Advanced Analytics for Manufacturing - Case Study
When one of our customers, a global medical equipment manufacturer, needed to set up Spotfire for its business analytics unit, our data specialists designed and developed dashboards to meet their requirements.

Each report created enables business users to instantly pull and save their daily reports and send them to their managers. These dashboard reports also help users to track everything from the types of products manufactured, to the length of time products take to be manufactured, where each product is located and by what production process.

With just a few clicks, business users could easily tell which products bring in the most revenue, which have the biggest manufacturing volume, which are most expensive to make and which take the longest to manufacture.

With this solution, our client’s business users avoided many hours compiling data for reports and spent more time making fast, accurate decisions. The solution which was implemented and is now being maintained by Syntelli Solutions, supports over 1,200 users.


Client: Large Appliance Manufacturing Organization

Business Need:

Mapping the consumer experience to identify behaviors that occur at targeted points and developing insights in order to positively influence the process and drive consumer behaviors

Challenges:

  • Lack of insights on how to properly target the consumer, resulting in increased ad spend without a direct link to revenue results.
  • Understanding what web content drives sales.
  • Understanding which marketing media channels contribute to sales

Solution:

  • Syntelli’s data science team calculated consumer lifetime value to provide value for the consumer throughout product ownership and ongoing laps around the consumer experience
  • Built marketing science practice with: net present value, forecasting, record matching and data lake
  • Built models that estimated historical contribution of all marketing media channels and pricing strategy to sales.

Value Added:Advanced Analytics in Manafucturing

  • Created a relationship graph of all inbound consumer website activity
  • Established a link between “Where to Buy” web searches and sales activity
  • Identified web content, product pages, and search activity that are predictors of sales
  • The consumer lifetime value model allows for better determination of marketing spend to maximize value of marketing and products to consumers

 

Read about the details of this case study here: Read Case Study 

 


 

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