A CRM is a customer relationship management system. Data is captured into the CRM to create business intelligence. Think of a CRM as a database that houses everything your sales, client service, and financial reporting needs to know about clients and prospects. This can include contact information, roles, accounts, and interaction points. Workflows can be triggered by these data points, especially when they meet triggers within the software. In this sense, a CRM is a system of record, meant to house information that is reliable and actionable. That system of record can be thought of as a memory bank or footprint of a business' customer-focused activity.
To make data actionable, CRMs layer in analytics and reporting that transforms raw data into business insight. Ultimately, businesses use CRM data to assess their client and sales health. This helps with optimizing workflows, improving client health, and creating better financial projections.
As an example, a Software as a Service company may want to know what their internal customer retention is. That can be analyzed through accounting software (even a spreadsheet), as customer retention is largely an accounting identity. But if a business wants to go a layer deeper than a headline retention figure and understand the underlying reasons for churn (or upsell), they may want to understand how customers are using their product, how they are being onboarded, and how they are interacting with service. This type of contextual data can be stored and then analyzed with a CRM.
The difficulty with CRMs is their use case is very unique across different organizations. So the software that powers them has to balance front-end ease of use with flexible customization. This often requires systems engineering, consultants, standard data practices, and countless custom integrations to make right. All of this is costly. Furthermore, getting sales and customer service employees to leverage the CRM can be challenging.
In busy knowledge working verticals such as investment banking, ModuleQ addresses these conundrums by connecting our Unprompted AI with the bank's CRM. This allows us to push insights from that system of record directly to a banker or wealth manager, via Microsoft Teams (their communications portal).
Returning to our memory bank analogy, Unprompted AI is like a synapse that knows how to connect to long lost memories that you may not readily recall. By firing that information directly to our attention, we gain value from that bank in ways that standard reporting and sleuthing can fail to capture.
This alleviates the reporting and log-in requirements that lead to "last mile" failures when it comes to extracting value from a CRM. It is a core belief of ours that breaking data silos unlocks the value of data, and tools such as Unprompted AI can lead the charge in revolutionizing the workflows embedded within CRMs.
Read More from ModuleQ:
CRM is a Four Letter Word, AI Can Fix That (Nov 2023)
Oracle: A customer data platform (CDP) is software that collects and unifies first-party customer data—from multiple sources—to build a single, coherent, complete view of each customer.
Salesforce: CRM tools can unify customer and company data from many sources and even use AI (artificial intelligence) to help better manage relationships across the entire customer lifecycle, spanning departments like marketing, sales, digital commerce, and customer service interactions.
Zendesk: CRM ensures businesses can exchange key data and insights across sales, support, and marketing.