Decoding Chatbots Simple Growth Tools for Small Businesses

Understanding Chatbots A Basic Introduction

Chatbots are software applications designed to simulate conversations with human users, especially over the internet. For small to medium businesses (SMBs), chatbots represent a significant opportunity to enhance customer interaction, streamline operations, and drive growth without requiring extensive technical expertise or large investments. Think of them as digital assistants capable of handling routine tasks, answering common questions, and guiding customers through simple processes.

Chatbots are digital assistants for SMBs, automating interactions and streamlining customer service.

The core value proposition of chatbots for SMBs lies in their ability to provide instant responses and 24/7 availability. Unlike human customer service Meaning ● Customer service, within the context of SMB growth, involves providing assistance and support to customers before, during, and after a purchase, a vital function for business survival. representatives who have limited availability, chatbots can operate continuously, ensuring that customers receive immediate support regardless of the time of day. This always-on presence is especially beneficial for SMBs that operate outside of traditional business hours or cater to a global customer base.

Moreover, chatbots can significantly reduce operational costs associated with customer service. By automating responses to frequently asked questions (FAQs) and handling basic inquiries, chatbots free up human agents to focus on more complex issues and tasks that require human judgment and empathy. This efficiency gain translates into reduced labor costs and improved resource allocation, allowing SMBs to operate more leanly and effectively.

From a customer experience Meaning ● Customer Experience for SMBs: Holistic, subjective customer perception across all interactions, driving loyalty and growth. perspective, chatbots offer consistency and speed. They provide standardized answers and processes, ensuring that every customer receives the same level of service and information. This consistency is vital for building trust and brand reliability. The speed of chatbot responses is also a major advantage in today’s fast-paced digital environment, where customers expect immediate gratification and quick solutions.

Identifying Quick Wins Initial Chatbot Applications

For SMBs new to chatbot technology, starting with simple, high-impact applications is key to demonstrating value and building confidence. Several areas offer immediate opportunities for chatbot implementation and quick wins:

Frequently Asked Questions (FAQs) Automation

One of the most straightforward and beneficial uses of chatbots is to automate responses to FAQs. Every SMB fields repetitive questions about operating hours, location, services offered, pricing, and shipping policies. A chatbot programmed with these answers can instantly address these inquiries, reducing the workload on customer service teams and providing customers with immediate information. This application alone can significantly improve customer satisfaction Meaning ● Customer Satisfaction: Ensuring customer delight by consistently meeting and exceeding expectations, fostering loyalty and advocacy. and free up staff time for more complex tasks.

Lead Generation and Qualification

Chatbots can play a proactive role in lead generation Meaning ● Lead generation, within the context of small and medium-sized businesses, is the process of identifying and cultivating potential customers to fuel business growth. by engaging website visitors and social media users in conversations. They can be designed to ask qualifying questions, gather contact information, and even schedule appointments or consultations. This automated lead qualification process ensures that sales teams receive only the most promising leads, improving conversion rates and sales efficiency. For instance, a chatbot on a real estate website could ask visitors about their budget, preferred location, and type of property, filtering out unqualified leads before they reach a human agent.

Basic Customer Support

Beyond FAQs, chatbots can handle a range of basic customer support Meaning ● Customer Support, in the context of SMB growth strategies, represents a critical function focused on fostering customer satisfaction and loyalty to drive business expansion. tasks. They can assist with order tracking, provide product information, guide users through troubleshooting steps, and even process simple returns or exchanges. By handling these routine support requests, chatbots allow human agents to concentrate on more complex issues that require personalized attention, such as resolving complaints or providing technical assistance. This tiered support system ensures that customers receive prompt assistance for common issues while reserving human expertise for more demanding situations.

Choosing Your First Platform Key Considerations

Selecting the right chatbot platform is a crucial first step for SMBs. The market offers a wide array of platforms, ranging from simple drag-and-drop builders to more sophisticated AI-powered solutions. For initial implementations, SMBs should prioritize platforms that are user-friendly, affordable, and require minimal technical expertise.

Ease of Use and No-Code Functionality

For SMBs without dedicated IT departments or coding skills, no-code chatbot platforms Meaning ● Chatbot Platforms, within the realm of SMB growth, automation, and implementation, represent a suite of technological solutions enabling businesses to create and deploy automated conversational agents. are ideal. These platforms offer intuitive visual interfaces that allow users to build and deploy chatbots without writing a single line of code. Drag-and-drop interfaces, pre-built templates, and guided setup processes make chatbot creation accessible to anyone in the business, regardless of their technical background. This ease of use empowers SMBs to quickly implement and manage their chatbots without relying on external developers or incurring significant development costs.

Integration Capabilities

Even for basic applications, integration with existing SMB tools can significantly enhance chatbot effectiveness. Consider platforms that offer seamless integration with popular customer relationship management (CRM) systems, email marketing platforms, and social media channels. CRM integration allows chatbots to access customer data Meaning ● Customer Data, in the sphere of SMB growth, automation, and implementation, represents the total collection of information pertaining to a business's customers; it is gathered, structured, and leveraged to gain deeper insights into customer behavior, preferences, and needs to inform strategic business decisions. and personalize interactions. Email marketing integration enables chatbots to capture leads and automatically add them to email lists.

Social media integration extends chatbot reach to platforms where customers are already engaging with the business. These integrations create a more cohesive and efficient customer communication ecosystem.

Scalability and Pricing

SMBs should choose a platform that can scale with their growth. Start with a platform that meets current needs but also offers the flexibility to expand chatbot capabilities as the business evolves. Pricing structures vary widely among chatbot platforms. Look for transparent pricing models that align with the SMB budget.

Many platforms offer tiered pricing based on usage volume, features, or the number of chatbots. Some platforms offer free trials or free plans with limited features, allowing SMBs to test the waters before committing to a paid subscription. Carefully evaluate pricing plans to ensure they are cost-effective and sustainable as chatbot usage increases.

Table 1 ● Initial Chatbot Platform Feature Comparison

Avoiding Common Pitfalls Simple Strategy for Success

Implementing chatbots successfully requires careful planning and a focus on user experience. SMBs can avoid common pitfalls by adopting a strategic approach from the outset.

Overcomplicating Initial Chatbots

A frequent mistake is trying to build overly complex chatbots right away. Start simple. Focus on addressing one or two key business needs, such as FAQs or lead generation. Begin with a limited set of features and functionalities.

As you gain experience and gather user feedback, you can gradually expand chatbot capabilities. Starting simple allows for quicker implementation, faster results, and easier iteration based on real-world usage.

Neglecting User Experience

The chatbot user experience Meaning ● User Experience (UX) in the SMB landscape centers on creating efficient and satisfying interactions between customers, employees, and business systems. is paramount. Ensure that chatbot conversations are natural, intuitive, and helpful. Avoid overly robotic or confusing language. Design conversations that are easy to follow and provide clear options for users.

Test chatbot flows thoroughly to identify and address any usability issues. Gather user feedback regularly and use it to refine and improve the chatbot experience. A positive user experience is essential for chatbot adoption and achieving desired business outcomes.

Ignoring Analytics and Optimization

Chatbot implementation is not a set-and-forget activity. Regularly monitor chatbot performance Meaning ● Chatbot Performance, within the realm of Small and Medium-sized Businesses (SMBs), fundamentally assesses the effectiveness of chatbot solutions in achieving predefined business objectives. using built-in analytics dashboards. Track key metrics such as conversation completion rates, user satisfaction scores, and goal conversion rates. Identify areas where the chatbot is performing well and areas for improvement.

Use analytics data to optimize chatbot flows, refine responses, and enhance user engagement. Continuous monitoring and optimization are essential for maximizing chatbot effectiveness and ROI.

By focusing on simple applications, choosing user-friendly platforms, and prioritizing user experience and continuous optimization, SMBs can successfully leverage chatbots to achieve quick wins and lay a solid foundation for future growth.

Scaling Up Chatbot Strategies Enhancing Customer Engagement and Efficiency

Integrating Chatbots Deeper into Business Operations

Once SMBs have established a basic chatbot presence, the next step is to integrate chatbots more deeply into core business operations. This intermediate phase focuses on leveraging chatbots to enhance customer engagement, streamline workflows, and drive greater efficiency across various business functions.

Integrating chatbots across business operations enhances customer engagement Meaning ● Customer Engagement is the ongoing, value-driven interaction between an SMB and its customers, fostering loyalty and driving sustainable growth. and streamlines workflows for SMBs.

Moving beyond simple FAQs and lead capture, intermediate chatbot strategies Meaning ● Chatbot Strategies, within the framework of SMB operations, represent a carefully designed approach to leveraging automated conversational agents to achieve specific business goals; a plan of action aimed at optimizing business processes and revenue generation. involve connecting chatbots with other business systems and using them to manage more complex customer interactions. This deeper integration unlocks new opportunities for automation and personalization, leading to improved customer satisfaction and operational gains.

Personalization and Segmentation Tailoring Chatbot Interactions

Generic chatbot interactions can be effective for basic inquiries, but personalization is key to creating more engaging and impactful customer experiences. Intermediate chatbot strategies emphasize personalization and segmentation to tailor chatbot conversations to individual customer needs and preferences.

Customer Data Integration for Personalized Responses

Integrating chatbots with CRM systems allows access to valuable customer data, such as past interactions, purchase history, and preferences. This data can be used to personalize chatbot responses and provide more relevant and helpful information. For example, a chatbot connected to a CRM could greet returning customers by name, offer personalized product recommendations based on their past purchases, or proactively address potential issues based on their known preferences. This level of personalization makes customers feel valued and understood, fostering stronger relationships and increasing customer loyalty.

Segmented Chatbot Flows for Different Customer Groups

Not all customers are the same. Segmenting customers into different groups based on demographics, behavior, or purchase history allows for the creation of tailored chatbot flows that cater to the specific needs of each segment. For instance, new customers might receive a different onboarding flow than returning customers. Customers interested in specific product categories could be directed to specialized chatbot flows that provide detailed information and assistance.

Segmentation ensures that chatbot interactions are highly relevant and targeted, maximizing engagement and conversion rates. This approach moves beyond one-size-fits-all chatbot interactions to deliver more personalized and effective customer service.

Dynamic Content and Conditional Logic

Intermediate chatbot platforms offer features like dynamic content Meaning ● Dynamic content, for SMBs, represents website and application material that adapts in real-time based on user data, behavior, or preferences, enhancing customer engagement. and conditional logic, which enable chatbots to adapt conversations in real-time based on user input and context. Dynamic content allows chatbots to insert personalized information into messages, such as customer names, order details, or account balances. Conditional logic enables chatbots to branch conversations based on user responses, ensuring that users are guided down the most relevant path.

These features make chatbot interactions more interactive and responsive, creating a more natural and engaging conversational experience. By using dynamic content and conditional logic, SMBs can create chatbots that feel less robotic and more human-like, further enhancing personalization.

Expanding Chatbot Applications Sales and Support Enhancement

With a solid foundation in basic chatbot applications and personalization, SMBs can expand chatbot usage to enhance sales processes and provide more comprehensive customer support.

Proactive Sales Assistance and Upselling

Chatbots can be deployed proactively to assist customers during the sales journey. On e-commerce websites, chatbots can engage visitors browsing product pages, offer assistance in finding the right products, and guide them through the checkout process. Chatbots can also be used for upselling and cross-selling by suggesting related products or premium options based on customer browsing behavior or stated needs.

This proactive sales assistance can significantly increase average order value and improve conversion rates. For example, a chatbot on a clothing website could recommend accessories that complement items in a customer’s shopping cart.

Advanced Customer Support and Issue Resolution

Beyond basic support tasks, intermediate chatbots can handle more complex customer support scenarios. They can be integrated with knowledge bases to provide detailed answers to technical questions, guide users through complex troubleshooting steps, and even initiate service tickets for issues that require human intervention. Chatbots can also collect detailed information about customer problems, ensuring that human agents have all the necessary context when they take over.

This streamlined issue resolution process reduces customer frustration and improves overall support efficiency. For example, a chatbot for a software company could guide users through common software errors and, if necessary, automatically create a support ticket with detailed error logs for a technical support agent.

Multi-Channel Chatbot Deployment

To maximize reach and accessibility, SMBs should deploy chatbots across multiple channels where their customers are active. This includes not only the company website but also social media platforms like Facebook Messenger, WhatsApp, and even SMS. Multi-channel deployment ensures that customers can interact with the chatbot on their preferred platform, enhancing convenience and accessibility.

Consistent branding and messaging across all channels are crucial for maintaining a unified customer experience. Managing chatbots across multiple channels may require a platform that offers centralized management and analytics, simplifying operations and ensuring consistency.

List 1 ● Intermediate Chatbot Strategy Checklist

1. CRM Integration ● Connect chatbot to CRM for customer data access.
2. Personalized Responses ● Implement dynamic content and conditional logic.
3. Customer Segmentation ● Tailor chatbot flows for different customer groups.
4. Proactive Sales Assistance ● Use chatbots for upselling and cross-selling.
5. Advanced Support ● Integrate with knowledge bases for issue resolution.
6. Multi-Channel Deployment ● Extend chatbot presence to social media and SMS.
7. Performance Monitoring ● Track key metrics and optimize chatbot flows.

Measuring ROI and Optimizing Performance Data-Driven Improvements

As chatbot implementations become more sophisticated, measuring return on investment (ROI) and optimizing performance based on data become critical. Intermediate chatbot strategies emphasize data-driven decision-making to maximize chatbot effectiveness and ensure that chatbots are delivering tangible business value.

Key Performance Indicators (KPIs) for Chatbots

Define specific KPIs to track chatbot performance and measure ROI. Relevant KPIs may include:

• Customer Satisfaction (CSAT) ● Measure customer satisfaction with chatbot interactions through surveys or feedback mechanisms.
• Conversation Completion Rate ● Track the percentage of chatbot conversations that successfully achieve their intended goal (e.g., answering a question, qualifying a lead, resolving an issue).
• Lead Generation Rate ● Measure the number of leads generated by chatbots.
• Conversion Rate ● Track the percentage of chatbot-generated leads that convert into customers.
• Customer Support Resolution Rate ● Measure the percentage of customer support issues resolved by chatbots without human intervention.
• Average Handling Time (AHT) Reduction ● Track the reduction in average handling time for customer support interactions due to chatbot automation.
• Cost Savings ● Calculate the cost savings achieved through chatbot automation, such as reduced labor costs or increased efficiency.

A/B Testing and Iterative Improvement

Use A/B testing to compare different chatbot flows, messages, and features to identify what works best. Experiment with variations in chatbot greetings, response phrasing, call-to-actions, and conversation flows. Analyze A/B test results to determine which variations lead to better performance based on defined KPIs.

Implement winning variations and continuously iterate on chatbot design based on ongoing testing and data analysis. This iterative approach ensures that chatbots are constantly evolving and improving to maximize their effectiveness.

Analyzing Chatbot Conversation Data

Go beyond basic metrics and analyze chatbot conversation data to gain deeper insights into customer behavior Meaning ● Customer Behavior, within the sphere of Small and Medium-sized Businesses (SMBs), refers to the study and analysis of how customers decide to buy, use, and dispose of goods, services, ideas, or experiences, particularly as it relates to SMB growth strategies. and identify areas for improvement. Review conversation transcripts to understand common customer questions, pain points, and areas of confusion. Identify drop-off points in chatbot flows where users are abandoning conversations. Analyze user feedback and sentiment to gauge customer satisfaction and identify areas where the chatbot experience can be enhanced.

Use these insights to refine chatbot content, improve conversation flows, and address customer needs more effectively. This qualitative data analysis complements quantitative metrics and provides a richer understanding of chatbot performance and user experience.

By integrating chatbots deeper into operations, personalizing interactions, expanding applications, and focusing on data-driven optimization, SMBs can unlock the full potential of chatbot technology to enhance customer engagement, improve efficiency, and drive significant business growth.

Transformative Chatbot Strategies AI-Powered Growth and Competitive Advantage

Leveraging AI and NLP Intelligent Chatbot Capabilities

For SMBs ready to push the boundaries, advanced chatbot strategies harness the power of Artificial Intelligence (AI) and Natural Language Processing (NLP) to create truly intelligent and transformative customer interactions. This advanced phase focuses on leveraging AI to automate complex tasks, personalize experiences at scale, and gain a significant competitive advantage.

AI-powered chatbots offer transformative potential for SMBs, enabling intelligent automation and personalized customer experiences.

Moving beyond rule-based chatbots, AI-powered chatbots Meaning ● Within the context of SMB operations, AI-Powered Chatbots represent a strategically advantageous technology facilitating automation in customer service, sales, and internal communication. utilize machine learning Meaning ● Machine Learning (ML), in the context of Small and Medium-sized Businesses (SMBs), represents a suite of algorithms that enable computer systems to learn from data without explicit programming, driving automation and enhancing decision-making. algorithms to understand natural language, learn from interactions, and provide more human-like and effective responses. These advanced capabilities enable SMBs to automate sophisticated customer service processes, gain deeper customer insights, and deliver exceptional personalized experiences that were previously unattainable.

Natural Language Understanding (NLU) Conversational AI at Scale

The core of advanced chatbot capabilities lies in Natural Language Understanding Meaning ● Natural Language Understanding (NLU), within the SMB context, refers to the ability of business software and automated systems to interpret and derive meaning from human language. (NLU). NLU allows chatbots to understand the meaning and intent behind user messages, even when expressed in varied and complex language. This goes beyond simple keyword recognition to truly understanding the nuances of human conversation.

Intent Recognition and Sentiment Analysis

NLU enables chatbots to accurately identify user intent, even when expressed indirectly or ambiguously. For example, a user might ask “I’m having trouble with my order” instead of explicitly stating “I want to track my order.” NLU algorithms can infer the user’s intent to track their order from the context of the message. Furthermore, sentiment analysis allows chatbots to detect the emotional tone of user messages, identifying whether a customer is happy, frustrated, or neutral.

This sentiment detection enables chatbots to tailor their responses accordingly, providing empathetic and appropriate support. For instance, a chatbot detecting negative sentiment could prioritize escalating the conversation to a human agent or offering extra assistance.

Contextual Conversation Management

Advanced chatbots maintain context throughout conversations, remembering previous interactions and user preferences. This contextual awareness allows for more natural and flowing conversations, avoiding the need for users to repeat information or re-explain their needs. Chatbots can use conversation history to personalize responses, anticipate user needs, and provide more relevant and efficient assistance.

Contextual conversation management creates a more seamless and human-like conversational experience, enhancing user satisfaction and engagement. This is particularly important for complex interactions that span multiple turns and require remembering details from earlier in the conversation.

Language Flexibility and Multilingual Support

AI-powered chatbots can be trained to understand and respond in multiple languages, expanding their reach to a global customer base. NLU algorithms can handle variations in language, dialects, and colloquialisms, ensuring effective communication across different linguistic backgrounds. Multilingual support is crucial for SMBs operating in diverse markets or serving international customers.

Advanced chatbot platforms often offer built-in translation capabilities or integrations with translation services, simplifying the process of deploying multilingual chatbots. This linguistic flexibility allows SMBs to communicate with customers in their native language, improving accessibility and customer experience.

Predictive Chatbots and Proactive Engagement Anticipating Customer Needs

Taking chatbot capabilities a step further, predictive chatbots Meaning ● Predictive Chatbots, when strategically implemented, offer Small and Medium-sized Businesses (SMBs) a potent instrument for automating customer interactions and preemptively addressing client needs. leverage AI to anticipate customer needs and proactively engage with users before they even ask for help. This proactive approach transforms chatbots from reactive support tools to proactive engagement Meaning ● Proactive Engagement, within the sphere of Small and Medium-sized Businesses, denotes a preemptive and strategic approach to customer interaction and relationship management. engines.

Behavioral Analysis and Predictive Recommendations

By analyzing user behavior data, such as website browsing history, purchase patterns, and past interactions, predictive chatbots can identify potential customer needs and offer proactive assistance or recommendations. For example, a chatbot on an e-commerce website could proactively offer assistance to users who have been browsing product pages for an extended period or who have abandoned their shopping carts. Predictive recommendations can also be used to suggest relevant products or services based on user browsing history or preferences. This proactive engagement can significantly improve conversion rates, increase sales, and enhance customer satisfaction by providing timely and relevant assistance.

Personalized Onboarding and Customer Journeys

Predictive chatbots can personalize the customer onboarding process and guide users through tailored customer journeys based on their individual profiles and goals. For new users, chatbots can proactively offer guided tours of website features, provide personalized tutorials, or answer common onboarding questions. For existing customers, chatbots can proactively offer personalized recommendations for new features, services, or products based on their past usage and preferences.

This personalized onboarding Meaning ● Personalized Onboarding, within the framework of SMB growth, automation, and implementation, represents a strategic process meticulously tailored to each new client's or employee's specific needs and business objectives. and journey guidance enhances user engagement, reduces churn, and maximizes customer lifetime value. By anticipating customer needs and providing proactive support, predictive chatbots create a more seamless and personalized customer experience.

Anomaly Detection and Proactive Support

AI-powered chatbots can be used to detect anomalies in customer behavior or system performance and proactively offer support or intervention. For example, a chatbot could detect unusual website traffic patterns or identify customers who are exhibiting signs of frustration or confusion. In these cases, the chatbot can proactively reach out to offer assistance, troubleshoot issues, or escalate the situation to a human agent if necessary.

This proactive support Meaning ● Proactive Support, within the Small and Medium-sized Business sphere, centers on preemptively addressing client needs and potential issues before they escalate into significant problems, reducing operational frictions and enhancing overall business efficiency. can prevent potential problems from escalating, improve customer satisfaction, and minimize negative impacts on business operations. Anomaly detection Meaning ● Anomaly Detection, within the framework of SMB growth strategies, is the identification of deviations from established operational baselines, signaling potential risks or opportunities. and proactive support demonstrate a commitment to customer care and can significantly enhance customer loyalty.

Table 2 ● Advanced Chatbot Feature Set

Advanced Analytics and Optimization Continuous Improvement Loop

Advanced chatbot strategies rely on sophisticated analytics and continuous optimization to maximize performance and ROI. Moving beyond basic metrics, advanced analytics Meaning ● Advanced Analytics, in the realm of Small and Medium-sized Businesses (SMBs), signifies the utilization of sophisticated data analysis techniques beyond traditional Business Intelligence (BI). provide deeper insights into chatbot effectiveness and customer behavior, enabling data-driven improvements and strategic decision-making.

AI-Powered Chatbot Analytics Dashboards

Advanced chatbot platforms offer AI-powered analytics dashboards that provide comprehensive insights into chatbot performance. These dashboards go beyond basic metrics to provide more granular data and visualizations, such as conversation flow analysis, intent recognition accuracy, sentiment trends, and user behavior patterns. AI-powered analytics can automatically identify areas for improvement, highlight successful conversation flows, and surface key customer insights. These advanced dashboards empower SMBs to monitor chatbot performance in real-time, identify optimization opportunities, and make data-driven decisions to enhance chatbot effectiveness.

Machine Learning-Driven Optimization

Leverage machine learning algorithms to automatically optimize chatbot performance over time. Machine learning can be used to refine NLU models, improve intent recognition accuracy, personalize response phrasing, and optimize conversation flows based on real-world user interactions. Automated optimization reduces the manual effort required to maintain and improve chatbot performance, ensuring that chatbots are continuously learning and adapting to evolving customer needs and preferences. Machine learning-driven optimization creates a continuous improvement loop, maximizing chatbot effectiveness and ROI over the long term.

Integration with Business Intelligence (BI) Tools

Integrate chatbot analytics Meaning ● Chatbot Analytics, crucial for SMB growth strategies, entails the collection, analysis, and interpretation of data generated by chatbot interactions. data with business intelligence (BI) tools to gain a holistic view of chatbot performance in the context of broader business operations. BI integration allows SMBs to combine chatbot data with data from other sources, such as CRM, marketing automation, and sales platforms, to gain deeper insights into the impact of chatbots on overall business performance. For example, BI tools can be used to analyze the correlation between chatbot usage and customer lifetime value, track the impact of chatbots on sales conversion rates, or measure the ROI of chatbot investments across different business units. BI integration provides a comprehensive and data-driven understanding of chatbot value and enables strategic decision-making at the organizational level.

By embracing AI and NLP, leveraging predictive capabilities, and implementing advanced analytics and optimization strategies, SMBs can transform chatbots from simple customer service tools into powerful engines for growth, competitive advantage, and exceptional customer experiences. This advanced approach positions SMBs at the forefront of chatbot innovation and enables them to unlock the full potential of conversational AI.

References

• Kaplan Andreas M., and Michael Haenlein. “Siri, Siri in my Hand, Who’s the Fairest in the Land? On the Interpretations, Illustrations and Implications of Artificial Intelligence.” Business Horizons, vol. 62, no. 1, 2019, pp. 15-25.
• Shawar, Bayan A., and Erik Cambria. “A Review of Definition, Types and Applications of Chatbots.” 2023 3rd International Conference on Computer Science and Information Technology (CSIT), 2023.