Attribute Lift Model (ALM™)

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What product attributes (features, ingredients, claims, etc) are consumers willing to pay a premium for? Does the perceived value of the product change pre-COVID and during COVID-19? Market Fusion Analytics (MFA)’s proprietory Attribute Lift Model (ALM™) can quantify the willingness-to-pay for each, or a bundle of product attributes at different times.

A product could have more tangible attributes such as its pack size, form, packaging, scent, etc. The attributes could also be less tangible like brand or claims. Consumer willingness to pay for premium or other differentiated product attributes changes as the economic conditions change. The past recessions showed some premium features being price inelastic while others responding strongly to economic pressure.

Volume Decomposition Through ALMTM

In addition to measuring consumer’s willingness-to-pay, ALM™ can also isolate the incremental impact of a product attribute on overall in-market sale performance while controlling for price, distribution, execution, and in-market conditions. The incremental impact is measured as a % of lift over the “base” category item. ALM™ models are built using product (UPC) level scanner sales data and account for a) claims and attributes delivered to consumers currently in the marketplace, b) differences in distribution/merchandising across UPCs, and c) differences in brand, portfolio & category level impact.

ALM™ Process in a Nutshell

ALM™ offers strategic insights into the category footprint of white space potentials and forward-looking pricing and innovation planning. These insights are based on actual sales data and can be leveraged on a very granular level, by geography or even by account. 

If you are interested in learning more, please contact Tamir Choina at