What do you know about your customers? Not your audience – but each of your individual customers. The fact is, there’s enough to do on a daily basis without keeping track of where each of your clients is in the sales cycle, what past purchases they’ve made, or the scope of their business in B2B sales. That’s why virtually every company relies on customer relationship management (CRM) software. These programs allow businesses to provide top-notch customer service, transition clients between representatives, and much more, but as software capacity grows, it’s raised questions. Specifically, users have started to wonder whether CRM platforms should be standalone programs or part of something more complex.
CRM Platforms for Business
Beyond Operational CRM
When we talk about the difference between CRM as standalone software and CRM that’s integrated with other tools, we’re typically distinguishing between operational CRM and analytical CRM. Operational CRM is used to manage routine sales, to track a customer through the pipeline, and for functions like lead generation and marketing. That’s a fairly robust piece of software on its own, but analytical CRM takes things a step further by mining customer data, predicting sales, providing data that can boost conversions, and much more.
In addition to CRM platforms that are built out to perform a greater number of tasks, like analytical CRM, there is also professional services automation (PSA) platforms that include CRM functions within their suite of tools. By combining CRM capabilities with integrated billing, help desk ticketing, and inventory management tools, PSA platforms take CRM to the next level. And while many of the added elements that come with a PSA look beyond the immediate demands of the customer, targeting elements like back-office automation, these functions allow staff to focus on meaningful customer service and interactions – the stuff computers can’t do.
Growing Through Machine Learning
Most CRM platforms offer some degree of data mining and analysis; they wouldn’t provide much in the way of insights, otherwise. However, they largely lack the ability to apply machine learning to CRM data to make that data more useful – or most didn’t, until now. Some new platforms are applying the principles of natural language processing to CRM in order to enhance the knowledge discovery process, automate account organization, and interpret subtle cues in client communications that could help the company perform better.
A Critical Market
CRM tools serve a huge audience, with more than 90% of businesses with over 10 employees using a CRM platform to manage their accounts. That means that even small advancements reach a huge number of users and that, though people may not realize it, virtually everyone’s consumer experience is shaped in some way or another by CRM tools.
Finally, while the majority of businesses rely on CRM programs, they aren’t one size fits all systems. To get the most out of CRM software, then, businesses need to be able to customize the system based on their preferred approach, and systems featuring more complex integrations open up a world of opportunities to businesses that basic operational CRM can’t provide.