Expert’s Thoughts
"The recent statistics say that the global market value of AI in marketing has reached almost 50 billion USD, and the number will double by 2028 already. In addition, the most effective applications of AI in marketing automation are audience targeting, analytics, personalization and customer engagement.
Silk Data prepared the following blogpost to show how AI is used in customer engagement solutions that bring efficiency and business value to company’s marketing and customer support policies."
Yuri Svirid, PhD. — CEO Silk Data
What does AI Customer Engagement Mean?
The question of using AI for consumers attraction or finding the best AI tools for customer engagement requires consideration of several important aspects.
A Few Words About Customer Engagement
Customer engagement is the sum of all interactions and experiences a person has with a company’s brand. It's not a single transaction but the ongoing, financial and emotional relationship between a consumer and business. While customer acquisition is about making a first impression, customer engagement is about building long-last relations.
It's typically measured by a customer's active participation in the life of your business, their loyalty to brand and willingness to advocate for you company. This includes everything from opening your emails and reading your content to making repeat purchases and defending your brand in online discussions.
This genuine connection is one of the most valuable assets of modern business. A highly engaged customer is not only more likely to be loyal but also more profitable over their lifetime. Through that, customer engagement has one of the highest priorities in marketing, and no small part of AI solutions are developed to assist marketers in this task.
Why do You Need AI in Customer Engagement?
This question touches on the need to fulfill customer expectations and ensure competitive survival. Today's customers don't just want good service – their demand is for personalized and seamless experiences along with unprecedented convenience across every channel.
Through that, companies need AI because they believe it can transform customer engagement. Business gets the opportunity not to just response to the market shifts or ever-changing customer demands, but to proactively grow. AI implementation will allow to fulfill a few business needs.
- To keep pace with modern expectations. Customers expect the highest level of convenience while interacting with your brand. They need instant answers and flawless service. AI-powered agents provide immediate resolution, solving the problem. If properly fine-tuned, they can provide answers to user requests quicker than any human specialist.
- To understand your customers on a scale. No human can analyze millions of data points from emails, websites and social media chats and purchases info to understand a single customer's journey. AI can use this data to deliver personalized product recommendations, content and support.
- To empower your marketing team. By automating low-level routine queries, AI frees your human specialists to focus on other tasks, like handling complex, emotional and high-value interactions that require empathy and creativity in problem-solving.
- To move from reactive to proactive strategy. Advanced AI agents can predict issues before they happen. By analyzing user behavior and intelligent monitoring of activities, AI can identify a customer who is struggling and automatically offer help or alert a support agent to intervene. Such a policy reduces customer frustration to a minimum, increasing the overall satisfaction of interacting with the company’s products and services.
In other words, you don't implement AI to replace humans, but to increase overall efficiency of your business and marketing activities. Through that, AI becomes a valuable tool that allows companies and their marketing and customer support departments to build deeper, more meaningful and, in the end, more profitable relationships with every single customer, without being limited by time or resources.
Technologies Lying Behind AI-Based Customer Engagement
AI’s work in customer engagement is based on various technologies that allow it to efficiently perform its functions.
- Natural language processing.NLP allows machines to read, process, understand and make sense of natural human language. It powers chatbots and virtual assistants, enabling them to perceive a customer's question (even with typos or slang), understand its intent and generate human-like responses.
- Machine learning. ML is the mechanism that allows AI agent to learn and improve its work over time without being explicitly programmed for every customer interaction scenario. It analyzes vast amounts of historical data (like purchase history, customer support tickets or clickstream data) to identify patterns and make predictions. This is the technology that drives personalization engines and routes tickets to the best-suited human specialist, if the AI capabilities are not enough.
- Predictive analytics. This is the technology of AI using historical data and statistical algorithms in combination with ML techniques to identify the probability of future events and outcomes. It forecasts customer behavior, such as the probability of a customer making a purchase or their interest in a specific upsell. In other words, predictive analytics is a technology that allows for highly targeted marketing campaigns and proactive retention strategies.
- Computer vision. This technology enables machines to ‘see’ and interpret visual information. In customer engagement, it can be used for visual search (like snapping a picture of a product to find it online), augmented reality try-ons or automated images analysis shared with customer support (for example, identifying a damaged product from a photo).
What are the Benefits of AI Customer Engagement?
Integrating AI into your customer engagement strategy is about unlocking valuable traits that allow companies to transform relations with their audience. Here are some of the most impactful advantages.
24/7 availability
The modern consumers pay less attention to standard business hours but operate on their own schedule. A question can arise at midnight, or an order can be placed from a different time zone on a weekend. AI ensures that your brand is always ready.
AI-powered chatbots and advanced AI assistants can handle a vast range of common queries, from orders tracking to answering client requests, instantly, at any hour of the day.
This round-the-clock service dramatically improves customer satisfaction and loyalty, by eliminating the frustration of waiting. For your business, it means capturing leads and supporting customers without the additional costs of hiring an additional human team for 24/7 availability.
Enhanced scalability
Any sudden surge in market demand can overwhelm traditional customer service, leading to long wait times, dropped queries and damage to your brand. AI provides a scalable solution.
A properly fine-tuned AI system can handle tens of thousands of user requests and data flows simultaneously without any sufficient delays. Through that, your business can work with peak-season traffic, so organic growth spikes smoothly and consistently.
As a result, your business scales its customer operations with minimum effort, you reduce the workflow on your human operators, while the quality of service remains high.
Proactive engagement
An AI tool allows you to shift your marketing and customer support strategy from a reactive model (i.e. waiting for the customer to complain) to a proactive model (i.e. solving it before it occurs or somebody notices).
By analyzing user behavior in real-time, the agent can identify signals of confusion or frustration. This is an approach of using AI-based predictive analytics that will also attract your customers through demonstration of your attentiveness to their needs.
Overall, this method helps reduce the number of support tickets, decreases cart abandonment rates and builds trust in your brand.
Smart content suggestions
Customers expect recommendations that are tailored to their unique tastes and behaviors. Smart AI agents can ensure this at a level of precision that is hard to achieve and maintain manually.
The implemented machine learning algorithms analyze user's browsing history, their past purchases and engagement patterns to build a detailed customer avatar. This avatar is then used to curate and suggest products, articles or services that the individual is most likely to find relevant to them.
This hyper-personalization drives key business metrics. It increases average order value through effective cross-selling and up-selling, boosts conversion rates by showing customers exactly what they want, and enhances engagement by making every interaction feel unique.
Bonus. Use cases
To reinforce the value of possible benefits you can get from AI implementation, we present a few successful examples of its usage.
- Skillshare’s predictive recommendations.Skillshare is one of the world’s largest online learning communities for creativity, that now offers more than 30 thousand classes to almost 800 thousand students. The company’s marketing team leverages AI-based predictive recommendations to increase both efficiency and personalization of its marketing affiliation campaigns. These recommendations match each user in the corporate client system with courses suited to their unique needs. The match itself is based on analysis of user behavior, their activity and interests demonstrated in the service.
- Sweetwater’s smart client segmentation.Sweetwater is one of the leading online music retailers, whose marketing team leverages AI to enrich client interactions, using predictive AI models to identify customers most likely to engage. The result is used to tailor messages based on each customer’s musical preferences and browsing behavior. In addition, Sweetwater’s extensive product catalog is enhanced by AI-powered recommendations that ensure each customer receives relevant, personalized suggestions.
- CarParts’ products recommendations.CarParts is one of the leading online auto parts and accessories retailers. With a catalog of over 1 million SKUs, the marketing and sales teams rely on AI to recommend relevant products and content based on each user’s vehicle type, browsing their activity and behavior. These personalized recommendations span across web and email channels. This approach has delivered a 400% increase in click-through rate, and the marketing team saved 50 hours per week on average by automating time-consuming tasks that once required engineering department support.
Vital Considerations
While the benefits are obvious, a successful AI implementation requires careful consideration of several critical challenges.
Data privacy concerns
AI systems are powered by data, and the task of properly handling this data occurs. Customers are highly concerned about their personal information security, and various data security and privacy regulations (like GDPR and CCPA) enforce companies to follow strict guidelines.
The business leveraging AI in customer engagement must ensure that the data collected for AI training and operation is securely stored and used with all ethical and legal considerations. A data breach or misuse of personal information can result in massive loss of trust.
To solve the problem, the company should implement robust data governance policies, anonymize data where possible, and choose AI solutions based on DevSecOps policies.
Integration issues
An AI tool is the most efficient, as it is connected to your existing business ecosystem. Even the most advanced AI that doesn't interact with your CRM, can’t work with marketing and customer support ticketing system or e-commerce platform will lead to additional data fragmentation and poor customer experience.
Poor integration leads to an AI that has an incomplete picture of the customer journey, providing inaccurate or irrelevant responses.
The solution to the problem lies in a consistent phased implementation strategy with a clear API-first approach. Developers should be able to build custom connectors and ensure seamless data flow between your new AI agent and the existing tech stack.
Customer trust issues
Recent research by Statista indicates that only 46% of customers were satisfied with AI usage in commercial services, while more than 50% experienced discomfort of digital brand ambassadors. The dissatisfaction of interacting with a bot, along with fear of depersonalization, can make customers wary of AI. Statistics say that most people want to know they are being understood by a real human.
This is the problem of overall quality of AI implemented into your marketing and customer engagement system. If an AI agent makes obvious errors or fails to timely delegate the task to a human agent, it will frustrate customers and discourage their trust in your brand.
To solve the problem, the company should be honest with customers. It must be clear when a customer is interacting with an AI. Design the experience with clear off-ramps to human support. The focus should be on using AI to augment and reinforce human agents, not on total replacement. Even the most prominent AI agents are still bad at dealing with complex or emotional issues.
Ignoring all the above-mentioned issues can lead to AI implementation project failure, wasted investment and damage to your brand reputation.
How does Silk Data Help in Building AI Customer Engagement Solutions?
Successful dealing with the complexities of AI implementation requires a partner with both technical expertise and a firm market vision. At Silk Data, we guide you through the entire lifecycle, transforming the potential of AI into a real efficient tool for your business.
Full development cycle
We don't just code – we provide a full-fledged solution. Our team manages your project from mere concept to real-world launch, ensuring every step is aligned with your business goals.
Our approach is in smooth development and cooperation process that includes:
- Initial consultation (discussing your plans and business goals from AI integration).
- Requirements setting and project planning (defining the functional requirements for the future solution and setting the project stages).
- Data auditing and preparation (gathering and cleaning the data necessary for model training and setting its working patterns).
- Model selection and training (choosing either between ready-to-use API, like that of ChatGPT and other popular LLM, or custom model development from scratch).
- Integration with your systems.
- Quality assurance (performed at every stage, from testing of the initial requirements to final product quality assurance).
In other words, we focus on building AI that is not just technically sound, but also perfectly tailored to your unique operational needs and customer journey.
Proof-of-concept
Before committing significant resources into a new AI project, it's crucial to validate the feasibility and potential prospects of the solution.
Silk Data provides AI proof-of-concept services that will allow to develop a focused, functional prototype to demonstrate the core value of the proposed AI solution in a real-world scenario. This PoC allows you to test your hypotheses, gather stakeholders' feedback and make a data-driven decision on whether to proceed with a full-scale project. The PoC itself will require minimal upfront investment, and the result can be presented in mere weeks or even days.
Maintenance and support
To remain accurate and efficient, any AI agent requires continuous monitoring and refinement.
Through that, we provide ongoing maintenance and support services to ensure your AI solution evolves with your business and your customers. This includes:
- Performance monitoring.
- Model retraining (loading new data to the model to optimize its performance according to new conditions).
- Updating the system (to handle new edge cases).
- Technical support.
In other words, we ensure your AI engagement platform gets smarter over time, delivering lasting value.
Conclusions
Integrating artificial intelligence is no longer a magical advantage but a fundamental component of modern business strategy. From providing 24/7 support and unparalleled personalization to enabling proactive service and effortless scalability, AI empowers businesses to build deep, meaningful customer relationships that drive loyalty and growth.
Naturally, when business executives search for the best AI tools for customer engagement, they are looking for more than just a piece of software. They are seeking a strategic solution that can seamlessly integrate into their operations, respect customer privacy and evolve with the ever-growing market needs. The question of which AI offers the best customer engagement does not have a one-sided answer, as the ‘best’ solution is the one that is tailored to your unique business goals, data ecosystem and customer journey.
This is where the journey begins. By addressing vital considerations like data privacy, integration issues and overall consumer trust and by partnering with an experienced team for the full development cycle you can confidently leverage the power of AI.
Frequently Asked Questions
The key benefits are 24/7 availability for instant support, enhanced scalability to handle traffic spikes, proactive engagement that solves issues before they escalate and smart content suggestions that drive sales and increase customer satisfaction through hyper-personalization.
The primary risks involve data privacy concerns, as AI requires careful handling of customer data, integration issues with existing systems like your CRM and customer trust issues, which can arise if the AI provides poor experiences or isn't transparent. A phased, strategic implementation is crucial to mitigate these risks.
Your business is likely ready if you have a consistent volume of customer inquiries, an understanding of the necessity of response times and personalization improvements and a clear set of goals (like reducing support tickets or increasing sales). Starting with a PoC is an excellent way to test feasibility with minimal investment.
Our Solutions
We work in various directions, providing a vast range of IT and AI services. Moreover, working on any task, we’re able to provide you with products of different complexity and elaboration, including proof of concept, minimum viable product, or full product development.
