Using machine learning to predict sales and ROI at POS
Owing to operating sales from various points of sale, a renowned tobacco company was struggling to find out an efficient way to improve results. When they came to us at Glorious Insights we helped them by optimizing their process of marketing, increasing sales, and effectively increase their ROI at different points of sale. Check out this case study that discusses how machine learning helped in the prediction of sales and ROI at POS.
Customer background
This case study is about a well-known tobacco company. The company has its clients at many geographically distributed areas covering a vast region on the map. Also, it provides a wide range of tobacco products to cater to different types of customers. It uses various marketing strategies and techniques to increase the visibility of its products and increase its sales.
As the company operates its sales from different points of sale, it needed a solution to understand the demand at each point of sales. The quest of the company for an effective solution, that can predict the sales and help improving it ended with the Glorious Insights.
Challenges
The key challenges faced by the company can be better understood in two parts.
- Optimizing the marketing process
The company has various outlets distributed over a wide geographical range. The preferences of the customers at each point of sale is likely to be significantly different from those on the other. A solution is needed to understand this diverse preference of the customers and optimize the marketing process accordingly.
- Increasing sales and return on investments (ROI)
With a better understanding of the interest and expectations of the customers, the solution must enable the company to increase its sales. It also looks for an increase in returns on every penny spent on advertising and promoting the products.
The present system works manually, which means the prediction of sales is solely based on the experience and intuitions of the sales executives. An automated system is needed that can provide more accurate and comprehensive information much faster to enable better marketing.
Solution
The team at Glorious Insights worked with the company’s sales and marketing teams to understand their requirements for business intelligence. We decided to work on an iterative model that would allow us to work closely with the company and let them use the system from the beginning stage itself. The company provided valuable feedback that helped in the regressive improvement and helped deliver exactly what was needed.
- Functional aspect
The Glorious insights developed the solution that could provide faster and timely access to the statistical models developed on the basis of the company’s datasets. These models give a comprehensive view of the market trends and marketing expenses and their impact on sales.
The solution system could analyze different parameters like POS location and others that are related to geographic and socio-demographic factors. It could also process seasonal consumer behavior, local macroeconomic factors, and consumer solvency. It could replay the scenarios to pick the best marketing strategy. The system enabled this analysis at different levels such as POS, groups of POSs, and region.
- Technical aspect
To process the data, a cloud-based infrastructure was used that could provide a scalable solution and work well with big data. It also allowed us to capture data from diverse sources such as customer feedback, social media reviews, marketing texts, weblogs, etc.
We created the system by deploying ready-to-use machine learning algorithms in the form of data mining libraries and open components. ML algorithms provide efficient and faster modeling of uplifted predictions of the ROI.
Regression machine learning helps in stimulating and replaying market scenarios to derive the most suitable marketing strategy. It makes it possible to allocate resources more efficiently than could yield more returns on investment.
Results
The new system fits excellently in the distributed functioning of the company. It provides timely insight into the critical factors that drive the marketing policies and impact significantly on sales and revenue generation. The new system is scalable and can accommodate and encourage business growth. Main benefits achieved by the solution system are:
- Customer segregation and targeted campaign
With more precise information analysis, it is now possible to segregate the customers based on different factors like age, geography, etc. The timely delivery of this information enables the team to develop area-specific targeted marketing campaigns.
- More accurate price model and margin forecast
The system also simplifies the creation of a more accurate price model. These models have a better allocation of resources to maximize the margin.
- Sales forecast, planning, and channel management at each POS
The company can now predict the sales precisely and plan the strategies accordingly. It is much easier now to implement these strategies at each POS and adjust and improvise in real-time.
