SMEthod in English

Segmenting SMEs for better innovation support


The SMEthod project aims to provide a methodology for segmenting SMEs for better innovation support.

The project's primary purpose is to answer three key questions:

- How efficiently are SMEs supported?

- How can we segment innovating  SMEs?

- How can we optimise public support?


SMEthod will evaluate the existing methodologies for segmenting SMEs for innovation support and deliver an improved methodology for segmenting SMEs that:


- Takes into account enterprise lifecycle, industrial sectors, regional characteristics and innovation cycles

- Better matches innovation support measures with segments

- Provides an online decision support tool to help innovation-supporting agencies support SMEs.


This will lead to:

- A better understanding of innovation in SMEs and the influence of specific innovation support measures

- Increased uptake and efficiency of funding mechanisms

- Improved targeting and timing of innovation support measures

- Smart targeting of innovations with the most desirable societal impact

- More predictable and successful innovation by SMEs, which will improve the competitiveness of the EU economy.


Why is this important?


Small-and -medium-sized enterprises (SMEs) have a significant impact on the EU economy and play a crucial role as innovators. However, SMEs often lack the finance to realise their innovation potential and economic impact. Support instruments and policies address this problem, however there is a lack of adequacy, especially when we consider local, regional and national dimensions. Support instruments and policies require strong segmentation methodologies to guide SMEs towards the most appropriate and value creating measures. The SMEthod project aims to address both issues and deliver an improved methodology for segmenting innovating SMEs, whilst considering different levels and types of support.


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The SMEthod project runs from December, 2017 – June, 2020 and involves seven specialist partners from five countries:




©2017-2020 SMETHOD This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement number No. 777491.