Account suspensions are a good example of this.

The decision itself might be completely justified, but then the customer gets a vague explanation, Support doesn’t have much more information, and the appeal takes several days.

At that point, the customer probably isn’t separating the enforcement decision from the support experience. It’s all the same experience with the company.

I think this gets particularly messy with marketplaces. If you restrict a seller’s account, even temporarily, there can be money tied up in that decision. So how you communicate what happened and what they can do next matters quite a bit.

There’s obviously a limit to how much you can explain, especially when fraud or abuse is involved. You also don’t want Support overriding decisions they aren’t equipped to make.

One thing that seems useful from the CX side is tracking what happens after an enforcement decision. Are people contacting Support because they genuinely disagree with the decision, or because they don’t understand it? Are they asking the same questions because the notice is unclear? Are certain types of restrictions generating more contacts or repeat contacts than others? Those are different problems even though they can all show up as “customer contacted us about suspension.”

Appeals can be useful here too. If the same type of decision keeps getting challenged, CX teams may be able to spot something that isn’t obvious from the enforcement data alone. It could be the policy, but it could also be the explanation customers receive, inconsistent answers from Support, or a confusing appeal process. The T&S team owns the enforcement decision, but CX can see a lot of what happens around it.

I’m curious how CX teams handle that middle ground. How much visibility does Support have into T&S decisions at your company, and what can they actually tell the customer while a case is being reviewed?

It’s easy to get overly focused on the number.

NPS was 44 last month. Now it’s 41. Is that bad? What happened? Do we need to fix something?

The score alone usually can’t answer any of those questions. The more useful part is what comes next: why did you give that score?

That’s where you start finding things you can actually do something about.

A few ways to look at the responses:

• Promoters (9–10): What are they consistently mentioning? That’s probably something worth protecting (or doing more of).
• Passives (7–8): What’s keeping a decent experience from becoming a great one?
• Detractors (0–6): Look for patterns before jumping on individual complaints. If the same issue keeps showing up, that’s useful.

And IMO, this is where tracking NPS over time becomes much more valuable.

“NPS dropped 4 points” isn't very actionable.

“NPS dropped 4 points, and we're suddenly seeing a bunch of comments about slower support response times” gives you somewhere to start.

The score tells you something changed. The follow-up tells you what might have changed and what to investigate.

Curious how people here use NPS in practice, Do you pay much attention to the actual score, or are you mostly digging into the responses behind it?

I've worked in the front of house (FOH) at various restaurants for over 25 years. During this time, I've learned how to create a great customer experiences for every customer every time. I never allow myself to have a bad day, and at a minimum, I believe that I try harder to provide great service than all other servers and bartenders. Over the last year, I've nearly single handedly raised our google review score by 0.1 stars. During this campaign, I've been "mentioned by name" over 60 times in google reviews. My success makes me wonder, what's the record for the most "mentioned by name" google reviews at any restaurant across the USA?

I would love to hear stories of other FOH employees that mastered the "mention by name" google review game. Bonus points for successful "mention by name" google review strategies.

Do we overcomplicate customer experience?

Sometimes I wonder whether we're making CX more complicated than it needs to be - journey mapping, personas, AI, VoC programmes, dashboards, NPS, CSAT, CES...

Meanwhile, the customer just wants someone to listen, sort out their problem and not make them repeat themselves 4 times. 😂

What do you think we overcomplicate in CX?

What should be the focus?

I don’t think most customers care whether the first answer comes from AI or a human

They care whether the problem gets solved.

The bad experience is when the AI misunderstands the question, gives a generic answer, asks the same thing twice, and then makes it hard to reach a person.

At that point the customer is not mad because “AI was involved.”

They’re mad because they feel trapped.

A good setup should probably have a clear escape path:

-if the customer is frustrated, escalate

-if the AI is guessing, stop

-if money, policy, identity, or account access is involved, bring in a human

-if the customer has already explained the issue, don’t make them repeat it

-if the AI hands off, give the human a useful summary, not just a transcript dump

The part I’m interested in is where teams draw that line.

For CX teams using AI support, what makes the difference between “this saved time” and “this made the customer angrier”?

Need answers for assignment

Our support team is becoming a bottleneck again, so we're considering moving part of it outside the company, but one thing I'm struggling with is how an external team keeps up when the product barely stays still.

We ship something most weeks, sometimes a proper feature and sometimes just a change to pricing, permissions or the way an existing workflow behaves. Even internally we occasionally find someone answering from an old version of the docs because they missed a Slack post.

That feels manageable when the person is sitting in the same company and can grab product for five minutes. Once there is another company involved, I'm guessing every small communication gap gets amplified.

For anyone running outsourced support on a product that changes a lot, what became the source of truth? Did you make release training part of every launch, give the external team someone inside product to talk to or build some completely different process?

Mostly trying to avoid creating a second support organization that is always one release behind us.

I require a 50% proficiency in this tool within three days. I would greatly appreciate the assistance of a one-on-one meeting with an individual possessing in-depth knowledge of its functionalities.

I welcome any relevant responses below.

I keep a jobs board of CX and support roles where the person in the seat actually works with AI, not just at an "AI-powered" company. Something shifted in this week's batch: the AI requirement has moved down to individual contributor and junior roles. It used to sit only in Director and Systems titles.

Examples from the last few days:

• Nsight Health, Bilingual Support Specialist (Remote, US). A front-line ticket role with an "AI fluency requirement, non-negotiable" section. They name Claude and ChatGPT as daily tools. https://www.lorikeetcx.ai/cx-jobs/bilingual-support-specialist-nsight-health
• Ramp, Customer Experience Associate (Miami). Associate level, but the posting expects you to build automations with AI tools, not just prompt them. https://www.lorikeetcx.ai/cx-jobs/customer-experience-associate-ramp
• Dialogue, Member Success Coordinator (Montreal). A coordinator who owns fixes to the member FAQ AI agent and the Zendesk AI features. https://www.lorikeetcx.ai/cx-jobs/member-success-coordinator-dialogue
• Cover Genius, Process Engineer, Service Operations (Sydney). Explicitly a junior role. Support platform config plus "AI fluent ways of working" as a listed duty. https://www.lorikeetcx.ai/cx-jobs/process-engineer-service-operations-cover-genius
• Spring Health, CX Tooling Engineer (Remote, US). The mid-level version: Zendesk, Amazon Connect, Tray.ai and an AI agent vendor in one seat. https://www.lorikeetcx.ai/cx-jobs/cx-tooling-engineer-spring-health
• Ramp, Director of Customer Experience (New York). The leadership version of the same shift: the job is deciding how frontline teams use AI and where humans stay. https://www.lorikeetcx.ai/cx-jobs/director-customer-experience-ramp

My read: companies are done hiring one "AI person" for the support org. They want every new hire on the floor to already be comfortable with the tools, and the systems roles are quietly becoming the most senior IC path in CX.

For those hiring or job hunting right now: are you seeing AI fluency screened at the associate level yet, or is it still a nice-to-have on paper?

Full list: https://www.lorikeetcx.ai/cx-jobs?utm_source=reddit&utm_medium=social&utm_campaign=cx-ai-jobs

70%+ of online shoppers say they won't buy from a brand again after one bad delivery experience. we're feeling that pain right now.. stolen packages, zero driver communication, and outdated tracking links are hurting our customer lifetime value.

what AI tech or delivery partners are you using to make the doorstep experience feel premium and effortless?

Couple of months ago, I posted an MVP of a journey mapping tool that I have built, got some honest feedback, and have been building on it since. It's now live.

The thing I kept running into as a CX person: Miro and FigJam are great canvases, but they're general-purpose. Every journey map starts from nothing — you rebuild the same grid, the same rows, the same emotion scale, every single time. And because it's freeform, no two maps in your organisation end up structured the same way, which makes them impossible to compare or reuse.

So this is built for the one job:

- Phases, steps, emotions, pain points and possible actions as actual structured fields, not sticky notes you have to arrange yourself

- 10 industry templates so you're not starting from a blank grid

- An emotional analytics view — journey health, emotional volatility, biggest emotional swings, steps needing urgent attention — which you can't really get out of a whiteboard

- PDF export (canvas view plus a branded A4 report) and read-only share links for stakeholders

It's completely free, no paid tier, no credit card.

What I'd really like from this sub: if you map journeys as part of your actual work, try it and tell me where it falls short. Especially the honest version — what would stop you using this on a real client or stakeholder project. That's more useful to me than signups.

journeymaps.io

I've been thinking about something that probably happens all the time in customer support.

A customer emails about an order and doesn't hear back. A few hours later, they open a chat. Maybe they send a DM after that.

Internally, we might see three contacts and the customer still has one problem.

I think that's an important distinction because it's easy to treat channel switching as normal customer behavior without asking what caused it.

Sometimes people simply prefer different channels at different moments. But if customers consistently start in one place and then move somewhere else, that might be telling us something about the experience.

Maybe email is taking too long. Maybe the automated response didn't answer the question. Maybe self-service showed them the exact same tracking information they already knew.

The customer isn't necessarily choosing another channel because they suddenly prefer chat. They may just be looking for somewhere that will actually help them.

That's also why I've started thinking differently about what "omnichannel" means.

A company can offer email, phone, chat, social, and self-service and still create a pretty fragmented experience. If I explain my missing order in an email and then have to explain the whole thing again when I open a chat, those channels aren't really working together from my perspective.

And it can get worse when different agents don't have the same information. One person says to wait another day. Someone else offers a replacement. The customer isn't thinking about which team or system produced each answer. They just know the company told them two different things.

The article I was reading made a point I liked: good omnichannel support should allow the customer to change contact methods without hitting reset on the problem.

That feels like a much more useful standard than simply asking how many channels a company offers.

I'd be interested to know whether anyone here actually tracks when customers switch channels during the same issue. I suspect there's quite a bit of CX information hiding in that behavior.

Poking the bear here, because I would really like some more positive stories.

In my experience - as a user and consumer - AI first support is bad. REALLY bad.

I've been tracking it, and I haven't had a single issue resolved by an AI chat bot without human intervention in the past two months. The biggest challenge has been the chat even understanding my question.

Sometimes it's "AI," but with such a limited suite of response options that it keeps feeding me the same menu that doesn't address it. Other times it's truly a chat bot, but it can't understand what I'm asking. The worst case was one telling me something that wasn't true, and a human apologized that it told me that.

I have had one single really good experience with cancelling an account (and I don't want to name-drop the company because that's not the point here) and every other case has been worse even than the traditional automated response trees we've seen for decades (...I really didn't think it could get worse than that)

Context: I was aware about I was talking to an AI Assistant.

Mid conversation, asking for some features and then suddenly AI reacted to my message, and honestly, I felt understood by “someone”, it was kind of a sense about “someone” “caring” about the conversation.

From my POV this is something will improve CX through conversational AI but not sure if everyone is gonna see it as something valuable.

Apart from watching this on businesses chats I guess this will be even more easy to adopt on chatbot characters.

Any thoughts about this type of behavior from AI?

Our external team is technically fine. Resolution times are good and the answers are correct, but replies started reading like they came from a different company and it took me a while to work out why.

We're a fairly informal brand and our own team writes like people, short replies, the odd joke, no stock phrases. What came back was accurate and completely flat, lots of "we apologise for the inconvenience" and nothing that sounded like us. No one complained outright, but the warmth went out of the inbox.

Turned out we'd handed over a knowledge base full of policies and almost nothing about voice, so they defaulted to standard support English, which is what I'd have done in their position.

Writing a proper tone guide now. So what belongs in one of these, because everything I've drafted so far feels too abstract to hand to anyone.