Optimize price decisions using Cube RM Tender Central

Leveraging machine-learning, competitive intelligence, and tender evaluation criteria

The Pricing challenge

Finding the right price is one of the most important decisions when preparing a tender response, and any sales quote for that matter. If you charge more than your competitors or more than the customer is willing to pay then you might lose the deal. On the other hand, if you price your products and services lower than you could have, then you are leaving money on the table. Although these challenges are common to all types of sales quotes, tenders impose additional complexities. More and more tenders are using a mix of qualitative and pricing criteria to select winners making pricing decisions even more difficult. And some tenders may allow multiple winners, each taking a fraction of the requested quantity based on their weighted scores. In this case, it might make sense to quote at a higher price and target a lower but “eligible” position, if this results in increased sales revenue despite the lower unit sales. If you consider all these, it’s easy to understand why selecting the right price for tenders can be a complex and challenging process. And if you decide poorly this could result in losing sales opportunities, increased price erosion and revenue leakage, all affecting your sales performance and profitability.

Balancing sales performance with probability to win

Cube RM Predictive Intelligence

Cube RM uses a fusion of Machine Learning, applied economics, and industry-specific market dynamics to generate actionable predictive insights and transform data into business value. This can work either at a strategic, long-term level or at an operational, per deal level and forecast sales performance, identify existing and future market trends, and predict the impact of pricing or other decisions. All these can be used to optimize pricing and provide guidance at a strategic level or even specific deals. Because of the business-oriented approach of Cube RM’s Predictive intelligence, the generated insights are easier to understand by business users and can be more easily derived from limited data, which is a common challenge, especially for B2B companies.

The architecture of Cube RM’s Predictive Intelligence

Tender Pricing guidance with Cube RM Tender Central

Cube RM Tender Central, a specialized software for tender management and evaluation, can help improve sales effectiveness by testing several sales scenarios leveraging machine-learning pricing guidance and competitive intelligence. More specifically, the user can create and test alternative sales scenarios for pricing, products, and the competition. Furthermore, the system can automatically generate additional scenarios for different price ranges and products for the company and the competition. For each scenario, the system can use Cube RM’s Predictive Intelligence leveraging past tenders’ information, competitive intelligence, and available tender evaluation criteria to:

  • Automatically calculate scorecards, including pricing, qualitative, and total scores
  • Estimate the probability to win the tender
  • Estimate the potential revenue or profitability
  • Identify the optimum price to maximize revenue or profitability

Tender pricing guidance using machine-learning in Cube RM Tender Central

Based on this information, the system can offer pricing guidance for tender responses, suggest optimum price levels, and identify the most likely winner at different price levels. This can considerably help decision making and improve success rates and profitability for tenders.

Find the best price for your tenders - Never miss an Opportunity!