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Improving Gross Profit with a Promotions Strategy
技术
- 分析与建模 - 机器学习
- 分析与建模 - 预测分析
- 功能应用 - 企业资源规划系统 (ERP)
适用行业
- 食品与饮料
适用功能
- 销售与市场营销
- 商业运营
服务
- 数据科学服务
- 系统集成
挑战
This beverage company’s promotional efforts were falling flat for three key brands. Their strategy was to heavily promote their flagship product during major sporting events to drive top line revenues and earn greater market share. With some success, this strategy became costly and did not generate the return on investment the company was looking for. In addition, other promotions were not sufficient to drive brand profitability as well. The company was lacking insights into the ways that their key three brands should be positioned in three major sales channels – the huge mass retailers, supermarkets, and convenience stores. What was the best way to invest promotional spend to drive revenue, be competitive, and return a greater profitability by brand by channel? Promotions were an important part of this beverage company’s strategy, but company executives realized that they needed better analysis and a simulation tool to understand how to carry out that strategy. They turned to Antuit and asked for a set of “golden rules” that could guide them in terms of what to do – and what not to do – for future promotions.
关于客户
The customer is a major beverage company with a broad range of challenges involving their brand promotion performance. They were looking to improve sales and margins, and gain a better understanding of how to improve ROI. The company faced issues with visibility of overall performance and needed insights into how to position their key brands in major sales channels such as mass retailers, supermarkets, and convenience stores. They sought a data-driven approach to optimize their promotional investments across their brand portfolio, aiming to drive revenue, be competitive, and achieve greater profitability.
解决方案
Antuit addressed the problem with a trade promotion analytics approach that addressed the issues of volume uplift, gross profit, promotional frequency, timing and their impact on ROI. Looking at data from the previous 12 months, Antuit reviewed 75 different promotions across the three brands and three sales channels. Antuit used a machine learning approach to analyze promotions that generated greater than 60 percent volume share to understand the significant factors that contributed to promotional success. Leveraging this deep analytical approach, Antuit produced a scorecard that demonstrated that the company’s past promotions were misallocating the wrong brand in the wrong channel and often against the wrong competitor. It showed that mass retailers and convenience stores were prime opportunities for one of their secondary brands to replace their flagship brand due to a high cost to distribute with little ROI. This brand switching was also critical to be competitive within the hypermarket and convenience store channels by blocking competitive distribution during key occasions. This same analysis was done for supermarkets, and it was clear that another brand was the best choice for supermarkets as well. The flagship brand, despite its limited success with sporting event ties, was one that the data showed should be downplayed. This was a direct result of a lack of local popularity of this brand within the geographical area. With a deep analytical approach, Antuit found that with minor investment in one of the brands, the company could expect an impressive 300 percent uplift through brand switching. The data also revealed, to the company’s surprise, that price was not the most significant factor in predicting promotional effectiveness. More surprisingly, price wasn’t even in the top five most significant factors for driving promotional success. It turned out that the size of the package (how many bottles or cans were in a pack) was the key to improving margin, while the brand itself was the most important factor in driving sales volume.
运营影响
数量效益
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