stores stock the item?

How large are those stores?

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All Commodity Volume $ (ACV) Explanation

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Confidential & ProprietaryCopyright 2008 The Nielsen CompanyFoundation of Analysis:Retail Measurement Data

Slide 83

The 7 Food Stores

In This Market Sell

$300,000 Per Week

JONESsD) $36,000 (12%)

JONESs

A) $60,000 (20%)

SMITHsB) $48,000 (16%)

SMITHsC) $48,000 (16%)

SMITHs

A) $36,000 (12%)

JONESsB) $36,000 (12%) JONESs

C) $36,000 (12%)

SMITHs Grocery Chain

* Has 3 stor es in the mark et

doin g $132,000 per week

for a total of 44% of the ACV

JONESs Grocery Chain

* Has 4 stor es in the market

doin g $168,000 per week

for a total of 56% of the ACV


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Slide 84

If These 3 Stor es

Sold Your

Produ ct This Week,

What Would The%ACV Be?

JONESs

A) $60,000 (20%)

SMITHsC) $48,000 (16%)

SMITHs

B) $36,000 (12%)

JONESsB) $36,000 (12%)

SMITHsB) $48,000 (16%)

JONESsD) $36,000 (12%)

JONESsB) $36,000 (12%)


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Slide 85

JONESsD) $36,000 (12%)

SMITHsB) $48,000 (16%)

JONESsA) $60,000 (20%)

ANSWER:

20% ACV +16% ACV +

12% ACV = 48% ACV

y ( ) p

Breadth of Distribution -- % ACV

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Slide 86

Breadth of Distribution % ACV

% ACV Selling serves as a good weighting factor whenmeasuring distribution.All stores are not created equal Higher ACV stores serve more consumers

A measure of breadth, or reach, indicates howmany consumers have the opportunity to buy theproduct

% ACV Selling is NOT Distribution

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Slide 87

% ACV Selling is NOT Distribution

Real on-shelf distribution isalmost always higherMost products do not

sell in every store everyweek

Out-of-stocks canhappen

One other point to rememberJust because an item is authorized

at Chain Headquarters does notmean that every store actually

stocks it.

Analysis Tip - % ACV Selling

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Slide 88

Analysis Tip % ACV Selling

Brand ASales

Week1

Week2

Week3

Week4

4-WeekTotal

Store A(40% ACV)

X X

Store B(35% ACV)

X X X X

Store C

(25% ACV)

X X X

Total 40% 60% 60% 35% 100%

Average Weekly % ACV = 48%

Use longer timeframes to get the

best picture of distribution

Use 4 WkPeriods only!

Analysis Tip - % ACV Selling

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Slide 89

Analysis Tip % ACV Selling

In most cases, use the latest period when analyzing %ACV Selling

% ACV Selling7570

55

67

4 wks ending

Apr

4 wks ending

May

4 wks ending

Jun

Latest 12 wks

AVG

Represents the current state of the business Averaging longer time periods may mask more recent trends

Depth of Distribution

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Slide 90

Depth of Distribution

Depth assesses the variety of different itemsbeing 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 storecarries

Average Number of Items HandledOn average, the number of sku's carried in the

stores that sell your brand


Cumulative Distribution Points (CDP)

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Slide 91

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 95% 95

Flavor 2 90% 90

Flavor 3 80% 80

Flavor 4 30% 30} Sum =295


Difference from %ACV

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Slide 92

Difference from %ACV

CDP shows us that while Brand A and Brand B are bothsold in 100% of the stores in this market, Brand A hasmore items available in each of the stores.

% ACV CDPBrand A 100% 2100Brand B 100% 990

%ACV tells us

breadthofdistribution

CDP tells us

depth ofdistribution

Average Number of Items Handled

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Confidential & ProprietaryCopyright 2008 The Nielsen CompanyFoundation of Analysis:Retail Measurement Data Slide 93

Average Number of Items Handled

Dividing Cumulative Distribution Points by %ACV givesthe Average Number of UPC's Carried within those storesselling the brand.The average store in this market carries 21 upcs of

Brand A.

AVG #% ACV CDP Items

Brand A 100% 2100 21.0Brand B 100% 990 9.9


Analysis TipAverage Number of Items

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y p gHandled

Use Average Number of Items Handled to compute aFair Share index comparing share of items to share ofsales

AVG #Items

Share ofItems

Share ofSales

Fair ShareIndex

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 Bs share of items is underdeveloped

relative to its share of sales. Potential to add additional Brand

B items to the shelf

Analysis TipCumulative Distribution Points

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y p

CDPs may explain volume changes that might not be

seen when looking at % ACV

690 685 693 658

609 584

100 100 100 100 100 100

1 2 3 4 5 6Period

Distribution Points % ACV

Interpretation; The brands base sales began eroding in period 4,

yet % ACV remained at 100%. However, depth of distributiondeclined as the brand lost the equivalent of one item.

When To Use - ACV facts

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Breadth of distributionthenumber of stores carryingyour product

% ACV Selling

Trending overall depth or

quality of distribution overtime

Cumulative Distribution

Points;Total Distribution Points

How many skus are carried

in stores that sell your brand;

Fair Share Analysiscomparing share of shelf toshare of sales

Average Number of ItemsHandled

Velocity

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y

Measures brand strength while controlling fordistribution

Sales Per Million ACVAverage sales of a product for every million dollars of

ACV that is scannedComparisons across and within markets

Sales Per PointAverage sales of a product for every percentage point

of ACV distributionComparisons within markets only

Uses of Velocity

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y

Marketing

Is my growth distribution driven or velocity driven? Velocity driven growth can be long term,

signaling consumers like your product and arebuying more.

Distribution driven growth can be limited

because soon you will run out of new stores tocarry your product.

Sales Prove your product sells faster than the competition

and deserves shelf space.

Analysis Tips - Velocity

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y p y

When comparing brands with differing numbers of UPC's,use Sales Per Cumulative Points of DistributionDivide sales by CDPBrands with a greater number of UPC's will tend to

have stronger turns as more items contribute to overallsales

Use caution when tracking Sales Per Point of Distributionfor a new productDistribution will be growing as the product gains

distribution in new retailers and markets, resulting influctuating turns

CDI/BDI MEASURES

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Comparison of CDI and BDI identifies product

opportunity or vulnerability by geographic area.

Category Development Index

Category volume indexed to the population indexin 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)

CDI/BDI MEASURES

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% of Total U.S. Population in Chicago: 7%

% of Total U.S. Brand A $ Sales in Chicago: 13%

% 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.

Population Development IndexThe importance ofproduct sales compared to the importance of the populationin a market.

How to calculate a Development index...

Analysis TipCDI/BDI

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y p

Use CDI/BDIs to prioritize market opportunities

Analysis TipCDI/BDI

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y p

Calculate an Opportunity Index to further prioritize

markets

CDI BDIOppyIndex

Chicago 106 95 112

Indianapolis 159 116 137

How to calculate an Opportunity index...

CDIBDI

X 100 = Opportunity Index

InterpretationThe brand has a larger opportunity gap inIndianapolis even though both the category and brand indices areabove 100, compared to Chicago where the category is over 100and the brand is under 100

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Promotion, Promotion Effectivenessand Pricing

Understanding the Whys to Changes in

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Incremental Volume

Incremental sales can be impacted by different

merchandising factors.

PromotionSupport(Quantity

Incremental Volume

Promotion Effectiveness(Quality)

Level of Support Promotion Mix

Level of Price Discount

Competitive Conditions inPromoting Stores

Promotion Price


Promotions

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Week 1 Week 2 Week 3 Week 4 Week 5 Week 6

Sales

What could cause this spike in sales?

Promotion Types

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Temporary Price Reductions (TPR)A 5% discount (or more) off a

product's regular price

FeaturesPrint ad placed by the retailer

used to promote a specificproduct

DisplaysTemporary secondary stocking

location for a product

Nielsen measures three types of trade promotions

Features

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Features are retailer print advertisements or other specialprinted promotions:Ads inserted in NewspapersStore Flyers / Circulars

Nielsen Feature Coders collect and classify all retailerfeatures 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 aremanufacturer promotions

Displays

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Information collected for all Nielsen sample stores everyweek

Three conditions to be considered a display:Temporary secondary locationSpecial effort by the retailer to attract attention and to

boost sales of the itemContain actual merchandise accessible to the

customer.

Temporary Price Decrease (TPR)

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Foundation of Analysis:Retail Measurement Data Slide 110

Consists of those Stores/Weeks where a Price Decreaseof at Least 5% is present, but no Feature Ad, Coupon Ador Display accompanies the Price Decrease (TPR)

Lower price becomes new base price after 7 weeks

Promotion Conditions

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PromotionalConditions aremutually exclusive atthe UPC level.A UPC is

either Promoted or NotPromoted.

PriceDecrease

(TPR)

Featurew/out

Display

Displayw/out

FeatureF&D

Promotion SupportUse 1 Wk

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% ACV Promoted% of ACV that sold at least one unit on deal during the

time period

Store Weeks of SupportNumber of weeks a product is on deal weighted by theACV of the stores participating in the promotion

% Base SupportHow much of a brand's everyday business (baseline

volume) is exposed to a deal

Three ways to view Quantity of trade supportUse 1 Wk

Periods only!

% ACV SupportU 1 Wk

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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?

Measures the amount of consumer traffic

exposed to a promotion


Store Weeks Support

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Measures the quantity of weeks the brand was on

promotion

Actual %

ACV ANY DSP

Week 1 20%

Week 2 100%

Week 3 60%

Week 4 30%

Week 5 50%

260% /100 = 2.6 weeks

Interpretation - Brand received the equivalent of 2.6 weeks ofDisplay activity in the five-week period

% Base Support

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pp

Weights the importance of the store to the brand. Gives more credit for an important SKU

Is additive/combinable across markets, time, productsand retail conditions

Measures the % of Base business exposed to

a particular promotion type

% Base Support Calculation Example

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Base Sales Promotion?

Store 1 10 NoStore 2 10 Feature

Store 3 25 Feature

Store 4 20 No

Store 5 15 Feature

Total Base Volume = 80Feature Base Volume = 50% Base Support = 50/80 = 63%

Interpretation63% of the brands base volume was exposed toa feature during the promotion period

When To UsePromotion Support facts

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Level of trade participation in anevent;

Amount of consumer trafficexposed to promotions

% ACV Support

Duration of support Store Weeks Support;Cume Weighted Weeks

How much of a brands base

volume was exposed to apromotion

% Base Support

Promotion Effectiveness

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Measures how much incremental volume eachpromotion generated

Percent Lift

Promotion Effectiveness Index (PEI) Incremental Weeks Efficiency

Promoted Baseline Volume

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Promoted

Non-Promoted

Incremental

Base Non-PromotedBase

Promoted Base

Incremental

that is a resultof promotion

Also Knownas

SubsidizedBase

Promoted Baseline Volume

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Confidential & Proprietary

Copyright 2008 The Nielsen CompanyFoundation of Analysis:Retail Measurement Data Slide 120

In Week 4 all the volume is

promoted, but only 95 unitsare incremental; 75 unitsare subsidized base

170


Unit Sales

75 75 75 7575

DisplayWeek

95

Promotion Efficiency

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Copyright 2008 The Nielsen Company


Percent of promoted sales that were incremental

Tells how efficient was the promotion What percent was incremental to baseline? What percent was subsidized?

Note: The more subsidized volume that is generatedduring a promotion the less efficient that promotion will

be!

Incremental SalesPromoted Sales

x100

Promotion Effectiveness

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Promotion Effectiveness Index (PEI) Indexes Total volume to Base volume

% Lift Similar to PEI but expressed as a

percentage

Incremental Weeks Similar to Lift but expressed as a number

of weeks

Measures how much incremental volume eachpromotion generated

Promoted Sales

Promoted Base Sales

x 100

Promoted SalesPromoted Base Sales

- 1

Promoted SalesPromoted Base Sales

x 100 - 100

Analysis Tips - Interpreting PromotionResponse

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Response

PEISales indexed at 227 vs. baseduring the promotion week

% LiftThe promotion drove a

127% increase in sales

Incremental WeeksThe promotion generated1.3 additional weeks of sales

Promotion Efficiency56% of the promoted volumewas incremental to the brand

170

170

75 x 100 - 100 = 127%

17075

- 1 = 1.27

week 4

75

DisplayWeek

95

95170

x 100 = 56%

17075

x 100 = 227

Analysis TipsPromotion Effectiveness

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Slide 124

Promotions will yield different results depending on:Type of merchandising occurring in the store - ads,

displays, TPR'sDepth of discount offered to consumersCompetitive activity

When reviewing promotion effectiveness, take intoaccount the size of the brandSmaller players, with small base businesses, have a

much easier time generating big lifts

When to UsePromotion Effectiveness Facts

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Slide 125


Measuring the increase in volumedue to promotions;

Determining which promotionsgenerate the largest incrementalgains

% Lift;Promotion

Effectiveness Index(PEI);Incremental Weeks

Measuring the ability of a

promotion to minimize subsidizingexisting volume

Promotion Efficiency

Pricing

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Foundation of Analysis:

Retail Measurement DataSlide 126

Nielsen databases track pricing in four ways:

Average Retail PriceWeighted price of a product, representing both non-

promoted and promoted prices

Non-Promo PriceAverage scanned price of a product in stores where

there was no promotion

Any Promo PriceAverage scanned price of a product in stores where

there was a promotion

Base PriceEstimate of the normal, non-discountedprice of a

product in a store

Base Price =Non-Promoted Price

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Non Promoted Price isbased solely on storeswhere the item in not being

promoted

Base Price is based on allstores, not just non-promoted stores

Price Discount

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Measures the differencebetween Base Price andPromoted Price

The deeper the price

discount the greater theexpectation that consumersales will increase

Average Retail Price - Precautions

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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

Analysis Tips - Pricing

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Analyze price at the SKU levelPrices at the brand level are an average of all sizes and

multi-pack counts

Match like items when comparing price to competitionSelect similar-sized competitive items for comparisonOr use equivalized price

Use the most recent period to measure base price

Longer timeframes may mask recent trends

When to usePricing Facts

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What consumer is paying on average Average RetailPrice

What is the average price for an itemwhen not on promotion

No Promo Price

What the consumer is paying onpromotion/deal

Any Promo Price

Tracking price trends;

Impact of price on baseline volume

Base Price

Magnitude of savings passed on tothe consumer

% Price Discount

Analysis Tips - RecommendationsIf Volume Change is Potential Actions

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If Volume Change isdriven by:

Potential Actions

An increase in BasePrice

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 BaseVelocity

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 adistribution drive

If base velocity is low, improve velocity (see point above) to justify

increased distribution

A decrease in AverageItems Carried

Introduce new products

Change item mix

Address any Out-of-Stock issues

Analysis Tips - Recommendations

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If Volume Change isdriven by:

Potential Actions

An increase in PromotedPrice

Reduce promoted price

Implement a price multiples strategy (e.g. 2 for $5)

A decrease in the %ACVwith QualityMerchandising

Increase number of stores with features or displays

Determine which promotion condition works best for eachbrand / segment

Improve event timing / frequency

A decrease in the # ofPromoted Items

Identify targets for number of items on feature or displayProvide consumer incentives for purchase of multiple items

A decrease in PromotedVelocity


Coordinate & integrate trade promotion with other mix elements(e.g., advertising, coupons, consumer events)

Identify stronger items for promotion

Develop promotion themes

A decrease in PromotionEfficiency


Improve Customer Targeting (loyals vs. switchers)

Wrap Up

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