The author John C. Maxwell once said, “If you’re proactive, you focus on preparing. If you’re reactive, you end up focusing on repairing.”
For the majority of CX history, companies have been primarily focused on repairing their relationships with customers, instead of preparing for issues. Although proactive customer support is not a new idea, companies still struggle with how to heighten its impact with big data.
The combination of technology and proactive support is creating a monumental shift in CX by making strategies more customer-centric, improving customer loyalty by 5%, and increasing overall revenue. By curating thoughtful customer experiences and meeting customers on their terms, CX operations can be less of a cost center and more of a profit center.
Proactive customer support is critical to any CX strategy because of its ability to anticipate customer needs and their preferences, and provide a well thought out experience with a brand. By keeping simple customer queries at bay, it reduces operating costs and unnecessary friction which keeps bottom lines low and CSAT scores high.
Proactive Customer Support: The Stats and Facts
A proactive approach to support is an organization’s ability to foresee certain problems before they occur and implement early processes to help contain the negative impact it might have on customers.
For instance, if a retailer is experiencing a hiccup with a logistics company that’s causing mass order delays, they can do one of two things:
Quickly train agents on their response to the influx of calls they are about to receive (reactive)
Promptly send out an SMS message to impacted customers letting them know their delivery is delayed by X amount of days (proactive)
Option two clearly offers the least amount of friction with customers and immediately decreases the amount of potential call volume and thus, reduces costs long term. By strategically implementing proactive support, companies have reported a:
- Reduction in inbound call volumes by 20-30% in 12 months
- 25% decrease in operations costs
- 3-5% increase in customer retention
But being proactive isn’t just something companies should strive for, it’s what customers want. A survey found that 87% of customers want to be contacted proactively by a company about service issues.
When Shift Happens
Although in the moment proactive support decisions make an immense impact on operational costs and brand perception, the real value and shift in CX comes when it’s powered by big data.
Big data is the collecting and analyzing of data and should be used throughout the customer journey, not just the beginning micro moments–an opportunity I see a lot of CX leaders overlook. When you couple big data and proactive support approaches, you move away from the break-fix style of support and shift toward a strategic predict-pivot methodology.
For example, if a customer is trying to upgrade their subscription, and have no luck using self-service tools, email, or chat the last resort is calling the company. When the customer is prompted by the IVR, a company should know their channel hopping history. Ideally, a proactive automated message that addresses the customer and asks if they are calling about switching to a different subscription or something else. Once their selection is made, they should be routed directly to an agent for help. This proactive approach eliminates the stress and frustration of a customer repeating themselves and increases speed to solution.
By consistently monitoring how customers use your products, services, and self-help resources, it empowers CX teams to proactively respond to issues before they arise. By piecing together the breadcrumbs of a customer’s journey, companies can utilize that data to view the full distance of the customer, past purchase behavior, and their likely next step.
How to Get Started
A lot of ideas and concepts in CX take a lot of time and money upfront, but proactive customer support that’s powered by big data works with what you have already. To begin the process, review your customer feedback from last quarter and extract the weaknesses customers noted.
What do these problems mean for this quarter and the quarters to come? What data do you have around the issues to inform what a proactive approach might be?
Start making a new chapter in CX history by starting a proactive, data-based shift in the way you deliver experiences to your customers. Once you get started, you will definitely notice a positive difference in key metrics like AHT, call volume, CSAT, and NPS. The combination of big data and proactive customer support has saved some companies up to $10 million. How much will you save?
Guest post written by: Jennifer Turner, Vice President, Business Development, Retail, TaskUs