Re(AI)magine CRM Migration to Microsoft Dynamics 365 with GenAI

Digital enterprises thrive on high productivity, efficiency, and faster turnaround – enabled by highly automated, intuitive systems offering readily available insights backed by a single source of truth.

This is especially the case for customer relationship management (CRM) systems – one of the crucial pillars of organizational success. An intuitive CRM application that consolidates cross-functional data to provide relevant insights at the right time can prove game-changing. However, existing CRM systems at most enterprises inherently lack the interoperability, scalability, performance, and user experience that digital, cloud-based CRM can deliver. Despite spending millions on licenses and maintenance of existing CRM systems, this is why:

• Enterprises spend up to 30% more time on administrative tasks compared to those using modern, automated solutions.
• Nearly 50% of organizations cite user adoption as the most significant challenge.
• 43% of organizations cite that they use fewer than half of their CRM functionalities.
• According to a Gartner® survey, one of the top three reasons for switching to CRM software is inefficiency, cited by 40% of respondents.¹

A modernized cloud-based CRM system, such as Microsoft Dynamics 365, is the way forward. The Dynamics 365 CRM suite is a top-of-mind choice for leading enterprises due to its ease of integration with enterprise-grade applications, embedded AI/ML capabilities, and data interoperability, bringing in competitive agility and efficiency.

However, replicating the current CRM landscape in Dynamics 365 will only prove counterproductive. Years of customizations on existing CRM applications, siloed data and business processes, and a lack of transactional visibility are the reigning factors behind why one in three CRM projects fail.

Four Reasons Why CRM Migrations to Dynamics 365 Fail

Since CRM systems have been integral to marketing and sales operations for decades, they need to be optimized for data and processes before they can be migrated. Below are the roadblocks that enterprises can encounter when migrating existing CRM systems to Dynamics 365:

• Missing documentation: After years of customizations, organizations usually lack crucial documentation of how these customizations were done and to what end. Without this technical and functional documentation, migration can be challenging, time-consuming, and prone to errors, impacting the integrity and functionality of CRM data and processes.
• Undefined migration scope: CRM systems are mammoth due to objects and attributes accumulated over time. Without understanding the out-of-the-box functionalities offered by the Dynamics 365 CRM suite and mapping existing business-critical objects or attributes with them, migration projects become untenable due to redundancies, leading to cost and time overruns.
• Untamed data sprawl: Migrating huge volumes of data has been a reigning factor of migration failures. Data in enterprise CRM systems often exists in silos and can be duplicated or irrelevant to current business processes. Investing time and effort in migrating huge volumes of duplicated, irrelevant data results in migration projects being abandoned midway.
• Complex customizations: One of the most complex pieces of this puzzle is maintaining the integrity and functionality of existing CRM processes in the target environment by migrating complex customizations. Given the rapid pace of change that enterprises experience, not all customizations have a business justification, and neither would all of them justify the return on effort that would be required to replicate them in the cloud CRM application. Enterprises need to weigh in on which customizations are business-critical and are not covered in Microsoft’s out-of-the-box functionalities.

Re(AI)magining Migration Challenges with GenAI

Generative AI (GenAI) accelerates migration projects by parsing volumes of structured and unstructured data to generate code, summarize key points, and provide contextual recommendations.

• Supplement missing documentation: GenAI can reverse engineer the CRM customizations to create detailed documentation on critical components, describing how these processes are structured, their purpose, and how they integrate with user interactions. It can also explain how customizations enhance the CRM system’s overall performance and user experience, including the business case for retaining or retiring them, giving critical insights to migration teams on how business users use CRM.
• Optimize objects and attributes with a business-first lens: GenAI can read through available documentation and underlying codebases to understand which objects and attributes in the current CRM system most align with business needs. It can compare the current CRM functionalities with the ones offered by the Dynamics 365 CRM suite to rule out redundant attributes and objects, saving significant time and effort during migration.
• Improve data quality: By analyzing and identifying gaps, errors, and duplication in data stored across siloed enterprise applications, GenAI can cleanse the data landscape by removing stale records or flagging data errors pre-migration. GenAI can ensure a stable migration with successful post-migration operations by optimizing data based on business logic and user needs.
• Ensuring data privacy and security: GenAI can learn from role-based access policies and ensure data in transit is not exposed to unauthorized users. It can compartmentalize sensitive data that only authorized personnel can access. It can also recommend changes to governance policies that make the enterprise more compliant with data protection standards, such as the General Data Protection Regulation (GDPR) and California Consumer Privacy Act (CCPA).
• Address customization migration complexities: GenAI can examine custom-built code libraries to understand their functionalities. It can also recommend steps to optimize codebases before migration, ensuring a smooth transition and lower CRM maintenance costs in the long run.
• Boost user adoption: GenAI can help devise training material and user-friendly guides that allow business users to understand new functionalities post-migration and how they help them perform better than earlier.

Introducing Persistent SwiftShift: GenAI-led CRM Migration to Dynamics 365

Persistent partnered with Microsoft to develop SwiftShift, a GenAI-based CRM migration accelerator that delivers a 40% faster turnaround time at a 50% reduced cost of migration, based on our collaborations with clients.

SwiftShift has already demonstrated significant cost and time savings for leading enterprises moving existing CRM systems to Dynamics 365. For instance, we migrated marketing processes from Click (erstwhile ClickDimensions) to Dynamics Customer Insights for a large medical-surgical manufacturer. We leveraged GenAI to automate the discovery of the Click object models and successfully migrated these to Dynamics CRM within a week — reducing the overall migration timeline by 40%.

We leveraged Azure OpenAI to map the Click objects with Dynamics Customer Insights entity models. This enabled a smooth data migration between the two platforms, ensuring the data was optimized for data insights before the transition. We also developed comprehensive marketing dashboards for the client’s executive team, providing valuable insights and enhancing decision-making capabilities.

This halved the migration costs, which were a major concern for the client and due to which it previously deprioritized migration. The new streamlined and efficient CRM processes will further optimize operational costs, leading to an additional 30% savings.

To know more about SwiftShift, download the brochure here. To streamline your CRM migration to Dynamics 365 with GenAI, get in touch with us here. 

^[1] Gartner Digital Markets, How to Stand Out in Your Category: Buyer Insights for CRM Software, Caroline Hogan, August 30, 2024
GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally and is used herein with permission. All rights reserved.