Online CPG: A major retailer that offered consumer products online was challenged with ineffective pricing strategies and techniques. The company needed to understand the demand drivers, monitor the marketplace effectively, and develop a pricing strategy to increase profits.
Working with the ‘pricing teams’, it was possible to use SMART AI to expand from a handful of pricing strategy alternatives to a multitude of alternatives that were defined systematically in order to consider the full scope of options. In addition, the demand prediction of their online products improved dramatically allowing foresight to avoid ‘stock-outs’.
Result: 15% higher revenues and improved customer satisfaction by avoiding ‘stock-outs’
Global Quick Service Restaurant Chain: A global QSR chain in need of improvement of their promotional budget spending strategy. They wanted to optimize their advertising spend related to GRP acquisition and coupon-based discounts.
For coupon-based discount optimization, the timing and dollar amount of discount allowed per item had to be calculated for a multitude of scenarios so that decision makers could optimize their strategies. Without curated datasets and machine learning, this would not be possible to the level of accuracy that was achieved.
Result: 98% daily prediction accuracy on promotion revenue.
Global Personal Care Product Company: This international, personal-care brand runs promotions in multiple channels for different product categories on an annual basis. It wanted to understand the impact of price differences with its competitors on its market share for a few of its most competitive products.
We established the basis for a multi-dimensional pricing model by understanding how market dynamics were affected by price changes. We called this a price-demand sensitivity analysis.
In addition, we developed a microapp to deliver optimized predictions and prescribed actions for decision-makers. The microapp simulated market variations resulting from price changes, allowing for “what-if” scenario analysis, and then optimization analysis—in this case on price related to market share. The app was delivered to the company via a web-based interface.
Sales Force Productivity and Optimization
An international pharmaceutical company was having difficulty with its sales force productivity and were looking for changes that could be made to improve their market coverage strategy and product offerings to improve the success of their sales force.
Analysis of purchase history data from doctors and pharmacies along with external data providing context to the purchase history, allowed for an optimized customer segmentation plan of the various markets. The sales force better understood their customers in terms of when, where and what to sell to each customer segment.
In addition, new employee incentives sales programs were optimized and outlined for the sales force by applying SMART AI to a combination of data leading to __ restructuring of incentives for their teams that improved sales and benefits to the teams.
Result: 15% increase in sales revenue.