[Spoiler warning!] Yes, it is

Nowadays most of the chatbots are B2C oriented. B2C Chatbots acts as text user interface for activities like customer support issues communication or native human communication powered by Artificial Intelligence machine learning model.

But chatbots are not limited only to consumer use; they also can be applied to business use cases.

At this article, I’ll provide a brief introduction to B2B chatbots: use cases, type of chatbots, chatbot frameworks, public connectors to databases and technologies, which can produce you some useful results based on your database or NLP methodic.

OK, so what is chatbot? The chatbot is a natural language interface to software application powered with Natural Language Understanding, Conversation Algorithm or Database information. Most B2C chatbots are using conversation algorithm, that can be easily built by using graphic chatbot builder services. Feel free to ask Google about “chatbot builder services” and you get lots of companies, which offers a user-friendly graphic interface for building basic chatbots.

Top Articles on How Businesses are using Bots:

It’s not necessary for all bots to be NLP-capable, it is fully depending on the purpose of the chatbot. Like B2B chatbots are using database connectors and Natural Language to SQL transformation. NLP capabilities are useful only if you have a complex scenario, that requires a lot of conversation with the user. The basic purpose of B2B chatbot is help for user to save time for SQL scripting, work in excel or modifying system dashboards, so NLP capabilities are not playing important role in the B2B use case.

Most of the enterprise chatbots for company employees are task-oriented and require simple dialog conversation like:

user request → clarifying question → reply for the user request

Example of basic HR chatbot communication with employees:

- [USER] What is my monthly target KPIs?

- [SAP CHATBOT] Do you want to get current month KPIs?

- [USER] Yes

- [SAP CHATBOT] Your current monthly KPIs:

EBITDA target 0.26 Mio USD;

YourProduct penetration 35%.

Do you want to get your actual results?

- [USER] Yes

- [SAP CHATBOT] Your current monthly

EBITDA is 0.3 Mio USD and

YourProduct penetration is 28%.

Do you want to get a waterfall chart?

- [USER] No

- [USER] What is my last month KPIs execution?

- [SAP CHATBOT] Your last month KPIs execution is 110% for EBITDA

and 95% for Penetration

- [USER] Show me the waterfall graph of last month EBITDA my actual results?

- [SAP CHATBOT] Here you go:

Waterfall graph created by NLSQL software

Abovementioned example of the Chatbot, that is responsible for HR communication with the employee. Of course, you can try to ask it a question about the Donald Trump salary, obviously chatbot will be confused in case Donald Trump is not your employee 😊

Another use case example of using B2B chatbot for getting the information from the company IT ecosystem:

Demo example of B2B chatbot use case

There 3 principal methods for developing chatbots:

1. Using SDK with development framework. This method has its own limitations caused by existing tools

2. From scratch using only programming language. That is the most flexible way to build bots because you can develop your own features, that nobody has without any limitation. This option is good only for experienced bot developers, who can develop programming scripts from scratch. The most popular programing language for building the chatbots are Python and Java with good opensource support

3. Mixed method. The most reasonable method because you can code your own chatbot with unique features, integrations and secured API interfaces from existing SDKs. User requests forwards through messaging API to your chatbot application.

Modern chatbot bot frameworks allow developers to integrate chatbots with multiple integrations to different messenger platforms such as Skype for Business, Slack, Telegram, Facebook Messenger, Skype, Cortana, Twilio, MS Teams, Kik, Web chat, API interface, etc. Once you build a chatbot using Microsoft Azure Bot framework, you can quickly integrate it to any messenger platform or even voice-assistants.

Facebook Messenger platform is worth to mentioned here because they did a good job in terms of marketing, that already created a great community for Facebook Messengers bot builders for customer support purpose. If the user performs communication via FB messenger with your chatbot, you have default ability to take communication control to yourself and continue dialog as a human from chatbot control page. This feature is working perfectly in case of nonstandard user problem, that requires human interruption.

SAP also released its own messaging platform SAP Conversational AI, which has user channels to connect to many messaging platforms. Chatbots there born to simplify user interaction with SAP, for example:

- You can add SAP material using text interface with buttons in your webpage messenger instead of the usual SAP forms application

- You can easily access the information by Natural Language Interface to SAP database using NLSQL software

Please see below the video how existing solutions working with SAP S4/HANA:

Natural Language Interface for SAP S/4 HANA via Skype chatbot

- You can submit and approve requests using chatbots. You can be notified by a chatbot, that some of the requests are assigned

- You can substitute your work email with a chatbot. Emails are good for official communication, but most of employees communication perform by internal messengers. So why do you need to switch between different application? You can read your emails via chatbots and reply to it by prebuilding responses

- Persons in charge of equipment maintenance can be informed with equipment notifications and warnings before the failure occurs

- You can ask your personal KPIs and get notified with payroll statistics by chatbot in SAP

In case you decide to start using chatbots with SAP, you will enjoy the world of the Natural Language Interfaces beyond websites and mobile applications.

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