Author: Franz Malten Buemann

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Did you know that LinkedIn already existed way before the likes of Facebook, Instagram, and Snapchat? Despite its age, the career networking platform is far from outdated. Nowadays a staggering 94% of recruiters look at your profile in selecting potential candidates. But most of them are not human, so it seems.

The importance of a solid online profile is greater than ever. Your personal LinkedIn page serves as your digital business card and it’s the most used tool for recruiters in the selection process of new candidates. There are strict requirements, and chances are that you have already been rejected by a robot several times. A robot? Yep, you heard that right. Many companies use robo-recruiters in their search for new employees and only 2 percent of job-seekers manage to get the better of these very strict AI-driven machines. So the question is, are there ways to get past them? The answer is yes, by taking the right steps you will too get that job invite you really want.

Inevitable shift

The increasing number of Applicant Tracking Systems (ATS) as these robots are officially called, results from the fact that the current job market is more competitive than ever before. Back in 2016 for example, investment bank Goldman Sachs received as many as 250.000 applications for a single vacancy. Not only are there more players entering the field, but competing candidates also tend to become more and more qualified over the years. In the US the percentage of individuals holding a bachelor’s degree or higher increased from 29 to 37 percent between 2000 and 2018, a development that stresses the need for algorithms to filter out the cream of the crop.

Trending Bot Articles:

1. How Chatbots and Email Marketing Integration Can Help Your Business

2. Why Chatbots could be the next big thing for SMEs

3. My Journey into Conversation Design

4. Practical NLP for language learning

Computer says no

It may sound harsh, putting in loads of effort to make your profile tip-top only to get a firm no from a recruiter without a pulse. Unfortunately, that is how recruiting works in this digital day and age. Lucky for you, there are online tools like My Talent Path you can use to outsmart the system. This platform allows you to upload your profile to check how desirable you currently are to recruiters. Afterward, you will get feedback on how to improve by performing simple actions that will boost your score right away, making you a lot harder to ignore — even for robots.

Don’t forget to give us your 👏 !

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Beat the bots: the rise of robot recruitment was originally published in Chatbots Life on Medium, where people are continuing the conversation by highlighting and responding to this story.

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Starting May 25–27th 2021

If you could ask Google, Salesforce, GoDaddy, T-Mobile, IBM Watson, Rasa, Twilio, anything about AI, Bots & Voice what would you ask?

Discover how Enterprises are using chatbots, AI and Voice to decrease costs and increase revenues. We will explore latest trends, use cases, and get a behind the scene look at what is working best and how you can apply it in at your company.

We features speakers from many of the leaders in the space such as Google, Facebook, Amazon, Rasa, IBM, Salesforce, Intuit, Walmart, and many more.

3 Reasons you need to Attend:

1. Save Time: Discover how Enterprises are using Chatbots, AI and Voice from Top Industry Experts. Attending our events puts you in touch with Top Experts in AI, Bots , Voice and saves you a lot of time and trial and error.
2. Certified Workshops: Learn how to Design and Develop Chatbots and Voice Apps in our full day workshops. Workshops like this typically cost between $2,000 — $5,000. Workshop details below.
3. Networking & Virtual Happy Hour: We have digitized the networking experience! In our upcoming event, you will be able to virtually network with speakers, attendees, vendors and exchange contact information with the click of a button.

How the Chatbot Conference is Organized

Day 1: DISCOVER |May 25th

Chatbot Conference & Live Q&A

On Day 1, of the Chatbot Conference, our Goal is to give you an overall understanding of the Conversational AI Ecosystem, to discover the best business application that are producing an ROI, and to do deep dives in the most essential areas.

Deep Dive into Use Cases:

• AI Customer Service: Exploring how Enterprises are using bots in Customer Service to increase customer satisfaction and decrease costs.
• Sales & Marketing: Latest on how Enterprises are generating leads and sales using Bots.
• B2E, Backend & RPA’s: This is the biggest use cases no one is talking about! Backend bots are bots that automated tasks between employees and enterprises such as HR, password reset, employee on-boarding, document management, proof reading, and much more.
• Voice & Virtual Assistants: Latest on Voice from Google Home, Alexa, & Siri.

Deep Dive into Execution:

• Artificial Intelligence & NLP: ​Latest on NLP & AI for Bots
• Conversational UX: Latest design conventions and a look at what’s working.

We aim to give an overview of the Conversational AI space and help you identify the most important areas. We then jump in and do deep dives in each of these focus areas and try to answer the most pressing questions such as ‘what use cases have the biggest ROI’, ‘what is possible given the current state of AI & NLP ’, ‘what is the best way for Enterprises to get started’ and many more. The Live Q&A is the perfect time to ask them questions and go in depth on their topic of expertise.

Virtual Happy Hour, Networking & Virtual Round Tables

We have digitized the networking experience! In our last event, attendees had 1700 conversations! Our events are the perfect place to connect with industry experts and network in the Conversational AI industry.

Here is how it works

In our Virtual Networking Area, you will automatically be matched to someone who has similar interests and have the opportunity to talk for a few minutes. After that time, you can exchange contact information with the click of a button or move to the next person.

Day 2: DESIGN | May 26th

Certified Conversational UX Workshop

In this year’s event, we are featured two Certified workshops that build on each other. First, you will design a bot in our Conversational UX workshop and then develop it in our an AI Development Workshop. By the end of our workshops, you will have a Conversational Agent that you can implement at your company or take it back to your supervisor.

The Project

Your bot will be able to answer 10 FAQ questions, have a great on-boarding experience and a number of fall backs. You will learn how to design and develop a bot using NLP/NLU Platforms and deploy your bot to a website, sms, messaging channel or voice.

Conversational Design Certification: In this workshop, you will learn how to design a great chatbot. You learn about copy writing, user research, UX design and how to use data and analytics to improve your chatbot or virtual assistant.

Day 3: DEVELOP | May 27th

After you Conversational Agent has been designed, we will take that preliminary design and develop it into a fictional MVP. In the workshop, the NLP section will be implemented and your bot will be able to answer 10 FAQ questions.

Certified NLP Workshop| May 26th

AI Developer Certification: In this workshop, you will learn how to build a bot using Natural Language Processing. You will learn about intent classification, entity extraction, dialogue management, and you’ll learn how to make your bot conversational using NLP!

After completing the workshops, you will be able to build a high quality chatbot or virtual assistant using an NLP.

Lastly, students who take the workshop, will earn a Certification upon completion!

See what our Attendees are saying

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Chatbot Conference Online 2021 was originally published in Chatbots Life on Medium, where people are continuing the conversation by highlighting and responding to this story.

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A quick summary of 7 important DO’s and DON’Ts when designing a chatbot testing strategy. We are continuously seeing teams ignoring those actually rather simple rules.

DO’s and DON’Ts

✅DO plan for iterations

In german we say rome was not built in a day — same applies for your chatbot training data. A robust chatbot is built by multiple iterations, training and testing cycles and by ongoing monitoring and performance tuning: CODE, TEST, DEPLOY, REPEAT

❌ DON’T underestimate the need for constant performance measurement

Without measuring performance with real user conversations, you will never know if your chatbot is really working for your users.

✅DO apply the 80/20 rule for testing utterances

Most teams are tempted to use 100% of the available data for training. Do not do this. You won’t know if your training data works if you use parts of the training data additionally for testing. Rule of thumb is to use 80% of data for training and 20% for testing.

If and only if the amount of available data is very small you may try K-Fold validation to get some insights about the quality of your data.

❌ DON’T rely on smoke tests or happy path tests

Again the 80/20 rule — 20% is the work spent for the comfort zone, 80% of the work is testing and bugfixing. 20% of your users will follow the happy path, 80% will break out. Prepare for this.

✅DO: spend a reasonable amount of time with explorative testing

Automated regression testing is superior for finding defects that you know can happen. It won’t help to find defects you don’t know about. Spend some time with explorative (=manual) testing: try to bring your chatbot to its limits and beyond.

Trending Bot Articles:

1. How Chatbots and Email Marketing Integration Can Help Your Business

2. Why Chatbots could be the next big thing for SMEs

3. My Journey into Conversation Design

4. Practical NLP for language learning

❌ DON’T: ignore the need to re-test after training

You can never know what effect adding some training data on one end of your fine-tuned NLU model will have on the other end, until you try out. Do a full regression test of your NLU model every single time you make changes.

✅DO: test processing of out of order messages

One of the most human-like bevaviour is to scroll up the conversation history in the chatbot window and resume from a previous step. Most chatbots out there will fail this challenge if not prepared accordingly.

Action Plan

Here are suggestions to address the DO’s and DON’Ts.

Establish Continuous Testing Mindset

Testing is a crucial part of the development process. There is no such thing as a single testing phase when bringing a chatbot to life. Testing has to be part of the team’s daily business, just like coding, design and monitoring.

Holistic Testing

For chatbots as for software products in general, there is more than unit tests coded by the programmers.

• Regression Testing — Identify flaws in the conversation flow before going to production
• NLP Testing — Improve your chatbot understanding
• E2E Testing — Verifying the end-user experience
• Voice Testing — Understand your users on voice channels
• Performance Testing — Ensure your chatbot is responsive under high load
• Security Testing — Making your chatbot secure
• Monitoring — Get notified when problems arise

Get the Right Tools In Place

Without the right tools you will be lost. With Botium Box you are prepared for the challenges of getting them in place and integrate them into your chatbot development lifecycle.

Get your free Botium Box Mini instance here

Don’t forget to give us your 👏 !

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4 DO’s and 3 DON’Ts for Chatbot Testing Strategies was originally published in Chatbots Life on Medium, where people are continuing the conversation by highlighting and responding to this story.

No-Code Platforms — Future of chatbot development

Increasing focus on digital transformation has been driving the popularity of conversational AI and text & voice-based chatbots. Many enterprises are leveraging these solutions for automating as well as humanizing conversations and enriching customer interactions.

As chatbots are becoming the quintessential tool to deliver premium customer support as well as automating operational routines, organizations are looking for solutions that augment existing capabilities in these areas. AI-powered bots that can understand, learn, and even recommend based on customer behavior are gaining top-mindshare among executives. There is a huge demand in the market for solutions that can deploy AI-powered bots within minutes to enhance lead generation and support branding activities. The value proposition of these solutions is the convenience to convert contact centres into business generation centres within no time.

In a competitively fierce market, businesses have started turning toward enterprise-grade applications with capabilities to offer ultra-personalized customer experiences to improve brand value and differentiation. The market is witnessing a heightened sense of urgency, especially with customer interactions, as these are increasingly correlated with several business metrics and are pressurizing software development teams to deliver applications faster than ever before. In addition, there are significant gaps between developers and business requirements, which are impeding the rising demand for customer-facing applications among enterprises. Quite often, chatbot developers don’t indulge in understanding the nuances of the deployment environment, domain knowledge, and the perceived value of the bots leading to unsatisfactory results.

Can anyone develop chatbots?

Yes, using KLoBot’s chatbot builder platform, anyone can develop and deploy chatbots with minimal programming expertise. Knowledge managers in law firms are always on the lookout for advanced automation technologies to enhance lawyer’s productivity as well as minimize their spend on repetitive routine activities.

Knowledge management professionals and teams are moving beyond traditional management practices to uncover efficient solutions to connect people, process, and technology. In addition, these solutions typically do not require expert programming knowledge and lessen dependency on expensive IT expertise. Platforms with the ability to shift from current transactional work to transformational value are witnessing increased traction.

No-Code platforms for rapid delivery of intelligent chatbots!

No-Code development platforms have risen as the path towards innovation that reduces enterprise dependency on developers and third-party software developers. These platforms are reinventing the way chatbots are built by using prebuilt modules, reducing the development time, and transforming the business process.

Targeting at organizations requiring tools for faster and easy to build bots, No-Code chatbot builder platforms allow rapid development and deployment of chatbots, becoming the preferred choice for startups, enterprises, and non-technical developers.

Trending Bot Articles:

1. How Chatbots and Email Marketing Integration Can Help Your Business

2. Why Chatbots could be the next big thing for SMEs

3. My Journey into Conversation Design

4. Practical NLP for language learning

KLoBot — A No-Code chatbot builder platform

KLoBot Inc., a disruptive startup, is accelerating enterprise digital transformation initiatives by simplifying human–machine interactions with their chatbot solution, “KLoBot”. The No-Code DIY chatbot builder platform makes it easier to develop web, mobile, and business applications especially for businesses with minimal IT support.

KLoBot’s elegance lies in the ability to build customer-facing applications using a simple drag and drop interface. The No-Code development platform offers agility, reduced development costs, and enhanced productivity by designing and deploying chatbots within a few hours.

KLoBot’s chatbot building process

Creating or Selecting Skills:

Clients using the drag and drop interface, can either create their own skills or select available skills from KLoBot’s reusable skills categories, which consist of reminders, information, tasks, QnA, and Flow.

KLoBot enables users to build AI-enabled chatbots for simple as well as complex tasks, including transaction completion process, knowledge repository search, and virtual personal assistants among others. The bot also provides seamless integration with NetDocuments, allowing users to access NetDocuments content by using voice or text.

Configure and Train Chatbots:

KLoBot’s custom channel deployment allows enterprises to configure chatbots on a wide range of communication channels, including Facebook, Skype, Cortana, Slack, Telegram, Microsoft Teams, Twilio, web chat, email, etc. Other than these standard channels offered by KLoBot, enterprises can even configure chatbots with their specific client applications using direct line as a channel.

KLoBot leverages ML to train chatbots to continuously enhance Chatbot & Human interactions using natural language. In addition to learning, these bots are capable of comprehensive reporting and generating insights based on user interaction. These functionalities help businesses to better understand and target the key metrics resulting in improved service capabilities and ROI.

Robust Security Features:

Some adjustments are needed after configuring skills to chatbots. KLoBot’s bot builder user interface assists clients in managing all their chatbots from a centralized location, with minimal customized settings.

End-to-End Testing:

The final step of KLoBot’s chatbot building process involves testing, which ensures that the organizational AI chatbot requirements are met. It includes testing of configured skills across chatbots on different communication channels. This final step ends the KLoBot’s turnkey chatbot development process.

Don’t forget to give us your 👏 !

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No-Code Platforms — Future of chatbot development was originally published in Chatbots Life on Medium, where people are continuing the conversation by highlighting and responding to this story.