Boots masking & Exclusions - PowerPoint Presentation

Boots masking & Exclusions
Boots masking & Exclusions

Boots masking & Exclusions - Description


March 2020 What is masking amp why does It happen Why does masking happen Nielsen is contractually obliged to apply Boots sensitivity rules to any data where Boots is included in coverage This means that where they feel there would be an over exposure of trading for a product the product ID: 926593 Download Presentation

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Slide1

Boots masking & Exclusions

March 2020

Slide2

What is masking & why does It happen?

Why does masking happen?

Nielsen is contractually obliged to apply Boots sensitivity rules to any data where Boots is included in coverage. This means that where they feel there would be an over exposure of trading for a product – the product will be masked.

Boots inclusion in the Health & Beauty market requires masking rules to be applied – these rules apply to all data providers.

What is Data Masking?Data considered sensitive based on a criteria set by Boots will have the data zeroed at the relevant level of sensitivity within the database i.e. no value/vol/unit data will be available.NO data is ‘missing’ from the total database as a result of masking – other Exclusion rules apply (see further on).What is Boots criteria for masking data?The criteria for masking is sensitive and is triggered at a point where Boots have a certain level of market share.The exact market share figure that triggers the masking is confidential.Nielsen maintains the masking, which is reviewed every 4 weeks.

Search for: What is Masking?

Slide3

Where is masking applied to?

The channel Boots is situated in depends on the

category.

Masking is assessed in the primary channel where Boots is

situated.Masking is applied in the channel and to Total Coverage.MedicatedPersonal Care

Slide4

The process of applying masking

All products are placed in the appropriate levels of the database

We review the masking criteria

If appropriate, product is masked

Database deliveredMasking is reviewed each data run and if appropriate the masking is lifted

Appropriate pair-masking is identified and applied

Slide5

How does this work in practice?

Total Category

Company A

Company B

Brand 1Brand 2CleansingCleansing

Everyday

Product A

Product C

Product D

Type 1

Type 1

Type 1

Category

Trading Company

Brand

Benefit

Product Identifier

Type

Moisturiser

Product B

Type 2

All products are placed in the appropriate levels of the database

All Other Companies

Slide6

How does this work in practice?

Total Category

Company A

Company B

Brand 1Brand 2CleansingCleansing

Everyday

Product A

Product

C

Product

D

Type 1

Type 1

Type 1

Category

Trading Company

Brand

Benefit

Product Identifier

Type

Moisturiser

Product B

Type 2

We review the masking criteria

High share in Boots

High share in Boots

All Other Companies

Slide7

How does this work in practice?

Total Category

Company A

Company B

Brand 1Brand 2CleansingCleansing

Everyday

Product A

Product C

Product D

Type 1

Type 1

Type

1

Category

Trading Company

Brand

Benefit

Product Identifier

Skin Type

Moisturiser

Product B

Type 2

If appropriate, product is masked

All Other Companies

Slide8

How does this work in practice?

Total Category

Company A

Company B

Brand 1Brand 2CleansingCleansing

Everyday

Product A

Product C

Product D

Type 1

Type 1

Type 1

Category

Trading Company

Brand

Benefit

Product Identifier

Skin Type

Moisturiser

Product B

Type 2

If appropriate, product is masked

All Other Companies

Slide9

How does this work in practice?

Total Category

Company A

Company B

Brand 1Brand 2CleansingCleansing

Everyday

Product A

Product C

Product D

Type 1

Type 1

Type 1

Category

Trading Company

Brand

Benefit

Product Identifier

Skin Type

Moisturiser

Product B

Type 2

Appropriate pair-masking is identified and applied

All Other Companies

Slide10

How does this work in practice?

Total Category

Company A

Company B

Brand 1Brand 2CleansingCleansing

Everyday

Product A

Product C

Product D

Type 1

Type 1

Type 1

Category

Trading Company

Brand

Benefit

Product Identifier

Skin Type

Moisturiser

Product B

Type 2

Appropriate pair-masking is identified and applied

All Other Companies

Company B or some other Trading Company would become pair-masked with Company A

Slide11

Facts about masking

Masking is based on Boots contribution to a particular segment / brand /

sku

(unless the product is pair-masked).

Masking is applied to volumetric facts, i.e. Value, Volume, Units and any associated expressions.Distribution and Price info is not masked.Masked lines are not removed from totals.Masking is applied at the level at which it is sensitive.Masking is applied to all time periods.Each database production cycle takes databases through “Release Rules” checks.Large database changes e.g. hierarchy changes will require

additional masking checks to be done before it can be delivered.

Slide12

Boots exclusions

Slide13

What are premium boots exclusions?

Why do Boots

premium exclusions

happen?

Boots provide Nielsen (& other data providers) with a list of brands which Boots consider ‘Premium’. These brands must be excluded entirely from the data as a condition of receiving Boots sales data.What brands are excluded?We cannot share exactly which brands are part of the Boots premium exclusions list.Brands that are premium exclusions are ones where Boots does not feel comfortable sharing any information about how the brands are performing.These brands will not appear in any Nielsen data, at Total Coverage or when looking at Boots KAD data.

Slide14

NOW IT’S YOUR TURN…

Slide15

Pick one

database to complete these activities

Please complete the quiz following the link below

https://

forms.gle/3vMeDTfmgf3jYykm6

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