The client, a large US public utility, was looking to understand the key drivers that influence the propensity to enroll in their program. They wanted to identify which residential customers are the best prospects for the program and optimize campaign costs by targeting the best subset of prospective customers. The challenge was to develop a robust and scientific framework to decrease mailing costs, and increase the campaign response rate by targeting only the best prospective customers for select rate plans.

The client, a large technology company, wanted to better target profitable segments for acquisition and enhance engagement with their profitable customers to drive digital utilization. They aimed to propagate engagement to drive customer brand advocacy. The company sought to create more personalized engagement initiatives based on digital profiles, avoiding a one-size-fits-all approach in their marketing campaigns and considering customer preference in defining engagement models.

The client, a leading devices and services company in the IT industry, recognized the potential of predictive maintenance in transforming their strategic and operational environment. However, due to the industry’s infancy, the client faced challenges in understanding the competitive dynamics and the impact of predictive maintenance on their business. They wished to analyze the market landscape of predictive maintenance offerings and gain insights into key vendors, company backgrounds, details of offerings, launch timelines, use case stories, industry focus, and list of customers.

The retail client, based in Dubai, was already running in-store mass promotions every year to drive sales and enhance customer relationships. Each sale period ran for about four weeks and customers received a discount ranging from 25% -75% with every item they bought during the sale period. However, the client wanted to increase revenues and footfall and thus, asked Blueocean Market Intelligence to devise personalized targeted campaigns (BTL-Below the Line).

The client, a leading US PC manufacturer, 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 be used as input to launch targeted digital campaigns.

The client, a leading devices and services company, wished to carry out a market scoping and ecosystem study to validate its perceptions on the opportunities in the machine to machine market before making investments. The client hypothesized that as the M2M industry extends its focus beyond niche verticals, efficient device management, onboarding and IoT functions will become essential. These functions will make more M2M services viable and will encourage more consumers, enterprises and governments to trust and embrace M2M. M2M device management standards will safeguard and secure M2M devices. These standards will also unlock new service opportunities by making it easier to harmonize, simplify and scale M2M operations to support billions of connected devices. This has created considerable business opportunities for various devices and IT solution providers, including the client.

Blueocean Market Intelligence was tasked with providing a comprehensive market roundup of the top digital wallets available globally and assessing various business models to understand how the market is evolving to include different and innovative payment solutions. The client wanted to understand the current prevalent industry business models and gain strategic competitive insights. The research was to be executed using an all-inclusive secondary/desk research, pulling information from syndicated sources, publicly available information, and other existing research owned and shared by the client.

The client, a leading Fortune 500 global technology company, was facing a challenge in deploying real-time, interactive, and user-friendly dashboards for cross-functional stakeholders. They needed custom and personalized reporting solutions that incorporated multi-layer drill downs showcasing revenue, traffic metrics, orders, funnel conversion rates, etc. Part of the solution required integration with various online and third-party data sources for a 360-degree view of the client's business.

The client, a leading pharmaceutical company, was seeking to drive better city/state-specific campaigns to increase the adoption and sales of their sunscreens. They wanted to develop weather-based campaigns to drive effective selling of the seasonal product and enhance the ROI on campaigns. The challenge was to understand the business drivers, activities, and define the type of business scenarios and products that could be ingested in the campaign.

The client, a leading PC manufacturer, was looking to track unaided consideration and other brand health metrics for themselves and their competition. They wanted to assess the reasons for consideration and non-consideration. The challenge was to conduct a brand tracker study based on a 360 approach in over 40 countries. The core methodology was to be based on quantitative primary research, augmented with Market Intelligence/ Competitive Intelligence and social intelligence.

The retail client was in need of a balanced scorecard model that would enable its senior leaders to understand the drivers of store-level financial performance and empower the delivery of the company’s brand promise. The client’s hypothesis was that the delivery of its brand promise would directly impact customer loyalty - supporting client retention, repeat purchasing and cross sales. They also believed that effective delivery of the promise was driven by employee satisfaction and productivity. To prove their hypotheses and achieve their objective, the client needed to merge a multitude of different research studies – past and present - into one single database, and then analyze that data at both the customer and store level.

Blueocean Market Intelligence’s client, a leading technology multinational, had huge volumes of user experience data and wanted to mine insights to enhance the user experience. The goal was to improve customer satisfaction by ensuring ease of navigation and user preferability. This included identifying patterns in data and making data cuts to suggest linkages in constituents which otherwise seemed to be absolutely disjoint. The client also wanted to give pointers to the software quality management team for ensuring better quality. The client was faced with key questions such as: Are users enjoying the experience as they navigate through the product? Is the GUI comfortable for the user? What causes bugs? How can the User Interface (UI) be improved?

The client, a leading insurance provider in India, had recently acquired Adobe Marketing Cloud solution. They sought the expertise of Blueocean MarketIntelligence to assist with the implementation of Adobe Marketing Cloud, specifically Adobe Analytics and Adobe Target, for their four web properties. These properties included their e-commerce site, corporate site, mobile website, and CSG application. The client needed a robust platform implementation that would provide advanced analytics support and create incremental revenue opportunities.

The client, a large US public utility, was faced with the challenge of developing a sequential, bottom-up impact model to establish the relative impact of nearly 50 separate customer touchpoints associated with specific functional dimensions related to overall Trust and Service Experience, on overall Customer Satisfaction. The client also needed to identify improvement areas for each quarter and establish an algorithm to develop customer satisfaction goals for performance measurement.

India’s largest telecommunications company, with over 200 million mobile customers and an online revenue of USD one billion, was struggling to leverage its vast customer base effectively. The company was using disparate offline data sources to track bill payments, recharge history, and minutes usage, but it was unable to identify customers uniquely. The company's key objectives were to identify online users as soon as they landed on the site, assign a unique ID to them, map the unique online customer ID to offline data using Adobe Audience Manager, create and render personalized offers to customers based on various variables, and create opportunities for pushing mobile APP to smartphone users.

The client, a leading US PC manufacturer, was seeking to obtain performance business intelligence. They wanted to capture the revenue performance for the product categories for various consumer segments, measure KPIs such as the likelihood of customers to repurchase, and capture the satisfaction level for security, quality and profitability for different products and services. The challenge was to clean and model data across 13 areas, 30 sub regions and over 100 accounts, and implement complex dynamic dashboards providing different levels of access to key stakeholders based on the functional need and geography.

The trading and distribution company wanted to increase its market share by adding new customers to its portfolio. The client did not have a comprehensive list of the customers which they were not servicing. The company aimed to increase their customer base by identifying potential customers on a street level basis and obtain a mix of existing and potential customers to identify and target the segments which would be most profitable.

The client, a leading insurance company, was facing a challenge of accessing lapsed insurance policies with a potential of repayment within a specific time bracket. The company was witnessing revenue loss and wanted to reactivate these lapsed policies. However, they wanted to ensure that the strategy resulted in minimum wastage of money and effort.

The company wanted to segment its customers according to their transaction patterns and other behavioral traits in order to identify the profitable customers and target relevant ones for the loyalty program. They also wanted to identify the customers performing adversely as compared to the cluster average and timely target them for reactivation. The goal was to perform targeted campaigns based on the behavioral pattern of the customers for revenue maximization.

The client, a leading US PC manufacturer, was struggling to understand the ROI generated from their digital marketing efforts and assign the right dollar value to each channel. They were finding it difficult to implement a data-driven marketing optimization strategy. There was no standard process in place which could distinguish different customer segments based on variation of traits and characteristics. The client wanted to implement robust, data-driven marketing and sales workflows to enable better ROI with maximized sales revenue.

The client, a leading PC manufacturer, had been investing in promotions across product lines based on internal factors like product lifecycles and costs. However, they wanted to identify indicative segments that could be used by marketing for cross-sell and up-sell opportunities. The challenge was to source sales data from aggregators like NPD/GFK/Context and utilize price bands customized by regions and countries to create segments based on customer budgets. The client also wanted to revamp the promotion data processing to include a price band structure.

The client, a large US public utility company, wanted to build a base of knowledge regarding the social media practices of small and medium businesses in the utilities sector. They wanted to understand to what extent these businesses would find value in receiving energy-related information from the utility company via social media platforms. The challenge was to identify target businesses who had the highest usage of general social media channels for business purposes as well the size and type of business that had the highest energy management needs and where to best reach them in social media conversations.

The client, a leading technology company, had a vision to integrate multi-channel, multi-source, and different types of data (structured and unstructured) into a single platform. This platform would provide a single source of truth for all business KPIs and metrics for stakeholders. Until this initiative was planned and launched, different geographic regions (GEOs) 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, the client specifically required data from different sources to reside in a single platform where reporting, BI, and insights would reside.

The client, a leading technology company, was capturing consumer conversations from multiple channels such as tech forums, call center agent transcripts, email, and chat. They were categorizing the customer experience (text data) manually on a minimized sample basis which did not provide a holistic view of customer experience insights. The client wanted to automate the text classification on the entire so they could gather more detailed insights about the customer experience.

The client, a large utility company, had been partnering with Blueocean Market Intelligence on a brand and customer satisfaction tracking study. However, a recent event in their service department made them question how much trust their customers actually had for the company. They requested Blueocean Market Intelligence to develop a robust metric that would allow them to assess their trustworthiness and determine which underlying factors drive the metric. Further, the study would need to determine the role of trust, customer experience and rate the overall satisfaction of communication with the utility.

The transportation and logistics industry has undergone significant changes in recent times. Due to its cross-functional role, it is a critical link between industries and is often a mirror that reflects imminent changes. Globalization has led to a geographical and service expansion by many logistics providers, with supply chains becoming more complex and comprehensive. Many technology companies are targeting this market, especially the fleet management space, which is growing at the rate of more than 20% year-over-year. The fleet management services market encompasses independent software vendors, system integrators, software as a service (SaaS) and application enablement platform providers in its value chain. Various vendors are capitalizing on the increasing need for operational efficiency, which is expected to be the primary driver for this market.

The client, a leading apparel manufacturer, was considering changing the brand name for a product line extension. The study was designed to determine which of three names should be retained. The decision was to be based on assessing overall name preference, understanding the imagery associated with each name, and developing a comparative estimate of potential sales volumes under each name.

The Pascua Yaqui Tribe was seeking a training program not only to get employees in compliance but also to develop the next wave of leadership within the tribe. Many employees were transitioning into leadership roles and the tribe felt the need to provide them with leadership tools, skills, and resources to aid their professional growth. Additionally, the tribe identified several areas where they needed a more comprehensive and automated system to address compliance standards like HIPAA, workplace harassment, safety, and ethics.

Carnegie Robotics, founded in 2010, initially focused on research and development with a small portion of the company’s resources devoted to manufacturing. However, with a rapidly growing manufacturing business and contracts with the government, the company found it increasingly difficult to manage their ever-growing collection of policies and assembly instructions through email and spreadsheets. The company needed a robust policy management system that could accommodate its growth and the need to mature its business processes.

Attain, Inc., a non-profit organization supporting people with developmental disabilities, was struggling with its paper-based policy management system. The system was inefficient and made it difficult to verify when an employee had attested to a policy or whether they had fully understood it. This led to knowledge gaps and process problems within the organization. Whenever a process problem occurred, the organization would write a memorandum or policy and distribute it among departments. However, there was no assurance that anyone read or understood it. This lack of clarity and understanding led to inefficiencies and potential risks within the organization.