Make better pricing decisions with big data

&http://www.aliyun.com/zixun/aggregation/37954.html ">nbsp; The importance of correct pricing is difficult to assess. As the average price of a product rises by 1% per cent, the operating profit of an enterprise increases by 8.7% (of course, assuming there is no loss). However, according to our estimates, up to 30% per cent of thousands of pricing decision makers each year fail to provide the best pricing. This is a huge loss to the business. It is particularly disturbing that the vast amount of available data provides companies with an opportunity to make better pricing decisions, but that large data is complex and that the value of solutions to large data complexity is enormous.

We do not think this is a simple matter: the number of customer contact points as a source of digital proliferation, resulting in multi-channel complexity growing. and price points need to keep in sync with them. Many companies have missed millions of of dollars in profits without discovering or exploiting the opportunities offered by big data. The secret to increasing profit margins is to use large data and to find the best pricing for the product based on the level of the product rather than the category, rather than drowning in the torrent of numbers.

Success is not easy.

For each product, the enterprise should be able to find the customer is willing to pay the best price. Ideally, they would consider very specific observations that could affect pricing, such as the cost of the next highly competitive product and the value of the product to the customer, and then achieve the best pricing. Indeed, for a company with a small number of products, the pricing method is simple.

This approach is cumbersome when product numbering types proliferate. About 75% of the typical companies ' income comes from their standard products, which are of thousands of different kinds. The practice of setting up a pricing manual is time-consuming and almost impossible to foresee as a pricing model that can release value. For large corporations, it is stressful to analyze and manage the complexity of these changing pricing variables. At the heart of the problem is that this is a big data problem (see chart).

Based on willingness to pay, the analysis and display of different customer-product level opportunities.

Many marketers blindly shun the issue of product pricing. They develop product pricing only on the basis of simple factors such as product cost, standard profit margin, price of similar products, volume discount and so on. They manage their products according to past practices, or cite "market prices" as an excuse not to take the initiative. Perhaps worst of all, they are always relying on seemingly time-tested historical practices, such as the price of any product rising at a rate of 10%.

"In practice, the growth of our prices each year is based on size and quantity, not on science-based algorithms," he said. "said Roger Britschgi, head of the sales business at Linde gases. "We don't think there are other ways to price, and, frankly, we're not ready to convince our customers that there is a need to raise prices," he said. ”

Four steps to convert data to profit:

The key to better pricing is to fully understand the company's existing data. It requires the company not to view the data, but to enlarge the data after the specific analysis. As Tom Oblein, the vice president and general manager of the marketing and sales department at the Cable group believes that "the sales team understands their pricing and they may also be aware of market capacity, but this approach contains more: detailed data-the real meaning of the product from each invoice, Detailed data on customer and packaging classification.

In fact, some of the big data in the Business-to-business field of practical applications of exciting cases, such as beyond pricing and contact with the company's other business systems of practical applications. For example, dynamic trading scores in the personal transaction level, decision escalation points, incentives, performance scores and more transactions based on similar mode of transmission/win, provide pricing guidance. Because the factors associated with any transaction are variable, the use of smaller sample sizes, the relevant transaction samples is necessary, and the variable factors lead to a group of important transactions as a reference to become useless. We have seen its application in technology has been a great success, that is, 4%-8% of the sales profit of the huge revenue growth (relative to the same company control group).

The following four departments can help companies to get accurate pricing through data:

Listen to the data. The challenge of setting the most appropriate pricing is not the data (the company already has a huge data trove), but rather the analysis of the data. Good companies know how to interpret and organize the data wealth owned by the company, but business-to-business companies are meant to manage data rather than use it to drive decisions. Good analysis can help companies identify factors that are often overlooked by companies, such as what has been revealed in a broad economic context that drives each customer segment and product price, for example, product preferences and sales reps ' negotiations.

Automation。 Manual analysis of thousands of products is time-consuming and expensive. Automated systems can identify narrow product segments, determine what factors drive each subdivision's value, and match historical transaction data. This allows the enterprise to price the same class of products and subdivisions based on data. Automation also makes it easier to copy and modify the analysis, thus avoiding the need to start from scratch every time.

Improve your skills and confidence. Implementing new prices is a double challenge to communication and operation. Successful companies are willing to invest excessively in deliberate transition projects to help their salespeople understand and accept new pricing methods. Companies need to work closely with their salespeople to explain the reasons for price proposals and how the system gets the best pricing they can trust to buy. It is also important for companies to develop a clear set of communication methods designed to provide a basis for new pricing to highlight value and then pass these parameters on to the customer. Strengthening negotiation training is also essential to enhance confidence and provide convincing evidence for sales staff to communicate with customers. The best leadership is the ability to accompany salespeople with hard to convince customers and focus on quick wins, so that salespeople can also increase their confidence in accepting new pricing methods. "The leadership behind the new pricing strategy is critical. "Pangas, general manager of the company, Robert Crigg said. "We have been negotiating with engaged and difficult clients not only to help our sales staff, but also to show them how to do the debate." ”

Positive performance management. In order to improve the performance management of enterprises, enterprises need to set useful goals to support sales staff. The biggest impact comes from ensuring that front-line personnel have a clear understanding of the profitability of their customers, and also that the business market has the right analytical skills to identify and exploit this opportunity. Salespeople also need to be given the power to adjust prices, rather than relying on centralised teams. This requires a certain degree of creativity in the formulation of customer-specific pricing strategies, as well as a mindset for entrepreneurs. Incentive mechanisms may also need to change as pricing strategies and performance evaluation methods change.