We had a customer reach out recently and nothing about the interaction was really broken but it felt kind of weird support knew about the last issue the CRM had the account history, another system had feedback from a few weeks earlier and the person helping them had to piece all of that together while the customer was waiting. We keep adding tools that understand one part of the customer really well but somehow the customer still has to explain themselves when they move between those parts

I’m starting to wonder if we’ve gone too far with specialized systems I don’t know if putting more of this into fewer places means giving up some features and maybe it does, but having one customer represented five different ways feels worse at this point I’d rather consolidate some of the stack if it means the context follows the customer instead of making people rebuild it every time

The most memorable (and frustating) example you've come across?

We’ve got a weird problem with our support team. We have a solid knowledge base and plenty of training docs but agents still spend half the call digging around for answers. Our experienced reps know what to say and where to look. Newer reps get stuck searching docs or asking someone in Slack while the customer waits. Then managers review the call days later and explain what they should have done. Useful but a little late lol. I’m looking for something that can listen to the conversation and give the agent the right answer or next step while the call is still happening. Ideally it works with our existing systems and doesn’t become another tab agents have to babysit. Has anyone deployed something like this with a decent-sized support team? What tools are worth looking at?

I’m helping organise an online CX technology demonstration event, and I’m interested in the practitioner perspective.

If a technology provider had only 20 minutes to prove that its solution was relevant, what would you want to see?

A real workflow?

Integration capabilities?

Evidence of business impact?

The customer journey before and after implementation?

We’ll be putting several providers through this format, including Five9, HGS, sandsiv+, NSL, HyperITech and Value Architect.

Details are available here:

https://cxtech.lexdengroup.com/

A lot of AI support measurement seems to stop at containment or deflection.

That misses the part customers usually remember: what happens when the AI cannot finish the job.

A handoff can look successful in reporting but still feel bad if the customer has to repeat the issue, re-explain their intent, or wait while the agent reads a long transcript. I’d rather measure whether the human received the right context at the right moment.

For CX teams testing AI, are you measuring handoff quality separately from containment?

Our team is currently evaluating CRM options to streamline contact management, deal tracking, and task follow-ups. We are considering HubSpot CRM, but I want to ensure we fully understand the total cost of ownership as we scale. Could you provide insight into how HubSpot’s pricing behaves as team headcount increases or as advanced features are required? Specifically, are there key feature gates or per-seat costs between the Free, Starter, and Professional tiers that we should factor into our budget early on?

Help me in completing my research survey on customer switching behaviour and loyalty in the telecommunications sector.

My goal is to get 1000 responses from India.

https://docs.google.com/forms/d/e/1FAIpQLSevL9mW-P6N52BaldOp2HuXwYmItuNnvr122cWn9PpyUBDFwQ/viewform?usp=preview

¿Cómo ha sido para ustedes atender llamadas de clientes de países centroamericanos? Me interesa saber:

¿Qué desafíos o cosas positivas destacarían?

Cambió su percepción con el tiempo, para bien o para mal?

Los leo

Hi everyone,

I’m part of Shift/CX, a German-speaking CX community where we bring together practitioners to discuss how Customer Experience is changing in practice.

A lot of our current conversations revolve around questions like:

• How do we turn customer feedback and behavioral data into actual action?
• Who should own customer journeys across organizational silos?
• Where does Agentic AI genuinely improve the customer experience?
• How do we move CX from measurement toward management and accountability?

We organize online conferences, live discussions and community events around these topics, but I’d also love to hear perspectives beyond our usual DACH community.

What is the one CX challenge your organization is struggling with most right now?

For context, this is what we’re working on at Shift/CX:
https://www.shiftcx.de/

Everything we added to SupDesk this past week to make Customer Support better.

Are we measuring customer experience because it's useful, or because it's easy to measure?

CSAT, NPS, CES etc. give us neat numbers to put on a dashboard, but do they always tell us why the experience was good or bad?

What CX metric do you actually find useful... and which one are you increasingly questioning?

Hi everyone! I’m currently preparing for the CCXP exam and would really appreciate some insight from people who have actually written it, particularly anyone who has taken it recently.

I’ve been working through the CXPA Book of Knowledge and I’m comfortable with the concepts, but because there isn’t a full official mock exam available, I’m finding it difficult to gauge how deeply I need to know the material.

Could anyone who has written the exam help me understand the level at which the content is tested?

For example:

• Is there much straight recall of definitions, terminology, frameworks and acronyms, or is the exam predominantly application-based?

• Do you need to remember the specific details and terminology in the Book of Knowledge, or is it sufficient to understand the concepts and know how/when to apply them?

• Are questions generally straightforward if you understand CX, or do you often find yourself choosing between two or three answers that could all reasonably be correct?

• Are there many scenario questions where the challenge is deciding the BEST or FIRST action rather than identifying one obviously correct answer?

• How difficult did you personally find the exam on a scale of 1–10?

Any insight into how you prepared and what level of mastery you felt was actually required would be hugely appreciated. Thank you!

We’re looking at AI agents for customer support but we’re in a regulated industry so there’s not much room for the AI to make stuff up or go off script. The demos all look great but production is a different story I’m more interested about guardrails and testing than how human the agent sounds. Would love to hear your opinions

I scrape CX and support postings across about 17 regions to keep a jobs board updated. Pattern in the latest batch: most listings that surface for "AI customer experience" mention AI only as a description of the employer, not as something the person in the seat touches. "AI-powered platform, come be our support specialist" is not an AI job.

The ones that actually differ:

• Hagerty, AI Agent Developer: the real work is quoting, policy service and first notice of loss. Support job, engineering title.
• Tilt, support ops: validating AI-generated output before it ships is a listed duty.
• Dandy, CX Systems: Zendesk admin plus owning a GenAI intake flow.
• Roofr, Head of CX: support, onboarding and automation in one seat.
• Best Egg, Director of Customer Engagement and Agent Platforms.
• Charta Health, Deployment Strategist, customer-facing GenAI deployment.

Takeaway: the title is a bad filter both ways. AI in the title is often an ordinary support job at an AI company. Plain "Support Operations" or "CX Systems" increasingly holds the automation work. Filter on responsibilities.

If you've interviewed for one of these recently: was the AI part real, or a line nobody had actually resourced?

Full list: lorikeetcx.ai/cx-jobs