Achieve Profitable Growth

Parcels networks make millions of pricing decisions per year, having a critical impact on business performance.

These decisions are complex because they depend on an increasing number of cost and willingness to pay drivers: service levels, type of good, origin, destination, weight, customer’s industry, revenue tier, sales area, pickup time, parcels’ dimensions, delivery density…

Customers requests quicker quotes, sales reps and analysts are unable to screen all these drivers, which leads to profit leakage.

Digital Pricing uses machine learning to compute all this complexity in seconds so that sales reps and analysts can make accurate pricing decisions based on all relevant support data.

DELIVERING PRICING POWER

Build a Pricing Data Mart
Gather and made available in seconds all historical data that is necessary to calculate accurate prices in real-time. This covers internal data (transactions, costs) with all logistics parameters (weight, dimensions, origin, destination) and external data (market prices and market events).
Implement an AI Driven CPQ
Take business savvy decisions by adopting a profitability simulation capable solution, which predicts the willingness to pay of your interlocutor based on a price benchmark of similar customers.
Optimize customer lifetime value
Identify the right actions to capture the maximum business and value from your customers, including rerating strategies and targeted promotions differentiated by customer.
Last mile pricing
Address your e-commerce customers challenges regarding B2C expectations such as delivery flexibility and product returns. Dynamic pricing solves all of these with additional positive side effects, among which delivery rounds rationalization which helps reduce CO2 emissions to preserve the environment.

OUR CLIENTS

React, Rebound and Reinvent
10 Solutions to Help Parcel and Freight Carriers to Recover and Strengthen. This research is based on interviews with carriers about their challenges and how they have been dealing with the current crisis.

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Predicting Willingness to Pay
Find out how market research and data science show that customers have different willingness to pay (WTP) and that many customers are more sensitive to value than price.

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