Why adding chatbots makes financial sense
Adding a chatbot to your organisation’s website can provide a more interactive experience for your users while at the same time reducing demands on your staff’s time. Chatbots can help to:
- free your team to deal with more complex enquiries or tasks
- speed up employee training by providing a very accessible and intuitive source for staff to obtain information internally
- automate complex workflows (such as providing quotes or booking services)
- provide availability 24/7, 365 days a year
- provide an alternative user interface for your apps than the traditional point and click menu/button system
Further to my previous post about this, we have managed to get this working successfully now with a variety of guest users (with email addresses which are outlook.com, or associated with Azure Active Directory or Azure ADB2C accounts).
Why is this so useful? Because it means that in order to collaborate with users outside your organisation (including being able to share files, hold online conversations, video chats, do online voting within your team), all you need is one of the following Office 365 subscriptions (see this Microsoft link)
Guest access is included with all Office 365 Business Premium, Office 365 Enterprise, and Office 365 Education subscriptions. No additional Office 365 license is necessary. Guest access is a tenant-level setting in Microsoft Teams and is turned off by default.
This should not only be much cheaper than alternative collaboration software (e.g. box.com) but also allows your staff and guest users to use tools that they will increasingly become familiar with (Office 365).
As a “proper” programmer, used to programming in heavy duty, compiled languages like C# (and before that C++ and C), my reaction on discovering during my Data Science journey that R and Python are heavily used by data scientists was: why??
Why would anyone use an interpreted language, which is therefore bound to be slower, and why would anyone go to the trouble of using yet another language when there are perfectly good compiled languages around like C#, F# and VB.net?
The answer seems to be partly that R and Python are free (open source), and also because R and Python have excellent visualisation tools, which the other languages currently lack.
In particular, in classification problems, it is very easy in R or Python to produce conditioned or faceted charts, e.g. histograms of features (which is what independent variables are often called in Data Science) conditioned on the values of a categorical label (the name often used for the dependent variable, or the variable which we are trying to predict). This conditioning, together with using aesthetics (e.g. the use of colour or shapes) to project additional dimensions on to what is of necessity usually a two dimensional chart, really helps when exploring the data to try and find features which are likely to help predict the label.
It seems that Microsoft have recently amended Microsoft Teams (their collaboration tool within Office 365) so that “guest users”, that is to say users who are not part of your organisation’s Office 365 subscription, can be added to Teams. If so, that is a very welcome development, because:
- Microsoft Teams is a great collaboration tool
- it means that external users (e.g. clients, suppliers, or simply people from other organisations) who want to can share information or work together on a project with your internal team.
I mentioned a couple of days ago (here) that I had completed the 10 courses required for the Microsoft Professional Program for Data Science. I was delighted to receive confirmation earlier today from Microsoft via a nice certificate (see pic above), or you can view it here.