Data Science Across Domains
SteppeChange works alongside businesses engaging in digital transformation, complementing user experience strategies with outcome driven science and design. Digital interactions create an abundance of data, allowing a variety of analytical approaches that leverage multiple data assets—predicting customer loyalty and contextualizing user engagement. Our consumer behavior specialty helps us to create blended solutions, weaving digital and legacy analytics—understanding behavior as a whole and steering away from a singular approach. We also collaborate with our clients to design 360° customer behavior segments, understand customer life-stage models, and cultivate analytical approaches for marketing channels.
Today’s customers enhance their lives through mobile devices. Companies are leveraging the power of mobile channels and adjusting offerings to service mobile-first audiences. Thanks to their omnipresence, mobile devices empower consumers with new moments for search and discovery, but are also impacted by the frictions of the outside physical world. The old mental model of web behavior cannot be transferred to mobile, fractured in micro-moments and operating at the edge of the physical and digital. Mobile data needs offbeat ways of collecting, storing, and analyzing, enabling companies to extract insights and design mobile centric algorithms to power customer dialogues. Drawing on the extensive expertise in machine learning, we uncover hidden meanings, new variables, and untapped connections at scale. SteppeChange builds and deploys intelligent solutions that help mobile operators to improve long-term customer value, modernize customer service, and be more competitive in today’s marketplace.
SteppeChange’s analytical offerings include support of all stages of hypothesis and offer testing—from sample selection to test design and performance evaluation. Focusing on the specifics of a policy or campaign, our team works to create a customized testing matrix that drives statistically viable performance reads across testing dimensions. Sophisticated multi-factor offerings can benefit from experimental design approaches, evaluating multiple factors with a minimal number of parameters and within budget. Our test design capabilities help determine the winning approach in domains with multiple offer points such as pricing, interest and fees, mobile bundles, subscriptions, and other factors. When A/B testing grows costly or might yield a negative customer experience, we employ machine learning algorithms to provide cost-saving and customer-friendly alternatives.
SteppeChange is realizing the potential of unutilized data to transform credit scoring. We apply our proprietary machine learning techniques to determine the creditworthiness of otherwise “invisible” customers and enable customer acquisition that is both cost-efficient and does not suffer from adverse selection. We work in collaboration with client organizations, over a number of stages, to develop effective credit-scoring strategies and solutions. The data-discovery stage focuses on identifying promising data sources and assessing a high volume of potential data. Data access can be secured through direct collaboration, third-party data acquisition, or seamless integration with SteppeChange’s big data platform. Data wrangling and feature engineering utilizes advanced machine-learning capabilities to extract data signals that are predictive of a diverse set of credit behaviors. We offer advisory and implementation services based on credit scores specific to customer targeting and treatment.
SteppeChange helps companies to optimize pricing points across products and channels in order to improve profitability and grow the market share. Our analysis of transactional behavior discerns customer pricing elasticity, to determine the drivers behind customer's choices and buying decisions. Our data ingestion process involves collection and analysis of multiple data points at the most granular level across promotions, time, and product bundles. Analysis of transactional data is essential to derive unbiased quantification of true pricing elasticity. SteppeChange works with organizations to translate analytical outcomes into pricing recommendations and targeting criteria. Combined with the targeting and testing services, our intelligent pricing solutions help organizations to establish comprehensive pricing lifecycles, from behavior measurement to evaluation of pricing strategies.
Data-based decision-making is becoming a competitive necessity. New economic models of distribution are emerging, accelerating cooperation between previously unfamiliar players or between former competitors. Dimensions of information are growing exponentially, while requiring faster decisions to innovate continuously. SteppeChange works with clients to maintain nimble, yet comprehensive process of converting data into insights – and insights into decisions. We apply advanced analytics and machine learning techniques to channel contrasting quantitative information into clear outcomes and scenarios that drive business strategies and facilitate collaboration across value chains.
Big Data Practice
We help organizations establish the critical foundation of big data competency by deploying state-of-the-art architecture that accelerates value extraction and deployment to achieve tangible business goals. We evaluate business objectives and constraints, and formulate solutions that are technologically advanced, cost-efficient, and compatible with the existing IT domain. We analyze strategic requirements, while envisioning specific use case applications together with business and technical stakeholders. We view data workflows, data requirements, and technical capabilities as part of the overall platform roadmap—supporting both long-term strategy and minimal viable solutions, with a vision to deliver immediate value and then build upon that value over time. The outcomes of our data strategy services are advisory reports, needs or gap analyses, data environment roadmaps, or specification requirement formulas that can be also extended into development and use case piloting.
Our data architecture services introduce data ingestion, storage, and organization technologies capable of storing and analyzing data of previously unattainable velocity and volume. These services assist organizations to deploy next-generation data platforms, scaling billions of data points from structured and unstructured sources. Depending on the client needs, our custom platforms offer a full spectrum of data value extraction, including integration with third-party data, cleansing, enrichment, data science capabilities, and resulting prescriptive analytics. Our data architecture services are customized to offer services from advisory to implementation and can be deployed in phases or in modular combinations. The advisory parts of such engagements address aspects of data quality, data reliability, and lineage—as well as overall governance and data security processes. The development parts of such engagements focus on deployment and implementation of the data environment, allowing prototyping of data science and insight capabilities.
Our data engineering facilitates a close working relationship between data architecture and data science, accelerating design and scaling deployment of analytical capabilities. Data engineering blends principles of distributed data management and DevOps practices. Our approach is instrumental in bridging the gap between analytical advisory and deployment, helping to implement proposed analytical solutions in production in near real time. The data engineering practice also provides services related to data integration, cleansing, feature engineering, customized Extract-Transfer-Load solutions and standardization of the processes. The services can be utilized separately or in a modular fashion. Based on a client’s preferences, SteppeChange performs projects on premise or in the cloud, relying on the open source software of Hadoop stack, Cassandra, and MongoDB, as well as the proprietary technologies of Vertica, Oracle, and Amazon stack, including Redshift and Aurora.
SteppeChange collaborates with clients to develop and deploy innovative technology solutions. We specialize in scalable solutions for high transaction applications, massive data volumes, and eclectic data sources. Our services extend beyond code development and into deployment, maintenance, and user experience design. Our applications are highly detail oriented, while maintaining the link to the client’s goals and roadmaps. Our expertise in agile development accelerates time-to-market and return on investment for our clients. Our software engineers are experienced in working on a wide variety of platforms, programming languages, databases, and software development technologies.
SteppeChange works with clients to design and implement mobile solutions that seamlessly connect with customers across all platforms and corresponding devices. We offer a complete portfolio of mobile applications and services for platform-based and web-based applications. Our high-performing and scalable mobile solutions transform utility functions into personal experiences, while instantly connecting to data environments. As a result, our solutions enable companies to recognize behavioral metrics of an application performance and deliver unique user experiences, driven by embedded data science.
Our program management services facilitate collaborative, yet focused business processes. We specialize in complex projects requiring cooperation between experts from multiple disciplines. Engagement management can be extended in the standalone mode, steering projects where interpretation of multi-faceted quantitative information can drive concrete decisions that an organization will make with confidence.