Confidential & Proprietary Copyright © 2008 The Nielsen Company Nielsen Training Katz Graduate...

Confidential & Proprietary • Copyright © 2008 The Nielsen Company

Nielsen Training

Katz Graduate School of Business

January 16, 2009

Confidential & ProprietaryCopyright © 2008 The Nielsen Company

Foundation of Analysis: Retail Measurement Data

Slide 2

Agenda

•Overview of Nielsen•Data Collection•Foundation of Analysis

– 4 Dimensions– Overview of terms,

definitions•Nitro training / demonstration


Company Overview



Slide 4

We are the world’s leading provider of marketing and 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 information and the expertise of our people to help businesses of all kinds discover their growth opportunities through better understanding of consumers, markets and industry trends.

Who We Are

What We Do

Why We Do It

We’re in business to serve business and aim to provide our clients with superior service and value, to grow our business profitably, and to deliver superior returns to our shareholders.

The World Leader in Understanding Consumer Behavior



Slide 5

Nielsen Global Reach Services in over 100 countries

The The AmericasAmericas

Schaumburg, Illinois

Europe, Middle East and AfricaEurope, Middle East and AfricaWavre, Belgium

Asia Asia PacificPacificHong Kong,

China

World HQWorld HQNew York, NY

ACNielsen Presence



Slide 6

Provides millions of people around the world with business and professional

intelligence

Market leader with premium brands

New York (USA)

42,000 employees worldwide

$4.3 billion (2005)

Quick Facts – The Nielsen Company



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



Slide 8

Our Assets & Brands are Leveraged to Support and Grow our Partners businesses

ClientClientBusinessBusinessPartnerPartner


Nielsen Client Partners

…Many of the World’s Best-Known Brands


Data Collection & Quality Source of Scanning Information



Slide 12

A Look at the Consumer Packaged Goods [CPG] Industry

Consumer

Manufacturer

Retailer



Slide 13

Nielsen Collects Data from Retailers & Consumers...

Consumer

Manufacturer

Retailer

Data



Slide 14

Nielsen Collects Data from Retailers & Consumers...

…& sells / trades data to the manufacturer & retailer

Consumer

Manufacturer

Retailer

Data



Slide 15

Data Collection & QualitySource of Information

Consumer salesConsumer sales Retail priceRetail price

Retailer Sample Retailer Sample StoresStores



Slide 16

Data Collection & Quality Source of Information

Consumer sales Consumer sales Retail priceRetail price


ACNielsen’s Field ACNielsen’s Field AuditorsAuditors

Display presenceDisplay presence Custom observations(inventoryCustom observations(inventory levels, facings, linear shelf levels, facings, linear shelf measurements, etc.) measurements, etc.)



Slide 17

Data Collection & Quality Source of Information


ACNielsen's Field ACNielsen's Field AuditorsAuditors

ACNielsen’s ACNielsen’s Feature CodersFeature Coders

Consumer sales (audit or scan)Consumer sales (audit or scan) Retail priceRetail price

All retailer print advertisingAll retailer print advertising Standardized ABC feature codingStandardized ABC feature coding

Display presenceDisplay presence Custom observations(inventoryCustom observations(inventory levels, facings, linear shelf levels, facings, linear shelf measurements, etc.) measurements, etc.)



Slide 18

We Collect Data Across Multiple Outlets ...

Drug StoresDrug Stores

Gas ConvenienceGas ConvenienceStoresStores

IndependentIndependentFood StoresFood Stores

SupermarketsSupermarkets MassMassMerchandisersMerchandisers

Chain ConvenienceChain ConvenienceStoresStores

SupercentersSupercenters



Slide 19

We Use Two Primary Methods to Collect Raw Data . . .

ScanningScanning

andand

In-Store Field AuditsIn-Store Field Audits

• 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 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 of the common differences in facts and help determine the best choice for an analysis.

Goal and Objectives



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 I interested in?

Facts What type of issue?



Slide 23

Periods



Slide 24

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)



Slide 25

Markets



Slide 26

4 Regions & 9 Divisions for Census

Pacific

Mountain

West SouthCentral

West NorthCentral

East NorthCentral

NewEngland

Mid-Atlantic

SouthAtlantic

East SouthCentral

West CentralEastSouth

26



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



Slide 28

ACNielsen Total U.S. 52 SCANTRACK Markets

P ortland

S eattle

S acram en to

S an F ran cisco

L os Angeles

S alt Lake C ity /B o ise Denver

P hoenixL as Veg as

S an D ieg o W est Texas/New M exico

O klah om a C ity /Tulsa

S an A ntonio

Dallas

Ho uston

O m ah a Des M oines M inn eapo lis

Tam p aKansas C ity

L itt le R ock

M em phis

New O rleans/M ob ile

B irm ing ham

G ran d R ap id sM ilw au kee

S t. Lo u isCh icag o

Cleveland

Detroit

Ind ianapo lis

C incinnati

Co lum bu sP ittsb urgh

Bu ffalo /Ro ch ester

Nashville

M iam i

Atlan ta

O rlando

L ou isv ille

Ch arlotte

Jacksonville

R ichm on d

Raleig h/Du rh am

W ash in g to n DC

Baltim oreP hilad elphia

Hartfo rd /New Haven

New Yo rk

Bo sto n

S yracu se

Alban y

• Note: Markets Defined by Nielsen



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

WhitfieldMurray

Gilmer

Fannin UnionTowns

White

Clay

Lumpkin

DawsonPickensGordon

BartowFloyd

Chattooga

Cherokee

Cleburne

Polk

Carroll

HeardRandolph

Chambers

Harris

Troup

Meriwether

CowetaFayette

ClaytonHenry

Spalding

Pike

Upson

Lamar

MonroeJones

Baldwin

Hancock

PutnamJasper

Morgan

Greene

OglethorpeClarke

Oconee

Walton

Gwinnett

RockdaleNewton

De KalbFulton

Fulton

Douglas

PauldingCobb

CherokeeForsyth

HallBanks

Jackson

Barrow

Haralson

Butts

Talbot

Alabama

TennesseeSouth Carolina

Georgia



Slide 30

_______________________________________________ ATLANTA __________________________________________________________ | Supermarket Composition and | Claritas Estimates NSUS Sample Representation | as of January 1,2004 as 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 Stores PUBLIX 135 YES | ACNielsen Control Estimates INGLES 70 YES | as of December 31,2001 SAVE RITE 43 YES | Number % US ACV ($000) % US BI 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 AL SUPERVALU YES | BALDWIN GA BANKS GA BARROW GA BARTOW GA PIGGLY WIGGLY ALABAMA DIS YES | BUTTS GA CARROLL GA CHATTOOGA GA CHEROKEE GA MERCHANTS DISTRIBUTORS YES | CLARKE GA CLAYTON GA COBB GA COWETA GA MITCHELL GROCERY YES | DAWSON GA DE KALB GA DOUGLAS GA FANNIN GA ASSOC 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



Slide 31

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



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 SCANTRACK® Trade Area - Cub Minneapolis

St. C ro ix

W right

Sherburne Isanti C hisago

Anoka

H ennepin

C arver

Scott D akota

R am sey

W ashington

Minnesota

W isconsin

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



Slide 33

________________________________________CUB TWIN CITIES TRADING AREA________________________________________________ | Supermarket Composition and | Claritas Estimates NSUS Sample Representation | as of January 1,2003 as 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 Stores RAINBOW (ROUNDY'S) 31 YES | ACNielsen Control Estimates BYERLYS 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 4,569,714 SUPERVALU 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 MN Trade 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 that cooperate in the sample in these counties. They include only Rainbow and Cub Foods for the Minneapolis Cub Comp Market



Slide 45

Products



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 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



Slide 47

Facts



Slide 48

• 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

Why is it important to understand facts?



Slide 49

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.



Slide 50

• Numbers tell you little by themselves.

• Usually you look at numbers in terms of other reference points

• Or you combine them with other information to form a conclusion, answer questions, set objectives, make plans, etc.

So, What Do I Do With the Numbers?



Slide 51

Analysis Tip – The 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

Competitive Activity

Other Factors

Promotion Support

(Quantity)

Promotion Effectiveness

(Quality)

Level of Support

Promo Mix

Promo Price

Price Discount

Competitive Activity



Slide 52

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

Level of Detail

Category

. Segments

Manufacturers

Competitive Brands

Your Brand

DistributionEveryday

Pricing

Trade SupportDiscount

Total Volume Trends Base vs

Incremental

Base & Incremental

Drivers

Recommended Level of Detail

Dependent upon level of chg

Incremental

Base



Slide 53

Volume and Share



Slide 54

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



Slide 55

Share

• Measures the % of sales that a product accounts for

• Influenced by two different measures–Brand Sales and

Category Sales



Slide 56

• 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

Share Activity



Slide 57

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



Slide 58


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 innovationExamples: 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 spaceExamples: Frozen departments, Checkout-aisle racks, coolers

Department Growth

Macro consumer trends affecting your category and related categoriesExamples: Categories affected by Low Carb diets, Convenience, Trans-fats

Equivalized Sales

When To Use – Volume Benchmarks

Use Benchmarks to compare category and brand trends



Slide 59

Different Ways to Look at Volume

TOTAL VOLUMETOTAL VOLUME

+PromotedVolume

PromotedVolume

Non-Promoted Volume

Non-Promoted Volume

+BaselineVolume

BaselineVolume

Incremental Volume

Incremental Volume



Slide 60

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.



Slide 61

Analysis Tip – Promoted 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 it’s

share of sales• Our competitor’s promoted volume share is under-indexed relative to it’s market share

Brand Share Trend

17.5

13.1

19.7

11.2

Our Brand Competitive Brand

Total Volume Share Promoted Volume Share



Slide 62

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



Slide 63

Baseline Calculation

week 1 week 2 week 3 week 4 week 5

170

Unit Sales

75 75 75 75

DisplayWeek



Slide 64

Baseline Calculation

170


Unit Sales

75 75 75 75

In Week 4 Baseline estimate would be 75 units based on pre and post week sales

75

DisplayWeek



Slide 65

Baseline Volume Includes Marketplace Conditions 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



Slide 66

• 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)

Reasons for Total/Baseline Volume Differences



Slide 67

Incremental Volume

• Represents the additional predicted volume that results from in-store promotion

• Calculation:Total Actual Volume -

Baseline Volume = Incremental Volume



Slide 68

Incremental Volume

Unit Sales

In Week 4 Incremental volume would be 95 units

170


75

DisplayWeek

95

75 75 75 75



Slide 69

How Can Incremental Volume Be Negative?

• If actual sales are less than expected sales– Out-of-stocks– Competitive activity


Unit Sales

75 75

75

75

Actual sales are below estimated Base – Incremental is negative 15 units

75

170

60



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 exWM

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 from base or incremental volume is a good way to start an analysis



Slide 71

Analysis Tip - Base and Incremental Volume

Base and Incremental trends will determine potential strategies



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 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

Incremental Volume = Promoted Volume



Slide 73


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

When to Use – Base, Incremental, Promoted, Non-Promoted Volume



Slide 74

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



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 Apr

May Ju

nJu

lAug

Sep OctNov

Dec

Sea

son

alit

y In

dex TOTAL BASELINE-UNITS



Slide 76

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



Slide 77

ACV Distribution and Velocity



Slide 78

Velocity

Baseline Volume

Distribution

Base PriceSeasonality*Advertising Support*Manuf. Coupons/FSI’s*Brand Awareness/Image*Product Quality*Weather*Consumer Promotions*Sampling

Competitive: Distribution Price Merchandising *Advertising *Coupons

% ACV(Breadth)

# of ItemsCarried(Depth)

* Non-Nielsen measures

Baseline sales can be impacted by different market factors.

Understanding the “Whys” to Changes in Baseline Volume



Slide 79

How Is Distribution Measured?



Slide 80

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



Slide 81

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?



Slide 82

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)



Slide 83

The 7 Food StoresIn This Market Sell$300,000 Per Week

JONES’s

D) $36,000 (12%)

JONES’s

A) $60,000 (20%)

SMITH’sSMITH’s

B) $48,000 (16%)

SMITH’sSMITH’s

C) $48,000 (16%)

SMITH’sSMITH’s

A) $36,000 (12%)

JONES’s

B) $36,000 (12%) JONES’s

C) $36,000 (12%)

SMITH’s Grocery Chain* Has 3 stores in the market doing $132,000 per week

for a total of 44% of the ACV

JONES’s Grocery Chain* Has 4 stores in the market doing $168,000 per week

for a total of 56% of the ACV

All Commodity Volume $ (ACV) Explanation



Slide 84

If These 3 Stores Sold YourProduct This Week,What Would The %ACV Be?

JONES’s

A) $60,000 (20%)

SMITH’sSMITH’s

C) $48,000 (16%)

SMITH’sSMITH’s

B) $36,000 (12%)

JONES’s

B) $36,000 (12%)

SMITH’sSMITH’s

B) $48,000 (16%)

JONES’s

D) $36,000 (12%)

JONES’s

B) $36,000 (12%)




Slide 85

JONES’s

D) $36,000 (12%)

SMITH’sSMITH’s

B) $48,000 (16%)

JONES’s

A) $60,000 (20%)

ANSWER: 20% ACV +16% ACV +12% ACV = 48% ACV




Slide 86

Breadth of Distribution -- % ACV

• % ACV Selling serves as a good weighting factor when measuring distribution.

• All stores are not created equal• Higher ACV stores serve more consumers

A measure of breadth, or reach, indicates how many consumers have the opportunity to buy the product



Slide 87

% 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.



Slide 88

Analysis Tip - % ACV Selling

Brand A Sales

Week 1

Week 2

Week 3

Week 4

4-Week Total

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 Wk Periods only!



Slide 89

Analysis Tip - % ACV Selling

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

% ACV Selling75

70

5567

4 wks endingApr

4 wks endingMay

4 wks endingJun

Latest 12 wksAVG

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



Slide 90

Depth of Distribution

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




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% 95Flavor 2 90% 90Flavor 3 80% 80Flavor 4 30% 30

}Sum =295




Slide 92

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.

% ACV CDP

Brand A 100% 2100Brand B 100% 990

%ACV tells us breadth of distribution

CDP tells us depth of

distribution



Slide 93

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.

AVG # % ACV CDP Items

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




Slide 94

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



Slide 95

Analysis Tip – Cumulative Distribution Points

CDP’s 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 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.



Slide 96


Breadth of distribution – the number of stores carrying your product

% ACV Selling

Trending overall depth or quality of distribution over time

Cumulative Distribution Points;Total Distribution Points

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

When To Use - ACV facts



Slide 97

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



Slide 98

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.



Slide 99

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



Slide 100

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)

CDI/BDI MEASURES



Slide 101

% 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.

CDI/BDI MEASURES

Population Development Index—The importance of product sales compared to the importance of the population in a market.

How to calculate a Development index...



Slide 102

Analysis Tip – CDI/BDI

Use CDI/BDI’s to prioritize market opportunities



Slide 103

Analysis Tip – CDI/BDI

Calculate an Opportunity Index to further prioritize markets

CDI BDIOppy Index

Chicago 106 95 112

Indianapolis 159 116 137

How to calculate an Opportunity index...

CDIBDI

X 100 = Opportunity Index

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



Slide 104

Promotion, Promotion Effectiveness and Pricing



Slide 105

Understanding the “Whys” to Changes in Incremental VolumeIncremental sales can be impacted by different merchandising factors.

Promotion Support(Quantity

Incremental Volume

Promotion Effectiveness(Quality)

Level of Support • Promotion Mix

• Level of Price Discount• Competitive Conditions in Promoting Stores

• Promotion Price




Slide 106

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

Sales

What could cause this spike in sales?

Promotions



Slide 107

Promotion Types

• 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

Nielsen measures three types of trade promotions



Slide 108

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



Slide 109

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.



Slide 110

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



Slide 111

Promotion Conditions

Promotional Conditions are mutually exclusive at the UPC level. A UPC is either Promoted or Not Promoted.

Price Decrease

(TPR)

Feature w/out

Display

Displayw/out

FeatureF&D



Slide 112

Promotion Support

• % 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

Three ways to view Quantity of trade supportUse 1 Wk

Periods only!



Slide 113

% ACV Support

• 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




Slide 114

Store Weeks Support

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 of Display activity in the five-week period



Slide 115

% Base Support

• 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

Measures the % of Base business exposed to a particular promotion type



Slide 116

% Base Support Calculation Example

Base Sales Promotion?

Store 1 10 No

Store 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%

Interpretation – 63% of the brand’s base volume was exposed to a feature during the promotion period



Slide 117


Level of trade participation in an event;Amount of consumer traffic exposed to promotions

% ACV Support

Duration of support Store Weeks Support; Cume Weighted Weeks

How much of a brand’s base volume was exposed to a promotion

% Base Support

When To Use – Promotion Support facts



Slide 118


Measures how much incremental volume each promotion generated

• Percent Lift• Promotion Effectiveness Index (PEI)• Incremental Weeks • Efficiency



Slide 119

Promoted Baseline Volume

Promoted

Non- Promoted

Incremental

Base Non-Promoted Base

Promoted Base

Incremental that is a result of promotion

Also Known as

Subsidized Base



Slide 120

Promoted Baseline Volume

In Week 4 all the volume is promoted, but only 95 units are incremental; 75 units are subsidized base

170


Unit Sales

75 75 75 7575

DisplayWeek

95



Slide 121

Promotion Efficiency

• 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 generated during a promotion the less efficient that promotion will be!

Incremental SalesPromoted Sales

x100



Slide 122


• 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 each promotion generated

Promoted SalesPromoted Base Sales

x 100


- 1


x 100 - 100



Slide 123

Analysis Tips - Interpreting Promotion Response

PEISales indexed at 227 vs. base during the promotion week

% LiftThe promotion drove a127% increase in sales

Incremental WeeksThe promotion generated1.3 additional weeks of sales

Promotion Efficiency56% of the promoted volumewas incremental to the brand

170

17075

x 100 - 100 = 127%

17075

- 1 = 1.27

week 4

75

DisplayWeek

95

95170

x 100 = 56%

17075

x 100 = 227



Slide 124

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



Slide 125


Measuring the increase in volume due to promotions;Determining which promotions generate the largest incremental gains

% Lift;Promotion Effectiveness Index (PEI);Incremental Weeks

Measuring the ability of a promotion to minimize subsidizing existing volume

Promotion Efficiency

When to Use – Promotion Effectiveness Facts



Slide 126

Pricing

Nielsen databases track pricing in four ways:

• Average Retail Price–Weighted price of a product, representing both non-

promoted 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



Slide 127

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 non-promoted stores



Slide 128

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



Slide 129

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



Slide 130

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



Slide 131

When to use – Pricing Facts


What consumer is paying on average Average Retail Price

What is the average price for an item when not on promotion

No Promo Price

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



Slide 132

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



Slide 133

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

• Identify targets for number of items on feature or display• Provide consumer incentives for purchase of multiple items

A decrease in Promoted Velocity

• 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

A decrease in Promotion Efficiency

• Improve event timing / frequency • Improve Customer Targeting (loyals vs. switchers)



Slide 134

Wrap Up

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