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.
Get outside expertise on the integration plan. Seek guidance and partner referrals from your cloud provider, which has a vested interest in extending its platform for new, innovative uses. You will need to determine platform and network technical considerations, such as the following:
- On-premises or SaaS connectivity; (Consider that you’ll be limited if integrating with an on-premises system, since you’ll have to manage updates on your own, and the CRM functionality won’t keep pace easily with advances in cloud and AI.)
- New security and privacy requirements for exchanging data with your IaaS partner;
- Availability of resources for AI development expertise; and
- Integration with other systems.
3. Build a progressive cloud business strategy. The beauty of SaaS is that you can start immediately to realize the cloud benefits. Many of those benefits revolve around automatic updates and enhancements and constantly evolving technology.
For an organization to get the most from being cloud native, IT leaders should ensure that all parts of the business are connected to the cloud infrastructure. For example, integrating your warehousing and logistics systems with your CRM adds a lot of value. Issues with delivery and inventory directly affect your customers. Tying these core systems together makes predictive modeling much easier so you can keep customers happy and coming back.
Looking at expansion? Think about how your CRM can help you. Data on localization needs and currency fluctuations can and should be tied to your CRM.
What’s exciting about infusing ordinary business applications with AI is that the future is still quite unclear. We’re just scraping the surface of knowledge about benefits to both employees and their customers from letting machine learning play with data.
Most companies want to know more about what their customers are doing today, their interests and frustrations, and what they would most likely purchase tomorrow. By exploring the possibilities of connecting a CRM system to a cloud back end, companies can gain a competitive edge in a saturated global marketplace.