An Introduction to

February 2013

Contents

1. KPIs for Managing Brand Health

2. Foresight Household Panel

3. Panelytics … the Panel Software

4. Household Panel Key Facts

5. Which tool is best designed to measure which KPI?

KPIs for Managing Brand Health

Holistic brand health management

Managing brand health … 3 core set of KPI data

Foresight Household Panel

What is household panel?

Household panel is a permanent, syndicated & representative sample of target-population to regularly (continuously) observe & measure Consumer Behaviour.

Panellists are trained to keep a record of every item they purchase, hence for each item we know what, where, when, how much and who purchased.

So, it is a continuous monthly tracking of ‘household purchases’, where the source of information (respondent) is the housewife, i.e. ‘decision maker’.

Advantage of the household panel

→ How categories\brands are developing

→ How have your marketing activities effected the brand performance

→ Whether launching a new variant could develop your consumer base

→ The underlying factors behind the growth or decline in your brand share

→ Your main objectives for the forth coming year(s): more buyers, more market share, more spend per buyer?

→ The main drivers of your brand performance. How these compare competitively

→ The right mix of variants in your portfolio for your existing buyers and the category

→ How the category is purchased: Frequency; where are the gaps and the various development opportunities

→ Whether the consumers you reach are in line with your target market

→ Where else and how you could get your brand promoted

To identify …

Basic ingredients

→ We have recruited a representative sample of homes from the population of households in the country

→ We visit these panellists monthly to record their monthly purchases in the selected categories. We record all details: brand, size, variant/flavour, pack type, price, quantity purchased, place of purchase, frequency of purchase, etc. We also record loose/ unbranded products

→ Our data collection method is ‘bin’ plus an exit interview. We have placed a ‘bin’ in all the panel-households. Panellist are trained to keep the wrappers/ empty-packs of the used packs in this bin

→ Finally, data from all panel households is statistically projected to estimate the overall markets for the brands/ categories

→ Our Panellists demographically represent population of Pakistan. So the way they behave reflects the way nation is behaving

What data is being recorded

What bought? Brand (or loose product) , variant/ flavor/ form, pack type

Where? Retailer (General store, self service store, Sunday market, etc.)

When? How many times during the month (frequency of purchase)

How much? Pack size, number of packs, price paid (quantity purchased)

By who? Demographic/regional profile

Household Panel … authentic source of information

→ Foresight Household Panel is the only data source in Pakistan which is 100% verified

→ Interviews are conducted face to face and data is being punched into the mobile phones – a data entry application is developed using android application; GPS location of the panellist is recorded while interview is being conducted. This eliminates any doubt of interview being conducted at other place than the panellist home

→ Similarly, the device automatically records ‘start time’ & ‘end time’ of each interview along with the data

Nationwide Coverage … large sample size, plans to increase further

•1308 urban homes from 10 cities

•348 rural homes from 19 villages

Sind

•431 urban homes from 6 cities

•200 rural homes from 8 villages

Baluchistan

•3532 urban homes from 26 cities

•857 rural homes from 52 villages

Punjab

•768 urban homes from 6 cities

•306 rural homes from 16 villages

KPK

Overall

Urban

Rural

• 7,750 homes

• 48 cities & 95 villages

• 6,039 homes

• 48 cities

• 1,711 homes

• 95 villages

Foresight household panel covers almost 95% of Pakistan population. FATA, FANA, tribal areas & military cantonment areas are out of scope.

→ While designing the panel representation of both smaller & gibber cities is ensured

→ Similarly, rural sample is also well spread

Depth of coverage

Population Strata

Population Range

# of towns in sample

Sample size

1 > 5 Mn 2 1,224

2 0.5 - 5 Mn 8 1,468

3 100 - 500k 11 1,135

4 50 - 100 k 10 961

5 25 - 50k 8 683

6 < 25k 9 568

Total 48 6,039

Urban sample depth

Categories currently tracked in household panel

1. Laundry soaps 2. Washing powders 3. Fabric blues 4. Fabric bleach 5. Fabric conditioner 6. Dish wash NSD bars 7. Dish wash Scourer powders/

pastes 8. Toilet cleaners

Household Care Personal Care Foods

9. Skin cleansing soaps 10. Shampoos 11. Hair conditioners 12. Skin creams & lotions 13. Tooth pastes 14. Face wash/ body wash 15. Deodorants

16. Tea 17. Coffee 18. Make to Drink: Red syrups,

squashes & Powder beverages

19. Ready to Drink: Juices & Nectars

20. Ice creams 21. Desserts 22. Ketchup 23. Noodles, Spaghetti, Macaroni 24. Butter & margarine 25. Spreads & mayonnaise 26. Spices, recipe mixes, cooking

aids 27. Instant soup 28. Diary 29. Cooking oil & ghee

Existing clients of household panel

25 categories since 2009

1 category since 2010

1 category since 2012

1 category since 2011

1 category, started in 2013

Panelytics … the panel software

Panelytics … the panel software

→ Windows based desktop software, database attached to the user PC

→ Easy to use, requires very minimum training

→ Software is organized into 4 tabs, they are:

1. Product: brand, SKU, size, etc.

2. Market: national, urban, SEC, province, etc.

3. Fact: all KPIs of the household panel

4. Time: months, quarters, year, etc.

→ Additionally, there are 3 modules in the software:

1. Standard facts,

2. Brand switching analysis, &

3. Consumer DNA analysis

→ All outputs of the Panelytics are directly produced in MS Excel 2007

Household panel key facts

Household panel key facts

→ Usership (%)/ user households (‘000)

→ Exclusive/ Solus users and Conjunction users

→ Usership (%), volume market (tonnes), market (million rupees)

→ What else do they buy? Duplication with markets/ brands

→ Penetration 1+ month users (%)

→ Market size (volume & value) & share (%)

→ Consumption (& spend): per household/ category user/ brand user)

→ Consumption Index

→ SOR (share of requirement)/ loyalty & loyalty distribution

→ Source of gain/loss analysis

→ Frequency of purchase

→ Light/ Medium/ Heavy user analysis

→ Lapsed/ Retained/ New user analysis

→ Consumer DNA

Loyalty as defined in household panel

Household buys 10 packs of Category: 3 Blue, 2 Green, & 5 Purple

Loyalty = Quantity bought of Brand ÷ Quantity Bought of Category

Therefore Loyalty to each brand is;

= 30% = 20% = 50%

Definition

→ How much of my consumers’ category consumption is apportioned to my brand?

→ Am I THE “ preferred” brand among my buyers?

→ Note of caution - Loyalty is not repeat … I can repeat yet not loyal to the brand

Loyalty vs. relative penetration

This analysis helps in brand management strategy, to decide which brands to grow & which brands to discontinue

Loyalty

Rel

. P

enet

rati

on

+

- +

Good Potential

Too much duplication

or/and low repeat

• High Quality

• High Brand Value

• Leaders

Kill these if remain

in this quadrant

“Niche” brands

How to increase loyalty / profitability Product/ Differentiation (increase choices within brand)

Weight of purchase (pack size, promotions)

Customer satisfaction

How to increase penetration Trial pack

New variants

Distribution

Promotion (sampling)

Advertising

Pricing

Brand switching (Gain & Loss) analysis

Uses & applications

→ Where is my brand’s volume coming from / going to?

→ How much volume am I losing to my competitors?

→ Is my main competitor who I think it is?

→ Are the other brands in the market suffering in the same way, or a different way?

→ What is the underlying movement for the market?

→ Where has my new brand’s volume come from?

Brand switching (Gain & Loss) analysis

4 sources of volume change: Definitions

Volume loss because of HHs who have stopped using the category, i.e. they were users in P1 but didn’t use any brand (category) in P2

Volume loss because of HHs who have stopped using the brand in P2, however they are users of the category

Volume loss because of HHs who continue to use the brand, however their consumption of the brand had declined in P2 vs. P1

Volume loss to other brands in the category

Brand switching (Gain & Loss) analysis

A sample report

P1 = 429.1 tonnes, P2 = 404.4 tonnes, ∆ = - 25 tonnes.

Loss Gains

Heavy-medium-light (buying intensity) analysis

What can it tell me?

→ Who are the heavy category consumers?

→ How much volume/ value do they contribute?

→ What is their demographic profile?

→ What is the general buying behavior of the heavy buyers?

→ How frequently do they purchase?

→ What pack size do they buy?

→ Where do they shop?

→ Which brands do they like?

→ My brand profile versus my competitors?

→ Is my brand attracting the key category consumers?

→ What is my brands strength or weakness amongst these buyers?

Heavy-medium-light (buying intensity) analysis

Definition

Heavy users

Minimum number of users accounting for 50% of the volume

Medium users

Next tier of users accounting for 30% of the volume

Medium users

Last tier of users with 20% volume contribution

Heavy-medium-light (buying intensity) analysis

A sample report

Sunsilk Triers 63 % Sunsilk Consumed 2,625 T

Lig

ht

He

avy

Me

diu

m

HH cons per month (mls)

% vol Contribution

SOR

55 %

29 %

10 %

25 %

% of users HH

20 %

25 %

55 %

100 %

48 %

32 %

20 %

100 %

38 ml

20 ml

6 ml

16 ml

69 ml

68 ml

60 ml

64 ml

Total shampoo

consumption

New, repeat & lapsed (NRL) analysis

Definition

New users

New Users are those households who have bought the selected brand in reference period (P2) but not in base period (P1).

Repeat users

Repeat Users are those households who have bought the selected brand in both reference period (P2) & base period (P1).

Lapsed users

Lapsed Users are those households who have bought the selected brand in base period (P1) but not in reference period (P2).

New, repeat & lapsed (NRL) analysis

A sample report

Lapsed Buyers = 1,812 in P2

Buyers in P1 = 5,072 Avg. Cons. = 297 gms

New Triers in P2 = 860

Retained Buyers = 3261 in P2

Buyers in P2= 4,121 Avg. Cons. = 265 gms

64%

36%

P1: Jul – Aug 2008

P2: Jul – Aug 2009

What will happen to brand ‘A’ if it discontinues its ‘X’ SKU …

Brand ‘A’ will loose 82% of its ‘X’ SKU volume if the SKU is discontinued …

Brand ‘A’ ‘X’ SKU Volume 1,890 tonnes

if brand discontinues

the pack

Retain 344 tonnes

1546 tonnes

Brand ‘A’ other SKUs to gain from its ‘X’ SKU

Loose

B

C

D

E F

G

Gain of ‘X’ SKU of other brands

Which tool is best designed to measure which KPI?

3 tools co-exit, they complement each other NOT replace

RETAIL AUDIT HOUSEHOLD

PANEL BRAND HEALTH

TRACKER

Volume/ Value market, shares Yes, much stronger Yes No

Distribution, OOS Yes No No

SISH, stock cover days Yes No No

Price point, & RPI analysis Yes Yes No

Ever Use, current use, exclusive/ conjunction use No Yes, Much Stronger Yes

New, Retained & Lapse user analysis No Yes, Much Stronger Yes

Brand switching analysis (G&L analysis) No Yes No

Loyalty analysis & matrix No Yes, Much Stronger Yes

Pareto analysis (light/ medium/ heavy user analysis) No Yes No

Frequency & place of purchase No Yes, Much Stronger Yes

Trip size No Yes No

Average household spend/ consumption index No Yes No

Consumer DNA – HH info, Media habits, grocery habits No Yes, Much Stronger Yes

Brand Awareness & disposition No No Yes

Brand Image Analysis No No Yes

Perception Maps No No Yes

Brand Equity No No Yes

Combined analysis of RA & HHP generates insights

Would your reading be the same … your Marketing and Trade actions be similar?

M1 M2 M3 M4 M5 M1 M2 M3 M4 M5

M1 M2 M3 M4 M5 M1 M2 M3 M4 M5

Distribution Penetration

Case 3 Case 4

Case 1 Case 2

Combined analysis of RA & HHP generates insights

Or even … ?

M1 M2 M3 M4 M5

Distribution Penetration Loyalty Volume

Both distribution & penetration are increasing, though loyalty among brand-users is on the decline, resulting in no growth for the brand despite more number of buyers.

HHP is the logical follow-up of BHT to understand brand performance

How HHP & BHT complements each other

Brand awareness

Brand set/ repertoire / brand image

Likelihood to purchase

Actual Purchase

New, retained & lapse user analysis

Sources of gain & loss

FOP, POP, trip size

Loyalty

Ever Use/Trial, exclusive & conjunction usage

→ Household Panel is based on pantry-audit, so brand is actually verified rather than being recorded on consumer-claim. Too often consumers mix the brand they are using with their TOM brand or the brand they desire to use

→ Even the extent of pantry checking in HHP is more comprehensive than any other research tool can achieve. The fact that we visit these panellists every month, gives us access to their kitchen, fridge, store & even bath-rooms – hence we are able to record things with greater accuracy

→ Ability to report to the brand by size, variant, packaging & price point

→ Cross category usership analysis are also possible. These becomes very handy when planning for cross category promotions:

→ To generate trial among non-users, it is recommended to go with brand with least conjunction usage. Reverse is true when want to increase the loyalty of existing users

→ At times we like to see how many of brand-users have used the brand at least ‘x’ months during the last 1 year – only HHP provides this information

→ Globally in the presence of both HHP & BHT, always HHP data is used for usership

New, Retained & Lapse user analysis

→ HHP is a time series data; each panellist is being interviewed every month. This allows comparison of the brand used in period 1 vs. period 2 at household level (in both periods this information is verified)

→ So, actually households can be tagged as ‘new-users’, ‘lapsers’ & ‘retain-users’. Once users are tagged as NRL users of the brand, all kind of analysis, such as, but not limited to:

→ % new, retained & lapse users

→ Their volume/value contribution to the brand

→ Average spend on the brand & on other brands by these user groups

→ Loyalty among NRL users, etc.

→ Above can be done at brand level & for any size, pack of the brand

→ On the contrary in BHT, not only this is based on ‘claimed purchases’ but also for identification of new, lapse & retain users this is based on consumers responding for the period of 1 year, last 6 months, last 3 months – which compromises the data quality

→ Globally in the presence of both HHP & BHT, always HHP data is used for NRL analysis

Brand Switching analysis

→ It is a volumetric measure and can only be calculated based on the analysis of time-series data available via household level

→ Calculating it at incidence level (usership) is at best indicative, worse it can miss-lead

→ Brand switching analysis based on HHP provides with 4 sources of volume change, which are not available via BHT. The sources of volume change are:

→ new/lapsed market buyer

→ Increase/ decreased brand purchase

→ Added/dropped from repertoire

→ Brand switching

→ Globally only HHP data is used for brand switching (G&L) analysis

Loyalty analysis & matrix

→ Loyalty is a multi-facet fact & can be defined from attitudinal & behavioural perspective

→ BHT is the best source to define attitudinal loyalty, while HHP is the best source to define loyalty based on consumer behaviour. While it is expected that the two will have high/medium correlation, it is not supersizing that attitudinal loyalty does not always translates into behavioural loyalty. For instance, for a premium brand typically one would always get very high attitudinal loyalty, which often doesn't translate into that high volumes – hence it is usual to use BHT as a measure for equity, disposition & use HHP for loyalty

→ Additionally, there are very few exclusive brand users across the categories & conjunction users don't divide their spending between the brands equally. So, for each consumer a matrix could be constructed explaining how it divides volume between various brands – this is only available via HHP

→ Globally only HHP data is used for Loyalty & Loyalty matrix analysis

Pareto analysis … heaviness of consumption

→ Light, medium & heavy user analysis is only possible via HHP

→ It actually analyses each consumer’s interaction with the brand keeping in view all consumer’s combined interaction with the brand to tag brand-users as light, medium or heavy

→ Heavy user of one brand in HHP can be the heavy user of another brand

→ Heavy user of one brand can be light/ medium user of the category

→ In fact, by cross-tabulating the brand & category users one can define the MVC (most valuable consumers) for the brand

→ Once users are tagged LMH users of the brand, all kind of analysis, such as, but not limited to:

→ % light, medium & heavy users

→ Their volume/value contribution to the brand

→ Average spend on the brand & on other brands by these user groups

→ Loyalty among LMH users, etc.

→ Globally only HHP data is used for LMH analysis

We look forward to start our relationship with you. In case of further query, please contact on below numbers Muhammad.zubair@foresight.com.pk (+92-21) 34527402, 34527302, (+92) 321-2007179