Cross-channel assortment optimization
Lower costs by putting the optimal assortment in each channel
What it does for you
The impact of price changes on buying behavior is often captured by scanner data; where price changes are monitored over time and the influence on volume changes measured in each of the channels your products are sold. Even though real purchase data is used, scanner data measures always include external factors, which cannot be taken out of the equation. For example, multiple products change in price simultaneously or competition is running a promotion. This influences buying behavior and makes it impossible to find the optimal price and or features for each product of your portfolio separately.
Helping you answer questions like
- How can we optimize prices across Mass retailers (including E-commerce trade-out)?
- Is there room to introduce a new product or value pack (pack of products) in each of the purchasing channels?
- How can we best change our current promotion strategy (depth and frequency) within each of the purchasing channels?
- What is the optimal price for our key SKUs and brands in order to maximize portfolio value and market share in each of the purchasing channels?
How it works
SKIM’s decision behavior platform builds on over 30 years of experience in practicing and advancing choice modeling techniques. We provide an adaptive approach to each project with the appropriate blend of methodologies to fit the project and market needs. Our approach is based on survey testing with the relevant customer base away from your store or website. By changing multiple product features in “virtual shopping trips” we identify the optimal product configuration (features) and price.
These virtual shopping trips can be adapted to different channels, allowing us to test different prices and products in each of the channels your products are sold. We use conjoint methodologies to test new market scenarios in a survey environment providing all the required insights. Choice-based conjoint allows you to test different feature/price bundles as concrete products and test which product mix works best to maximize share and revenue.