Because in theory everything works.<\/p>\n\n
But in practice…<\/p>\n\n
What really happens<\/h2>\n\n
A customer enters your chatbot.<\/p>\n\n
Ask for a product.
Try to get a quote.
Wait for a clear answer.<\/p>\n\n
But:<\/p>\n\n
- \n
- the bot responds somewhat incoherently<\/li>\n\n\n\n
- does not understand the context<\/li>\n\n\n\n
- does not follow the expected flow<\/li>\n\n\n\n
- does not deliver what it should<\/li>\n\n\n\n
- or simply “lost” in the conversation<\/li>\n<\/ul>\n\n
And the worst:<\/p>\n\n
\ud83d\udc49 no one finds out.<\/strong><\/p>\n\n
No alert.
No warning.
No visibility.<\/p>\n\nJust a bad experience… that already happened.<\/p>\n\n
The problem of monitoring AI with traditional logic<\/h2>\n\n
Most monitoring systems work like this:<\/p>\n\n
- \n
- ask fixed questions<\/li>\n\n\n\n
- expect specific answers<\/li>\n\n\n\n
- validate whether or not it matches<\/li>\n<\/ul>\n\n
But modern chatbots (AI) don’t work like that.<\/p>\n\n
\ud83d\udc49 do not always respond in the same way
\ud83d\udc49 do not follow rigid scripts
\ud83d\udc49 may vary language, tone, structure<\/p>\n\nThen…<\/p>\n\n
traditional monitoring falls short.<\/p>\n\n
A different approach: conversational monitoring<\/h2>\n\n
This is where dVirtualUser, a dParadig software,<\/strong> comes in.<\/p>\n\n
Instead of validating exact answers…<\/p>\n\n
\ud83d\udc49 the entire experience<\/strong> is validated.<\/p>\n\n
With dVirtualUser<\/a><\/strong>:<\/p>\n\n
- \n
- define a natural language target
“I want to quote a truck”.<\/li>\n\n\n\n - the robot initiates a real conversation<\/li>\n\n\n\n
- asks questions<\/li>\n\n\n\n
- interprets answers<\/li>\n\n\n\n
- tries to move forward as a customer would<\/li>\n<\/ul>\n\n
And most importantly:<\/p>\n\n
\ud83d\udc49 evaluates whether or not the objective is achieved<\/strong>.<\/p>\n\n
It doesn’t matter if the chatbot responds differently each time.<\/p>\n\n
The important thing is:<\/p>\n\n
- \n
- did you offer the product?<\/li>\n\n\n\n
- did you allow to quote?<\/li>\n\n\n\n
- Did it derive correctly?<\/li>\n<\/ul>\n\n
![\"\"](\"https:\/\/24cevent.com\/wp-content\/uploads\/2026\/03\/1773953292779-1024x576.jpg\")
<\/figure>\n\nThe problem is not just detecting… it’s reacting…<\/h2>\n\n
So far, so good.<\/p>\n\n
But now comes the critical part.<\/p>\n\n
Suppose something goes wrong:<\/p>\n\n
- \n
- the bot does not offer the product<\/li>\n\n\n\n
- does not respond correctly<\/li>\n\n\n\n
- cuts off the flow<\/li>\n\n\n\n
- provides incorrect information<\/li>\n<\/ul>\n\n
dVirtualUser<\/a><\/strong> detects it.<\/p>\n\n
But now the key question is:<\/p>\n\n
what happens next?<\/strong><\/p>\n\n
If it only remains in a dashboard…
or in a report…<\/p>\n\nit’s too late.<\/p>\n\n
This is where 24Cevent comes in<\/h2>\n\n
This is where 24Cevent<\/a><\/strong> takes a key role.<\/p>\n\n
Because detecting a problem is of little use if no one acts in time.<\/p>\n\n
When dVirtualUser<\/a><\/strong> identifies that something is not working as it should:<\/p>\n\n
- \n
- an automatic alert is generated<\/li>\n\n\n\n
- the full context is included<\/li>\n\n\n\n
- evidence is attached (such as conversation or even video)<\/li>\n<\/ul>\n\n
And that’s where 24Cevent<\/a><\/strong> comes into action:<\/p>\n\n
- \n
- immediately notifies the correct team<\/li>\n\n\n\n
- use effective channels (not just emails that get lost)<\/li>\n\n\n\n
- ensures that someone takes charge<\/li>\n\n\n\n
- scales automatically if there is no response<\/li>\n<\/ul>\n\n
\ud83d\udc49 you go from “something went wrong”
\ud83d\udc49 to “someone is already seeing it.”<\/p>\n\nActual example<\/h2>\n\n
Imagine this:<\/p>\n\n
A user tries to quote a truck through your chatbot.<\/p>\n\n
The chatbot:<\/p>\n\n
- \n
- responds out of context<\/li>\n\n\n\n
- does not follow the expected flow<\/li>\n\n\n\n
- does not provide a clear choice<\/li>\n<\/ul>\n\n
With traditional monitoring:<\/p>\n\n
\ud83d\udc49 probably nothing happens<\/p>\n\n
With dVirtualUser<\/a> ( dParadig<\/a> software)<\/strong> + 24Cevent<\/a><\/strong>:<\/p>\n\n
- \n
- the robot detects that the flow failed<\/li>\n\n\n\n
- the entire conversation is recorded<\/li>\n\n\n\n
- visual evidence is generated<\/li>\n\n\n\n
- 24Cevent sends an immediate alert<\/strong><\/li>\n\n\n\n
- the team is notified<\/li>\n\n\n\n
- someone takes the case<\/li>\n<\/ul>\n\n
\ud83d\udc49 problem is no longer invisible<\/p>\n\n
The important (and not very obvious)<\/h2>\n\n
Today, many companies already have:<\/p>\n\n
- \n
- chatbots<\/li>\n\n\n\n
- IA<\/li>\n\n\n\n
- automation<\/li>\n<\/ul>\n\n
But few have:<\/p>\n\n
actual visibility of whether it is working well<\/strong><\/p>\n\n
And even less:<\/p>\n\n
\ud83d\udc49 Ability to react in time when something goes wrong.<\/p>\n\n
So what changes with this approach?<\/h2>\n\n
Raisins from:<\/p>\n\n
“we have chatbot”<\/p>\n\n
a:<\/p>\n\n
\ud83d\udc49 “we know if it’s working and we react when it’s not.”<\/p>\n\n
And that, in automated service channels, is the difference between scaling or losing customers.<\/p>\n\n
<\/h2>\n\n
AI is transforming the way businesses serve.<\/p>\n\n
But it also introduces a new challenge:<\/p>\n\n
\ud83d\udc49 monitor dynamic experiences, not fixed responses.<\/p>\n\n
And in that scenario:<\/p>\n\n
- \n
- dVirtualUser<\/a>, dParadig<\/a>‘s software<\/strong>, validates that the experience works<\/li>\n\n\n\n
- 24Cevent<\/a><\/strong> ensures that someone acts when they do not<\/li>\n<\/ul>\n\n
Because in the end, it is not enough to detect that something went wrong.<\/p>\n\n
\ud83d\udc49 the important thing is that someone solves it in time.<\/strong><\/p>\n\n
<\/p>\n\n
If you are already using chatbots as a support channel, this type of monitoring is no longer optional.<\/p>\n\n
dVirtualUser<\/a>, a software from dParadig<\/a>, together with 24Cevent<\/a>, allows not only to detect faults in real conversations, but also to trigger an immediate response with full context, ensuring that no problem goes unnoticed.<\/strong><\/p>\n","protected":false},"excerpt":{"rendered":"
Today many companies already have chatbots.
\nThey serve customers, quote, answer questions, even sell. But there is an uncomfortable question that is rarely asked: How do you know that your chatbot is really working well all the time? <\/p>\n","protected":false},"author":2,"featured_media":4854,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":""},"categories":[167],"tags":[169,170,168,171,173,172],"class_list":["post-4921","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-management-software-and-other-tools","tag-chatbot","tag-chatbot-failing","tag-chatbot-monitoring","tag-chatbot-with-problems","tag-monitor-chatbot","tag-my-chatbot-does-not-work"],"_links":{"self":[{"href":"https:\/\/24cevent.com\/en\/wp-json\/wp\/v2\/posts\/4921","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/24cevent.com\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/24cevent.com\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/24cevent.com\/en\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/24cevent.com\/en\/wp-json\/wp\/v2\/comments?post=4921"}],"version-history":[{"count":2,"href":"https:\/\/24cevent.com\/en\/wp-json\/wp\/v2\/posts\/4921\/revisions"}],"predecessor-version":[{"id":4926,"href":"https:\/\/24cevent.com\/en\/wp-json\/wp\/v2\/posts\/4921\/revisions\/4926"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/24cevent.com\/en\/wp-json\/wp\/v2\/media\/4854"}],"wp:attachment":[{"href":"https:\/\/24cevent.com\/en\/wp-json\/wp\/v2\/media?parent=4921"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/24cevent.com\/en\/wp-json\/wp\/v2\/categories?post=4921"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/24cevent.com\/en\/wp-json\/wp\/v2\/tags?post=4921"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}} - 24Cevent<\/a><\/strong> ensures that someone acts when they do not<\/li>\n<\/ul>\n\n
- dVirtualUser<\/a>, dParadig<\/a>‘s software<\/strong>, validates that the experience works<\/li>\n\n\n\n
- define a natural language target