Your product portfolio success strongly depends on the extent to which your products fulfill the needs of consumers and the price they are willing to pay for it. SKIM Portfolio Revenue Optimizer™ can help you identify the optimal set of products or services to offer and the right price. The recommended price is one that leads to the highest revenues or profits and is in line with the customers’ willingness to pay.
Whether you need to optimize pricing for a predefined set of products, or the product specifications themselves, SKIM Portfolio Revenue Optimizer can help. The solution, built on advanced choice modeling techniques, will consider and tailor all product features (e.g. pack design, size, flavors, price etc.) to yield the highest consumer preference for your product mix, in combination with their prices.
Optimize prices for a predefined set of products
While real purchase and scanner data can monitor price changes and the impact on volume changes, it doesn’t account for external factors affecting shopper buying behavior. For example, scanner data won’t reveal when multiple products experience price changes simultaneously or whether the competition is running a promotion. Since these external factors affect the context in which purchase decisions are made, it can be challenging to find the optimal price and/or features for each product in your portfolio separately.
SKIM Portfolio Revenue Optimizer isolates the effect of price changes for any product in your portfolio, as well as predefined new product introductions. By uncovering how customers’ choices for products interact, we will recommend the optimal price for your product.
Focusing on a predefined set of products, we can answer questions like:
- What is the optimal price for our brands and products to maximize portfolio profitability: market share by value, or market share by volume?
- How will new products interact with my existing products and competitor products?
- What is the optimal price for new products?
- What will happen if I delist some of the products in my portfolio?
- Are there clear price barriers for each of my brands/SKUs?
- How price sensitive are consumers towards each of my products and brands?
- What is the optimal price architecture for my entire portfolio/category (e.g. positioning by brand, size, format etc.)?
Optimize product features and prices together
Sometimes your product offer may be clearly defined and your main research objective is to optimize its price. However, in some cases, you may need to consider updating your product offer more rigorously, such as changing the mix of products and product features to stay ahead of the competition. Depending on the industry (e.g. telecommunications and technology services vs consumer goods), these changes can occur frequently or they can be more time/cost intensive, occurring less often.
Across industries, SKIM Portfolio Revenue Optimizer can identify the optimal product configuration (features) and the right price.
By optimizing product features and prices together, we can answer questions like:
- How should our portfolio be configured in terms of features and price?
- What product concepts have the highest potential for entering a new market category and which features should these concepts include (pack design, name, size etc.)? How should they be priced?
- Which of my current brands is best capable to steal value and share from competitors in segment X (relaunch); what features should be changed and what price should it have?
- What is the consumers’ preference for our new product? Which features should it include, and what is the optimal price?
Drawing on our deep analytical roots in advanced choice modeling techniques, our adaptive approach will blend the appropriate methodologies to tackle your project and market needs, online and/or in-store.
How does SKIM Portfolio Revenue Optimizer work?
As the decision-making environment continues to change, we recommend surveying customers in a setting that mimics reality as close as possible, to generate the most accurate insights. With our “virtual shopping trips,” powered by conjoint methodologies, we replicate store shelves or websites, which include competitive offerings. This robust approach helps to identify the optimal product (features) and price for each of your offerings or propositions. Choice-based conjoint analysis allows us to test different feature/price bundles as concrete products, and test which product mix works best to maximize your share and revenue.