Big Data Can Be The Key To Better Pricing
Marketers often struggle to get their pricing right. Getting an inappropriate price for your product often indicates a loss in revenue. Researchers currently see big data can play a big role in getting the pricing decision right. While the increasing data available today provides companies with an opportunity to make significantly better pricing decisions, a recent report by McKinsey and Co. suggests, marketers can harness the flood of data available from customer interactions to price appropriately—and reap the rewards. The secret to increasing profit margins is to harness big data to find the best price at the product level, says the report
According to the McKinsey report, the key to better pricing is to understand fully the current data at a company’s disposal. As Tom O’Brien, group vice president and general manager for marketing and sales at Sasol, said of this approach, “The [sales] teams knew their pricing, they may have known their volumes, but this was something more: extremely granular data, literally from each and every invoice, by product, by customer, by packaging.”
To have an insight on these minute details of data, the report highlights a few effective steps companies can use big data effectively to turn data into profits.
Listen to the data: Setting the best prices is not a data challenge (companies generally already sit on a treasure trove of data); it’s an analysis challenge. The best B2C companies know how to interpret and act on the wealth of data they have, but B2B companies tend to manage data rather than use it to drive decisions. Good analytics can help companies identify how factors that are often overlooked—such as the broader economic situation, product preferences, and sales-representative negotiations—reveal what drives prices for each customer segment and product, says the report.
Automate: It’s too expensive and time-consuming to analyze thousands of products manually. Automated systems can identify narrow segments, determine what drives value for each one, and match that with historical transactional data. According to researchers, this allows companies to set prices for clusters of products and segments based on data. Automation also makes it much easier to replicate and tweak analyses so it’s not necessary to start from scratch every time.
Build skills and confidence: Implementing new prices is as much a communications challenge as an operational one. Companies need to work closely with their sales forces to help them understand and embrace new pricing approaches, says the report. Equally important is developing a clear set of communications to provide a rationale for the prices in order to highlight value, and then tailoring those arguments to the customer. Intensive negotiation training is also critical for giving sales reps the confidence and tools to make convincing arguments when speaking with clients.
Actively manage performance: To improve performance management, companies need to support the sales force with useful targets. The greatest impact comes from ensuring that the front line has a transparent view of profitability by customer and that the sales and marketing organization has the right analytical skills to recognize and take advantage of the opportunity. The sales force also needs to be empowered to adjust prices itself rather than relying on a centralized team. This requires a degree of creativity in devising a customer-specific price strategy, as well as an entrepreneurial mind-set. Incentives may also need to be changed alongside pricing policies and performance measurements.
“We’ve seen companies in industries as diverse as software, chemicals, construction materials, and telecommunications achieve impressive results by using big data to inform better pricing decisions,” mentions Walter Baker, principal in McKinsey adding that to get the price right, companies should take advantage of big data and invest enough resources in supporting their sales reps—or they may find themselves paying the high price of lost profits.
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