STEAM is a digital distribution and gaming platform developed by Valve Corporation, a multiplayer gaming and social networking services company. Steam give access to more than 10,000 game titles and connects its 125 million active users to each other. Through Steam, fans can buy, play, share, modify, and build communities around Valve products as well as titles from other independent game studios. This is in direct competition with the client’s app store that also sells popular PC games. Understanding the competition in detail, their strengths and weaknesses and user profiles will help the client develop strategies to tackle competition.

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 leading eCommerce company, wanted to understand the payment preferences in India, China, Russia, and Europe. The eCommerce and payments industry has seen significant changes over the years with the introduction of many new and innovative hassle-free payment methods. Electronic payments and digital transactions have become much more common. However, each country has specific payment preferences. The client wanted to analyze the payment industry for each country, understand the competitive landscape and emerging needs of the consumers, and evaluate current tools and technologies.

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 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 insurance and BFSI company in Asia, was struggling to evolve from their previous platform and migrate successfully to the Adobe Marketing Cloud platform. They wanted to set up marketing channels, traffic performance, and overall site health scorecards for immediate stakeholder delivery. The client also wanted to understand the reasons for deviations between web leads to CRM fulfilled leads, which were caused due to faulty tag implementation and accounting issues.

In the hyper-competitive telecom world, the client needed to find a cost-effective and efficient way to keep their divergent teams abreast of news, rumors and published research findings related to competitor product offerings, rate changes, and network developments. In addition, they needed assistance with more strategic, market opportunity assessments to fuel their new product development process. Internally, their small team struggled to find, review and distribute information consistently, even though late breaking market developments often had an immediate impact on their strategic initiatives.

The client, a leading technology company, was facing several challenges. They wanted a unified view of their customers across different business lines – B2C, B2B, EPP and B2V. Insufficient customer details and incorrect data was 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 centralized database and “single view of the customer”. They were also unable to measure the efficacy of their marketing plans.

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 gain insights into the market landscape of predictive maintenance offerings, including details such as key vendors, company background, details of offerings, launch timelines, use case stories, industry focus, and list of customers.

The B2B retailer company was looking to increase sales from existing customers by creating customized offers such as discounts and bundled offers. This strategy was aimed at giving them a competitive edge in the market. Additionally, the company wanted to reduce inventory levels of slow-moving SKUs to reduce costs and wastage. The challenge was to analyze past purchase history, identify product associations, and determine appropriate discounts for SKUs for each customer.

The client, a leading global technology company, had over 1000 campaigns running each week on their website. They wanted to ensure automated campaign tracking and classification solutions. Regional stakeholders were working with individual agencies to set up campaigns and track them manually. This led to gaps with the tracking mechanism, and final reports did not portray the complete picture since the attribution quality was poor. The client wanted a consistent and clearly defined process to track campaign performance, ensuring 100% compliance with business logic prior to going live.

The client, a large US public utility, was facing a challenge in understanding 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 traditional response rate of program participation was 4%, and the client wanted to increase this rate while decreasing mailing costs.

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 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 US-based auto finance company, was approving all loan applications at the origination stage. They desired to build a new risk-based loan application analytics solution to better understand their existing customers and manage risks, profitability, and growth more effectively. The challenge was to profile, model, extract, and automate data into one repository for the loan origination process. This included statistical evaluation of the borrowers’ characteristics, risk-based pricing model based on the riskiness of the customer, and real-time decision-making application for monitoring performance, decision support, and automated scoring of customers.

Blueocean Market Intelligence was tasked with providing a comprehensive market opportunity assessment for a prospective CCN technology developed by the client company. The challenge was that CCN is a new technology, not yet commercially deployed, so a similar and more current technology had to be considered to study the prospective market. The market size was calculated referencing a similar technology (CDN).

The client, a large US public utility, was facing a challenge in identifying which customers on a Time-of-Use (TOU) price plan would switch to an alternate price plan. They needed to understand the factors that predict this switching behavior and create propensity scores for each of the current TOU price plan customers to identify their individual likelihood of switching to a different price plan. The goal was to correctly predict a likely switcher approximately 70% of the time.

Microsoft needed a solution to more effectively analyze the thousands of conversations taking place online about a wide array of the company’s products. These conversations take place globally 24/7 and in huge volume in Microsoft forums, other forums and across social media platforms (Twitter, Facebook, blogs) and in more traditional news sources. While the company was already monitoring some of these sources, there was no one integrating the conversations and providing insights into their relevance to improving product quality and the customer experience.

The client, a leading consumer products company, had developed around 50 concept ideas for toothpaste and mouthwash categories combined. They received around 5,000 responses from consumers from a short survey which contained details of what they liked and did not like about each of these ideas. These open-ended verbatims had to be analyzed to arrive at the broad themes and analyzed across demographics. The key challenge was to analyze these 5,000 verbatim responses and create the report only three to four.

The client, a leading consumer products company, wanted to develop an in-depth understanding of the bi-cultural Hispanic segment in the US, which was expected to grow from 13% of total US households in 2014 to 35% by 2030. The aim was to define strategies and tactics to drive current and future growth in key categories such as oral care, home care, and personal care. The existing research included a mix of commissioned research and external partner-led research studies.

In the hyper-competitive eCommerce industry with dynamic business models, Blueocean Market Intelligence’s client needed to understand the costs associated with setting up a new eCommerce website for retail and digital goods. The client wanted to also gain a competitive perspective so that an appropriate solution could be devised based on the scale of the merchant’s business requirements (small, medium or large). The challenge was to identify different types/layers of vendors that a merchant or seller needs to tie up with in order to launch and operate an eCommerce webstore, and to understand the cost structure of identified vendors.

Asia’s largest Telco, with over 200 million mobile customers and an online revenue of USD 1 billion, was struggling to leverage its vast customer base. The company was using disparate offline data sources to figure bill payments, recharge history, and minutes usage, with no uniquely identified online customers. The key objectives were to identify online users as soon as they land on site and assign a unique ID to them, map the unique online customer ID to offline data using Adobe Audience Manager, create and render custom offers to customers based on various variables, and create opportunities for pushing mobile APP for smartphone users.

The client, a leading money exchange company, experienced a decline in remittance transactions from Country X to Country Y. They identified several factors responsible for the decrease in transaction volume and sought the expertise of Blueocean Market Intelligence to investigate and develop a plan to address these challenges. The client needed to understand the transactional and customer trends by key variables such as age, emirate, and send agent. They also wanted to measure the impact of exchange rate, margin percentage, and competitor pricing on transactional volume.

The client, a US-based property and casualty insurance company, was facing several challenges. They lacked a measurement system to understand the effectiveness of their digital initiatives. This inability to measure marketing ROI was impacting their sales and leading to a fragmented customer experience. The company needed a solution that could integrate data from different platforms, provide real-time analytics, and drive effective data storage practices.

The client, a multinational CPG company, conducts brand tracking around the world and across all of their product categories. These include health, hygiene and home products among others. They wanted to adopt a harmonized brand tracking dashboard for different categories of product. In order to stay ahead in the game, the client wanted a competitive and comparative study for product and brand level performance. The client’s demand was challenging since the company has 120+ product portfolios of its global and regional brands. The primary goal of CPG companies is to maintain long-term relationships with retailers and ensure products are being promoted and sold across all locations. To enable this, the client wanted to understand the different purchase drivers, which are responsible for the sales. This included capturing awareness, familiarity and purchase drivers and barriers.

The client, a leader in the international movie industry, had recently expanded its chain of movie theaters in the United States. The US corporate marketing team needed comprehensive profiles of 11 key markets to set strategic directions and develop market-level tactical plans. Local operators also needed fact-based profiles of their current and potential customers, as well as the breadth of competitive entertainment opportunities their customers could choose from. Due to tight budgets, all information was drawn from publicly available sources.

The client, a global hi-tech and cloud solution company, had recently migrated from Adobe Marketing Cloud to Google Analytics and required assistance during the migration effort. They were running more than 50+ campaigns a week and wanted to understand the efficacy of their omni-channel campaign efforts. They aimed to create and run comparative dashboards for key site sections and pages, pilot, iterate and operationalize dashboards with insights to answer business questions related to digital pathing analysis, campaign efficacy measurement, and marrying campaign and digital path data to create customer personas/segments.

The client, a top 15 pharmaceutical firm globally, was facing challenges with their existing reporting system. The processes were cumbersome, manual, and time-consuming. Despite having a plethora of data sources, there was no defined analytics architecture. The client wanted to capture all the geo and product level data at a central location for easy competitive and comparative study.

The client, a US-based technology company, wanted to track and measure the performance of its online campaigns. They were interested in understanding the efficacy of their online research base campaigns and video games performance. The data they wanted to analyze included creating awareness of their gaming product in the US and UK, finding out how many users use their gaming product app, analyzing how many users purchase the product, and identifying how many users have heard about various video games. The challenge was to extract and analyze this data in a meaningful way to inform future business decisions.

Mobiles/smartphones are a commodity today with multiple brands – both global and local – selling around 25,000 new models in the market at all perceivable price-points. While original equipment manufacturer (OEM), such as Apple sell devices in the millions with minimal effort, it is a herculean task for other OEMs to get a buyer to select their device – unless differentiation is shown to the buyer that is peerless and value that is unparalleled. In order to develop a unique customer experience that included the device and accompanying service, the client wanted to understand the various pain points experienced in their mobile journey.