Unlocking the Power of Hyreo's Post-Offer Solution: Enhancing Engagement, Candidate Experience, and Reducing Decline Rates

The client represents a prominent Japanese organization specializing in Information and Communication Technology (ICT). This corporation champions sustainability and societal trust through innovation as its core mission. To realize this objective, it seeks to attract, engage, and retain talent that aligns with its vision.

The Asia Pacific division primarily offers consulting and IT services to various industries. It excels in IT Consulting, Application Services, Infrastructure Services, Managed Services, Digital Transformation, Industry-specific solutions, Cybersecurity, IoT, and SAP Services.

The corporation's vision for its workforce involves cultivating a diverse, inclusive, and innovative environment. It places a high value on employee growth, work-life harmony, and ethical behavior while fostering a global perspective and a customer-first approach. The company promotes collaboration, environmental stewardship, and a steadfast commitment to customer satisfaction.

Business Challenges

The company's talent acquisition team set out to breathe new life into the existing candidate journey, stay closer to them, and create 'wow' moments, especially in the 'offer to onboarding' phase of recruiting. But the journey started to get bumpy soon enough. Managing candidate expectations and staying in touch with them 24/7 was a big problem. The lack of personalized interaction risks created a disconnect between the candidates and the company.

  • Traditional methods of recruiters reaching out to candidates periodically needed more predictability and personalization to understand individual candidate needs.  
  • FAQs or requests for information took time, as this solely depended on recruiting managers’ availability.  
  • The inability to track back the issues raised by candidates posed a big challenge. 
  • Organizational leadership needed actionable insights on common candidate concerns, process bottlenecks, and areas of improvement.

There was a steep increase in the rate of candidates declining the position. Uncertainty of offer conversion also loomed over.

  • There was an average 39% decline in job offers or candidates who did not join after the selection and job offer stage, which was a staggering loss of time, effort, and money.  
  • Understanding whether a candidate would accept an offer and ultimately join the organization was a complex puzzle that could not be solved.  
  • Numerous variables influenced candidate decisions, making it more difficult to predict their behavior in a structured manner. 


The adopted approach for solving the problem was implementing an AI-based automation layer in the company's existing recruiting technology infrastructure. This is where they met Hyreo- a global recruiting CRM solution that creates a scalable and data-driven model for candidate relationships. Hyreo could ingest data from existing Applicant Tracking System (ATS) solutions, enhancing the candidate experience. It could do so by bolstering talent engagement, facilitating automation, providing insightful data, and issuing alerts designed to optimize the cycle of human intervention.

The critical components of the solution included:

Intelligent candidate funnel engagement

The key to understanding candidates and their preferences lies in staying in touch with them and understanding critical information about their needs and concerns. Hyreo was pre-built with an intelligent nudge algorithm and communication layer powering email and SMS-based outreach, ensuring candidates open and consume such communication. In the process, it helped the company decode patterns crucial for deciphering user behaviour.

The nudge system came with built-in intelligence to make the nudges effective through pattern identification by collecting data on when/what/which nudges were opened, their response rates, and of course candidate behavior. The solution was powered by advanced algorithms based on collaborative filtering and content-based filtering to identify candidate-level preferences and make communication more effective.

Through continuous data collection and real-time learning, specific recommendations evolved with every interaction. The company slowly uncovered the patterns and preferences of their candidates. Whether a candidate preferred to open emails in the early morning or late at night, the system adjusted to deliver content precisely when they are most engaged. Based on each candidate's behavior in the platform, the curated email subject lines and content that aligned perfectly with what they were expecting were triggered.

  • Critical tools for recommendation engine: Matrix factorization, deep learning models, and reinforcement learning techniques  
  • Key Metrics: Email or SMS open rate, click-through rates, and response rates  

Intelligent candidate funnel engagement

In line with the philosophy of staying in touch with candidates, there was a compelling requirement for an automated, real-time communication channel. The solution included a candidate support chatbot or agent equipped with sophisticated Natural Language Processing (NLP) to provide real-time, personalized responses to candidate queries. This proficiency was achieved through supervised learning, continuous intent classification, and monitoring, thus enabling it to represent the brand and its culture aptly.

The bot provided real-time, personalized responses to candidate queries, adapting to different communication styles and preferences- outperforming human support agents, offering instant, relevant, and customized answers. In complex scenarios, chatbots efficiently created support tickets for human-led support.

The categorizing and prioritizing of queries ensured the right person with the necessary expertise handled each ticket, saving time and providing accurate responses. The Chatbot could keep candidates informed about their support ticket's status and automated follow-ups and make decisions on recurring and non-strategic activities, enhancing the overall candidate experience and reducing recruiter efforts.

Propensity Analysis & Actionable Insights

The next big problem was an increased number of drop-offs. To address this risk, the recruiting team needed an intelligent solution to understand the joining propensity of candidates. Early warnings on risk helped develop a more realistic model for risk mitigation in the talent supply processes. Hyreo had a data science-backed approach for measuring candidate joining risk with an in-built recruiter alert mechanism to enable quicker action.

Propensity analysis in Hyreo employed state-of-the-art machine learning algorithms, including Logistic Regression, Random Forest, and Gradient Boosting. By analyzing a candidate's historical behavior and interactions, the system calculated the likelihood of a candidate accepting an offer.

Sentiment detection using NLP helped to continuously understand candidate sentiments based on data from candidate email correspondences, CSATs, and interaction history, indicating doubts, hesitations, or uncertainties about joining. Should the system detect a risk of a candidate declining an offer, recruiters were promptly alerted with insights on risk parameters and strategies for effective engagement.

With over 50+ behavior and interaction parameters, such as date of joining change, low satisfaction of job role or compensation, hiring manager interactions, BGV documentation, etc., the system could understand and decode the intricate web of outcomes and their overall impact.


The Asia Pacific entity of the Japanese multinational underwent a remarkable transformation with the implementation of Hyreo's post-offer solution. Their candidates shared more feedback, with candidate concerns getting promptly attended to, and most importantly, they saw a whopping 20% improvement in overall offer conversion over and above the phenomenal improvement in overall recruitment experience, as noted in the CSAT trends in 12 months!

The impact of the collaboration was significant:

  • Declined offers saw a remarkable 20% improvement in 4 quarters.  
  • A staggering 74% of offered candidates wholeheartedly embraced the Chatbot, a reliable companion that accurately addressed 87% of candidate concerns.  
  • Achieved an impressive 89% resolution rate for tickets and issues raised by candidates, marking a monumental shift from the previous time-consuming manual process.  
  • The candidate’s Customer Satisfaction (CSAT) score soared to 92, reflecting their high level of contentment.  
  • Automation of the tactical steps in the candidate onboarding process yielded FTE savings equivalent to 26 person-months. 


The revamped enterprise post-offer solution opened up unprecedented opportunities for the Japanese MNC. It wasn't merely a solution; it acted as a revolutionary catalyst that took their company to the next level. It revitalized the entire recruitment experience, creating an environment where candidates were hired, cherished, guided, and listened to. This transformation led to such great results, which are evident in their growth, the enhancement of the employer brand, and a substantial surge in the company's market competitiveness.

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