Providing exceptional customer service that exceeds customer expectation is the service level organizations strive for. Without the right technology and processes in place, companies may never achieve this level of service. This is where CRM analytics can help your organization.
Today, organizations gather large volumes of data about customers from multiple sources, including the contact center, sales and marketing teams and even social media platforms. This customer data can exist within the organization, but it’s not always tracked, analyzed or made available to agents as a complete customer history.
CRM analytics and what an organization can gain from it
CRM analytics is a system of tools and processes used to analyze large volumes of customer data from multiple channels. With a CRM analytics strategy, organizations can manage and track all customer communications to gain valuable insight about clients.
Kate Leggett, senior analyst with Forrester Research Inc. and leading expert on customer service strategies, said that organizations need three things to provide exceptional customer service.
“You want to make sure the customer is able to start on one communication channel, like email chat or Twitter, and continue the communication on the next channel. You also want to have consistency and deliver the same knowledge to every customer across every channel,” she said.
Lastly, Leggett said that customer interactions must build on prior interactions so customers don’t have to repeat themselves with each new communication. To do this an organization needs the foundational capabilities that CRM analytics provides.
Common scenarios for a CRM analytics investment
The reasons a business needs CRM analytics vary. Often, the first key indication is when a company realizes that it simply doesn’t know who its customers are.
Other common scenarios that could indicate it’s time to invest in CRM analytics are when a company receives a poor customer service satisfaction score, when company policy or regulatory compliance issues arise or when operational costs are spinning out of control.
In making the decision for CRM analytics, Leggett recommends that a business first understand its customers and their needs. Some things to consider include:
- How do customers want to get service from the organization?
- Does the company want to support customers over multiple interaction channels?
- Are the target customers a younger crowd that wants only SMS text messages?
Once organizations have a better understanding of what customers need, they can plan technology and business processes to improve specific areas of customer service.
Develop an incremental roadmap for CRM analytics
Keep in mind that the ideal CRM analytics solution must be a good match for the size and structure of the organization.
One method is to use the knowledge gained about the specific information your company needs and tackle the project in small stages using an incremental roadmap.
An incremental roadmap helps keep a large project under control and allows the organization to better deal with issues that arise during deployment, such as a change in budget or business.
“Once you know what’s working and what is not, you need to put a roadmap together for incremental improvements. This could be specific goals such as adding a new communication channel or process improvement work to ensure agents have the same knowledge across all channels,” Leggett explained.
Build the right CRM analytics project team
Putting a project team together with the right executive sponsor is crucial for a CRM analytics project. The project team ensures control if the project becomes too big or there is misalignment between the shareholders.
Leggett recommends starting with a program manager to head the team and a C-level executive sponsor who is responsible for the implementation and maintenance budget. Then, bring the stakeholders together and a business VP -- this could be a customer service manager or director who may also want to involve a couple of team members.
Lastly, bring in IT and the front-line experts (the best agents) to test the system and provide feedback.
This was first published in September 2011