Price Optimisation to Survive in the Digital Age

Jun 7, 2019 | 2019 Sponsor Updates

Daniel Rueda, Founder and CEO of Open Pricer, describes the impact of digitalisation on pricing and explains why parcel and freight carriers must adopt new pricing methods and technology.

Price Optimisation to Survive in the Digital Age

Jun 7, 2019 | 2019 Sponsor Updates

Daniel Rueda is Founder and CEO of Open Pricer, a provider of price optimisation software for logistics networks. In this article, Daniel describes the impact of digitalisation on pricing and explains why parcel and freight carriers must adopt new pricing methods and technology.

This article is an extract from the Summer Edition of MER Magazine published in May 2019. You can read the full article as well as other articles from MER for free by visiting digital.mailandexpressreview.com.

In the digital age, data is ubiquitous, and everything changes very quickly. These mere observations lead to two imperative changes for pricing:

  • Speed: quotes, which often require several days of preparation, must now be completed within minutes. Most importantly, instant pricing becomes essential for digital channels such as e-commerce platforms and marketplaces.
  • Accuracy: average pricing methods are no longer relevant given the variable and ever-changing market conditions. Fixed prices are replaced by differentiated and dynamic prices.

This last change implies a dramatic increase in the number of pricing decisions that can no longer be managed by human experts. Automation is essential, but rule-based pricing is a sub-optimal answer. Data-driven dynamic models are required to continuously adapt to the market. This article describes how to create a data mart to support pricing decisions and key data-driven price optimisation models.

First step: build a pricing data mart

Before starting a pricing project, we ask our customers to extract data, such as shipments, customer attributes and historical quotes samples. Most of the time, this data is available in their systems, but the exercise often shows that it is in different silos, not easily accessible and not properly structured for pricing decision support.

Hence the first step is to create a pricing data mart that will collect all data required for price setting and monitoring, and make it available to users within seconds (versus several days or even weeks without a data mart).

The pricing data mart is fed on a regular basis (monthly, daily or even in real-time) from internal systems (TMS, Billing, CRM, CPQ) – or corporate data lake – and external sources as well (tender management system, e-forwarding platforms, transportation market places).

The main step is to gather transactions (billed shipments/parcels with their relevant pricing and costing attributes, optional services, supplements and other invoices/credit notes linked to each billing account/contract) as well as customer segmentation attributes.

It is then possible to gradually enrich the data mart with cost models, quotes, capacity/resources utilisation measurements and forecasts; and also to add public information available on the web such as competitors’ offers and market events, that have an impact on demand and willingness to pay…

This article is an extract from the Summer Edition of MER Magazine published in May 2019. You can read the full article as well as other articles from MER for free by visiting digital.mailandexpressreview.com.

Open Pricer are proudly sponsoring the World Mail & Express (WMX) Europe Conference 2019. WMX Europe is taking place at Croke Park in Dublin, Ireland (17 – 19 June 2019). Visit www.wmxeurope.com for more information.

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