Artificial intelligence can have huge impacts on business operations, but only when it’s quality and used effectively. In this article, the author covers some of the top takeaways from Gartner’s report on “How to Build a Data Strategy in Manufacturing Organizations” – many of which apply to any organization.
Successfully managing cost volatility has a material impact on customer satisfaction, sales team satisfaction, and profitability. That’s why it’s imperative to solve this challenge in a way that effectively serves all constituents, as the author explains.
Even in today’s digital world in which data about customers, their purchasing behaviors, price sensitivities, and buying experiences is readily available and consistently updated, making important pricing decisions can still be difficult. If your data is inaccurate, dated, or incomplete, your tactics won’t be as effective and you might miss out on potential prospects, as the author explains.
Many pricing professionals believe that a value-based approach is the best way to set a fair price for your products and services. But data-driven pricing, when done right, will also lift your profit margins in the short term. Here’s the story of how hunting down hidden data turned profits around for one company.
As pricers, we are analytics people and get very excited about the data that we collect and analyze, only to be frustrated when the rest of our organization doesn’t understand our enthusiasm for our data analytics and resulting pricing strategies. How do we take our insights and convert them into initiatives that our whole organization will support?
Industry studies prove the correlation between higher customer loyalty, growth, and price. Customer loyalty data gives insights that go beyond product attributes and into the value of the customer experience, often uncovering more value than you realize you deliver. By harnessing this customer loyalty data, companies can improve and strengthen their value pricing strategies, as the author explains.