Abstract
The study examined the role of data mining in improving productivity among Small and Medium
Enterprises (SMEs) in North East Nigeria. A descriptive survey design was employed for the
study. A sample of 300 SMEs was selected across six states in the region using stratified random
sampling techniques. Data were collected through structured questionnaires and semi-structured
interviews, and were analyzed using descriptive and inferential statistical methods. The findings
revealed that 63.3% of the SMEs were moderately to highly aware of data mining techniques,
but only 34.2% actively applied them in business operations, indicating low integration into daily
management practices. A strong positive correlation (r = 0.613, p < 0.01) was identified between
data mining usage and productivity improvements, with sales growth and customer retention
being the most significant areas impacted. Key challenges hindering adoption included lack of
technical expertise (71.2%), high cost of technology (60.1%), and limited access to reliable data
(55.4%). The study concluded that while data mining holds great potential to enhance SME
productivity, significant structural barriers must be addressed. It recommended that stakeholders
improve digital infrastructure, implement training programs, and introduce supportive policies to
foster greater adoption of data mining for sustainable SME growth and regional economic
development.
Keywords: Data Mining, SMEs, Productivity, North East Nigeria, Technology Adoption.
Publication Date: 2025-11-08