3 Reasons Why Operational Modern Data Management Outperforms CRM

3 Reasons Why Modern Data Management Outperforms CRMEmbed from Getty Images | E+ | geopaul

Companies deploy several operational applications such as CRM, marketing automation, order management, billing, shipping and customer support to serve and manage customers. Throughout their journey, customers interact with multiple channels like email, phone, web, stores and social media. Today, a massive amount of data flows through these systems.

When customers interact with the company, behind the scenes, they are routed to various departments such as sales, support, billing and ordering. All these departments collect customer information, transactions and interactions, and they store them in multiple systems like CRM, marketing automation, order management, ERP, shipping and support. The customer data is distributed across all these systems.

Moreover, as the business grows, and the technology progresses, companies add more systems and more channels, and are confronted with an ever-increasing volume of customer data.

Even though organizations are comprised of departments and use a myriad of systems, the customer thinks of you as a single company. The customer expects consistent and quick responses no matter which department they reach out to or which channel they choose.

Siloed and fragmented data across operational systems causes a multitude of problems, including, but not limited to:

  • Inefficient operations due to manual processes and manual data reconciliation
  • Incorrect orders due to poor customer or product data, leading to costly rework
  • Revenue loss due to wrong discounting or a poor understanding of customer entitlements
  • Compliance risks by not enforcing regulatory requirements for handling certain customers or products
  • Poor sales effectiveness, as professionals must hunt for customer information, what product(s) the customer currently has and what they need

To deliver a consistent experience and make sure the business processes that span departments and systems do not become inefficient or broken, companies must create a single source of truth of customer information.

Companies need to build this hub, which blends and cleans customer information from all internal, external and third-party sources. Such trusted customer data is then provisioned to all other operational systems to maintain data integrity and make business operations efficient.

Most organizations have recognized that attempting such customer master or Customer 360 within CRM application is a road to nowhere. CRM cannot be the single source of truth for all customer data. Companies spend tons of consulting time, add dozens of fields to the lead, contact and account objects, and install multiple add-on applications without any results.

Although some people have bought into the MDM story, others keep trying to push CRM boundaries. The reasons could be many – for example, perhaps they cannot afford MDM, or they do not have IT teams to help with complex setup.

But modern data management platform as a service systems can quickly help create a single source of truth of operational master data across all business applications and help achieve operational efficiencies.

A modern data management approach helps:

1. Establish data integrity and accuracy

Today’s CRM systems provide some data cleanup ability. For high volume data management with cleaning, matching, merging, unmerging, verification of data while maintaining full audit trails, status and lineage, CRM falls short. With multiple high-velocity data streams, it is very hard to keep up with data maintenance.

Data quality is one of the key sources of operational inefficiency in sales and marketing departments. A modern data management platform connects to all internal, external and third-party data sources, matches and merges the customer, product or account data and creates a foundation of reliable data across systems.

2. Provision data in context

Different systems, applications and channels need different information to process transactions. A 360-degree view isn’t achieved by dumping all the master data into one application page – it’s more about the context than about the content. It’s about providing the relevant customer information to the user, based on user’s role and the task at hand.

So, the 360-degree view for a sales rep visiting a client is different from that of a marketing manager doing segmentation for a campaign, and still different from a call center agent trying to resolve a service issue.

Once you’ve established the reliable data foundation, now you can visualize this information in the form of personalized data-driven applications built for a specific role and business goal and also provision the required accurate customer information to CRM, ERP or other systems.

3. Be flexible and agile

The Customer 360 view is evolving and expanding – it’s never static. And it doesn’t include only customer profile and interaction data. Now, we also want to include information from financial, logistics, support and training systems. We also wish to understand customer preferences and sentiment from social networks. And we want to uncover relationships between people, products and locations. Capturing all this information in CRM is not a viable option – the systems aren’t designed for that.

Modern data management platform as a service systems can manage data at a big data scale and offer flexibility to add unlimited attributes and data sources. You can build the data-driven applications the business needs and keep the applications as your business changes.

Customer 360

Modern data management helps construct a Customer 360 that delivers the desired business value and operational excellence. Going beyond a typical MDM solution and available as platform as a service, modern data management solutions eliminate the complexity and help build industry – and role-specific contextual data-driven applications.

Designed to consolidate data from all internal and external sources, applications built on modern data management platforms support an infinite number of attributes and help uncover relationships between people, products and places. They provide a single source of truth of information across all the operational applications and channels needed to support a customer’s journey and deliver a great experience throughout the journey.

Article written by Ajay Khanna for icrunchdata News Redwood Shores, California USA
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Channels: Big Data


About the Author
Ajay Khanna is the Vice President, Product Marketing at Reltio, the creator of data-driven applications. Prior to joining Reltio, he 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.