r/customerexperience

I'm curious to hear from people working in Customer Success and Customer Support.

Tools like Intercom, Zendesk, and similar platforms offer a lot of features, but depending on the team size and budget, they can sometimes feel unnecessarily expensive or complex.

I'd love to know:

• What platform does your team currently use?
• What's the biggest frustration with your current tool?
• Are there features you wish existed, or things you think these platforms overcomplicate?
• Have you considered switching to a more affordable alternative?

I'm working on a customer support platform called Asking (asking.com.br), and I'd rather learn from people dealing with these challenges every day than build features based on assumptions.

Honest feedback is very welcome!

Slightly weird problem. Our support dashboard has been getting greener for months while the conversations I'm reading don't feel noticeably better.

First response time is down because somebody replies quickly, even if the reply doesn't move the issue anywhere. Resolution looks good because the ticket gets closed, but customers sometimes come back a few days later with basically the same problem.

Now I'm questioning how much behaviour we're accidentally creating with the metrics themselves.

If you tell someone speed matters, they're going to optimize for speed. If you tell them closed tickets matter, eventually closing tickets becomes the job. None of that necessarily means the customer got what they needed.

For people running larger support teams, what numbers have you found hardest to game?

I'm trying to get us measuring whether the problem went away without turning the dashboard into 30 KPIs nobody pays attention to.

I’m trying to work out what makes someone update a bad review. Is it speed, an apology, a refund, the fix itself? If you’ve had one go from 1 to 4 or 5 stars, what did you do?

going back through traces, requests about connecting a second workspace were 0.8% of our onboarding assistant traffic six weeks ago. they're at 7.1% now and our hand built intent list doesn't even have a category for the flow. support spotted the pattern first. I started reading traces because the dashboard was still grouping these conversations into broader onboarding buckets.

what I noticed was where people stopped. 42% of the conversations end immediately after the permissions explanation and trace filtering surfaced phrasing I wouldn't have grouped together manually (several support tickets were describing the same conversation pattern in different words). now I can't tell whether the explanation itself is causing the drop off or whether people are learning something about permissions that changes their mind.

so I'm trying semantic clustering for intent discovery and tracking topic prevalence before we add another fixed category. cohort slicing by account type might tell us whether this is concentrated among particular setups and I want dataset promotion for representative traces once we know which cases belong together. still unclear where that boundary should be.

how are you deciding when an emerging pattern deserves its own tracked intent without locking the taxonomy around the first wording support happens to notice?

In a service/ utility industry what our the most common factors that drive calls and what have you implemented that helped reducing the calls !

We had a problem a lot of teams probably have: the same call could score 91% from one marker and 73% from another. Agents stopped trusting feedback and started asking "who marked it?" instead of "what can I improve?"

What fixed it was a monthly 60-minute calibration session:

1. Everyone scores the same call solo, blind, no chat

2. Reveal all scores side by side

3. Only discuss the questions where scores differ, lowest scorer explains first

4. Agree the score AND write down why in the scorecard guidance

We track two numbers each session: % of questions where every marker agreed (aim 80%+) and the gap between highest and lowest overall score (aim under 10 points).

Biggest surprise: most disagreements were about N/A. One marker was using it to avoid giving zeros.

Happy to share the session template if anyone wants it. How do other teams handle this?