Market Research

Our client: A parcel and express company with a Europe-wide network

Client's aim: To analyse the structure and demand for transport services in the procurement logistics industry in order to identify potential CEP volumes.

Our solution: Based on our date archives, we showed the market's size and its segmentation in the first step. Based on informative industry profiles, we assessed the demanders' most important industries and especially their potential affinity towards using CEP services. 

In the main stage of the project, we polled 3,000 commercial shippers and logistics providers. Based on this data, plus additional structural information on the covered segments, we developed a prediction model for the development and CEP volumes in the respective industries, their sub-segments and certain branches of trade.

Our customer: A leading express provider in Germany.

Client's aim: Getting an overview of the market and the main competitors in the so-called special-speed market.

Our solution: Initially, our team carried out a structural analysis of the courier and express segments.  The assessment covered both typical city couriers, as well as the so-called same-day market. In both segments, we compared the ten biggest players in both segments with the remaining market, and compiled a detailed company profile for each of the identified competitors. Besides corporate data and key financial figures, the profiles included the range of services offered by the networks. In the final step we made a five-year forecast for the whole market.

Our client: A global parcel delivery provider

Client's aim: Developing a forecast model for the domestic parcel market based on a comprehensive analysis of the domestic parcel market that allows a forward projection of parcel volumes over the next five and ten years respectively. 

Our solution: By conducting a detailed analysis of the parcel market, our team laid the foundation for developing the forecast model and identifying the influencing factors worth considering for the model. During the development, our team assessed the impact of several chosen factors on the development of parcel volumes with regression analysis. The functional relationship of the data was assessed by using optical and logical methods. Based on these assessments, the parametric objective function was modelled. 

Based on the relationship between the influencing factors that was identified by regression analysis, a system dynamics model was created that allowed the assessment of different scenarios. From these scenarios, our team derived each scenario's influence on the client's operations and made recommendations on how to maintain our client's operating efficiency under these projected circumstances.

Our customer: An international CEP provider

Client's aim: Providing a sound overview of the market, competitors and their production structures in the parcel market.

Our solution: In order ensure the compatibility of the results, our team carried out a detailed analysis of the delivery routes of the client's competitors in four different regions. These included an area where B2C deliveries were prevalent, a commercial zone, a mixed region and a peripheral region. By collecting structural information on deliveries in these four regions, we were, for the first time, able to provide exact cost items (for each route/ parcel) when using subcontractors or the company's own drivers. This overview of the market also contained a comparison of line-haul costs and comprehensive profiles of the client's competitors.

Our client: One of the globally leading logistics providers

Our client's problem: Seasonal and regional fluctuations are increasing the costs for outsourced transport services disproportionally.

Our approach: First, our team identified industries with potential collaboration partners with a multi-tiered top-down approach that was geared towards our logistics requirements. In the next step we identified fleet owners in two regions in co-ordination with our client, and portrayed these companies using utilisation profiles. In the last step, we asked the identified companies directly whether they were interested in a collaboration.