How Star Cooperative leverages KNIME to optimize pricing strategy
Business ServicesMarketingMarketing Analytics
Price optimization is the most effective lever for increasing profits and giving companies more potential to grow. This is because price has a direct influence on product margins, sales volume, and revenues. Furthermore, pricing measures require low investments and show fast results. Considerable potential for improvement lies for example in the reduction of manual effort, increase in transparency, and consideration of the customer perspective (e.g. customers’ price sensibility or willingness to pay). How do companies ensure holistic pricing?
A 5-step process to test pricing
Five steps using KNIME:
- Analyze product, price, and sales data to understand which factors influence sales performance on a granular level. KNIME is used to merge and transform data from different data sources. Grouping and pivoting as well as data visualization nodes are used when a deep-dive into the data is needed.
- Discover the need for price adaption by analyzing and comparing the data. Pricing expertise as well as product, customer, and market knowledge are required to interpret the prepared data from Phase 1.
- Adjust prices systematically – for example with the value-based pricing approach or the price line optimization approach. Both take different value components of products into account and therefore promote data-driven pricing. KNIME is used to realize both approaches. For a value-based pricing approach, the KNIME rule engine helps apply a complex set of value driver rules. For a price line optimization approach, different statistical models for clustering and regression are applied and combined.
- Calculate and evaluate the effects of the price adjustment. KNIME is used to simulate effects, however pricing expertise is needed to check the plausibility of new prices and to weigh up different pricing measures.
- Approve the final prices and document these within the pricing system (completed by the pricing manager).