CRM + CEM: The Perfect Pairing to Empower Frontline Agents and Uncover Predictive Insights

CRM + CEM: The Perfect Pairing to Empower Frontline Agents and Uncover Predictive Insights

Combining the data from a CRM and a CEM is a perfect pairing – like wine and cheese or peanut butter and jelly. Great by themselves, but amazing when combined. Together, a CRM + CEM can provide a well-rounded picture of what your customers are doing, and help to predict what they do next.

What is a CRM?

Customer Relationship Management (CRM) software provides useful information such as the amount of money that a customer has spent, how long they have been a customer, or what they usually buy at your establishment. What they do not offer, though, is information about the customers’ experiences, sentiments, and other contextual information that can help to color in the history of the customer’s relationship with a brand.

This is where customer experience management software (a CEM) is helpful.

What is a CEM?

What is a CEM? A CEM focuses on the customer journey from the perspective of the customer. It brings in a whole new layer of data, including how a customer feels and why they do the things they do. The problem is that CEMs offer a fairly anonymized sense of a customer – they don’t connect the customer experience to a real person with all the valuable context of who they are.

What data will I get from integrating both my CEM and CRM?

While both CEMs and CRMs have outstanding features that help provide excellent experiences to customers when used separately, using an integration to bring the two platforms together can provide a real-time, full view of the customer – not just what they’ve done, but how they feel about it too.

Let’s look closer at what specific benefits you’ll find when bringing CRM data into your CEM, a vice versa.

What you can do with your CRM data in your CEM

Segment customers for root cause analysis

By pairing experiences with customer data, you’re able to drill into even more specific customer cohorts by segmenting by your CRM data and performing deeper root cause analysis. Knowing the characteristic of specific groups (or cohorts) of customers can help identify the reasons why they might be acting a certain way.

For example, when just using a CRM, you can take a look and see that 37% of your customers spend over $150, and usually, customers only visit your store once. You may even be able to see what gender or age they are if that is something that you are tracking. That can be useful, certainly, but there isn’t very much storytelling or insights to be pulled from that data, other than that you probably want your customers to visit more. That’s when having an integration with your CEM becomes an important addition to your strategy.

With a CEM, you can take the data from your customers’ actions, and align it with the experiential data to better understand where you can improve your customer experience overall. Within your CEM, you may have data about NPS or ratings on your store experience, as well as other data about their store visit.  This gives you a unique opportunity to follow trends on experience, rather than just averages of sales data.

Predict the impact of CX changes on transactional KPIs

As a customer experience practitioner, you likely have a laundry list of improvements you’d like to put in place. But even though we intuitively know that they are important to the customer through surveys and qualitative data, we’re often left to hypothesize what those changes would do for the business. This can make it difficult to convince executives to invest in new initiatives.

By bringing CRM data into your CEM you can start to predict how these changes will affect transactional metrics like revenue, deal size and MRR. What size of customers consistently complain about the speed of service? What type of clients are canceling their subscriptions due to a poor selection of products? Who is rating you positively due to your product improvements? Path Analysis in CloudCherry, when powered by both CRM and CEM data, uncovers these key drivers for different types of customers.

Being able to see what CX attributes mean to different customers allows you to see how they impact customer behavior – and by extension – the transactional metrics that are critical to growing the business. Even more powerful is the ability to predict how the changes you make to CX attributes will affect specific cohorts – before you even commit to making the change.

What you can do with your CEM data in your CRM

Imagine trying to build a relationship, but not having any details about the person’s history, what they like and how they feel. It would be nearly impossible! But if your front-line employees are trying to build relationships with your clients only using CRM data – that’s what’s happening. You can’t build a relationship only around contract details and contact information.

Incorporating CEM data into your CRM gives front-line employees like account managers and customer service reps a clear picture of the customer. Say, for example, a customer calls in with a question about their account. From the CRM search bar, you can pull up their past purchases, any previous history they have with your company along with their demographic details (like where they live and how old they are). It might provide you with some context, but it’s not super helpful in solving their issue.

Add in CEM data and the picture becomes much more complete. You might be able to see from their tweets that they have been going through a stressful situation at work. Their last NPS survey might show that they’ve been frustrated with impersonal support in the past. You know that they’re a potential churn situation. Equipped with this information, you’re much more empowered to provide the level of service they need to stay a loyal customer.

Proactively handle situations before they become a problem

Incorporating CEM data into your CRM also equips your team to become more proactive in helping customers. Instead of waiting for customers to contact you about an issue that they’re already frustrated about, CEM data can identify customers that might be at risk of churning or not coming back.

For example, if a customer responds poorly to a survey asking them about their onboarding experience with a low score, incorporating this data into your CRM could trigger a notification for the customer success team to reach out to offer a personalized training session.

Identifying trends in customer experience data can help guide actions to improve customer relationships over time – without waiting for the customer to contact your team for help.

Break silos and use the data you already have

Delivering a well-executed customer experience requires integrating your customer data with customer feedback and other experiential data. The problem is that these two data sets are often stored in two very separate platforms.

CloudCherry’s lightning fast CRM integration will bring your valuable data out of CloudCherry and into your CRM to empower front-line employees to make better decisions. Pulling your customer data into CloudCherry will improve predictive analytics so that you can see how changes to CX will impact financial metrics.

Learn more about the CloudCherry CRM integrations today:

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