The chemical industry has been struggling to price its products and make huge profits. In recent years, the problem has been exacerbated by fierce competition, increasing demand from customers, consumers and regulators, and the accelerated pace of change driven by the covid-19.
What’s more, during the last recession, many chemical companies had to cut prices sharply to retain customers. Although the market recovered slowly, prices did not recover. As an example, we will discuss in detail, sales of a chemical company rebounded by 37%; however, EBITDA only increased by 1%. A key factor is often that chemical manufacturers have little or no understanding of their customers’ needs and strive to keep up with their changing needs. These changes are usually due to alternative sources, environmental awareness and, most importantly, the rapid acceleration of digital commerce intensified by cowid-19.
If real-time data is not available, chemical enterprises will not be able to predict customer demand, optimize prices, and gain market share. This also leads to the lack of confidence of chemical enterprises in the development of value based pricing. Many people in the industry don’t know the value of the products they offer, so they usually price by intuition, which further affects the profit margin.
How can chemical enterprises gain popularity, earn considerable profits, expand market share and exceed customers’ expectations? The answer lies in the digital transformation of end-to-end sales process with real artificial intelligence. In this way, chemical enterprises can take the initiative to meet the needs of customers, provide appropriate products at the optimal price, and sell according to the way customers want to buy. It also enables chemical companies to make the best pricing based on customer demand and willingness to pay, identify opportunities, maximize win in long-term contracts, and improve the purchasing experience.