Social Media Insights for Product Planning and Development: Global PC Manufacturer

Background
Lenovo, a global manufacturing giant with over $30BN in revenues wanted to integrate social media generated customer insights into their product planning process. They sought to incorporate the voice of the customer and competitive analysis to systematically be included into the R&D and product management processes.

Assignment
CoreCompete had to develop an overall process for incorporating these insights into the product planning process. We had to develop a roadmap for the client with the necessary customer insights based solution milestones that would fit into the product planning timeline. There was a need to deploy an interactive tool that would capture customer voice across various channels, generate meaningful insights based on customer expressions and sentiments shared online and piece in storylines that cater to various stakeholders in the product and portfolio planning processes.

Value Delivered
CoreCompete delivered the end-to-end solution over a 12-week engagement. We demonstrated the scope of customer insights driven concepts and the value they could add along the product development timeline. Our analytical model used advanced text analytics, sentiment analysis, segmentation and visualization techniques to harness the massive online data volumes into focused and actionable customer insights based recommendations. The final product was successful development of an advanced data management framework to automate and scale the end-to-end process of collecting unstructured online data to the final, user-friendly recommendation engine on visualization platforms.

Case Studies Customer Analytics & Marketing

Customer Retention: Using Social Network Analysis to Combat Telecom Churn

Background
Our client was a large Communications Service Provider (CSP) in Africa. This client had already implemented models for churn identification/ reduction utilizing traditional methods that score customers based on their individual behaviors. They wanted to expand on these traditional models using network behavior (Who’s communicating with Who? What type of communication? How frequently and How long?).

Assignment
CoreCompete was responsible for defining the data model, developing the ETLs and building the models that would allow the client to understand the role a particular subscriber plays in the network (influencer, follower). This system was required to work in an automated manner and needed to aggregate a large volume of call detail record (CDR) data. The system included capabilities for detecting issues such as super-nodes and other outliers and ensure that the recommendations were meaningful.

Value Delivered
CoreCompete completed this project in 12 weeks. The models incorporating this new input were generating 28% more lift than the previous models (that were based solely on a single subscriber level data). The system scales to deal with millions of CDRs on a regular basis. The entire process is automated to minimize the operational impact on the analytical and operations teams.

Case Studies Customer Analytics & Marketing

Price Optimization: Consumer Packaged Goods Company

Background
Our client, a global food manufacturer had more than 5000 individual SKUs that were sold through their direct and distributor network to major retailers across the US. They had very little insight into
what pricing tactics were effective when creating trade deals. They evaluated various optimization oriented solutions, but felt they were not the right fit for their organization due to their complexity and practicality in their sales and customer environment.

Assignment
The client asked CoreCompete to provide a capability that will allow them to systematically understand the key price points that need to be considered when creating trade deals. This was intended to be achieved through automated generation of insights that allowed the users to see the impact of price on case-volume. These key price points needed to be understood for base prices, promotional prices and key competitive price gaps.

Value Delivered
CoreCompete developed a system that takes weekly sales data and generates price point curves and identifies a meaningful relationship between price and volume, highlighting key price points. The account teams, sales and brand management can utilize this information in decisions such as: price list updates, trade deal creation and competitive price gap analysis.

Case Studies Merchandising & Supply Chain Analytics

Price Margin Visibility: Global Eyeglass Lens Manufacturer

Background
Our client had more than 10,000 individual SKUs that were sold to 30,000 major eye care groups across the U.S. using more than 1000 pricelists.  They lacked an understanding of customer pocket margin, causes for margin leakage, effectiveness of various price lists for achieving ASP growth, and impact of different pricing/ promotion tactics on price-volume-mix.  They evaluated various integrated pricing software solutions, but concluded that these were not practical due to cost, data requirements, and maturity of their organization.

Assignment
CoreCompete created a pricing data lake by combining data from more than six enterprise systems. We delivered self-service pricing analytics dashboards and tools for the pricing organization to systematically gain visibility into the customer pocket margin leakage, assess the impact of pricing changes on revenue-mix performance, and compare price lists for account level value capture. In addition, cross price-elasticity models were developed to estimate volume impact of price changes on the overall portfolio.

Value Delivered
CoreCompete delivered the key pricing analysis capabilities, enabling our client to identify more than $20 million in pricing benefits through more effective discounting and streamlining the annual rate increase program.  In addition, the pricing team has been leveraging the integrated pricing data lake to create additional analytical models and custom applications for improving price execution and providing guidance to the sales team on key account price negotiations.

Case Studies Merchandising & Supply Chain Analytics

Innovation Theater: Analytics Innovation Infrastructure for Global Manufacturer

Background
Our client embarked on a mission to transform their business using big data and analytics. They wanted to rapidly try new and innovative ideas in a rapidly changing marketplace. They needed initial investment in these ideas to be low and wanted to make a commitment once the idea was proven inside their organization.

Assignment
CoreCompete was asked to design and deploy a cloud based solution that will allow them to manage their range of analytic workloads such as: text analytics, forecasting, price elasticity, supply chain optimization and self-service BI/ data discovery tools. They needed these solutions to be capable of supporting pilots across a number of initiatives while being cost-effective.

Value Delivered
The initial go-live for this ambitious system was complete in 4 weeks. CoreCompete worked closely with the software vendors and ensured that all the tools that were required for this environment functioned effectively. We supported the client to migrate POCs that were being conducted on personal machines into a managed environment that was capable of supporting incremental data loads and a large number of users. Within 8 weeks of starting the implementation, Pilot projects were live, demonstrating the value of the big data and analytics for the organization.

A3 For Enterprises Case Studies

Agile Analytics Lab: Analytics Innovation Infrastructure for Pharmaceutical Major

Background
Analytics executives at this Fortune 500 client were constantly facing demand to reduce the time it takes to deliver on analytical requests/ innovations. Traditional procurement, budgeting, planning and prioritization were the key bottlenecks. They needed on-demand IT and computing to support their analytical organizations.

Assignment
CoreCompete was asked to deliver the Agile Analytics Lab on Amazon Web Services (AWS). This managed service enables the client’s analytics organizations to leverage cloud computing resources for their data warehousing, data mining, text mining and business intelligence needs and roll-out new analytical innovations in a matter of days. In addition, they wanted to be able to bring data from their partners online to support collaboration on generating insights.

Value Delivered
We completed the pilot in 12 weeks. The pilot demonstrated to the client the feasibility of utilizing the AWS infrastructure for analytical innovation and collaborating with value chain partners on key analytical initiatives. The infrastructure currently enables the client to utilize – data warehousing, text mining and self-service reporting capabilities.

A3 For Enterprises Case Studies

Agile Analytics on Amazon: For Enterprises

Analytics organizations need to rapidly bring large amounts of new data from a variety of sources and analyze using scalable and efficient infrastructures.

IT organizations are struggling to keep up with existing initiatives. In addition, traditional processes for data warehousing, budgeting and procurement do not lend themselves easily to innovation and agility.

A3 addresses these challenges by providing a secure and scalable infrastructure and complementary services that allow you to deliver analytical innovation without breaking the bank.

A3 For Enterprises Case Studies
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