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The Importance of ‘Self-learning Data Platforms’: In Conversation with Ajay Khanna, VP of Marketing, Reltio

By MarTechAdvisor

Please visit https://www.martechadvisor.com/interviews/data-management/the-importance-of-selflearning-data-platforms-in-conversation-with-ajay-khanna-vp-of-marketing-reltio/ for the complete article.

Ajay Khanna, VP of Marketing, Reltio lets us in on the strategic advantage of a self-learning data management platform and the barriers marketing leaders face in optimizing outcomes from their customer data. Ajay has previously held senior positions at Veeva Systems, Oracle and other software companies including KANA, Progress and Amdocs. He holds an MBA in marketing and finance from Santa Clara University.

Why should every marketer be thinking about building a unified customer data platform?

As a marketer, being data-driven is extremely important. It means communicating the right message to the right customer, at the right time and via the right channel. It means making data-driven decisions about what is working and what is not working.

Being data-driven allows you to gain a deeper understanding of customer preferences, behavior, and needs, and helps you align your message, content, and campaigns for maximum effectiveness.

To achieve this, you need a self-learning data management platform to blend data from all internal and external sources. This enable marketing and all customer supporting functions of business to gain real-time access to 360-degree profiles of customers. This ‘single-source-of-truth’ helps marketers deliver personalized and relevant information to customers in a timely fashion.

What are the big barriers to doing that? How can companies that don’t have structured or actionable first-party data hope to get started?

Today marketing must have data management capabilities that are responsive to the customer in real time, and help identify the right engagement, with the right message and at the right time.

  • Traditional master data management tools do not meet the needs of organizations in this new age of the customer.

  • Data is still scattered across technologies, applications, and in different departmental silos. In the realm of modern data management, its not just about the unified customer profile but also about their relationships, past interactions and transactions. We need to process these to glean more in-depth insights and help customer-facing teams with intelligent recommended actions.

  • Privacy and compliance is another concern. Enterprises need to meet the requirements of General Data Protection Regulation (GDPR). Companies will be mindful of what data they collect and for what purpose and must track how it’s stored and used.

A proper data strategy together with modern data management will give marketing unprecedented access to clean customer data with a deeper customer understanding so they can run their campaigns effectively and with the required compliance.

What are your top tips to CMOs wanting to build a data-driven culture?

Data-driven is not just about reporting and dashboards. Being data-driven makes your marketing more agile, more efficient, compliant, and improves customer engagement.

Think of an overall data strategy. Do not think in terms of engagement, reporting, data warehouses, and data lakes. Think how you can build a comprehensive data strategy that addresses your customer experience, operational, analytical, and compliance needs. Then look for a solution that helps you execute on a cohesive strategy.

How have you seen the concept of data-driven marketing evolve over the last few years, and where do you see it heading in 2020?

With the advent of the social, mobile and myriad of other channels, we have seen an exponential increase in data volumes available to marketers. As data volume, variety and velocity increase, poor data quality may lead you to the wrong decisions and investments.

Self-learning data platform tools help pulls in omnichannel interactions and match and merge to create reliable customer profiles. Graph technology helps uncover relations between people, products, and places and integrated predictive analytics and machine learning (ML) help provide relevant insights and intelligent recommendations to marketing teams for better-informed decisions.

With a unified platform that brings together master data, interaction data and advanced analytics, enterprises can learn more about customer needs, and, in turn, provide them with relevant information and offers.

How can marketers balance the desire to monetize their customer data while meeting the new compliance and protection requirements?

The right data strategy will not only help you improve business outcomes but inherently ensure compliance. Take GDPR, for example; such regulations will become more widespread and common. To meet these requirements, enterprises must bring together all customer data, manage and maintain rights and consent information, and put processes and workflows in place to manage customer requests for information access, changes to data, consent, or data erasures.

Marketing should think of GDPR compliance not just as a regulatory requirement but an opportunity to improve business operations and enhance the customer experience by providing more personalized services to customers.

Ensuring customer trust will have a long-term positive impact on brand loyalty and revenues.

How can a CMO approach the ‘attribution challenge’ in an omni-channel, real time customer engagement world?

Having proper data governance and data lineage will help marketers address the attribution challenge.

Firstly, determine why understanding attributions is essential and what they’re going to do with that information. Is it to improve customer experience or to prioritize investments? Hopefully, both.

Bring all customer data together and correlate with omnichannel transactions to help uncover insights like channel preference.

Use advanced analytics and machine learning to help determine the next-best-action of what channel to use and what product to offer on what time and day of the week.

What are the new skills and roles CMOs need on their teams to thrive in the present-day data-first business environment?

In today’s digital economy where all the leading companies are self-learning enterprises, understanding the impact of data strategy is critical.

Collaboration with CIOs, CDOs (Chief Data Officers,) and CISO (Chief Information Security Officers) to build a cohesive data strategy will determine success.

Customer data cannot be a hostage of a single technology or department; it needs to be brought together and continuously organized. Understanding the data value chain, its impact on compliance and customer experience is critical.

What are the big trends you are tracking going into the next couple years?

To survive and thrive in today’s economy, enterprises must be self-learning. We have seen the breathtaking growth of a new generation of companies like Google, Amazon, Apple, Netflix, Uber and Airbnb—which we can describe as digital self-learners.

These companies are using data to continually learn about their customers, products, partners, and suppliers.

In the coming years, more and more companies will join this set of digital elite. Becoming a self-learning enterprise offers enormous opportunity. With cloud-native self-learning data platforms, companies of all sizes can leverage their data like leading digital enterprises, using a platform that delivers continuous data organization, recommended actions and measurable results.