Summary: Not every line of raw text contains a story. Sometimes, what looks like a wall of data or code simply is what it appears to be—a technical system’s way of saying “No.” This post explains why assuming narrative exists in non-narrative text is a dead end, especially in the context of automated systems, and what marketers, developers, and stakeholders need to understand when machines speak back in cold, structured syntax.
What It Really Is: A JSON Error Message
When someone receives a raw data response that reads like this — {"error": "Insufficient account balance"} — it’s easy to misread it as input missing context or as content that could be salvaged, reworked, or “rewritten” into something meaningful or engaging. This is a false start. Simply put, this kind of message isn't a draft-in-progress or a half-formed thought. It’s a final output from a machine that failed to execute an instruction because of a predefined rule: a user’s account didn’t meet the conditions required to proceed.
There's no character, no plot, no conflict resolution. There’s cause and consequence. That’s it. A request was made. A rule-check was executed. That rule failed — insufficient credit, permissions, or tokens — and the response was sent back per spec. Nothing more is hiding in the weeds.
What It Isn't: A Misplaced Narrative
Some might be tempted to ask, “Could we extract something meaningful from this?” You could force a story into anything, but now you’re running the risk of fiction. Extracting narrative from transactional errors is like trying to write a biography from a PayPal receipt. It misses the point.
Technical messages are not written for humans to interpret creatively. They’re for developers and systems integrators to debug operations. Trying to derive a “story” from a credit error or billing failure is like psychoanalyzing a smoke detector for its views on fire safety policy.
If the input is code or a system message, the appropriate output isn’t poetry—it’s clarity. If that doesn’t sit well with the marketing dreamer in you, then maybe the better question is: what was the original goal of parsing the message?
The Real Issue: Misaligned Expectations
The real mistake here isn’t technical—it's cognitive. When someone submits a “raw text” that turns out to be a bare-bones error from an API or automated tool, what's actually off is the requester’s assumption that a story or content asset was being shared. But that’s not failure—it’s insight.
It shows a disconnect in understanding what system messages are and what they’re for. And that disconnect is worth talking about—especially in business environments where decision-makers and technical staff need to communicate across very different mental toolkits.
What did you think was being submitted?
That’s the kind of tactical empathy Chris Voss would recommend. Mirror the misunderstanding. Reframe. Ask: what did the person expect would happen? What were they hoping to get out of it?
That’s where the dialogue starts. Not in the error text itself, but in the unmet expectation behind it. This is where marketers can learn to stop speaking past their developers, and developers can stop assuming the marketers know the pipes and flow of transactional systems.
Power of ‘No’—And Why It Matters Here
This is a perfect example of why 'No' has power. The system refused the transaction. That was your 'No.' It wasn’t up for negotiation. But it was an invitation. An opportunity to ask the right questions. Why was the balance insufficient? What does that message block further up the funnel? What is now in jeopardy because the call failed? And most importantly: what’s the cost of ignoring small system messages like this in your sales, ops, or marketing stack?
Structured Data vs. Narrative Data
Most technical content traffic exists in the structured domain — logs, responses, triggers. These are not storytelling elements. They're diagnosis tools. That’s not a weakness, that’s design. Trying to force narrative where it doesn’t exist just creates confusion. It’s like grafting petals onto a spark plug.
But marketers can use this moment to sharpen their sense of clarity. Don’t jam the wrong tool in the problem. When something technical presents itself with finality—acknowledge the boundary. That helps everyone move faster toward a useful solution and keeps copy teams from wasting hours trying to extract metaphor from metadata.
How Do You Turn This Into Value?
Simple: use it as a teaching moment. Engineers and marketers working together need common diagnostic literacy. That includes knowing the signals for “This message doesn’t want copywriting — it wants troubleshooting.”
If you’re writing internal communication or documenting system-side messages, don’t pretend they need to sound like branded content. Just explain their meaning, context, and resolution path clearly. That’s the only story anyone actually wants in a moment like this—what failed, why, and how to fix it.
Final Thought: Respect Signals for What They Are
Machine error messages are not placeholders for human meaning. They're boundaries. They say: “The rules of this system weren't met.” Respecting that is part of working with systems intelligently. And learning to do that without turning it into unnecessary fluff is a sign of professional maturity—especially in marketing, product, and business operations.
So, the next time your content team receives a block of JSON and wonders if it’s a forgotten blog draft, stop. Ask better questions. Mirror the assumption. Use the moment to reset and learn. Let ‘No’ become the seed for a wiser ‘Yes.’
#TechnicalLiteracy #MarketingTruths #ErrorMessagesExplained #APIResponses #ContentBoundaries #ChrisVossNegotiation #StructuredData #MarketingWithClarity
Featured Image courtesy of Unsplash and Ilya Semenov (6uFROinaC3g)