Digital Transformation: Why Data Science Matters?

Data science is the basic instrument that allows companies to build the link between customers and their specific preferences with various levels of offerings.

July 02, 2017

Digital Transformation: Why Data Science Matters?

In recent years, modern corporations are undergoing a customer-focused digital transformation by shifting how customers interact with their goods or services, allowing them to intuitively offer customers what they need as an individual. Going beyond the dated “customer experience” model of identifying if a customer simply had a good or poor experience to a much more dynamic system of anticipating a customer’s needs and creating opportunities for customers to use goods and services in a refreshing way. For example, let’s say a customer who is looking for an exercise class has the ability to use any of the 5,000 sport studios in the city and select a class that’s near them, at a time that works for them based on their work schedule, and with a few touches of their finger. This is not simply an experience, but a completely different way of consuming a service – on demand and based on geo location, personal time constraints, and contextual preferences.

With customization, digital interaction becomes intuitive and full of different functions, but most importantly it anticipates real needs of customers and doesn’t just present them with an overwhelming list of options. The quality and customization of offerings grows exponentially when informed by data. Data science is the basic instrument that allows companies to build the link between customers and their specific preferences with various levels of offerings.

Digital transformation increases the number of business use cases addressable through analytics, making the options for contextual marketing far greater than just a few years ago. The notion of “understanding customer preferences” and “data-driven marketing” existed before – but certain combinations of contextual circumstances became available only in recent years. Some of it is due to the connection between operational environment and data collection, and some is due to the effective methods of predictions. Before the advent of big data, the question of “is it a weekday or a weekend” or “is it a working or off-working hour” were impossible to incorporate instantaneously and in a personalized way when shaping how a customer uses a service, whereas now it is a valuable customization that can be responsive in real-time.

The digital services needed for transformation include contextualized conversations, proactive ‘sensing’ of customer’s needs and habits, and intelligent self-service capabilities. This context needs to keep customer intimacy at it’s core and build better methods for customer personalization. Additionally, digitally optimized offers and product portfolios create the final touches for a cohesive and meaningful interaction between customers and the product or service of your corporation.

Applied data science makes this intimate interaction between user and service possible through robust quantitative insight that is fueled by a variety of data types, including semi-structured and unstructured. The latest advances in big data technologies and methodologies enable us to collect, transform, process and analyze all of a business’ data. Machine learning algorithms iteratively learn from data and enable us to find hidden insights for your business.

Analytics are now more powerful — they create predictive and prescriptive power and comprehensive models that allow for real time, circumstantial contextualization. Data science virtually walks hand-in-hand with the customer, in a variety of circumstances. The question of “who customers are” is becoming insufficient, while the questions of “what is the customer experiencing, here and now “, “how will she react to these experiences”, and “what will she be experiencing soon” are becoming much more critical.

Data science drives the decision science — enabling to create a new breed of digital products, services, or features that are personalized for digital customers. This improved interaction between customers and a business’ product or service will optimize relationship value for both the customer and company, increasing individual user value and transforming a corporation.

SteppeChange works with organizations to build big data projects that are catalysts for digital transformation. If you are ready to create new business opportunities with your big data, connect with us and together we’ll develop a strategy and build solutions that uncover new directions for growth.

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