Household Panel Data Reference
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Household Panel Data Reference. Household Panel Data Analyses. The types of analyses that can be done with Household Panel data can be broadly classified to address the following issues:. Understanding Basic Purchase Behavior Market Summary Reports Purchase Dynamics Deal Measures

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Household Panel Data Reference

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Household panel data reference

Household Panel Data Reference


Household panel data reference

Household Panel Data Analyses

The types of analyses that can be done with Household Panel data

can be broadly classified to address the following issues:

  • Understanding Basic Purchase Behavior

    • Market Summary Reports

      • Purchase Dynamics

      • Deal Measures

  • Identifying Key Target Groups

    • Demographics

    • Purchase Behavior

      • Heavy/Light

      • Loyal

      • Deal Sensitive

  • Evaluating New Product Introduction

    • Trial & Repeat

    • Source of Volume

  • Other Diagnostics

    • Combination Purchasing

    • New/Lost/Retained Buyer Flow Analysis

    • Shopping Expenditures

    • Market Structure/ Segmentation Study


Household panel data reference

Basic Applications

  • Market Summaries

  • Purchase Distributions (H/M/L)

  • Demographic Profiles


Household panel data reference

Market Summary Report

Report Model

  • Provides either a comprehensive “snapshot” or a dynamic look at consumer purchasing behavior for a category, its major segments and brands.

  • Aids in identifying appropriate marketing strategies and tactics.

Applications/Questions

  • How many households purchase this category ? My brand ?

  • Is my brand at a disadvantage in terms of purchase size or purchase frequency ?

  • How deal-reliant are my buyers ?

  • How deal-reliant are my competitive buyers ?

  • How have things changed over time ?


Market summary basics

Market Summary Basics

Consumer behavior data complements sales and share

measurement data.

Sales = # of Buyers x Amount Purchased per Buyer

Penetration x Buying Rate

Occasions per Buyer x Units per Occasion

(“Purchase Frequency” x “Purchase Size”)


Household measure definitions

Household Measure Definitions

  • Penetration - % of total U.S. households making at least one purchase of the specified item.

  • Volume per Buyer - (Buying Rate) How much the average buyer purchases in a given time frame.

  • Volume per Occasion - Average volume purchased per household each time a purchase was made.

  • Occasions per Buyer - Average number of times the specified item was purchased.

  • Share of Requirements - (Loyalty) Percent of the specified item’s buyers total category volume accounted for by the specified item.

  • Elapsed days - (Purchase Cycle) Average number of days between purchases among buyers of the specified item who made two or more purchases.

  • % of One Time Buyers - % of all the specified item’s buyers who purchased the item only once.


Household measure definitions1

Household Measure Definitions

  • % Volume on Total Deal - Proportion of all volume purchased on a consumer perceived coupon, feature, display, TPR.

  • % Volume with Coupon - % of volume purchased on a deal specified by panelist as coupon.

  • Average Price - Average price paid

  • Average Non-Deal Price - Average price paid when no consumer perceived deals were present.

  • Average Deal Price - Average price paid for purchases made on a consumer perceived deal.

  • % Volume Purchased by Outlet Type - % of specified item’s volume that was purchased in each outlet.

  • Buyers Projected - Number of households purchasing the specified item.

  • Raw Buyers (N =) - (Sample Size) Unprojected panel households purchasing the specified item.


Marketing tools affecting consumer purchase components

Purchase Components

Penetration

Buying Rate

Purchase Frequency

Purchase Size

Tools for Change

Advertising

Product Offering

Couponing, Features, Displays

Trial Packs

Product Sampling, Distribution

Competitive Activity

Smaller Package Sizes

Couponing

Displays

In-Pack/On-Pack Promotions

Sweepstakes/Contests

Advertising Alternative Uses

Two-For Deals

Bonus Packs

Trade Deals

Displays with Larger Sizes

Marketing Tools Affecting Consumer Purchase Components


Household panel data reference

Common Errors or Cautions in the

Interpretation of Market Summary Analysis

  • As a general rule, none of the base measurements are additive !

  • Buying rate, purchase frequency and purchase size, represent average

    behavior and should not be taken literally !

  • Average purchase frequency can not be used to calculate purchase cycle.

    • Example: 365 days divided by average annual category frequency of 10 times does not equate to a purchase cycle of 36.5 days.

    • Reason: Average purchase frequency includes households who make only one purchase during the given time frame and, therefore, do not have a purchase cycle. This measure can only be calculated among households with a purchase frequency of greater than one.

  • Loyalty (Share of Requirements) measurements over shorter time periods will almost always lead to higher figures.

  • Penetration-based marketing efforts can have a negative impact on loyalty. The more new brand buyers that are brought in, the greater the likelihood that total brand loyalty will erode. The reverse is also true.

  • Declines in penetration levels almost always lead to increased loyalty levels.


Household panel data reference

Demographic Profiles

Report Model

  • Identifies those demographic groups which make up the largest portions of a brand’s total buyer base as well as a disproportionate share of sales.

  • Provides a complete picture of the characteristics for brand buyers and other groups of interest.

Applications/Questions

  • What types of households typically buy my products ?

    • Is my product positioned (through advertising and promotion) to reach these buyers?

  • How do the buyers of my brand compare to buyers of my competitors ?

    • Should I target my advertising to buyers of their products ?

    • Should I introduce a product similar to my competitor’s to appeal to a different customer profile ?

  • How has the profile of my buyers changed ?

    • Did my line extension bring in a different type of buyer ?


Household panel data reference

Demographic Definitions

What are the demographic characteristics that we most

commonly utilize in analyses?

  • Household Income

  • Household Size

  • Female Head Age

  • Age/Presence of Children

  • Female Head Employment

  • Female Head Education

  • Household Head Occupation

  • Race/Origin

  • Household Lifestages

  • Household Affluency

  • County Size

  • Census Regions


Household panel data reference

Demographic Profile Definitions

Household Lifestages

  • Young Singles - Households with one member under 35 years old.

  • Childless Younger Couples - 1+ member households, under 35 years old with no children under 18.

  • New Families - Households with children under 6 years old only.

  • Maturing Families - Households with children aged 6-17 years old.

  • Established Families - Households with children aged 13-17 years.

  • Middle-Aged Singles - Households with one member aged between 35-54 years old.

  • Middle-Aged Childless Couples - 1+ member households, aged between 35-54 years old, with no children under 18.

  • Older Singles - Households with one member over 55 years old.

  • Empty Nesters - 1+ member households, aged between 55-64, with no children under 18.


Household panel data reference

Demographic Profile Definitions

Per Capita Income Definitions

HH’s are Defined by:PoorGetting ByComfortableAffluent

1 Member Income 0-$9,999 10-$19,999 20-$39,999$40,000+

2 Member Income 0-$11,999 12-$24,999 25-$49,999$50,000+

3 Member Income 0-$14,999 15-$29,999 30-$59,999$60,000+

4 Member Income 0-$19,999 20-$39,999 40-$69,999$70,000+

5+ Member Income 0-$24,999 25-$49,999 50-$99,999$100,000+


Household panel data reference

Common Errors or Cautions in the

Interpretation/Use of Demographic Profiles

  • Use caution when examining demographic profiles among buyer groups that contain less than 200 raw (unprojected) sample households.

  • Use caution when interpreting results from any demographic segment in which the raw buyer count is less than 30 households.

  • Analyses of indices can be misleading without also examining the relative size of a demographic segment. High volume or high buyer indices may not offer much potential if a segment accounts for a small percentage of the population.


Comparing household and store level data

Comparing Household and Store Level Data

  • Projected volume from the household panel can be compared to universe estimates from scanning data or shipment data.

  • While projected volume should not be expected to “match” exactly, the data should be directionally similar in terms of brand shares and trends.

  • An estimated 10% of Scantrack volume is purchased for use outside the home and, therefore, would not be reported by the panel.

  • The two services are sampling different universes:

    • Scantrack: $2MM + Grocery Stores

    • Household: Contiguous U.S. Households

  • Scantrack samples scanning stores only

  • Household collects purchase data from all stores

  • Sampling ratios are more robust for Scantrack than Household:

    • Scantrack: 1 in every 11 stores is a sample store

    • Household: 1 in every 2400 households is a panelist (40,000 household panel)


Issues to consider when comparing panel and scantrack data

Issues to consider when comparing Panel and Scantrack data

  • Scantrack measures all volume moving through $2MM+ grocery stores.

  • Household measures volume consumed by households usually in the home.

    • Some consumer purchases never make it into the home (i.e. candy bars, canned soda, single-serve snacks, travel size HBA’s)

    • “Industrial” purchases at retail (laundromats, day care centers) would not be captured.

  • Basis for volume projection is different:

    • Scantrack projects to all commodity volume

    • Household projects to Total U.S. population based on household type incidence.

  • Outlet types are self-classified by panelists (given guidelines)

  • Snantrack sample stores and organizations are specifically identified in the Scantrack sample.


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