The most embarrassing email mistake (and how to survive it)
you sent the wrong campaign to the wrong person. your customers saw it. let's fix this.
Hey team,
Happy Thursday. If you’re on the East Coast and want to strangle that groundhog, get in line.
We just finished digging out from the last snowstorm, and I was not exactly thrilled to pick up the damn shovel again.
It reminded me of a different kind of digging I’ve done more times than I’d like to admit. 🙃
The kind where you open your inbox and realize a campaign landed somewhere it absolutely should not have.
At some point in your retention career, you are going to send the wrong email to the wrong person. Not necessarily because you’re careless, but because your data has blind spots, your lists are never perfectly clean, and your customers are living lives your segments will never fully capture.
Like the win-back email that hits someone who just rage-canceled.
The re-engagement campaign that reaches a customer disputing a charge.
The promo that lands two days after someone paid full price.
You cannot eliminate those moments entirely.
What you can control is what happens next.
Today I want to talk about two things: how to reduce the odds before you hit send, and how to recover the relationship when you inevitably get it wrong.
Let’s jump in.
This week’s newsie is brought to you by KODIF AI.
As your brand scales, customer conversations explode across support, pre-purchase, and every corner of your site. The question becomes: do you build a larger team, or a smarter one?
The AI CX market is crowded, but here are a few reasons KODIF stands apart from what I’ve seen:
1️⃣ Built for complexity — not just basic FAQ.
From what I’ve seen other AI agents break when SOPs get multi-system and conditional. KODIF asks you to give them your most complex SOP, and automate that.
For example, I saw how KODIF chat agent handled Aura Frames complex troubleshooting product issues end-to-end — walking a customer through diagnostic steps and, if needed, triggering a replacement part order inside the same flow. I was impressed.
2️⃣ An AI CX team > one AI Agent
They build AI CX Team, purpose - specialized agents that mirror CX roles: an AI Support Agent for resolution, AI Concierge for pre-purchase and conversion, AI Analyst for insights, and AI Manager for continuous improvement. It’s a team model, not a catch-all model.
3️⃣ Deep ecommerce integrations (not surface-level)
They’ve built 178+ ecommerce integrations and shipped 88 new ones in 2025 alone.
You all know that matters because automation only works when the system can actually take action, not just answer questions.
Some recent cool reviews on the success stories:
“The customizability of KODIF is what excites me most. I’m in there every day. Containment is great and all, but quality matters just as much or more. Our automation rate is above 70% but more importantly we are leveraging KODIF for retention.”
— Jack Dukesherer, Sr. Manager, Member Engagement Ops
“The Chat AI Agent can walk someone through calibrating their grinder — it’s super resourceful with the right inputs. Furthermore, address changes and cancellations? Completely automated. I haven’t thought about a cancellation in ages.”
— Cindy Rodriguez, Director of CX
“We started with deflection as the goal, but it turned into more — now the AI helps customers discover products, understand ingredients, and convert. That’s real ROI.”
Cristina Fucchi, Chief Customer Officer
Something that stood to me is their founders’ strong engineering background. Their CTO, Norm previously built Uber’s customer support automation platform, automating 150 million customer requests per month.
KODIF is trusted by top ecommerce brands such as True Classic, Ruggable, Dollar Shave Club, Liquid I.V., One Skin, Aura Frames, Fellow, Neuro, Who Gives a Crap, Million Dollar Baby, Ivy City, Helix Sleep and many others.
Many teams review their CX stack in Q1, and if your support workflows are complex, it might be worth a conversation with Chyngyz and the KODIF team to see if it’s a fit. They promise to go live in 3-5 days.
Also, they are offering my readers 3-months for free… Just hit up their team and drop my name, Eli Weiss.
This offer is valid only through March 31, 2026.
Part one: How to recover when it happens
I recently spoke to a pet brand that ran a pretty standard re-engagement campaign a few months ago. Lapsed customers plus some new prospects from a third-party list, which is the kind of thing retention teams run every quarter without lighting candles and reflecting on the meaning of life.
The problem was simple and brutal. The list had no idea whose dogs had passed away.
The emails went out, and within hours, their inbox popped off in the worst way. Some people were confused, some irritated, and a few were grieving. It was the kind of Monday where you open Slack, see the subject lines stacking up, and immediately understand how the rest of your day is going to go.
The part that made this story worth repeating came after that. The brand happened to be using KODIF when the fallout began, and the responses were handled in a way that felt steady.
When someone wrote in saying their pet had passed, the reply acknowledged it directly and apologized without turning it into corporate theater. When someone was simply annoyed, they apologized and handled the opt-out cleanly without dragging the exchange out longer than necessary. It did not try to impress anyone. It just responded appropriately.
Their CX lead told me, “For the ones where the pet had passed, it was showing empathy. For the ones who just didn’t like it, it was saying sorry and passing along the feedback.”
Most teams would have fumbled that recovery, not because they are careless, but because their CX layer is usually optimized for speed. Close the ticket, hit the SLA, keep the queue moving.
That works when someone wants to know where their order is. It does not work when someone replies to your campaign with something personal that your segmentation logic could never have predicted.
Recovery is not complicated, but it does require discipline. You acknowledge what happened in plain language and you own it without turning the apology into a memo. You make the next step obvious. If someone wants to opt out, it should take seconds. If they need help, they should not have to explain their situation twice.
The reason this becomes difficult is scale. Doing this well requires context, and most teams do not have the capacity to craft nuanced replies consistently when a campaign misfires and hundreds of messages arrive at once.
Savings and deflection are useful metrics. They just are not the full story. The moments that matter most are the ones where the customer is reacting to something your brand did.
If a campaign goes sideways late at night and someone replies with something your team did not anticipate, that exchange often determines whether the relationship stabilizes or erodes.
Part two: How to limit the damage before it happens
You cannot fully prevent this, and anyone promising zero mistakes is selling fantasy. There is, however, a clear difference between brands that misfire once in a while and brands that seem to repeat the same avoidable mistake every quarter. That difference usually comes down to process.
Most of the time this is not a tooling issue. It is a coordination issue. Marketing pulls a list and hits send. CX finds out when the replies start landing. Now support is managing the emotional and reputational fallout for a campaign they did not know was going out.
That is less of a tech stack problem and more of a meeting problem.
The brands that handle this better usually build in one small pause before the send. Someone pressure-tests the list. Why are these people here? What do we actually know about them beyond purchase history? Where are the blind spots? If this lands badly, what is the most predictable reason it would?
That five-minute exercise catches more risk than another subject line brainstorm ever will.
Pre-send reviews tend to focus on creative and copy. Very few focus on the edges of the audience. The edges are where this goes wrong. Adding one deliberate “what are we missing?” check into your workflow costs almost nothing and prevents more damage than most teams expect.
Suppression logic is the other piece, and most brands build it reactively. You suppress recent purchasers because someone complains loudly enough. You suppress customers with open disputes because one campaign burned you. Over time the rules pile up, nobody maps them end to end, and the gaps sit there quietly until you trip over them again.
Once a year, it is worth auditing that logic intentionally. Are there customers in a transactional or financial situation where outreach right now is more likely to frustrate than help? You are not going to eliminate mistakes entirely, but you can meaningfully reduce the ones you cause yourself.
Third-party lists require a more honest internal conversation than most teams are willing to have. Your owned data is imperfect. Rented data is usually worse. When you email a list you did not build yourself, you are choosing higher variance on outcomes. That can be a rational tradeoff, but it should be explicit.
On paper, the campaign looked routine and the spreadsheet looked clean enough. What nobody paused to consider was what the file did not capture. That omission is usually where these situations begin, which is why it is worth naming the risk before you hit send
That’s it for this week!
Any topics you’d like to see me cover in the future?
Just shoot me a DM or an email!
Cheers,
Eli 💛
P.S. If you want to figure out how to get your brand to rank high in LLMs and show up in ChatGPT, Gemini, and more… check this out.
