There’s a version of the future that every major CRM vendor wants you to believe in. A customer has a problem, they message a chatbot, get seamlessly transferred to a human agent (if necessary) who already knows their full history, and the whole thing wraps up in minutes. No hold music. No ‘can you repeat that please?’ No being told to call a different number.
It’s a compelling pitch, and parts of it are genuinely coming together. But anyone who has actually worked in or around a contact center, knows the gap between the brochure and the reality can be pretty wide.
From chaos to…slightly different chaos?
For decades, contact center leaders have been duct-taping things together. Voice systems were built in one area, email in another, then came chat, SMS, Whatsapp, and social media, each bolted on through different vendors, different processes, logic, and so on. Customer data lived in silos. Getting a complete picture of a user’s journey felt like assembling IKEA furniture without the instructions.
Think about the last time you called your bank after already spending 20 minutes in their app chat. Did the agent know any of that? Probably not. “Can you verify your date of birth?” Yes..again. For the fourth time.
That’s the problem unified platforms are trying to solve. Rather than treating every channel as its own isolated workflow, the idea is one continuous thread – voice, digital, and everything in between – stitched together with shared context and AI doing the heavy lifting in the background.
In theory, the customer starts with a chatbot query, escalates to a live agent when things get complicated, and the agent picks up right where the bot left off. No reset or repetition. Just a resolution. That’s the idea anyway! The trouble is making it work when real customers are involved.
Where it falls down
The issue with integration is it doesn’t eliminate messiness. It just moves it somewhere less visible. Picture this: Someone messages a retailer’s chatbot about a missing order. The bot handles it fine. Then they follow up three days later but this time by phone, to say the replacement arrived damaged. From an infrastructure standpoint, both interactions are connected, but the voice agent is starting at a notes field that says “issue resolved” and has no real context for what happened. So they start from scratch.
It’s not a system failure but more so erosion. It doesn’t show up on any dashboard but absolutely shows up in how a customer feels about your brand.
Routing can compound things. Customers bounce between AI and human agents, across departments, sometimes without anyone (human or machine) owning the resolution. Edge cases? Good luck.
The real failure is none of this registers as failure internally. There was a successful handoff shown, the dashboard has the ticket resolved, so what’s the problem? Oh you know it. The customer, who is on Reddit writing a book about your customer service.
Read More: SalesTechStar Interview with Mark Walker, CEO at Nue
The testing problem nobody’s talking about
Traditional contact center testing was built for another time. You’d check: does the call route correctly? Does the message deliver? Does the integration work? Yes, yes ,yes.
That way doesn’t cut it anymore because a system where everything technically works can still produce an experience that feels very much broken.
Take for example testing a restaurant chain by checking whether the kitchen equipment is functional, the ingredients are in stock, and the reservation system is working. All go. But you haven’t actually tasted the food or that it takes 45 minutes to get a menu. The metrics passed but the experience failed.
The same thing happens in AI-driven contact centers. Testing what happens when someone switches from chat to phone mid conversation in a crowded train station. Or when they describe their problem in a very convoluted way. Or even when they’re frustrated and they stop being polite.
What to do about it
If you’re a contact center leader evaluating or already running a unified AI platform, stop testing systems in isolation and start testing journeys end to end. Run simulations that deliberately cross channel boundaries – start in chat, escalate to voice, throw in an edge case – and see what the customer would actually experience at each handoff. Do it before you go live, and do it regularly after to ensure the experience is the same.
Audit what your dashboards are measuring. Build in signals that reflect that customers encounter, like context retention across channels, resolution rates on first contact, and how the system handles inputs it hasn’t been really trained on.
The vendors building these platforms are moving quickly and the tech is genuinely improving. Organizations however that will get the most from it are the ones treating experience testing as seriously as they treat system integration.
Where does that leave us?
The move towards an AI-led, unified contact center isn’t wrong. Reducing fragmentation, centralizing data intelligence, and making interactions faster (time is money) makes sense.
But slick architecture and a working contact center are two different things. The companies that are going to get this right aren’t just the ones investing in the best tech, but are rather the ones honestly testing whether customers are actually having a better experience, not just that the systems are talking correctly to one another.
When it all comes down to it, the customer doesn’t care how unified your platform is. They just want to not have to say their date of birth five times.
About Klearcom
Klearcom provides global Voice and IVR testing capabilities to organizations with a dependency on customer communication
