In　the　today’s　competitive　environment,　employee　retention　is　a　challenge　faced　by　many　industries.　This　work　aims　to　identify　the　factors　that　influence　employee　retention.　This　is　done　using　employees’　feedback　and　various　computational　techniques.　A　survey　is　conducted　within　multiple　sectors　to　collect　data.　The　questionnaire　is　divided　into　two　parts:　the　first　part　includes　demographic　information,　whereas　the　second　part　contains　questions　pertaining　to　employees’　job　description　and　their　satisfaction.　The　questions　on　the　second　portion　are　based　on　theories　like　Herzberg’s　duality　theory,　expectancy　theory,　social　cognitive　theory,　and　sociocultural　theory.　These　theories　are　further　linked　with　factors　like　motivation,　recognition　and　reward,　bullying　and　work　harassment.　Later,　the　frequent　items　mining　technique　from　the　domain　of　data　mining　is　utilized　to　identify　the　frequent　factors　from　an　employee　perspective　toward　better　retention　rates.　A　test　is　also　conducted　to　ensure　the　reliability　of　the　data.　The　obtained　results　indicate　it　to　be　87%　reliable.　A　comparison　between　two　frequent　items　mining　methods　indicates　four　times　quicker　performance　of　the　k　Direct　Count　and　Intersect　(kDCI)　method　in　identifying　key　retention　aspects　from　the　data.　A　tool　is　utilized　for　analysis　of　variance　(ANOVA)　and　exploratory　factor　analysis　(EFA)　tests　to　find　factors　crucial　for　retaining　employees.　The　result　identifies　that　work　environment,　reward　and　recognition,　work　performance,　supervisory　support,　and　income　have　high　impact　on　employee　retention.　©　2020,　Springer　Nature　Switzerland　AG.