Streamlining SNCB's Social Media Chatbot
Customer Success Story:
About SNCB
SNCB is a national railway company of Belgium. As a company, it manages large quantities of customer queries daily regarding its services. Its chatbot, Mobi, greets customers on Facebook Messenger and WhatsApp, helping to answer questions about the services currently running and possible disruptions to their journey.
The team use a chatbot to answer the increasing volume of queries coming through social media. Answering questions in English, Dutch and French, Mobi was launched to reduce the workload of the social media care team. The chatbot currently covers around 160 intents and gives around 500 answers per language. Mobi handles around 20,000 queries a month and enables customers to access support 24/7 rather than during the working day of a support agent.
What drove their need for change?
Increased volume of queries post pandemic
Need to understand the effectiveness of fixes
Lack of users with an IT background
Difficulty identifying the origin of the training phrases causing conflicts.
Prior to Cyara Botium, the team were using a simple tool made by their own developers. With the limited usefulness it offered, there was a real need to delve more into the detail and establish whether their fixes were having the intended effect or causing more regressions.
The Challenge
Advice to other organizations on whether to make the move to Botium?
If you’re serious about your chatbot and investing in improving it, then yes.
Tim Lambrechts, Chatbot Specialist at SNCB spoke to us about their streamlining with Botium. This is what he had to say:
"The Work we can do in an hour with [Botium] probably took us a full working day before."
SNCB's Thoughts on Cyara
"[Botium] is like a satnav, but for NLP improvements. You could do without it, but you’re using outdated maps – and navigating the ever-growing jungle of conflicts between intents and training phrases is difficult and very time-consuming."
Staying Up-to-Date:
"Using [Botium], we’ve easily increased our correctness percentage by around 20% in just a couple of months."
Increased Accuracy:
"Because [Botium] points out which intents need work, and, more specifically, which training phrases are causing conflicts, we immediately know where to start working. This saves us a lot of time, which we can use to expand our chatbot’s knowledge or improve the existing intents even further."
Quicker Resolutions:
"These improvements [have] significantly lowered our fallback rate, so more customers now get a correct response. By adding more intents, testing their performance, keeping an eye on the performance of existing intents, and slightly lowering our confidence threshold (which we could analyze through [Botium]), the fallback rate [has gone] from 20-25% to 10-15%."
Improved Fall Back Rate:
"[Botium] is an especially helpful tool for the SNCB team as most of the colleagues working with it don’t have a background working in IT. For our newest colleague, only some basic NLP model explanation was necessary before she could get to work with [Botium], as the tool explained the rest."
Easy-to-Use No Code UI:
- Jeffrey De Meulemeester Digital Assistants Manager, SNCB
QBox [now Cyara Botium] helps us greatly in improving the quality of our NLP model, resulting in a better chatbot and a higher success rate for our bot. And a better bot leads to better KPIs and happier customers.
"Because [Botium] points out which intents need work, and, more specifically, which training phrases are causing conflicts, we immediately know where to start working. This saves us a lot of time, which we can use to expand our chatbot’s knowledge or improve the existing intents even further."
Quicker Resolutions:
Learn More about Botium
Learn More about Botium