Customer expectations for service continue to rise sharply, with a pivotal Zendesk study revealing that 73% of consumers will switch to a competitor after multiple negative experiences.
The modern customer expects companies to resolve issues swiftly and ensure seamless interactions throughout the lifecycle of their communication with them.
Yet economic uncertainties and turbulent headwinds constrain businesses from simply hiring more staff to meet this surging demand.
This mismatch puts immense pressure on contact centers to innovate rather than scale headcount.
In response, Amazon Connect is championing a shift toward proactive customer support—moving away from traditional reactive models to approaches that anticipate and address customer needs before they even arise.
But what exactly is proactive customer support? UC Today spoke with Pasquale DeMaio, VP of Amazon Connect at AWS, to unpack the concept and explore how this strategy can reduce inbound contact volumes and elevate customer experience when executed effectively.
Traditional Contact Center Support Versus Proactive Customer Support
Traditional contact centers commonly operate reactively, waiting for customers to reach out with issues and then resolve them.
Although this serves its function, the model has become synonymous with frustrating waits, repeated explanations, and drawn-out resolutions.
As Pasquale DeMaio explains,
“Traditional reactive service is about solving problems after they occur, which often involves customers waiting on hold, explaining their issue multiple times, and feeling frustrated.”
He characterizes this as a “transaction-based relationship,” where interactions only occur because something is wrong. This relationship focuses purely on problem resolution and often breeds negative sentiment.
By contrast, DeMaio defines proactive customer service as such:
“Proactive customer experience means anticipating customer needs before they even know they have an issue.”
Instead of waiting for customers to contact you with a problem, you’re using your understanding of them, their history, and what you know about other customers like them to fix problems before they even start,” he says.
For example, a rental car company might notice a customer’s flight delay and proactively message reassurance about vehicle availability, thus eliminating the anxiety of having to call for confirmation.
This approach transforms the customer-company dynamic into a “partnership relationship,” where the business actively looks out for customer interests, creating value well beyond the point of purchase.
At a fundamental level, this proactive support reduces the volume of inbound contacts by intercepting issues early that, although easily resolved, take up the time of agents and contact center capacity.
This proactive customer service not only lowers operational costs but enhances the customer experience significantly.
Beyond efficiency, this service fosters deeper loyalty by shifting customer perception from transactional to relational. Customers feel valued when businesses anticipate their difficulties and reach out with solutions or helpful information unexpectedly.
DeMaio notes, “Today’s consumers increasingly choose businesses based on service experience. The most successful organizations use these insights to drive customer loyalty and transform service from a cost center into a strategic advantage.”
When done right, proactive service can even leave customers more satisfied than if a problem had never arisen, by demonstrating attentiveness and empathy.
Furthermore, proactive strategies help businesses retain customers who might otherwise churn silently. By engaging customers early—such as those showing signs of waning usage or dissatisfaction—companies create an easy opening for customers to vent their frustrations instead of quietly canceling, better securing revenue.
Enabling Proactive Customer Support
Yet this shift from reactive to proactive is not just philosophical. It relies on extensive new infrastructure that utilizes customer data, AI, and advanced analytics to predict issues and personalize interactions dynamically.
Often, however, companies have some fundamental issues that hold them back from this. DeMaio points out the primary obstacle:
“The biggest challenge companies face when implementing proactive customer experience strategies is their fragmented data landscape.”
Customer information often resides scattered across multiple systems, making it difficult to form a coherent, unified view necessary for effective anticipation.
Without consolidating and harmonizing data, proactive initiatives are hindered by “garbage in, garbage out” issues, where poor data quality undermines prediction precision.
Amazon Connect addresses this with its customer profiles technology, integrating about 80 connectors across enterprise systems to merge data with high accuracy and deliver real-time insights.
It then brings together voice, chat, email, and social messaging in a single routing and automation engine that can use AI-powered segmentation and generative AI assistance throughout the entire customer journey.
A compelling instance of this proactive approach in action is Amazon’s own People Experience and Technologies team, which used Amazon Connect’s video capabilities to virtualize the hiring process for 1.2 million job candidates annually.
According to DeMaio, this proactive redesign reduced candidate wait times by 89%, handling times by 30%, and cut cost-to-hire by 90% through personalized outbound campaigns.
“This example shows what happens when you fundamentally rethink the entire experience, not just optimize a few metrics,”
DeMaio remarks.
This unified data foundation is therefore critical to effectively knowing when and how to intervene.
DeMaio also emphasizes the importance of prioritizing where proactive customer support is used in order to not overload or overcomplicate systems.
“The key is to work from big to small—start by addressing high-impact issues, like flight delays or service outages,” he advises.
Another common pitfall is relying on outdated or narrow metrics that encourage short-sighted behavior.
Traditional contact centers often obsess over average handle time or call deflection rates while missing the bigger picture of customer lifetime value or relationship strength.
Instead, DeMaio argues that shifting to proactive customer service requires measurement strategies that evaluate long-term impact on retention, spending, and brand perception.
Changing Success Metrics to Deliver Better Service
Proactive customer support has the potential for many contact centers to better handle capacity and keep customers happy at the same time.
Yet it requires a fundamental restructuring of their customer journey and the metrics by which they measure it.
While traditional KPIs such as average handle time or call volume can gauge operational efficiency, they do not capture the deeper business value generated through loyalty, retention, and lifetime customer value.
This necessitates advanced data integration and analytics that connect customer interactions so they can continuously optimize proactive engagement approaches.
This not only helps understand what to approach but also identifies the right moments and opportunities for proactive contact.
While the road requires investment and sustained effort, the payoff is meaningful: stronger customer relationships, lower operational costs, and measurable business growth.
As DeMaio summarizes, “Transforming service from a cost center into a strategic advantage is the real opportunity proactive support offers.”
