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PCU PMA Blog

Writer's pictureAnubhav SInha

Future and Potential Use Cases of AI in Freshworks Product(s)


Image - AI use cases in Freshworks - a conceptual thought


Purpose of this Article


I am writing this article as every organization in 2024 has an Org Initiative focused towards AI and Generative AI Technologies. It is aimed to be informative and thought-provoking, encouraging discussion and collaboration around responsible AI practices and I have had taken Freshworks products as an example for this article.


**All content are written from self-understanding and created by the author

**These use cases and scenarios are projected from the real-time learning and practiced work experience of the author.

Possible Organizational Initiatives for 2024:

Based on these indications, it's safe to assume that AI and Generative technologies are major priorities for Freshworks in 2024. Here are some possible initiatives:

Product-focused:

  • Expanding AI capabilities: Implement AI in more products, potentially including Freshservice (IT service management), Freshdesk (customer service), and Freshsales (sales management).

  • Deepening existing AI functionalities: Enhance existing AI features like Freddy AI, sentiment analysis, and predictive insights with more advanced capabilities.

  • Exploring generative applications: Implement generative technologies for tasks like personalized content creation, automated report generation, and even code generation.


AI Today: The Power of the (Smart) Assistant

Today, Freshworks products are focused to Customer Service, ITSM and Sales of which they are already leveraging AI at present to empower users and enhance experiences. Here are some key examples:


Customer Engagement:

  • Freddy AI: This intelligent chatbot handles routine inquiries, deflects tickets, and empowers agents with real-time suggestions. Think of it as a tireless sidekick for customer service teams.

  • Sentiment Analysis: AI analyzes customer interactions, identifying negative sentiment and helping teams proactively address potential issues.

  • Personalized Recommendations: AI suggests relevant knowledge base articles or next-best actions based on customer context, leading to faster resolutions and happier customers.

IT Service Management:

  • Incident Prediction: AI analyzes historical data and identifies patterns to predict potential IT issues, enabling proactive maintenance and preventing downtime.

  • Automated Ticket Classification: AI automatically classifies incoming tickets based on keywords and context, ensuring they reach the right agent faster.

  • Root Cause Analysis: AI delves deep into IT data, pinpointing the root cause of incidents, accelerating resolution and preventing future occurrences.


Available and potential applied Use Cases of the Freshworks Products


Freshworks offers a suite of products catering to various needs, so the use cases vary depending on the specific product. Here are some examples of how different Freshworks products can be used:


Customer Service & Support:

  • Freshdesk:

  • Ticketing and issue resolution for customer support teams.

  • Self-service knowledge base for customer self-help.

  • Live chat support for real-time assistance.

  • Community forums for peer-to-peer support.

  • Reporting and analytics to track customer satisfaction and identify areas for improvement.

  • Freshchat:

  • Conversational support through live chat, messenger apps, and email.

  • Chatbots for automated responses to common questions and tasks.

  • Proactive outreach to engage customers and offer assistance.

  • Multi-channel communication for seamless customer experience.

Sales & Marketing:

  • Freshsales:

  • Sales pipeline management and lead tracking.

  • Quote generation and opportunity management.

  • Sales forecasting and reporting.

  • Email marketing and automation.

  • Customer relationship management (CRM) for managing customer interactions.

  • Freshmarketer:

  • Multi-channel marketing campaigns across email, social media, and web.

  • Landing page creation and lead capture forms.

  • Marketing automation for personalized interactions.

  • Email marketing and analytics to track campaign performance.


IT Service Management:


  • Freshservice:

  • Incident management for resolving IT issues.

  • Asset management for tracking IT infrastructure.

  • Change management for implementing IT updates.

  • Self-service portal for employees to request IT assistance.

  • Reporting and analytics to track IT service performance.


Future and Potential AI use cases for Advanced Implementation

Freshworks already incorporates some AI capabilities in its products, particularly the "Freddy" AI suite. However, there's significant potential for further AI integration across its product lines. Here are some potential AI use cases for Freshworks products:


Customer Service & Support:

  • Advanced Chatbots: Deploy highly contextual and personalized chatbots to handle routine inquiries, deflect tickets, and escalate complex issues to agents.

  • Sentiment Analysis: Analyze customer support interactions to understand sentiment, identify potential dissatisfaction, and proactively take action.

  • Issue Prediction & Prevention: Leverage AI to analyze historical data and predict potential support issues before they happen, enabling proactive maintenance and preventative measures.

Sales & Marketing:

  • Lead Scoring & Nurturing: Utilize AI to score leads based on behavior, demographics, and engagement, prioritizing high-potential leads and automating personalized nurturing campaigns.

  • Sales forecasting & Recommendation: Leverage AI to analyze sales data and predict future sales performance, suggesting optimal sales strategies and resource allocation.

  • Product Recommendation & Personalization: Employ AI to recommend relevant products and personalize marketing campaigns based on customer preferences and purchase history.

IT Service Management:

  • IT Anomaly Detection & Root Cause Analysis: Utilize AI to identify anomalies in IT performance, predict potential outages, and automatically diagnose root causes for faster resolution.

  • Self-Service Optimization: Optimize knowledge base articles and chatbots by using AI to understand user intent and suggest relevant content for self-service resolution.

  • Automation of Repetitive Tasks: Automate repetitive tasks like incident triage, ticket categorization, and password resets, freeing up IT staff for more complex issues.


Industry-Specific AI Future Potential Use-Cases

  • Healthcare: Utilize AI for personalized patient care plans, medical image analysis, and drug discovery.

  • Education: Leverage AI for personalized learning recommendations, automated plagiarism detection, and intelligent tutoring systems.

  • E-commerce: Employ AI for dynamic pricing, product recommendations, and fraud detection in online transactions.


The future of AI in Freshworks with potential scenarios and cases as below:


Hyper-Personalization: Imagine AI not just suggesting articles, but anticipating customer needs and proactively offering solutions before issues arise. This personalized approach will redefine customer engagement.


Predictive Insights: AI could become a crystal ball for businesses, predicting customer churn, identifying upsell opportunities, and suggesting optimization strategies based on real-time data analysis.


Generative AI: Imagine AI-powered chatbots that not just answer questions, but also hold in-depth conversations, understand nuanced emotions, and even write personalized emails. This will revolutionize customer interactions.


Next-Level Automation: Think beyond ticket deflection. AI could automate complex tasks like incident resolution, report generation, and even service desk operations, freeing up human agents for strategic work.



Possible Challenges, Regulation, and Compliance in Freshworks' AI Future


As exciting as AI's potential is in Freshworks products, several challenges loom on the horizon. Navigating these challenges responsibly and proactively necessitates considering regulations and compliance measures. Let's go deeper:


Challenges:

  • Bias and Fairness: AI algorithms can inherit and amplify human biases, leading to discriminatory outcomes. Careful data selection, model training, and bias detection are crucial.

  • Explainability and Transparency: "Black box" AI models raise concerns about their decision-making processes. Explainable AI approaches and user education are essential.

  • Data Privacy and Security: AI relies heavily on data, raising privacy concerns.Strong data security measures, user consent, and anonymization techniques are critical.

  • Job Displacement: AI automation might displace some jobs. Reskilling initiatives,upskilling programs, and ethical considerations regarding job automation are paramount.

  • Misinformation and Malicious Use: AI misuse for generating fake content or manipulating users presents a significant threat. Robust detection and mitigation strategies are needed.

Regulation and Compliance

Several existing and emerging regulations impact AI development and deployment. Freshworks needs to stay abreast and ensure compliance with:

  • General Data Protection Regulation (GDPR): Protects EU citizens' data privacy,requiring transparency and user consent for data collection and processing.

  • California Consumer Privacy Act (CCPA): Grants California residents similar data privacy rights as GDPR.

  • Algorithmic Justice League Act: Aims to prevent discriminatory outcomes in algorithmic decision-making, potentially impacting AI systems.

  • Responsible AI Principles: Developed by various organizations, these principles outline ethical guidelines for AI development and deployment.

Compliance Strategies

Freshworks can proactively address these challenges and regulations through:

  • Building Ethical AI frameworks: Establish clear guidelines for responsible AI development, ensuring fairness, transparency, and accountability.

  • Investing in explainable AI: Develop and adopt explainable AI models that shed light on their decision-making processes.

  • Prioritizing data privacy and security: Implement robust data security measures, obtain user consent, and anonymize data when possible.

  • Upskilling and reskilling initiatives: Prepare employees for the changing workforce landscape through comprehensive training programs.

  • Collaborating with regulators and stakeholders: Actively engage with policymakers and industry leaders to shape responsible AI regulations.



About the Author


Anubhav Sinha stands at the forefront of product innovation and education, co-founding the esteemed Product Capability Uplift (PCU). In his pivotal role at PCU, Anubhav spearheads the development of cutting-edge programs, AI capabilities and courses, relentlessly driving the growth and capability-building initiatives of the Product Academy. His unique approach as a Product Thinker has significantly shaped the academy’s direction and impact.


With over 15+ years of rich experience in product management and development, Anubhav is a recognised authority in the field. His expertise spans across both B2B and B2IB product landscapes, where he has made substantial contributions, particularly in the start-up ecosystem. Renowned for his role in nurturing start-ups during their formative stages, Anubhav has also made his mark in established industry product organizations as a user-experience flow optimizer.


Anubhav's journey in product management began with a foundational Bachelor of Engineering in Electrical and Electronics, followed by a specialized Post-Graduation in Marketing - IB. His diverse educational background underpins his holistic approach to product management.


Throughout his career, Anubhav has donned multiple hats - from a Principal Product Owner to Co-founder to a Product and Design Thinking Coach. His transformative coaching style and profound knowledge in product ownership have made him a sought-after figure in the tech product realm.


A product coach and an avid technology product enthusiast, Anubhav's contributions and insights are not just limited to his immediate professional engagements. His passion for the field resonates through the valuable content he creates and the mentorship he offers, continually inspiring and guiding the next generation of product management professionals.

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