Predictive Analytics Connect People for Greater Predictive Power

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A leading data technology company which helps enterprises to boost revenue, Toovio Software, improves profitability, and enhance the customer experience by taking action based on real-time, customer behaviour insights. It is a SaaS-based marketing solution provider focused on enabling multi-channel offer orchestration, focused primarily on customer lifecycle based analytics like acquisition, cross-sell, and customer retention scenarios. In a conversation with Dibyoshnata Talukdar, ELE Times, Ashutosh Mehrotra, Business Head at Toovio Software, shares some light on technology trends, Advanced Data Analysis and business in India.

Dibyoshnata Talukdar: Kindly share with the readers of ELE Times about the role played by your company in Real Time Interaction Management Service?

Ashutosh Mehrotra: We are in the 21st century, where data rules! Today, data plays a crucial role in most businesses. Companies have been undergoing data-driven digital transformation and have started leveraging data as a strategic asset. Data-driven decision making is catching fire as companies find ways to use the vast amounts of data they collect to gain a competitive edge for better service and a better-quality experience for their customers.

But we can’t deny the fact that the human brain and today’s analytics platforms are not equipped to deal with that level of data complexity in real-time. Being a data technology company, we at Toovio, understand these issues and help enterprises boost revenue, improve profitability, and enhance the customer experience by taking actions based on real-time, customer behaviour insights.

We offer a highly scalable, real-time interaction management platform that can be plugged into any channel to optimize customer engagement. It enhances the user experience with behavioural data, response-history and advanced analytical capabilities, resulting in unique and personalized customer interactions. We strongly believe in teaching machines, specifically to make them understand marketers’ strategies, tactics and objectives so they apply advanced data technology solutions in a better way that can be consumed and deployed by organizations at larger scales.

Our ability to determine “when what and on which medium to promote”, significantly improves customer experience and sets us apart from our competitors.

Dibyoshnata Talukdar: Please throw light on Advanced Data Technology and its impact on business?

Ashutosh Mehrotra: Data analytics and business intelligence have come a long way in past a few years. Now, C-suite executives consider it as an important part of the overall business strategy to make better and faster business decisions. Companies will continue to leverage the power of data analytics and look for “top line” to be specialized in the field of data science.

In the coming years, every decision, every customer, and every single offer would be accompanied by a prediction that is consistently accurate and automatically adapts to changes to underlying data correlations. This capability operates with no human intervention. Adaptive predictive modelling will help the business to make the changes on the fly and get the desired outcome in terms of revenue or building the engagement score.

Toovio aggregates, transforms and derives new customer level data continuously from this stream and places it in our Adaptive Customer Data Profile through feature engineering. Toovio’s self-learning algorithms constantly get smarter with every customer event or engagement, increasing accuracy and customer engagement ratios.

Dibyoshnata Talukdar: What are the technology trends that are being applied to Machine learning in Telecom and Retail businesses?

Ashutosh Mehrotra: Machine Learning (ML) has come a long way in the past few years and has changed the way companies look at how they need to do business. Behavioral algorithms, suggestive searches, network optimization, pattern analysis, fraud detection, customer identification, churn prediction, recommendation engines, etc., are a few examples and applications of ML in use today.

Technological advancement has made almost everything possible. From accurately predicting Customer Lifetime Value (LTV) to pinpointing a customer’s preference and populating the best offering, network operators are truly reaping the benefits of continuous improvement in targeting the right audience at the right time in the right channel and with the right content by implementation machine learning techniques. Since powerful predictive capabilities came into existence, companies are investing heavily on voice assistants, chatbots, and other intelligent business processes.

Predictive analytics connect people for greater predictive power and high-impact insights. It enables leaders to make radical discoveries about their companies and dissect and solve complex business challenges. As a result, companies offer better business strategies leading to higher productivity and performance. Several mounting ingredients promise to further spread prediction even more ubiquitously: bigger data, better computers, storage sufficiency, wider familiarity, and advancing science.

Dibyoshnata Talukdar: What are the current requirements in BI platforms, data science platforms, analytic applications and Customer engagement suites in India?

Ashutosh Mehrotra: Indian C-Suite executives like chief information officers (CIOs), chief data officers (CDOs), and other data and analytics professionals/leaders must evolve traditional approaches and start focusing on business outcomes, go-to-market trends and adopting new technologies in coming years. With the right analytics platform, companies can empower business users. BI helps in implementing a flexible and scalable infrastructure that in turn increases responsiveness, reduces IT costs, workload, and drive better decision making across organization.

Organizations will continue to leverage “Data” as an asset using advanced BI platforms and the key elements of data management, like data integration, data quality, data governance, master data management (MDM).

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