Advanced Analytics Based on Digital Data © 2015 Blueocean Market Intelligence1

Setup and integrated multiple data sources to provide unified customer profiling and targeting platform © 2015 Blueocean Market Intelligence2 Client: Leading PC Manufacturer in the US Technology Industry: Seamless data integration. Scaled up customer Database. Highly accurate and robust platform acting as single source of truth Business Impact: Initial workshop: −Blueocean Market Intelligence conducted detail and in-depth analytics workshop to build initial understanding of business requirements and priorities Data integration and storage −Setup the cloud based technology stack to deliver global and scalable solution −Developed host of APIs and other data bridges to integrate data from different client owned and 3rd party platforms −Created metadata and schemas to be leveraged for scale −Leveraged industry MDM best practices to drive effective data storage practices Business insights and deployment −Developed visualizations by leveraging industry leading platform Tableau™ and created various analytics applications to meet business requirements Approach Study Objective The client wanted a unified view of their customers across their different business lines – B2C, B2B, EPP and B2V Insufficient customer details and incorrect data leading to inaccurate customer targeting causing low customer conversions Lack of integration among different databases and inability to link data among them hampered plans to create a central database and “one view of the customer” Inability to measure efficacy of marketing plans Result Integrated data from 45+ sources and scaled up unified customer database intelligence output delivered weekly 425+ business users leveraging the solution drive business strategies Lift of 17.5% on the upsell and cross sell programs Improved customer retention and enhanced customer experience by improving NPS at 20 basis points Consolidated 360 view of customer information

Integrated multi channel data for optimized attribution modeling and accuracy © 2015 Blueocean Market Intelligence3 Client: Leading PC Manufacturer in the US Technology Industry: Improved channel attribution and accuracy in reports. Better ROI level insights driven by custom BI solution. Improved brand advocacy and loyalty driven by actionable BU solutions. Business Impact: Blueocean conducted series of workshops to understand business drivers, activities and also define the actual list of hypothesis which need to be solved Prepared and integrated several data sources such as client CRM, web metrics, promotion and product data and publically available demographic data Blueocean team build a multi - regression based attribution model using to determine allocation for different channels to maximize the ROI Approach Study Objective To understand the contribution of online channel and marketing spends and measure the ROI thereof This analysis will help optimize marketing strategies/ digital offer policies To identify distinguished segments within overall customer pool This understanding would help employ customized marketing and targeting policies to maximize sales and revenue Result Integrated data from 35+ sources and scaled up unified marketing database A 70% accurate attribution model which improved the decision making process from a previous model at 15% Effective online strategies resulting in improving brand advocacy by 15% Historic Sales Social Media Industry Demand Seasonality / Promotions Secondary Data Attribution Model

Collaborated with the client to implement big data architectural roadmap to drive multi channel insights © 2015 Blueocean Market Intelligence4 Client: Leading PC Manufacturer in the US Technology Industry: Highly scalable and flexible solution. Seamless data integration. World class data architecture and governance plans. Business Impact: Blueocean team conducted a series of workshop to understand different data sources, significance of BU wise KPIs and metrics, closely watched numbers by GEOs, workflow management for all the varied data sources and a common primary identifier to connect Post month long workshop with all GEO level stakeholders, Blueocean team created data source and process blueprint – which would be used as the reference guide for implementation and deployment of the big data platform Blueocean team set up a global delivery center with team of big data specialists and business analysts to drive seamless transition between business to technical requirements Post sign off, Blueocean team set up proprietary technology stack based on different technology arms (e.g – APIs to drive different extraction procedures, Amazon S3 for storage, Talend solution for data classification and ETL processing and combination of Tableau / Qlikview for reporting business KPIs and metrics Approach Study Objective One of the leading technology clients in the US had envisioned a roadmap to integrate multi channel, multi source and different types of data (structure and unstructured) in a single platform to ensure business stakeholders believed one single source of truth for all business KPIs and Metrics Till the time this initiative was planned and launched – different GEOs, regions and teams were using their own reporting and insights techniques and methodologies to keep track of changing business patterns To drive more accountability and consistent reporting practices, client sponsors specifically required data from different sources to reside in a single platform based on which reporting, BI and Insights practice would be set up Result Achieved $85MM in incremental revenue Seamless integration of 40 disparate data sources, which currently process over 250 data transformations daily 64 standardize dashboards with 8300 instances of ad hoc analysis and insights delivered to client in first 4 months World class data architecture and governance practice, empowering data enrichment, visualization and multichannel analytics

Gender prediction using supervised learning algorithms for a fortune 500 company © 2015 Blueocean Market Intelligence5 Client: Leading online ecommerce company in the US eTail Industry: Accurate prediction algorithms. Real time GUI for end users driving higher degree of solution usage. Business Impact: Initial data provided by the client was a set of user IDs along with the application names Data cleansing and transformations were performed in order to ensure data can be fed to a supervised learning algorithm The data provided was highly imbalanced and skewed towards males as it was the dominant class to be predicted; applied weighted measures to give more importance to the minority class Support Vector Machines Learning Algorithm was applied to predict gender of the subscribers Approach Study Objective The client is a pioneer in measurement of mobile subscriber behavior and wanted to understand the gender of the subscribers based on installed Apps The metering application installed on smart devices captures behavior of the device accurately and this information was to be used by advertisers in order to ensure focused and targeted marketing Result Achieved accuracy close to 80% for both classes of interest Developed an integrated solution with a GUI to enable real time results to be obtained based on real time data feeds to the learning algorithm

Extracted insights from various forums using advanced text mining for a technology major © 2015 Blueocean Market Intelligence6 Client: Leading PC Manufacturer in the US Technology Industry: Better segmentation strategy. Automated issue classification. Enabled targeting marketing efforts based on data science. Business Impact: Merged and cleaned forum and agent transcript data to create 130,000 rows Data received had a breadth of topics and had 6 levels of classification for each row. Level 5 has the highest number of distinct nodes at 4277 followed by Level 3 at 616 nodes Team built a comprehensive dictionary based on a thorough understanding of the entire dataset Business rules were created combined with the synonym-sets to build the model Approach Study Objective The client was currently classifying issues manually (cost ineffective) which are posted by customers on the company’s multitude of Tech Forums and call center agent transcripts The client wanted to automate classification of text data to achieve accuracy close to what was being achieved manually Result Achieved accuracy close to 60% in the 1st iteration Provided a roadmap to enable classification of issues on general blogs and forums

Identified future attrition using a predictive scorecard and reduced attrition by 25% © 2015 Blueocean Market Intelligence7 Client: Leading bank in APAC region Financial Industry Industry: Insights into measures to reduce attrition. Customer level credit scorecarding. Propensity scores prepared using customer behaviour and attitudinal analyse. Business Impact: Attrition Scorecard to predict the propensity of customers to attrite given his current demographic & behavioural characteristics Approach Study Objective A leading bank had a high attrition rate Management wanted to know the root cause of this attrition Need road map for retention strategies Result From the model, we targeted top 3 deciles contributing to 68% of the total attriters and helped address attrition Customers that have higher likelihood to attrite Lesser frequency of ATM usage in last quarter Lower number of products customer is holding Have not been active on Bill payment or POS in last quarter Decreasing SA Average Balance or dormant in last quarter % of targeted clients 6% 68% Targeting Model deciles $ XX K increase in Net Income over 1 year 25% decrease in Attrition Top 3 deciles include over 68% of the total attriters

Implemented analytical measurement system to track ROI from B2B marketing initiatives © 2015 Blueocean Market Intelligence8 Client: Leading PC Manufacturer in the US Technology Industry: Seamless data integration. Scaled up customer Database. Better prospecting and profiling of B2B segment. Higher ROI from targeted campaigns Business Impact: The Blueocean Market Intelligence team set up a analytics hub consisting of datawarehouse specialists, data visualization specialist and digital scientists. A series of workshops were conducted to understand business activities to define KPIs for success parameters. The team integrated several data sources such as Eloqua,CRM ( Salesforce), web metrics, ( Adobe Marketing Cloud), Sales data (SAP)and agency Data (media spends and budgets). Consulting was provided to re-structure the digital tracking to capture required metrics and the existing BI and data integrations process was redesigned for more accurate tracking on RM / B2Bmarketing initiatives. The team conceptualized, designed and implemented a big data platform with proprietary technology stack to drive on demand, real-time dashboards and insights Approach Study Objective This client was struggling to attribute campaign measurement success KPIs across the board and wanted immediate help with proper reporting, attribution and analysis of ROI arriving from their B2B marketing initiatives. The existing CRM database used by the relationship marketers and B2B team had a good deal of non- standardized / unstructured data formats that needed to be cleaned. After completing the first two objectives, they also requested that the cleansed data to be used as input to launch targeted digital campaigns Result Integrated 21+ data from multiple sources, and scaled up the existing unified marketing database Implemented highly effective predictive models to forecast marketing spends and expected revenue at confidence levels of 85% and R2 values close to 75% Improved accuracy in tracking digital marketing data with close to 80% CL of attributing KPIs to campaigns Enabled a very seamless automated mechanisms of budget allocation for each B2B campaign – basis propensity models and visualization techniques

Implemented proprietary lead analytics engine using advanced analytical models (1/2) © 2015 Blueocean Market Intelligence9 Client: Leading Cloud Solutions Company in the US Technology Industry: Better lead scoring. Improved marketing to sales lead flows. Reduced lead leakage powered by more robust lead nurturing process. Business Impact: The Blueocean Market Intelligence team deployed a team of analytics SMEs and domain experts to analyze various metrics indicating prospect touch points on the funnel. Post exploratory data analysis (EDA), the team created a detailed modeling approach using logistic regression techniques to arrive at probabilistic scores highlighting prospect propensity to convert. They deployed cluster analysis to arrive at a decision sciences mode highlighting at risk vs. dormant customers. Prospect segmentation was then performed to identify and conduct RCA on non conversion of certain leads. A combination of quantitative methods and qualitative analysis were carried out to lock on reasons for a high sales follow up Approach Study Objective This client’s stakeholders were worried about issues related to poor lead quality and sales pipeline and funnel indicating lack of a robust lead scoring mechanism. Specifically, the client requested that Blueocean Market Intelligence create a propensity model at marketing team level based on the attributes of the identified leads to segment/tear them into high and low propensity of conversion. The team was tasked with creating a decision sciences model to analyze at risk and dormant leads, identify the factors leading to the non-conversion of leads at sales team level and identify the possible reasons or factors leading to a high sales follow up rate. Result Accurate decision making with customer micro-segmentation improved the overall funnel efficacy Targeted marketing - 25% increase in converted leads at the sales team level post implementation of recommendations TAT for lead conversion (aggregated) reduced by 15% Robust propensity score carding model achieved with weekly / monthly score carding provided to key stakeholders Follow up rate reduced by 20% QoQ Productized an insights process using attributes which highlight risky and dormant leads (e.g – months / days since last purchase, follow up rate, funnel conversion rate etc.)

Implemented proprietary lead analytics engine using advanced analytical models (2/2) © 2015 Blueocean Market Intelligence10 Features Multi attribute based model highlighting quality of leads coming via the sales Comparison of lead quality as they flow into marketing and sales funnel, during the qualification process Helped clients streamline the entire flow of lead generation using recurring reports and alert mechanism Project Advanced modeling project to create intelligence around a lead funnel

United States | United Kingdom | India | United Arab Emirates Transformation © 2015 Blueocean Market Intelligence11 For more information: Anees Merchant Bhaskar Dey