Use of Artificial Neural Network for Inquiry Follow Up System in Sales Operations for Two Wheeler Automotive Dealership
Vaidik Bhatt1, P Sashikala2
1Vaidik Bhatt*, Research Scholar, Department of Operations & IT, ICFAI Business School (IBS), Hyderabad, The ICFAI Foundation for Higher Education (IFHE) (Deemed, University.) Hyderabad.
2P Sashikala. Professor, Department of Operations & IT, ICFAI Business School (IBS), Hyderabad, The ICFAI Foundation for Higher Education (IFHE) Deemed, University, Hyderabad.
Manuscript received on December 17, 2019. | Revised Manuscript received on December 22, 2019. | Manuscript published on January 10, 2020. | PP: 1268-1272 | Volume-9 Issue-3, January 2020. | Retrieval Number: C8713019320/2020©BEIESP | DOI: 10.35940/ijitee.C8713.019320
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Artificial neural network can be the good classifier based on its capabilities of supervised learning and back propagation of the error. We have used this capability of ANN for distinguishing buyers and non-buyers in the automotive industry sales to save the time of the sales consultant in order to provide the better services to the potential buyer and convert the inquiry into the sales. Based on the six parameters with the ANN consisting of one hidden layer and 4 hidden units we have checked the results which is satisfying.
Keywords: Based on the Six Parameters with the ANN Consisting of one Hidden layer and 4 Hidden Units we have Checked the Results which is Satisfying.
Scope of the Article: Networking theory and technologies