You know how important customer data is for driving revenue and growing your business if you’ve ever used customer relationship management (CRM) software.
Making decisions based on your collected data is crucial to providing an excellent customer experience and keeping your customers happy. On that note, you’ve probably heard that machine learning and AI are the future of analytics.
You’ve heard right—they are.
If you’ve ever been confused about what machine learning is and what it can do for you, we’re here to help by explaining three different ways ML is transforming CRMs to better help businesses leverage their data.
- Machine learning is becoming a more common feature in CRMs and unlocks extra insight into the data you’re already gathering.
- Using machine learning to boost your predictive lead scoring and analytics will increase your ROI and conversion rate.
- Machine learning helps provide you with a 360º view of your customers and can find patterns for you before they become problems.
- Qualitative data is often hard to parse, but machine learning makes analyzing unstructured data a breeze.
What is machine learning anyway?
At its core, machine learning is a category of AI that aims to extract knowledge or patterns from a series of observations. Think of it like a person who looks at collected data and provides you with insight and analytics based on the data, while also learning and adapting with each set of data.
Except this person can look at every single point of data in less time than it takes you to grab a cup of coffee.
Within a CRM, it will look at all existing customer information (both structured and unstructured) and provide you with a more complete look at a customer’s story.
- ✓ It will look at your previous decisions and data to see which actions led to better solutions.
- ✓ It will help you make the most informed decisions with new customers by recommending next best actions based on fresh customer interactions.
- ✓ It will continually learn and adapt based on your updated strategies and outcomes from different decisions you’ve made.
The key here is that a lot of the most complicated aspects of machine learning are done by the vendors developing the algorithms. You just get to reap the benefits.
How machine learning is transforming CRMs
Below we’ll dive into three specific changes machine learning has brought to CRM software:
- Get a better ROI with predictive analytics
- Connect disparate customer data points to understand customer decisions
- Give value to unstructured qualitative data with ease
1. Predictive analytics leads to better ROI
Predictive analytics have been one of the key differentiators for CRM solutions in the past few years, and Gartner found that there’s growing interest around predictive functionality from marketing technology (full content available to Gartner clients).
With all the major players in the industry buying into this technology, even smaller businesses get to reap the benefits. The most common predictive analytics you’ll find in CRMs is predictive lead scoring.
Predictive lead scoring is a tool that uses an algorithm to look at the data you’ve collected in your CRM and external data found in the wild (such as on your website or email marketing efforts) in order to determine whether leads are qualified or unqualified.
Essentially, it uses machine learning to sift through your contact database to give you more structured information about client behaviors and trends that would take you much longer to manually do.
If you’ve always manually scored your leads and don’t trust the robots to give you accurate information, you can always use what the predictive models give you and go through the results with a fine-toothed comb the first few times to go further into your scoring.
Key takeaway: A CRM with predictive analytics and lead scoring will increase your revenue by arming you with better information. If you’re in marketing, you’ll be able to more accurately target the right consumers where they are during their buyer’s journey.
2. Connect disparate customer data points to understand customer decisions
You’ve probably gotten a call from a client wanting to cancel or move to another system before. Sure, most of the time that might have to do with cost (which is mostly outside of your control), but other times your rep might be blindsided by a list of complaints that you weren’t aware of.
Take this as an example: After the fact, you go through and check their profile, noticing they’ve submitted a few support tickets in the last month. That alone isn’t enough to cause concern, but you dig a little deeper and find their average use has gone down. Again, by itself, this isn’t a huge concern. After a little more digging you see your sales rep wrote down they had a new chief technical officer, which may not be a huge concern by itself either.
But put together, that paints a pretty clear picture. One you didn’t notice.
Key takeaway: A CRM with machine learning capabilities is able to go through each customer’s data and find these pain points or concerning behaviors and alert you before you receive the call asking to cancel, giving you time to be proactive and talk to the client before they hit their breaking point.
3. Give value to unstructured qualitative data with ease
One of the benefits of using a CRM is the ability to write notes about each individual client or customer so you can refer back to them before you contact that person. While useful for maintaining a good level of personalization, it’s difficult to use that data for anything else.
A CRM has a plethora of structured data that’s easily accessible, including revenue, location, or job title, but more qualitative data is harder to parse out and draw meaningful conclusions from without spending an unrealistic amount of time going through the data.
It’s, frankly, almost never worth the time spent by a human—and that’s where a CRM with machine learning capabilities comes in. With a CRM with natural language processing (NLP), you can leverage all of that unstructured textual information. It will crawl through all the text your CRM has natively and will even go through any other contact you have with customers via email or social media to give you a clearer picture into a customer’s identity.
Key takeaway: A CRM with machine learning and NLP can crawl through all your unstructured text to give value to all that qualitative data. By combining both qualitative and quantitative data, you’ll have a much greater understanding of your overall sales landscape, and you can draw more meaningful conclusions for your business.
CRM machine learning is here to stay—and you should jump on board
You might be thinking to yourself, “I’m a small or midsize business. I don’t have enough contacts or information for machine learning to be useful.” And you might be right.
In fact, machine learning or AI functionality wasn’t even on our list of top-requested CRM software features when we looked at feature requests from the small and midsize businesses who talk to our advisors.
But as this technology continues to advance and evolve and more vendors jump on board and develop their AI algorithms, the CRMs without machine learning will be in the minority. In fact, Gartner considers machine learning functionality as one of the most exciting new technologies available to CRM users (full content available to Gartner clients).
Even as a small or midsize business, you should consider utilizing a CRM with machine learning. The “learning” part of machine learning means that the longer you use it, the better it understands your business. It gets smarter about your customers and needs, leading to better insights and allowing you to make better decisions.
Better decisions lead to better ROI and happier customers.
For more information on what a CRM can do for your business, take a look at our CRM Buyers Guide, or give our team of expert advisors a call at (855) 444-0395.
Credit: Google News