Your customer knows when something is wrong. But in many cases, the brand already has the information needed to know it too.
Consumer electronics are prone to certain hiccups: a connected device starts throwing an error, a software update creates a recurring issue, a product starts behaving differently than its normal pattern, a warranty is approaching expiration, or repair is delayed because a part isn't available.
And yet brands expect customers to notice the problem, search for an answer, find the right support channel, explain what happened, and wait for someone to diagnose it.
Why are we still making customers work this hard?
Customers shouldn't have to diagnose the problem
Warranty support has historically been reactive. When something breaks, the customer calls, an associate diagnoses it, and a return merchandise authorization (RMA ) or repair begins. That model made sense when products were largely disconnected and brands had limited visibility into what happened after the sale.
But that's no longer the reality. Connected consumer electronics generate information constantly — device status, error codes, connectivity, software and firmware behavior, usage patterns, prior service interactions, warranty status, and repair history. In many cases, the brand already has enough information to recognize that something isn't right, before the customer has said a word.
In today’s connected world, the customer shouldn't have to be the diagnostic system.
From reactive responses to predictive resolution
Delivering more proactive customer support doesn't mean reaching out about every possible anomaly; that would just trade one kind of noise for another.
Brands must dig into their data and intelligence to answer a few questions first: Is this actually a problem? Does the customer need help? Can it be resolved remotely? Does the customer need to take an action? Does this require a repair or replacement at all?
AI should play a role here. Use the technology to comb through large volumes of data, identify patterns, flag anomalies, and identify next best actions. When AI keeps a constant, real-time eye on what’s happening, your CX can evolve from reactive to predictive and proactive.
The AI conversation at consumer electronics brands needs to become more sophisticated than simply, “Use AI to reduce calls." AI needs to be thought of as a judgment layer, not just a detection layer.
The smartest RMA is no RMA at all
We’re all too familiar with the traditional RMA path. An issue occurs, the customer notices, the customer calls, troubleshooting takes place, an RMA is initiated, the customer ships the product back, the product is inspected, and a repair or replacement is done.
But consider the benefits of a proactive path. An issue occurs, the brand notices and identifies the root cause, the brand notifies the customer, and the issue is resolved remotely. In some cases, no RMA is necessary at all.
Or, when a physical fix genuinely is needed: an issue is detected, the brand notices and contacts the customer, and the brand initiates a replacement. All this happens without the customer ever having to call in the first place.
In the first scenario, the burden falls on the customer – to notice the issue, to contact the brand, and to ship the product back. In the second two, the brand takes the initiative, which brings several benefits.
A proactive approach leads to fewer avoidable contacts, fewer unnecessary RMAs, lower logistics costs, faster resolutions, and less customer effort. It also generates more confidence in the brand, because the customer knows the company caught the problem before they did.
Technology is only part of the equation
For all of AI’s amazing potential, technology alone won’t revolutionize the RMA process. It needs to be part of larger, interconnected ecosystem.
Collecting data isn't the hard part; contact centers are treasure troves of data. Connecting it is what gets trickier. Product data, customer history, warranty information, support interactions, and service operations all need to come together, and then those combined signals need to turn into an actual decision, not just a dashboard.
The sequence should be: detect, understand, decide, act, learn. The system detects the issue. Intelligence determines whether it's meaningful enough to act on. The operation decides what intervention makes sense for this customer and this product. The customer receives the right action, ideally before they ever pick up the phone. And the outcome feeds back into the system, so the next detection is sharper than the last.
That's a closed-loop warranty experience, not a chatbot bolted onto an old process.
A new standard for warranty support
Warranty teams spent years asking, "How quickly can we resolve the customer's claim?" That evolved to, "How can we make the claim process easier?"
Leading consumer electronics brands are pushing it a step further and asking, "Why did the customer have to make the claim in the first place?"
This marks a real shift. The goal is changing, from building a better warranty call to eliminating the need for the call whenever possible.
For connected consumer electronics brands, it’s no longer enough merely to respond better when a customer raises their hand. Brand must use the signals already at their disposal — the ones sitting in device data, support history, and warranty records — to anticipate problems, intervene earlier, and resolve issues with less customer effort.
The best support interaction isn't the one your team handles perfectly. It's the one your customer never needed to start.
