ACNielsen Retail Audit Service Introduction
AC尼尔森公司历史
1923年成立于美国芝加哥, 创始人是阿瑟.查尔斯.尼尔森先生
20年代创立了零售追踪研究和“市场份额”这一概念
30年代,开始国际扩张
40年代开始进行收音机节目收听调查
50年代开始电视收视调查
80年代开始利用电子扫描数据进行市场调查
90年代通过收购SRG深入亚太市场
2001年与荷兰著名媒介资讯公司VNU(2001年美国《商业周刊》全球公司排名第517位)合并
AC尼尔森公司目前的市场地位
AC尼尔森是全球最大的市场研究公司
年度营业金额超过15亿美元
业务在全球的覆盖100多个国家和地区
全方位的市场研究服务:
专项研究服务
媒介研究服务
零售研究服务
网络资讯服务
AC尼尔森公司中国的业务发展历程
1984年以SRG的身份进入中国, 成为第一家进入中国市场的国外市场研究公司
1998年正式更名为AC尼尔森
目前在中国的三大业务范围
专项研究服务
媒介研究服务
零售研究服务
我们的服务
三种核心服务
AC尼尔森三大核心服务:
提供整体解决方案
个案研究
媒介研究
零售研究
营销管理中的市场研究
生产厂家
需求...
消费者
通过消费者研究:
目标人群的消费习惯等
研制满足需求的产品
随时跟踪其对产品的认知程度和态度
通过媒介研究:
目标人群接触媒介的习惯和规律
选择适当的媒体刺激目标人群的相关需求
监测同业在媒体的投放量,调整媒体投放计划.
直销
机关团体消费
批发
零售
零售研究
零售指数跟踪调查
(Retail Tracking)
Our Retail Products
Space
Management
MID
Advisor
National retail
market study
Continuous
retail tracking
In-store
Observations
Sabine
Casual
Data
Leader Panel
RETAIL MEASUREMENT
SERVICES
Retail Market Study
Provide update sampling frame for on-going retail services
The most detailed and comprehensive study currently available on the retail market in China.
Provide full pictures of retail market structure
Provides guidelines for improving market penetration.
Discover which channels and outlets to distribute through.
Retail census information is a powerful and cost effective tool for sales planning - essential for identifying where to distribute your products, and for establishing regional targets.
Includes:
Retail universe structure
Distribution of over fifty
product categories
Incidence of retail
facilities
Store names, addresses,
and characteristics
National Retail Market Study
Basic Methodology
The Retail Census was conducted by using traditional enumerator methods of data collection. Interviewers were given a map to follow, and visited blocks falling within predefined boundaries in order to record the names, addresses, and characteristics of retail outlets selling FMCG products.
National Retail Market Study
History: Conducted on annual basis
1996 & 1997 City Coverage :-
100 Cities throughout China
1998 City Coverage :-
3 Cities throughout China
1999 City Coverage :-
121 Cities throughout China
From 2000 rolling study instead of full study:
Key City, A city, BCD city
National Retail Market Study-Geographic Coverage
NORTH
N1- HEILONGJIANG, JILIN, LIAONING
N2- HEBEI, SHANDONG, SHANXI, TIANJIN
BAL. OF BEIJING MUNICIPALITY
BJ - METROPOLITAN BEIJING
EAST
E1 - JIANGSU, ZHEJIANG,
BAL. OF SHANGHAI MUNICIPALITY
E2 - ANHUI, HENAN
SH - METROPOLITAN SHANGHAI
WEST
W1- SHAANXI,
SICHUAN (EXCL. CHENGDU)
W2- GUANGXI, GUIZHOU, YUNNAN
CD - METROPOLITAN CHENGDU
SOUTH
S1 - HUBEI, HUNAN
S2 - FUJIAN, JIANGXI
GD - GUANGDONG
GZ GUANGZHOU
BOG BAL. OF GUANGDONG
PRD PEARL RIVER DELTA
BEIJING
SHANGHAI
CHENGDU
GUANGZHOU
W2
N2
E2
W1
S1
S2
N1
E1
GD
Cities & Town Governments / Townships
excludes Villages
Geographic Coverage: In about 200 cities in two years with over 100 cities covered each
year, a sample census to estimate total market conditions
Individual City Retail Market Study
Harbin
Changchun
Shenyang
Beijing
Tianjin
Shijiazhuang
Taiyuan
Jinan
Zhengzhou
Shanghai
Nanjing
Hangzhou
Hefei
Wuhan
Xian
Nanchang
Fuzhou
Changsha
Guangzhou
Nanning
Guiyang
Chengdu
Kunming
Qingdao
Shenzhen
Dalian
Chongqing
Ningbo
Xiamen
Wuxi
Suzhou
31 cities in total
Information can be
more flexible
Time can be more
free
Census to
insight City level
City Basic Report
Contents:
Shop Type by Sales Area; Shop Type by Monthly Sales Turnover Ranges
Aggregate Product Category Penetration;
Aggregate Retail Facility Availability
Format:
Hardcopy
Softcopy
City Store Listing
Contents:
Shop Name, Shop Address, Sales Area, Shop Type；
Retail Facility Availability : Air Conditioning, Refrigeration Facilities
Incidence of Product Categories Carried by Shop Type
Format:
Softcopy as Excel file
National Retail Market Study--Report
For Category BBB, overall FMCG shop penetration is 56%. Are you satisfied with this penetration rate? Is your expenditure justified by this rate?
Example - Basic Report Format
National Retail Market Study-Report
National Retail Market Study-Report
Example-Store Listing report
Example - Route Map of Shanghai
National Retail Market Study-Report
Hard Copy
Not softcopy
Continuous Retail Tracking
The Retail Tracking Concept
......continuous tracking of product movement through retail outlets.......
volume movement plus in-store activities
Providing the opportunity to measure at one source
Manufacturers Effort
distribution gains, the impact of promotional activity, range review, etc.
Retail Support
retail purchase trends, shelf volume, out-of-stock, etc.
Consumer Off-take
most IMPORTANTLY the consumers reaction, not just the retailers reaction
Why Retail Tracking ?
Historically Ex-factory data has been the only method of monitoring your performance in the market
Ex-factory data doesn’t provide an insight into :
the market, retailer support and most importantly COMPETITOR ACTIVITY which is becoming increasingly important as promotional activity becomes more aggressive
FOR EXAMPLE :-
Ex-Factory shipments are growing at 10% per annum
Year 1989 1990 1991 1992 1993 1994
Units 100 110 121 133 146 161 + 10%
......is everything OK ?
Why Retail Tracking ?
200
240
288
346
415
498
Total Market +20%
Competitors +28%
Our Brand +10%
1989
1990
1991
1992
1993
1994
Maybe not........
Retail Tracking is :-
the only independent and accurate measure of the market
the only way to monitor your performance & your competitors performance
the only measure of retailer support for your brands
the only true measure of consumer preference
Uses of Retail Tracking ?
Retail Tracking provides a factual basis for understanding
consumer purchasing
competitive performances
market conditions . Flavour / pack size trends, etc.
the impact of promotions
pricing activity
in-store support . share of shelf, out of stocks, etc.
etc. Retail Tracking can prove to be a useful tool for......
MARKETING:
How does demand vary by region ?
Where are consumers buying our product ?
Is our new product cannibalising sales of the old ?
How are our competitors performing ?
What effect have other brands had on our product ?
How is the category performing ?
Who is driving category growth ?
SALES:
What is our distribution by region ?
Where can we improve upon this ?
Are supply problems hindering our performance ?
Establishing sales objectives . what's my competitors distribution etc
Uses of Retail Tracking ?
ACNielsen Retail Tracking
Methodology
FIVE STEPS OF RETAIL TRACKING
Establish the Universe
Define store types and gain information on shop numbers & turnover
Design a representative sample
How many of each store type do we need to represent the
universe?
Data collection
at retail store level
Statistical expansion of sample to
universe
Reported Outputs
FIVE STEPS OF RETAIL TRACKING
Establish the Universe
Define store types and gain information on shop numbers & turnover
Design a representative sample
How many of each store type do we need to represent the
universe?
Data collection
at retail store level
Statistical expansion of sample to
universe
Reported Outputs
Establish the Universe
THREE DISTINCT STAGES:
Establish the Universe to be Measured
which regions of China is the retail audit going to measure
Define Store Types
in order to design a representative sample
Collect Information on Store Numbers & Turnover
conduct a retail census to determine the importance of each store group
i ) Universe to be Measured
- Geographical Coverage
National (City + Town) Service
NORTH
N1- HEILONGJIANG, JILIN, LIAONING
N2- HEBEI, SHANDONG, SHANXI, TIANJIN
BAL. OF BEIJING MUNICIPALITY
BJ - METROPOLITAN BEIJING
EAST
E1 - JIANGSU, ZHEJIANG,
BAL. OF SHANGHAI MUNICIPALITY
E2 - ANHUI, HENAN
SH - METROPOLITAN SHANGHAI
WEST
W1- SHAANXI,
SICHUAN (EXCL. CHENGDU)
W2- GUANGXI, GUIZHOU, YUNNAN
CD - METROPOLITAN CHENGDU
SOUTH
S1 - HUBEI, HUNAN
S2 - FUJIAN, JIANGXI
GD - GUANGDONG
GZ GUANGZHOU
BOG BAL. OF GUANGDONG
PRD PEARL RIVER DELTA
BEIJING
SHANGHAI
CHENGDU
GUANGZHOU
W2
N2
E2
W1
S1
S2
N1
E1
GD
Cities & Town Governments / Townships
excludes Villages
ii ) Define Store Types
A set definition of store types is needed
this is done by looking at the types of products which they sell and those products importance to a stores business
There are 15 defined FMCG store types within the universe, which are grouped into three reported market breakdowns:-
HYPER/ SUPERMKT/ DEPT/ GROC/KIOSK MISC STORES
Hypermarket
Department Store Grocery Cosmetic Store
Supermarkets Kiosk Barber Shop
Convenience Store Cigarette Speciality Store
Wine/Spirit Speciality Store
Western Drug Store
Chinese Drug Store
Soft Drinks/Ice Cream
Retail Tracking Market Position
MANUFACTURER
DISTRIBUTOR
WHOLESALER
FMCG RETAIL OUTLET
Retail Tracking
Retail Tracking monitors consumer and retailer activity within
a defined Retail Channel - FMCG Retail Outlets
CONSUMER
Retail Audit Channel Coverage
Retail audit monitors sales in defined FMCG retail outlets.
Supplier
Work Units
Wholesalers
Institutions
Consumer
Defined FMCG
Retailers
FIVE STEPS OF RETAIL TRACKING
Establish the Universe
Define store types and gain information on shop numbers & turnover
Design a representative sample
How many of each store type do we need to represent the
universe?
Data collection
at retail store level
Statistical expansion of sample to
universe
Reported Outputs
Design a Representative Sample
Methodology
To ensure that the retail audit produces the most accurate results, it is a “stratified, disproportionate, systematic, random sample”.
The sample is organised into “strata”
Each of which represents a different sub-region / city
Within each sub-region / city the sample is then further organised into individual “cells”
Each cell represents a group of stores for which independent sales projections are calculated.
The sample is “disproportionate”
We over sample the most important store types
This technique of is used to ensure that sampling error is reduced in the most important strata
Stratified Sampling
Extra Large Supermarkets within
“B” City of the South 2 Region
= SAMPLE CELL
Extra Large Supermarket
Large Supermarkets
Medium Supermarket
Small Supermarket
Super Grocery
“B” CITIES
“C” CITIES
N
o
r
t
h
1
N
o
r
t
h
2
S
o
u
t
h
1
S
o
u
t
h
2
“A” CITIES
Disproportionate Sampling
Universe
Store No. (%)
Sales
Importance (%)
Disproportionate
Sample
(% of Sample Stores)
10
58
32
45
35
20
30
55
15
Misc Stores
Grocery/Kiosk
Hyper/Supermarket/CVS
The above is an example and does not represent the China FMCG Universe / ACNielsen Sample Location
Systematic Random Sampling
2
3
4
1
Etc.
Ranking of store
FMCG Turnover
900
800
700
1000
Etc.
Rank the stores within the individual sample cell in terms of FMCG turnover
Systematic Random Sampling (Cont’d)
If there are 10 stores in the sample cell, and it is decided that 5
sample stores should be selected…..
Select one sample
store randomly
Systematically select the other sample stores down the list
2
3
5
6
8
7
9
1
10
4
SAMPLE CELL
Small
Supermkts
Shanghai
FIVE STEPS OF RETAIL TRACKING
Establish the Universe
Define store types and gain information on shop numbers & turnover
Design a representative sample
How many of each store type do we need to represent the
universe?
Data collection
at retail store level
Statistical expansion of sample to
universe
Reported Outputs
Data Collection
Manual Data collection
Full-time field auditors
Information is collected on :
A fixed format data collection sheet unique to each store
Listing those products active in the store during the previous period
The information recorded during the store audit includes:
Retail Stocks
Retail Purchases
Price
Based on the collected information, we calculate:
Consumer sales
Distribution
Out-of-Stocks, etc.
Consumer Sales
Previous period closing inventory 200 units
Purchases into the store + 500 units
Total available stock = 700 units
Current period closing inventory - 300 units
Consumer Sales = 400 units As average Retail Selling Price (RSP) for the products is recorded on the day of audit we can calculate value sales for the individual stores By dividing value and volume sales at a total market level the markets average RSP can be calculated
Audit Timing
Each store is audited on a fixed cycle:-
There are two audit cycle. Cycle 1 Audit Begins Audit Ends Cycle 2 Audit Begins Audit Ends
Jan-Feb Feb 1 Feb 28 Feb-May Mar 1 Mar 30
Mar-Apr Apr 1 Apr 30 Apr-May May 1 May 31
The Mar-Apr period, for example, reflects :-
Sales which occurred since the end of the previous audit on February 28th
The average in-store position of inventories, distribution & out-of-stocks is April 15th
Understanding audit timing is very important when :-
comparing data to factory shipments
analysing stock situations
monitoring the promotional / brand launches
FIVE STEPS OF RETAIL TRACKING
Establish the Universe
Define store types and gain information on shop numbers & turnover
Design a representative sample
How many of each store type do we need to represent the
universe?
Data collection
at retail store level
Statistical expansion of sample to
universe
Reported Outputs
Statistical Expansion of Sample
NUMERIC PROJECTION
Each individual cell is expanded to represent its universe: -
taking into account the sample cells size relative to the universes size
For Example :-
Cell Universe No’s = 100
Sample Store No’s = 10
Factor = 10
The data from each sample store in the cell is expanded
by 10 to represent the universe
SH Small Supermkt
SH
SUPERMARKETS
SH large Supermkt
SH Medium Supermkt
SH Extra-large Supermkt
SH Super Grocery
Expansion Methodology
Numeric Projection
Assumes that sample turnover = universe turnover
HOWEVER in practice this might not be the case
ACV Ratio Adjuster
Therefore an ACV Adjuster is applied to validate the numeric projection factor to ensure that the sample turnover = universe turnover
The adjuster dampens changes in the raw data caused by sample changes
ACV Ratio Adjustment
Sample Shop Category Sales ACV Sales
Shop A No 25 95
Shop B Yes 10 50
Shop C No 10 40
Shop D Yes 4 10
Shop E No 1 5
50 200 Sales under Numeric Projection
= (raw sales) * (universe / sample size)
= (10 + 4) * (5 / 2) = 35
Sales under Ratio Estimation
= (raw sales) * (ACV of universe / ACV of sample)
= (10+4) * (200 / (50+10)) = 47 more accurate result
FIVE STEPS OF RETAIL TRACKING
Establish the Universe
Define store types and gain information on shop numbers & turnover
Design a representative sample
How many of each store type do we need to represent the
universe?
Data collection
at retail store level
Statistical expansion of sample to
universe
Reported Outputs
Reported Outputs
Delivery Method
Electronic Delivery
Advisor
What is Reported
Products
Market, segments, full brand itemisation to individual SKU
Timescale
Bi-monthly/Monthly
Markets
National (City+Town), Four Regions, Four Reported Cities
By region & city we itemise by shop type
Department / Supermarket, Grocery / Kiosk, Misc Stores
Facts
Complete Fact Set
Reported Data Types
Consumer Volume & Value Sales/Shares
enabling you to identify market trends and determine your brands relative performance vs. your competitive set
Retailer Purchases
does your brand have retailer support, are supply problems hindering performance ?
Average Retail Selling Price
which price segments are driving category growth ?
Retail Stock Levels (Total, Reserve & Forward)
does your brand have adequate stock levels and share of shelf ?
Stock Cover Days
how many days stock do you have in the trade ?
Distribution (% of Outlets & Importance to the Category)
how many outlets handle your brand, distribution opportunities, what levels of distribution have your competitors achieved ?
Out of Stock
are out of stocks hindering your performance, what’s the cost, what’s the cause?
Reported Outputs
ACNielsen Retail Report Components
ACNielsen 零售研究的组成要素
Market(市场范围)
Where(在哪里？)
Product(产品范围)
Which Category/Brands?(何种产品,哪个品牌?)
Period(时间范围)
When(何时？)
Fact Type(数据范围)
What Happen?(发生了什么？)
ACNielsen Retail Report components -
Markets
ACNielsen零售研究覆盖的地区
北1
北2
西1
西2
南1
南2
东1
东2
广东
北区
北1 黑龙江，吉林，辽宁
北2 河北，山东，山西，天津
北京其他地区
北京 北京市区
南1 湖北, 湖南
南2 福建, 江西
广东 广东省
广州 广州市
PRD 珠江三角洲
BOG 广东其他地区
东1 江苏, 浙江
上海的其他地区
东2 安徽, 河南
上海 上海市区
西1 陕西, 四川 (除成都)
西2 广西, 贵州, 云南
成都 成都市区
西区
南区
东区
城市、乡/镇，不包括农村
ACNielsen零售研究行政级别划分
划分:
Total City : A, B, C, D 城市
Total Town: Town government, township
定义:
A city : 包括: 省会城市、自治区首府城市、直辖市（重庆市、天津市)外
加地级市大连，青岛和深圳。
B city : 指所有除上述城市以外的其它地级城市。
C city : 县级市政府所在地。
D city : 县政府所在地的镇。
Town Government : 指除县政府所在地的镇以外的其它所有的镇政府所在地。
Township : 指所有的乡政府所在地。
全国市场分层
总体乡/镇
总体城市
西区
南区
东区
北区
总体其他商店
总体食杂/零售亭
总体百货/超市
中国
城市+乡镇
总体A类城市
东区市场分层
(西区，北区市场分层相似)
东区乡镇
东区城市
东区其他商店
东区食杂/零售亭
东区百货/超市
上海市
东 2
东 1
东区
上海百货/超市
上海食杂/零售亭
上海其他商店
东区A类城市
南区市场分层
南区乡镇
南区城市
南区其他商店
南区食杂/零售亭
南区百货/超市
广州其他商店
广州食杂/零售亭
广州百货/超市
广州市
珠江三角洲
广东其他地区
广东省
南 2
南 1
南区
南区A类城市
ACNielsen Retail Report components -
Product
牙膏产品定义
目的: 确定所研究产品具备哪些特性，用以帮助数据采集人员判断哪些产品应被包括在研究范围内。
Definition 产品定义
任何与牙刷连用的用于清洁天生牙齿的物制剂。
包括可以声称有以下附加的功效:
-散发任何一种香味
-控制牙石
-控制牙垢膜
-保持口腔清洁或除口臭
-使牙齿增白并清除茶迹，烟迹，咖啡迹
-能够清洁天生牙齿及假牙
Broad guidelines for exclusion 产品不包括
牙齿上光增亮剂
牙粉
口腔清洗剂 / 漱口水
只适用于假牙的清洁剂
酒店专用的小支装牙膏
产品分类
Flavor 味道（按包装的前后描述，香型如有重复按下面的先后顺序）
Mint 薄荷：包括留兰香.冰凉薄荷.清凉薄荷及其他有薄荷字样的香型。
Fresh 清新 ： 指清新香型，不包括清新口气。只有‘清新’字眼可看作清新香型
Regular 普通：没有注明味道的产品。
Fruity 水果味：单一水果味或一种以上的水果味
Salt 咸味
Others 其他
Medication药物牙膏（按包装的主要描述）
Medicated 药物牙膏 ( 包含中药和西药成分 ) 例如：中草药牙膏
Non-medicated 非药物牙膏
Target Market 目标市场
Child 儿童：括各种学生产品。
Adult 成人：包括青少年产品
目的: 将收集到的产品按照可观测到的、可描述的
特性尽可能的分到单品(SKU)。
产品描述举例
COLGATE(CDC)
COLGATE(CDC) LO
COLGATE(CDC) LO ANTI
COLGATE(CDC) LO ANTI 1X120 GM
COLGATE(CDC) LO ANTI 1X120 GM MINT
COLGATE(CDC) LO ANTI 1X120 GM MINT REG
COLGATE(CDC) LO ANTI 1X120 GM MINT REG ADULT
COLGATE(CDC) LO ANTI 1X120 GM MINT REG ADULT PASTE
COLGATE(CDC) LO ANTI 1X120 GM MINT REG ADULT PASTE NON-MED
产品报告单位
报告单位： 升（Liter）
转换关系：1毫升=1克
ACNielsen Retail Report components -
Period
报告的时间范围及形式
双月报告
单月报告
好处：市场表现的趋势和各个阶段的比较：
MAT VS. MAT, CURRENT PERIOD VS. PREVIOUS PERIOD, CURRENT PERIOD VS. SAME PERIOD OF LAST YEAR
报告提供形式
Inf*Act / Advisor
报告提供时间
完成核数后的四个星期内.
ACNielsen Retail Report components -
Fact Type
ACNielsen 零售研究的市场反映模式
零售商的支持
零售商的进货
零售商的努力
库存的控制
零售价格
消费者的反映
购买
生产厂家的努力
铺货率
（广度和质量）
生产厂家的
销售队伍
分销商
批发商
消费者
零售商
进入零售商店
卖出零售商店
数值总体铺货率(Numeric Total Stock Distribution)
表示在核数周期内经营某种产品的零售店数量占零售店总体数量的百分比。 - 代表铺货的广度.
- 数值：店数的比重
加权总体铺货率(Weighted Total Stock Distribution)
指在核数期内经营某种产品的零售店，其经营该类产品的零售额占该类产品总体零售额的百分比。 - 加权：这些商店经营某类产品的总体零售额（不论品 牌、 单品等）的比重.
- 代表所铺的店可能为我们的品牌带来的销售机会，但加权总体铺货率的高低与市场份额的高低并不一定完全成正比。
生产厂家的努力
100
生产厂家的努力
=10
1
1
1
1
1
1
1
1
1
1
某城市FMCG零售商店共10间
各店咖啡类产品的零售额占此城市 所有FMCG零售店咖啡类产品零售总额的百分比
10间商店中有8间经营咖啡类产品，品牌A在4间店中有售。因此品牌A的:
数值总体铺货率是：40%
加权总体铺货率是：80%
30
20
15
15
4
4
7
5
0
0
=100
生产厂家的努力
总体铺货： 该期曾有进货或售卖记录
核数当天是否有售卖该品牌/单品
无：缺货
有：存货
生产厂家的努力
数值缺货率(Numeric Out-of-Stock Distribution)
指在核数期内经营过某种产品，但在核数日当天该产品
缺货的零售店的数量在零售店总体中的百分比。
加权缺货率(Weighted Out-of-Stock Distribution)
指在核数期内经营过某种产品，但在核数日当天该产品
缺货的零售店，其经营该类产品的零售额占该类产品总
体零售额的百分比。
缺货率的高低如何判定？何时需要采取行动？
趋势：
缺货率是否呈现长期上升的趋势？
比较：
与总体品类比。与竞争对手比。
与自己过去比。
综合考虑数值和加权：
是否在重要的店缺货（数值低但加权很高）？
100
生产厂家的努力
=10
1
1
1
1
1
1
1
1
1
1
零售商店
咖啡类产品零售总额的百分比
同样的例子, 但是假设品牌A在98年四五月份核数日当天在商店a有缺货现象，那么品牌A的:
30
20
15
15
4
4
7
5
0
0
=100
a
数值
总体铺货率 缺货率 存货率
加权
总体铺货率 缺货率 存货率
40% 10% 30%
80% 20% 60%
生产厂家的努力
数值存货率(Numeric In-stock Distribution)
指在核数期内经营过某种产品，而且在核数日当天该产
品仍然有售的零售店的数量在零售店总体中的百分比。
加权存货率 (Weighted In-Stock Distribution)
指在核数期内经营过某种产品，但在核数日当天该产品
仍然有售的零售店，其经营该类产品的零售额占该类产品
总体零售额的百分比。
ACNielsen 零售研究的市场反映模式
零售商的支持
零售商的进货
零售商的努力
库存的控制
零售价格
消费者的反映
购买
生产厂家的努力
铺货率
（广度和质量）
生产厂家的
销售队伍
分销商
批发商
消费者
零售商
进入零售商店
卖出零售商店
零售商的支持
数值进货铺货率(Numeric Purchase Distribution)
指在核数期内，购进某种产品的零售店的数量占零售店总体数量的百分比。
加权进货铺货率(Weighted Purchase Distribution)
指在核数期内，购进某种产品的零售店，其零售该类产品的金额占该类产品总体零售金额的百分比。
零售商的支持
进货量(Purchase)
指零售商采购某一特定品牌或库存单元的数量。通常用原始单位或者转换过的单位（如：升，公斤等）表示。
进货份额(Purchase Share)
指一特定品牌或库存单位在其总体市场或某一细分市场的进货量中所占的百分比。 对我们品牌的进货支持是否高于竞争对手？
零售商的支持
总结
在某一特定地区的零售市场：
零售商对整个产品类型、不同品牌的进货量趋势
某段时间内，有进货记录的零售商店在数量上是否稳定、重要的零售商是否持续进货。
未来消费者购买发展趋势的基础
ACNielsen 零售研究的市场反映模式
零售商的支持
零售商的进货
零售商的努力
库存的控制
零售价格
消费者的反映
购买
生产厂家的努力
铺货率
（广度和质量）
生产厂家的
销售队伍
分销商
批发商
消费者
零售商
进入零售商店
卖出零售商店
零售商的努力
铺面库存量(Forward Stock)
指在核数日当天，那些展示在店内的能被消费者看到并作出反应的货品数量。通常用原始数量单位或转换后的数量单位（如：升、公斤等）表示。
后备库存量(Reserved Stock)
指存放于店内无法被消费者直接见到并作出反应的货品数量。通常用原始数量单位或转换后的数量单位（如：升、公斤等）表示。
铺面库存量
+ 后备库存量
= 总体库存量
零售商的努力
总体库存量(Total Stock)
某一品牌或库存单位在核数日当天的铺面库存量和后备库存量的总和。通常用原始数量单位或转换后的数量单位（如：升、公斤等）表示。 - 能售卖的最大的量。
总体库存份额/铺面库存份额(Total/Forward Stock Share)
指一特定品牌或库存单元占其总体市场或某一细分市场的总体库存量/铺面库存量的百分比。 - 给我们的品牌的货架空间是否足够，是否比竞争对手的多？
存货天数(Stock Cover Days)
以零售店某类产品现在的销售速度， 所有库存全部销售完
所需的天数。（假设在此期间无库存补充）。 - 大概多久需要补货才能够减少出现缺货的机会？
百事可乐 600ml pet
97年二/三月
零售量: 305 升
每天零售量: 305/61=5
库存: 105 升
库存天数: 105/5=21
零售商的努力
库存周转次数(Stock Turn)
指一年内某类商品全部库存在一段时期内销售完的平均次数。
库存天数: Pepsi 600ml Pet
二/三 四/五 六/七 八/九 十/十一 十二/一
21 23 19 22 20 21
平均库存天数: 21
库存周转次数: 365/21=17
零售商的努力
零售价格
平均零售价格(Average Price)
指某一产品在零售市场的平均零售价 （总体零售金额除以总体零售量）。
单位包装平均价格(Price Per Pack)
指一特定品牌的某一库存单元在零售市场的平均零售价格。
.怡宝纯净水330毫升
商店 单价 零售量 零售量 * 单价
1 260 325
2 200 260
3 300 384
4 600 720
总计 1,360 1,689
单位包装价…………………………. (1,689/1,360)
零售商的努力
总结
在某个地区：
零售商对某种产品类型，不同品牌库存的管理：店面库存和后备库存的分配
零售商对不同品牌、包装单位在货架空间上的分配
不同品牌，包装单位的平均库存天数与同类产品平均水平的比较。
不同品牌，包装单位的平均库存周转次数与同类产品平均水平的比较。
某种产品类型、各品牌、包装单位在何种价格附近产生的销售最多。
ACNielsen 零售研究的市场反映模式
零售商的支持
零售商的进货
零售商的努力
库存的控制
零售价格
消费者的反映
购买
生产厂家的努力
铺货率
（广度和质量）
生产厂家的
销售队伍
分销商
批发商
消费者
零售商
进入零售商店
卖出零售商店
消费者购买
零售量(Sales Volume)
零售商店卖给最终消费者的零售品数量。通常用原始单位或者转换过的单位（如：升，公斤等）表示。
零售额(Sales Value)
零售商店卖给最终消费者的零售品金额 （人民币）。
零售份额（数量/金额)(Volume/Value Share)
某一产品类别、公司或某一品牌在市场上所占的百分比。
消费者购买
在某地区、从不同的商店类型：
消费者购买某种产品类型在数量、金额上的变化趋势
消费者购买该类产品中不同特性产品的变化趋势
不同产品所占购买份额的变化
生产厂家、零售商努力的最终反映， 同时也是影响生产厂家、零售商未来努力方向的指南。
Let’s work for your success!
Thank you！
Guangzhou ACNielsen Ltd.
Retail Measurement Service
Client Service Unit
Questions:
Why did we just conduct 3 cities census in 1998?
Because before 1998, we conducted full census in more than 100 cities
in 1996 & 1997. The methods were (take 1997 as an example):
we recruited campus students to interview all blocks in the city from
July of the year, therefore, in the end of same year, E&C can finish
data entry work. Then in the early of 1998, Statistic can check census
results,and conduct validation. Later on, they will put all the results into
retail audit database, but it’s nearly the end of 1998, which means,
retail audit database of late 1998 has to be adjusted by middle 1997
retail market results. It is not so well to reflect retail market picture in
1998.
In order to fast reflect retail market picture in our on-going retail
service,we decided to adjust our pace. In 1998, we just conducted
three key cities census(BJ/SH/GZ), since their retail market is fast
ever-changing. And in the early of 1999, we began full census. Thus
at the end of same year, we could put 1999’s census result into 1999
retail audit database.
Questions:
Does Acnielsen conduct census in each country?
No. Only in China, we conducted retail market study since we could not
find related information in Government Statistic book. And we do it each
year due to rapid retail market environment development and
Why does Acnielsen’s retail market study not cover all geographic
areas in China?
It can be explained from the following aspects:
- Seven provinces(InnerMongolia,Tibet,Xinjiang,Ningxia,Gansu,Qinghai
and hainnan) are excluded. Even though these provinces cover
around 50% geographic areas, population(target consumers) here are
rather small and their retail turnover just contribute about 10% of the
total country.
- Villages are not included, even though target consumer can occupy
70% of total country. Since their contribution to retail turnover is
about 20% of the total country, and it costs much to conduct census,
(clients have to share high cost)
