Promotional Spend Analytics Using AI for PFME Allocation and Coupon Redemption Optimization
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Abstract
Promotional fund management will also require smart resource distribution, good financial categorization, effective coupon redemption and budget management. The article proposes an at least AI-driven Promotional Fund Management and execution (PFME) allocation and coupon redemption optimization model through the balance between the predictive analytics and enterprise-wide process automation. The structure brings together promotions, product and brand level, client response, campaign, coupons, barcode interface, financial allocations, marketing funds. Promotional response and coupon redemption probability prediction are made by machine-learning models to recommend allocation of funds across products, brand, channels and campaigns that are subject to extracted budget constraints. The structure plans out the processing of Inmaar coupon and barcode redemption as well as establishing the Work Breakdown Structure (WBS) and General Ledger (GL) account. It also supplements Corporate, Regional and Local brand structure, settlement-rule and profit-centre decision at planning levels 3,5 and automatic budget approval based on product and brand structures. Constant-budget tracking recognizes where the budget might be exceeded, and can preventive measures against the limits on the marketing-plan. Learning system experience A closed-loop driven learning system will combine the results of the campaign, spending, sales and redemption values to rectify the subsequent decision. The suggested system provides a system of combined promotional analytical and financial governance. Promotional return on investment, incremental sales, redemption rates, processing efficiency, financial-mapping accuracy and budget-compliance metrics can be utilized in measuring its effectiveness.
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