5 Best Practices for AI-Powered CRM Readiness

Jack Wagnon
Director, Product Management
3 min read
5 Best Practices for AI-Powered CRM Readiness

With the advent of Generative AI, CRM applications are better positioned to fulfill their promise of providing a 360-degree view of the customer. It can also facilitate automatic processes in sales, marketing, and services, while analyzing vast amounts of data to deliver predictive analytics on business outcomes and improved customer experience.

Organizations are increasing their investment in AI with the goal of improving customer service to meet rising expectations. And with good reason: In a recent report sponsored by Salesforce, 91% of customers are more likely to make another purchase following a positive experience, and research from PwC finds that, “63% (of U.S. consumers) are willing to share more information for a product or service they say they truly valued.”

An AI-powered CRM leverages process automation, machine learning, and semantic interpretation to improve, automate, and enhance the CRM function. This has many potential benefits, including reducing repetitive tasks, decreasing human error, and accelerating workflows. But deploying AI within a CRM requires careful preparation with its effectiveness hinging on the accuracy, cleanliness and structure of its data.

Clean, consolidated data is the cornerstone of AI

A recent Forbes article asserts, “AI has a big Achilles heel…the problem isn’t with the technology. It’s with what the technology relies on: data.” And where is this data? Apparently, all over the place. In fact, Salesforce research finds data can be found in more than 800 business applications in the average enterprise, yet only 29% are interconnected.

This fragmentation prevents a comprehensive understanding of buyer behavior that can enable appropriate automated outreach actions. And it makes internal administration more difficult and inefficient by blocking optimized platform utilization.

Is AI-powered CRM right for you?

AI can be a powerful tool to enhance CRM, but it’s important to set your company up for success, starting with what to expect, and what to look out for. AI is not the answer for everything, so having realistic expectations on what AI will enable for your business—and what it can’t—must be communicated and planned for from the top down. To better assess how your organization might benefit from AI-powered CRM, take these five leading practices into consideration:

1. Start with the right vision and realistic expectations

To successfully assess and integrate AI into your CRM strategy, it’s essential to begin with a clear vision based on practical expectations. A well-defined vision, aligned with overall business objectives and customer experience goals, can help to ensure stakeholders understand desired outcomes and the role AI will play in achieving them. While AI can automate routine tasks, provide predictive insights, and enhance customer interactions, it’s not a panacea; take constraints and weaknesses into consideration.

2. Develop a master data strategy

A master data management (MDM) strategy for the entire organization can help you plan for success which includes strategy, design, governance, architecture, and maintenance. To succeed, the process of creating and implementing this plan must be driven by clearly defined outcomes and deadlines, and have a funded mandate from the C-suite. Involve your Enterprise Architecture team to provide guidance into the overall application portfolio strategy.

3. Design for scale

As you create your data strategy and architecture, set standards for structured data integrations to enable the seamless growth of your organization. The idea is to ensure that your CRM solution is designed to connect and scale with your Oracle, SAP, database, security, and other frameworks. Structured, integrated data will be increasingly important as digital operations expand and more applications are added. Solutions such as Mulesoft provide a powerful selection of prebuilt APIs allowing teams to combine multiple applications together.

4. Budget for AI feature enablement

Integrating AI features into your CRM and other applications within the context of a master data strategy requires resources. Engage the CFO’s office to collaborate with the finance team on how to budget for implementation of data architecture and AI project interdependencies and the required resources and expertise.

5. Prioritize AI use cases

AI has the ability to enhance a wide range of client-facing operations and practices, provide insights into revenue growth activity, help assess user sentiment, and operationalize advanced personalization. It may also assist in providing better customer service and experience across multiple channels via always-on automated chatbots. There are myriad other features to employ, so it’s vital that business leadership sets priorities for its use that match business needs and budgets.

Rimini Street can help

There are countless industry- and function-specific AI features you could enable. While the question of where to begin may seem daunting, start by prioritizing potential capabilities using a business impact rating systems that scores prospective features against five core categories: Cost reduction, cost avoidance, revenue growth, attrition mitigation, and risk and compliance.

Your business roadmap should most certainly explore the use of AI. Prioritize your next move by first mapping it back to these five economic drivers to weigh decisions accordingly. And get strategic guidance from a trusted partner. Rimini Street can help you blaze a trail to AI readiness with our Consulting Services that companies such as NTT Global Data Centers continue to benefit from.

Learn more: Discover how Rimini Solutions for Salesforce—from outsourced administration and managed services to forward-thinking strategic advisory services that help you implement and optimize growth and innovation—and help meet your evolving business needs.