Why “Fake Automation” is Hurting Your Business

Ask most operations or CX teams if they’ve automated their customer communication, and the answer is usually yes.

There’s a message scheduler. A few workflows in the CRM. Some trigger-based campaigns in WhatsApp or email.

On the surface, it feels like progress, messages are being sent without someone manually pushing the button, and that box on the digital transformation roadmap can be ticked, right?

But when you examine the outcomes, something often doesn’t add up.

Customers are still calling in to confirm basic things. Queries that should be self-service end up with an agent. IT is still getting pulled in for fixes and updates. And the overall service experience still feels reactive, clunky, or delayed.

What’s causing the disconnect?

You see, in most cases, the automation exists - but it’s shallow. Messages are going out faster, but the underlying process hasn’t actually changed.

The task still depends on the customer switching platforms, navigating extra steps, or waiting for a human to pick it up at the end.

And when that’s the setup, speeding it up just creates friction faster.

The message gets delivered. The system logs the send. But resolution still drags, and operations are left to fill the gap.

In the guide you’re reading right now, we will explore what real automation looks like, and why so many businesses have ended up with a version that looks efficient on paper, but creates more complexity in practice.

The Illusion of Automation (Why Most Businesses Get It Wrong)

When businesses talk about automation, the conversation usually starts with tooling.

There’s a workflow engine in place. Messages are scheduled. CRM events trigger outbound comms. Some of it’s handled through service queues, perhaps some through custom integrations built over time, and maybe some others through a marketing platform. On a whiteboard or a slide deck, it looks like a sophisticated, efficient system.

But when you trace the path from message to resolution, things start to unravel.

Let’s take a common use case - a customer receives a payment reminder.

The message goes out at the right time, triggered by the right event. Maybe it’s personalised with their name and amount due. But what happens next? In most setups, the customer is directed somewhere else: a login portal, a third-party form, an app they haven’t downloaded, and that’s where the flow breaks.

Sometimes they can’t remember their password. Sometimes the link is broken. Sometimes they’re unsure whether it’s secure or up to date. Whatever the reason, the task doesn’t get completed, and a few days later they’re back on the phone, speaking to someone who now has to fix what the automated system couldn’t finish.

But that isn’t a tech issue. The message was sent, the trigger fired, the data matched. On paper, everything worked.

The outcome however, is still dependent on human intervention.

And that’s the great “automation illusion”: automation that’s optimised for sending, not resolving. Sure, it gives the impression of speed, scale, and control - but underneath, the manual dependencies remain. Calls don’t go down, costs don’t shrink and teams are still reactive.

True automation doesn’t just move messages around faster. It eliminates the need for someone to step in later. It closes the loop inside the same interaction. It reduces work, instead of reshuffling it.

Many local businesses have built automation around communication, but not around the resolution itself.

Common Signs Your Automation Isn’t Actually Working

It’s easy to assume your automation is working because messages are going out on time, campaigns are running, and teams aren’t manually sending updates anymore. But the real measure of success is what happens after the message lands.

When automation doesn’t extend to the resolution layer, it creates hidden drag. The effort has just been kicked down the road or deferred. Customers still struggle to complete the task. Teams still have to follow up. And IT still gets pulled in to bridge the gaps.

If you’re seeing these patterns, it’s a strong signal that your current automation is only solving part of the problem:

You’re still relying on your call centre to complete basic tasks

Customers receive a message, but they still end up calling. Maybe the instructions weren’t clear. Maybe the link didn’t work. Maybe they just didn’t trust the process. Whatever the cause, the task bounces back into your queue, and now a person has to handle what the system couldn’t finish. If call volumes are staying flat despite increased automation, this is likely why.

Customers drop off before taking action

You’ve built a flow that looks good in testing. But in reality, users don’t complete it. They get partway through and stop. The login step becomes a blocker. The form is too long. They have to switch channels or start over. Each of these points introduces friction - and the more friction there is, the higher your abandonment rate climbs. The system appears to be working, but the outcome stalls.

Every tweak still needs help from IT

One of the promises of automation is agility - being able to adapt quickly as needs change. But if your messaging flows are rigid, hard-coded, or overly dependent on technical teams, even small updates become slow. If changing a field, fixing a trigger, or adjusting copy requires a dev ticket, then you’re not really automating, you’re just shifting the manual work into another queue.

You’re measuring activity, not completion

Automation dashboards are often filled with metrics: number of messages sent, open rates, delivery confirmations. But without visibility into how many of those messages resulted in a completed task - a payment made, a form submitted, a detail updated - you’re flying blind. High activity might feel like performance, but unless the system is driving resolution, the impact on your operations will be minimal.

The customer-facing experience may be automated, but the core resolution flow remains manual.

This is one of the most common patterns we see. A smart-looking front-end, personalised messages, triggered flows, dynamic content etc. backed by a process that still requires human involvement to close the loop. Maybe it’s a reconciliation step. Maybe it’s a confirmation that needs to be processed manually. Either way, you’re not really reducing effort, you’re just delaying or putting it off.

These signs aren’t fringe cases. They’re what automation looks like when it’s built for messaging volume, not task completion.

And over time, they create more pressure -  for your teams, your customers, and your bottom line.

[Case Study] How A Business Cut 70% of Inbound Calls by Automating Resolutions

A local financial service provider (FSP) had a familiar problem.

They’d already invested in customer communication automation. Their CRM triggered payment reminders. Their marketing platform handled renewals. They had SMS and WhatsApp flows running across multiple use cases. On paper, everything looked in place.

But operationally, they were still struggling.

The call centre was flooded with repetitive queries - customers confirming payment dates, asking about balances, requesting copies of invoices, or chasing up on reminders they’d already received.

None of these queries were complex, but they weren’t getting resolved inside the messaging flow, so customers defaulted to calling in.

The operations team started digging into the workflows, and what they found was a pattern. 

Every message asked the customer to act, but none of them let the customer complete the task.

• A reminder would go out with a prompt to log in. 

• A confirmation message would point to a portal. 

• A renewal notice would require phoning in. 

And if any of those steps failed - login issues, broken links, long wait times - the fallback was always a human.

The team decided to shift the focus away from reminders and towards resolution.

Instead of just sending alerts, they rebuilt the communication flows so that customers could complete tasks inside the message itself, so no logins, no downloads and no follow-ups. Each interaction was designed to contain the action: tap to pay, swipe to confirm, click to update.

The backend systems were already in place and the customer data already existed. The change was in how the message flows were structured ie: building the resolution into the front-end experience, instead of treating it as a separate process.

Within three months, inbound calls dropped by 70% in the targeted areas. Customers were no longer phoning in for tasks they could now complete on their own. Resolution times shrank. Internal ticket volumes fell. And for the first time, the automation layer was reducing work instead of just redirecting it.

Again, the technology hadn’t changed, but the outcome had. The goal had shifted from delivery to task completion, from start to finish.

Real Automation Means Eliminating Work, Not Just Speeding It Up

The mistake most businesses make is equating speed with efficiency. A faster notification. A cleaner workflow diagram. A quicker way to trigger a message.

But speed, on its own, just amplifies whatever’s already in the system, so if the process is broken, you get broken faster. If the task is incomplete, it stalls sooner, and if resolution still relies on human effort, then you’ve just delayed the work, not actually reduced it,

So to move beyond that, automation needs to stop being a comms function and start becoming a resolution layer.

That shift requires three things: containment, integration, and visibility.

Containment: Keep the task inside the flow

The fastest way to reduce operational drag is to prevent the task from spilling into another channel.

If a customer receives a message asking them to update their banking details, that update should happen inside the message, not via a link to a login portal, not through a PDF form, and definitely not over a phone call.

Containment means the action can be taken immediately, with no context-switching. It doesn’t mean turning every message into a full app experience, but it does mean stripping the task down to what’s essential and enabling it in the simplest, most direct way possible.

If you can’t complete the task from the message, the message is just an alert.

Integration: Connect the message to the system of record

Most comms flows today operate in isolation. A CRM triggers a message, and the message platform logs the send. But the actual result, whether the customer completed the task, is invisible to the source system.

That is a problem because what it does is creates blind spots. Ops teams can’t see where drop-offs are happening and follow-ups are generic. And you can’t close the loop, because nothing’s been connected.

Effective automation is therefore underpinned by integration. And no, that doesn’t mean full-stack digital transformation. It does mean tying your message flows back to the systems that matter - think payment platforms, case management systems, customer databases etc. so that actions taken in the message reflect where they need to.

When a customer confirms a new debit date, it should update directly in your billing engine. When they upload a document, it should hit the workflow queue without needing rekeying. Anything less than that is cosmetic.

Visibility: Track completions, not just sends

Too many teams are optimising based on message volume (How many were sent. How many were opened. How many were clicked etc.).

But the real question is: how many of those interactions led to a completed outcome?

Did the payment go through? Did the customer reschedule? Was the update logged successfully?

You don’t need to track every interaction at a forensic level, but if you can’t tell whether a message actually drove resolution, then you’re just measuring noise.

With real automation, the result isn’t just that fewer calls come in, it’s that you know which part of the message flow created that shift. You know which journeys are working, and where to focus effort. That’s how teams get more efficient without adding more complexity.

When these three layers are in place, the comms system stops acting like a notification engine and starts behaving like a digital front door. Not just telling customers what needs to happen, but letting them do it, right there, in the moment, without leaving the channel.

That’s the difference between automation that sends and automation that solves.

Self-Check – Is Your ‘Automation’ Actually Helping, or Just Keeping You Busy?

If you’ve already automated your customer comms, it can be hard to tell whether the system is doing real work or just giving the impression of progress.

The campaigns are live, messages are firing, and reports are full of activity. But things still feel reactive. Resolution still depends on people and the same queries keep coming back.

Before you push further into another round of automation or assume the job is done, it’s worth stepping back and asking a few pointed questions.

Start with these:

Where do we still rely on humans to complete the task after a message is sent?

If your team is spending time manually confirming details, chasing updates, or resolving things that the message was supposed to address, then the process still has automation gaps.

What percentage of our messages result in completed actions, not just clicks or opens?

You might be tracking the surface metrics, but unless you know how many messages lead to a resolved task, you’re not managing outcomes.

Are our automation flows reducing inbound effort, or just shifting it?

If customers are still phoning in to double-check, clarify, or redo something they already received digitally, then the message flow didn’t do enough. Speed doesn’t matter if the end state is the same.

How much of our automation stack can ops teams control without logging a ticket to IT?

True automation frees up internal teams. If the system still needs technical intervention for small changes, you’ve just created another bottleneck, it’s just further upstream.

If we stopped all automated messages today, which parts of the business would be affected, and why?

This one’s blunt, but useful. If the answer is “not much,” your automation probably isn’t carrying as much of the load as it should be.

Automation should give teams leverage, reduce resolution time, and move work off your plate.

If your current system isn’t doing that, it’s not too late to shift gears. But it starts by being honest about what you’ve really automated, and what you haven’t yet touched.