Astronaut loading animation Circular loading bar

Try : Insurtech, Application Development

AgriTech(1)

Augmented Reality(20)

Clean Tech(5)

Customer Journey(12)

Design(36)

Solar Industry(6)

User Experience(56)

Edtech(10)

Events(34)

HR Tech(2)

Interviews(10)

Life@mantra(11)

Logistics(5)

Strategy(17)

Testing(9)

Android(47)

Backend(30)

Dev Ops(7)

Enterprise Solution(27)

Technology Modernization(2)

Frontend(28)

iOS(43)

Javascript(15)

AI in Insurance(35)

Insurtech(63)

Product Innovation(49)

Solutions(19)

E-health(10)

HealthTech(22)

mHealth(5)

Telehealth Care(4)

Telemedicine(5)

Artificial Intelligence(132)

Bitcoin(8)

Blockchain(19)

Cognitive Computing(7)

Computer Vision(8)

Data Science(17)

FinTech(50)

Banking(7)

Intelligent Automation(26)

Machine Learning(47)

Natural Language Processing(14)

expand Menu Filters

5 Ways HR Chatbots are Simplifying Recruitment and Employee Engagement

3 minutes, 49 seconds read

So far, there were three most talked about recruitment metrics — time-to-hire, cost-per-hire, and retention rate. Due to the Covid-19 outbreak, the HR industry is facing another challenge of managing and interacting with the remote workforce.

The impact of Covid-19 will be felt beyond 6 months. Organizations are, therefore, keen on revising their HR processes. Apart from hiring and retaining talents, productivity remains a crucial concern for most employers. 

Over 70% of organizations are opting for virtual recruitment methods and technologies like Artificial Intelligence, Robotic Process Automation and Machine Learning are leading this change. HR Chatbots are a well-known implementation of AI technology in recruitment.

5 Important AI-powered HR Chatbots Use Cases

AI-powered HR bots can streamline and personalize recruitment and engagement processes across contract, full-time, and remote workforce.

1. Screening Candidates

Almost 50% of talent acquisition professionals consider screening candidates as their biggest challenge. Absence of standardized assessment process, lack of appropriate feedback metrics, overdependence on employment portals, and ignoring the pool of interested candidates are some of the factors that create bottlenecks in the recruitment process.

Finding the best fit for the organization is in itself a challenge. On top of that, the time lost in screening the ‘ideal candidate’ leads to losing the candidate altogether. Nearly 60% of recruiters say that they regularly lose candidates before even scheduling an interview.

AI can help in making the screening process more efficient. From collecting resumes to scanning candidates’ social & professional profiles, recent activities, and their interest in the industry/organization, AI can connect the dots and shortlist ‘best candidates’ from the talent pool. The journey begins with an HR bot that collects resumes and initiates basic conversations with the candidates.

HR operations chatbot – View Demo

2. Scheduling Interviews

The biggest challenge with scheduling interviews is finding a time that works for everyone. 

According to a recent HR survey by Yello, it takes between 30 minutes and 2 hours to schedule a single interview. Nearly 33% of recruiters find scheduling interviews a barrier to improving time-to-hire.

The barriers to scheduling interviews involve time zones, prior appointments, location, and commute. AI-powered chatbots can piece it together for both — candidates and interviewers and propose an ideal time in seconds. Moreover, today’s HR bots can handle reimbursements, feedback, notifications, and post-interview sentiments of the candidates.

Appointment scheduling chatbot – View Demo

3. Applicants Tracking

Many organizations have been using Applicants Tracking Systems (ATS) — a software for handling recruitment and hiring needs. ATS provides a central location and database of resume boards (employment sites). 

How ATS Applicants Tracking System Works
(Image)

HR chatbots with NLP capabilities can be integrated into ATS to facilitate intelligent guided semantic search capabilities.

4. Employee Engagement

Even after the orientation, employees (especially new joiners) face hurdles in keeping up with the organization’s procedures. Reaching out to HRs is the solution, but they’re also bound by time. In most of the situations, peer-support is a way through for activities like using time-sheets, leaves, holidays, reimbursements, etc.

Chatbots have always been great self-service portals. HR departments can leverage bots to answer FAQs on the company’s policies, employee training, benefits enrollment, self-assessment/reviews, votes, and company-wide polls. 

HR bots with NLP capabilities can converse with employees, understand their sentiments, and offer resolutions. 89% of HR professionals believe that ongoing peer feedback and check-ins are key for successful outcomes. Especially in large enterprises, HR chatbots can engage with employees at scale. Moreover, chatbot conversations provide actual data for future analysis. This will also help the upper management with an unbiased understanding of the sentiments at the bottom of the pyramid.

5. Transparency across Teams

Recruiting data is often siloed and confined with the recruiters themselves. Leadership only has a high-level understanding of recruitment at ground levels. Often, this data is not available to other members of the HR department as well. Less than 25% of companies make recruiting data available to the entire HR team.

One of the reasons for lack of information transparency is the use of legacy systems like emails, spreadsheets, etc. for generating reports and sharing updates.

HR chatbots - how are recruitment metrics shared
(Image)

With AI-powered systems, controlled sharing of data, dynamic dashboards, real-time analytics, and task delegation with detailed information can be simplified. AI-chatbots, integrated within HRMs can make inter/intra departmental conversations and information requests simpler.

Final Thoughts

Today, recruiters prefer technology-based solutions to make their hiring process more efficient, increase productivity and candidate’s experiences. Tools like conversational chatbots are becoming increasingly popular because of the intuitive experiences they deliver. Chatbots can simplify HR operations to a greater extent and at the same time provide better employee engagement rates than humans. 

Multilingual AI-powered HR Chatbot with Video – Hitee.chat

Cancel

Knowledge thats worth delivered in your inbox

10 Analytics Tools to Guide Data-Driven Design

Analytics are essential for informing website redesigns since they offer insightful data on user behavior, website performance, and areas that may be improved. Here is a list of frequently used analytics tools to guide data-driven design that can be applied at different stages of the website redesign process. 

Analytics Tools to Guide Data-Driven Design

1. Google Analytics:

Use case scenario: Website Audit, Research, Analysis, and Technical Assessment
Usage: Find popular sites, entry/exit points, and metrics related to user engagement by analyzing traffic sources, user demographics, and behavior flow. Recognize regions of friction or pain points by understanding user journeys. Evaluate the performance of your website, taking note of conversion rates, bounce rates, and page load times.

2. Hotjar:

Use case scenario: Research, Analysis, Heat Maps, User Experience Evaluation
Usage: Use session recordings, user surveys, and heatmaps to learn more about how people interact with the website. Determine the high and low engagement regions and any usability problems, including unclear navigation or form abandonment. Utilizing behavior analysis and feedback, ascertain the intentions and preferences of users.

3. Crazy Egg:
Use case scenario: Website Audit, Research, Analysis
Usage: Like Hotjar, with Crazy Egg, you can create heatmaps, scrollmaps, and clickmaps to show how users interact with the various website elements. Determine trends, patterns, and areas of interest in user behaviour. To evaluate various design aspects and gauge their effect on user engagement and conversions, utilize A/B testing functionalities.

4. SEMrush:

Use case scenario: Research, Analysis, SEO Optimization
Usage: Conduct keyword research to identify relevant search terms and phrases related to the website’s content and industry. Analyze competitor websites to understand their SEO strategies and identify opportunities for improvement. Monitor website rankings, backlinks, and organic traffic to track the effectiveness of SEO efforts.

5. Similarweb:
Use case
scenario: Research, Website Traffic, and Demography, Competitor Analysis
Usage: By offering insights into the traffic sources, audience demographics, and engagement metrics of competitors, Similarweb facilitates website redesigns. It influences marketing tactics, SEO optimization, content development, and decision-making processes by pointing out areas for growth and providing guidance. During the research and analysis stage, use Similarweb data to benchmark against competitors and guide design decisions.

6. Moz:
Use case scenario: Research, Analysis, SEO Optimization
Usage: Conduct website audits in order to find technical SEO problems like missing meta tags, duplicate content, and broken links. Keep an eye on a website’s indexability and crawlability to make sure search engines can access and comprehend its material. To find and reject backlinks that are spammy or of poor quality, use link analysis tools.

7. Ahrefs:
Use case scenario:
Research, Analysis, SEO Optimization

Usage: Examine the backlink profiles of your rivals to find any gaps in your own backlink portfolio and possible prospects for link-building. Examine the performance of your content to find the most popular pages and subjects that appeal to your target market. Track social media activity and brand mentions to gain insight into your online reputation and presence.

8. Google Search Console:

Use case scenario: Technical Assessment, SEO Optimization
Usage: Monitor website indexing status, crawl errors, and security issues reported by Google. Submit XML sitemaps and individual URLs for indexing. Identify and fix mobile usability issues, structured data errors, and manual actions that may affect search engine visibility.

9. Adobe Analytics:
Use case scenario:
Website Audit, Research, Analysis,
Usage: Track user interactions across multiple channels and touchpoints, including websites, mobile apps, and offline interactions. Segment users based on demographics, behavior, and lifecycle stage to personalize marketing efforts and improve user experience. Utilize advanced analytics features such as path analysis, cohort analysis, and predictive analytics to uncover actionable insights.

10. Google Trends:

Use case scenario: Content Strategy, Keyword Research, User Intent Analysis
Usage: For competitor analysis, user intent analysis, and keyword research, Google Trends is used in website redesigns. It helps in content strategy, seasonal planning, SEO optimization, and strategic decision-making. It directs the production of user-centric content, increasing traffic and engagement, by spotting trends and insights.

About the Author:

Vijendra is currently working as a Sr. UX Designer at Mantra Labs. He is passionate about UXR and Product Design.

Cancel

Knowledge thats worth delivered in your inbox

Loading More Posts ...
Go Top
ml floating chatbot