CRM IaaS-CRM systems are the lifeblood of many businesses, and the volume of customer data within them keeps growing as companies digitize more processes. That data often is not being used to its full potential, beyond basic reporting on sales metrics and marketing campaigns.
With the advent of mainstream machine learning and artificial intelligence technologies, this is all changing, and quickly. There is now a bevy of third-party machine learning systems that can hook into your CRM.
Machine learning can bring great business value to CRM users today in a number of scenarios. Intelligent algorithms can analyze website visits and produce faster, more accurate lead scores.
True personalized marketing is possible by matching the most appropriate content and offers to prospective buyers in seconds.
A company can use machine learning to analyze sales calls for best practices or improvements, or even provide tips to new sales reps using AI.
AI can help in the call center too, by applying past successful ticket resolutions to existing tickets, automatically prescribing the best steps for resolution, and by understanding customer sentiment through voice analysis.
In general, by applying AI to the task of discovering and combining unstructured and structured data about customers and trends, sales and marketing teams can be more proactive and predictive with offerings. They gain a better understanding of which marketing tactics work and which don’t, and how to improve online and offline processes for a better customer experience.
The CRM-IaaS Advantage for Advanced Analytics
While IT departments are starting to customize CRMs to achieve these functionalities through development or integrations, there is another approach: leveraging the public cloud.
Amazon, Google and Microsoft offer rich machine learning environments in which developers can use templates and tools to build and deploy AI plugins to front-end apps like CRM. They also can build entirely from scratch, developing the specific use case that’s most valuable for their customer base or R&D efforts — and that’s the real competitive advantage from AI.
A properly integrated IaaS and CRM platform provides a more comprehensive view of data across the entire organization — from customer interactions to logistics. CRM is just the beginning. Pulling data into the mix from other systems, such as inventory or financials, brings broader insights to your machine learning engine.
There are also get the benefits of scale, performance and optimization from IaaS and Platform as a Service technologies, which are important for extreme data crunching.
Tips for Getting Started
1. Develop the business case. IT leaders and marketing and sales execs should work closely to determine the business need and use cases for integrating CRM into the cloud infrastructure. Set measurable and realistic goals, e.g., to increase click-throughs on social media advertising through intelligent targeting.
2. Define integration needs. Determine which areas of your CRM should connect to which areas of your IaaS to help achieve your goals.
For instance, you might need to look at customer churn and get in front of any big losses before they happen. Marketing can do that by analyzing past churn metrics, overlaying that analysis with customer data, and predicting which customers are in danger of churn based on the actions they have taken, or other factors that would influence their behavior.