#AI-driven Recommendations

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How Product Recommendations in E-commerce is important to Boost Engagement & Sales - Wizzy.ai

Unleash the power of tailored product recommendations in e-commerce! Discover how to boost engagement and maximize sales with proven strategies. Learn why recommendations are vital for success in today’s digital marketplace. Optimize your Ecommerce store with seamless site search functionality.

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The Role of Personalization in Online Retail

In the fast-paced world of online retail, personalization has become the game-changer that sets brands apart. It’s not just about making shopping easier; it’s about crafting a Personalized Shopping Experience that feels almost tailor-made. From dynamic content to AI-driven recommendations, personalization transforms how we shop, turning routine transactions into engaging experiences. Let’s delve into the multifaceted role of personalization in online retail and understand why it's more than just a trend.

Understanding E-Commerce Personalization

Personalization in e-commerce is the practice of using data to provide a tailored shopping experience for each user. But what does that really mean? Simply put, it involves customizing the online shopping journey based on individual preferences and behaviors.

What is E-Commerce Personalization?

E-commerce personalization involves tailoring website content, product recommendations, and marketing messages to fit the specific needs and preferences of each visitor. By analyzing user data and behavior, retailers can present a shopping experience that feels uniquely relevant to each individual.

For instance, imagine browsing an online shopping site for clothes. Instead of a generic homepage, you’re greeted with products based on your past searches, purchases, and even browsing history. This level of customization enhances user engagement and drives sales.

The Benefits of Personalization

The benefits of personalization are manifold. Here’s a quick rundown:

Enhanced Customer Engagement: Personalized experiences keep users hooked and more likely to return.

Increased Conversion Rates: Tailored recommendations often lead to higher sales as they meet users' specific needs.

Improved Customer Retention: A personalized shopping journey fosters brand loyalty and repeat business.

The Power of Behavioral Targeting in Retail

Behavioral targeting involves analyzing user behavior to predict and influence future actions. By leveraging behavioral targeting, retailers can offer more relevant promotions and recommendations.

How Behavioral Targeting Works

Behavioral targeting relies on data collected from user interactions, such as:

Browsing History: Pages visited, time spent on each page.

Search Queries: Keywords and products searched.

Purchase History: Previous purchases and frequency.

This data helps create detailed consumer profiles, allowing retailers to craft highly targeted marketing campaigns. For instance, if you frequently browse for athletic wear, you might receive exclusive offers on sports gear or new arrivals in that category.

Examples of Effective Behavioral Targeting

Amazon's Recommendation Engine: Amazon’s "Customers who bought this also bought" is a prime example of behavioral targeting. It uses your browsing and purchasing history to suggest products you’re likely to be interested in.

Netflix’s Personalized Content Suggestions: Netflix’s algorithm analyzes your viewing history to recommend shows and movies you might enjoy, keeping you hooked to their platform.

Dynamic Content Personalization: Making Every Interaction Unique

Dynamic content personalization refers to the practice of changing website content in real-time based on user data. This technique ensures that each visitor sees a version of the site that’s tailored just for them.

Why Dynamic Content Matters

Dynamic content makes the shopping experience more engaging by presenting relevant products and offers. For example:

Homepage Customization: A visitor interested in electronics might see a homepage featuring the latest gadgets and tech deals.

Personalized Email Campaigns: Emails that highlight products based on recent searches or past purchases.

Implementing Dynamic Content Personalization

To effectively implement dynamic content, retailers need:

Robust Data Analytics: To collect and analyze user behavior.

Real-Time Data Processing: To update content as users interact with the site.

Flexible Content Management Systems: To manage and display personalized content efficiently.

Leveraging AI-Driven Recommendations

Artificial Intelligence (AI) plays a crucial role in enhancing personalization. AI-driven recommendations use machine learning algorithms to analyze vast amounts of data and provide personalized product suggestions.

How AI-Driven Recommendations Work

AI algorithms analyze:

User Behavior: Browsing patterns, purchase history.

Similar User Profiles: What other users with similar behavior have purchased.

Based on this analysis, AI can suggest products that are highly likely to interest the user. For example, if you’ve been looking at hiking boots, an AI system might recommend related accessories like trekking poles or waterproof jackets.

Benefits of AI-Driven Recommendations

Increased Sales: Personalized recommendations lead to higher conversion rates.

Enhanced User Experience: Users find it easier to discover products they like.

Efficient Inventory Management: By predicting trends and preferences, AI helps in better stock management.

Omnichannel Personalization: Integrating Online and Offline Experiences

Omnichannel personalization ensures a seamless experience across different platforms and touchpoints. It integrates online and offline data to provide a cohesive shopping journey.

What is Omnichannel Personalization?

Omnichannel personalization involves syncing user data across various channels:

Online: Websites, social media, email campaigns.

Offline: Physical stores, customer service interactions.

Creating a Unified Experience

To achieve effective omnichannel personalization:

Centralize Data: Gather and integrate data from all customer touchpoints.

Consistent Messaging: Ensure that marketing messages are consistent across channels.

Cross-Channel Engagement: Enable customers to switch between channels seamlessly, such as starting a purchase online and completing it in-store.

Personalized Shopping Experience: Real-World Examples

Let’s explore some real-world examples of how personalization enhances the shopping experience:

1. Sephora’s Beauty Insider Program

Sephora uses personalization to offer a tailored beauty experience. Their Beauty Insider program rewards members with personalized product recommendations, exclusive discounts, and customized beauty tips based on their purchase history and preferences.

2. Starbucks’ Personalized Offers

Starbucks’ loyalty program provides personalized offers and rewards based on users' purchasing habits. The app sends tailored promotions and suggestions, making each visit more relevant and enjoyable.

3. Zara’s Dynamic Website Experience

Zara’s website adapts in real-time to user preferences. For instance, if you frequently browse for men’s clothing, the homepage will highlight new arrivals and popular items in that category.

The Future of Personalization in Online Retail

Looking ahead, personalization will continue to evolve with advancements in technology. Here’s what to expect:

Enhanced AI Capabilities: More sophisticated algorithms will drive even better recommendations.

Greater Integration: Seamless integration across online and offline channels will become the norm.

Increased Privacy Considerations: As data usage grows, ensuring user privacy will be crucial.

Conclusion

The role of personalization in online retail is undeniable. It transforms the shopping experience from mundane to memorable by offering tailored content, recommendations, and interactions. As technology advances, the scope of personalization will only broaden, making it an indispensable aspect of modern retail. By leveraging e-commerce personalization strategies, retailers can enhance customer satisfaction, drive sales, and foster brand loyalty.

So, the next time you find yourself on an online shopping site for clothes, take a moment to appreciate the personalized experience crafted just for you. It’s not just about convenience; it’s about creating a shopping journey that feels uniquely yours.

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3 Ways to Boost Sales with Artificial Intelligence

Delivering Hyper-Targeted Ecommerce Experiences The era of generic, one-size-fits-all ecommerce experiences is fading fast. In its place, we’re witnessing the rise of hyper-personalization, driven by the power of Artificial Intelligence (AI). Gone are the days of basic product recommendations. Today, AI algorithms can analyze vast amounts of customer data – browsing history, purchase history,…

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Boost retail customer retention with AI-powered personalization, real-time analytics, and seamless experiences that keep customers coming back.

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Boost retail customer retention with AI-powered personalization, real-time analytics, and seamless experiences that keep customers coming back.

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Harness AI-driven recommendations to boost customer retention in retail, delivering personalized experiences at every touchpoint.

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How can AI improve customer retention rates in retail?

Harness AI-driven recommendations to boost customer retention in retail, delivering personalized experiences at every touchpoint. In today’s highly competitive retail landscape, customer retention is more than just a business priority—it’s essential for long-term success. With acquisition costs on the rise, retaining customers has become a more cost-effective strategy than constantly finding new…

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How can AI improve customer retention rates in retail?

See how AI-powered chatbots can boost customer retention by enhancing support and delivering personalized shopping experiences.

In today’s highly competitive retail landscape, customer retention is more than just a business priority—it’s essential for long-term success. With acquisition costs on the rise, retaining customers has become a more cost-effective strategy than constantly finding new ones. Artificial Intelligence (AI) offers a solution to this challenge by transforming how retailers engage with their customers. Through personalized experiences, predictive analytics, automated customer support, and intelligent loyalty programs, AI is revolutionizing customer retention. This article dives deep into how AI technologies drive customer loyalty in the retail industry, where customer experience expectations are high.

Introduction

The Importance of Customer Retention in Retail

Customer retention is the lifeblood of any successful retail operation. It is well-known that acquiring new customers is far more expensive than retaining existing ones. In the retail sector, which thrives on repeat business and customer loyalty, ensuring customers return consistently is critical. Moreover, loyal customers are more likely to engage with brands over time, offer valuable feedback, and advocate for the brand through word-of-mouth marketing.

Why AI is a Game-Changer for Customer Engagement and Retention

The rise of AI is reshaping customer engagement dynamics by enabling retailers to offer tailored, seamless, and proactive experiences. AI is no longer just a buzzword; it is a transformative tool that provides retailers with real-time data, deep insights, and automation to foster stronger connections with their customer base.

Key AI Technologies That Influence Retention Rates

Some of the major AI technologies influencing customer retention include:

• AI-driven personalization engines that curate shopping experiences.

• Predictive analytics to foresee customer behaviours.

• Automated customer support tools like AI-powered chatbots.

• Sentiment analysis tools to gauge customer emotions.

The Role of Personalization in Customer Retention

Personalization has become synonymous with customer satisfaction in today’s retail landscape. Consumers no longer want generic shopping experiences; they expect brands to understand their preferences and cater to their specific needs.

How AI Enhances Personalized Shopping Experiences

AI technologies analyse vast amounts of customer data to deliver personalized shopping experiences. This includes tailoring product recommendations, marketing messages, and shopping suggestions based on each customer’s previous behaviours and preferences. With AI’s ability to process big data, it can quickly recognize patterns, such as purchase history, browsing habits, and interactions with the brand, to deliver personalized offers and recommendations in real time.

AI-Driven Product Recommendations Based on Past Behaviour

Product recommendations are a prime example of AI enhancing personalization. AI engines analyse customer browsing and purchase history to suggest products that resonate with their taste and preferences. For example, Amazon’s recommendation system is powered by AI that identifies products a customer is more likely to buy based on what they have browsed or purchased in the past. These tailored suggestions drive more sales and foster customer loyalty.

Dynamic Pricing and Targeted Offers to Retain Customers

AI can also influence pricing models by providing dynamic pricing, where product prices fluctuate based on factors like demand, customer profiles, or market trends. This strategy can be used to offer targeted discounts or promotional offers to retain at-risk customers, thereby reducing churn and boosting customer loyalty.

Predictive Analytics: Forecasting Customer Behavior

Predictive analytics is one of the most powerful tools AI offers for customer retention. By leveraging historical data, AI-powered predictive models can forecast future customer behaviors, such as purchase patterns, potential churn, or changes in loyalty.

Identifying Churn Risk

AI-driven predictive analytics can help retailers identify which customers are most likely to stop engaging with the brand. For example, if a customer has not interacted with the brand or made a purchase for a certain period, the AI system can flag this as a potential churn risk. This allows retailers to take proactive steps, such as sending personalized offers or re-engagement messages to retain that customer.

Proactive Customer Retention Strategies

Armed with predictive insights, retailers can create retention strategies that are pre-emptive rather than reactive. AI allows businesses to address issues or concerns before they lead to customer loss. For example, predictive models can alert a retailer to send a special offer to a customer who has shown signs of disengagement, such as browsing products but abandoning the cart multiple times.

Case Study: AI in Retail Predictive Analytics

Several large retailers, including Walmart and Target, leverage predictive analytics to maintain customer loyalty. By analysing customer data in real-time, they can offer targeted promotions and prevent churn. These predictive models have proven to be effective in retaining customers and boosting long-term loyalty.

AI-Driven Customer Support for Better Retention

Customer service is often the cornerstone of customer retention. When issues arise, customers expect prompt and efficient support, and AI is revolutionizing how retailers meet these expectations.

AI Chatbots and Virtual Assistants

AI-powered chatbots have become essential for delivering fast and efficient customer support. These chatbots can answer FAQs, resolve basic issues, and even assist with product recommendations, all without human intervention. By handling a large volume of customer queries, chatbots free up human agents to focus on more complex issues, leading to quicker resolution times and improved customer satisfaction.

Automated Support Leads to Quicker Issue Resolution

With AI, automated customer support goes beyond chatbots. AI-driven systems can route more complex issues to the appropriate department, prioritize high-value customers, and even provide agents with suggestions on how to handle particular cases. This reduces friction in the customer service process, ensures faster resolution of issues, and boosts retention.

Importance of 24/7 Support for Retaining Customers

AI-driven customer support operates around the clock, offering 24/7 service that can meet the needs of global customers. This ensures that customers receive assistance whenever they need it, which is particularly crucial in retaining those who might otherwise feel neglected.

Leveraging AI for Customer Feedback and Sentiment Analysis

Customer feedback is a valuable resource for retailers to improve their offerings. However, manually analysing large amounts of feedback can be time-consuming and inefficient. This is where AI comes in.

Real-Time Feedback Analysis

AI allows retailers to analyse customer reviews and feedback in real-time. By processing thousands of data points from social media, surveys, and customer reviews, AI tools can extract valuable insights about what customers like and dislike.

Sentiment Analysis to Understand Customer Emotions

Sentiment analysis uses AI to detect and interpret the emotional tone behind customer comments. By understanding customer sentiment, retailers can quickly address negative feedback and refine their services. Positive sentiments, on the other hand, can be leveraged to strengthen customer relationships.

Leveraging Feedback for Better Customer Experiences

Retailers can use insights from sentiment analysis to adjust their strategies and offer better experiences. For example, if sentiment analysis reveals that customers are dissatisfied with shipping times, the retailer can prioritize logistics improvements to enhance customer satisfaction and retention.

AI and Loyalty Programs: Reinventing Retention Tactics

Loyalty programs are a proven tactic for retaining customers. However, AI takes these programs to a new level by making them more intelligent and personalized.

Creating Personalized Loyalty Programs with AI

AI allows retailers to create personalized loyalty programs by analysing customer behaviour and engagement. Rewards and offers can be tailored based on customer preferences, purchase frequency, and lifetime value, ensuring that loyalty programs are relevant and effective.

Dynamically Adjusting Rewards Based on Behaviour

AI systems can dynamically adjust loyalty rewards in real-time based on customer actions. For instance, if a customer frequently purchases a specific brand, the AI system might offer exclusive discounts or rewards for continued loyalty to that brand.

Examples of Successful AI-Powered Loyalty Programs

Sephora’s Beauty Insider Program is a prime example of an AI-driven loyalty program. Sephora uses AI to offer personalized product recommendations, targeted promotions, and dynamic rewards, leading to increased customer engagement and retention.

AI’s Role in Multi-Channel Engagement

In today’s retail world, customers interact with brands across multiple channels—both online and offline. AI helps retailers ensure consistency and continuity in these interactions, which is key to retaining customers.

Optimizing Interactions Across Platforms

AI-powered systems ensure that customer interactions are optimized across all platforms, whether they are engaging with the brand via email, social media, or in-store. This creates a seamless experience that increases customer satisfaction and loyalty.

Importance of Consistent Omnichannel Experiences

Consistency is crucial in omnichannel retailing. AI ensures that customers receive consistent messaging, offers, and service quality regardless of the channel they use. This builds trust and keeps customers coming back.

Case Study: Retailers Implementing AI for Multi-Channel Engagement

Brands like Nike have successfully integrated AI into their multi-channel engagement strategies. Nike uses AI to provide personalized recommendations through their app, website, and physical stores, ensuring a consistent and engaging customer experience.

The Ethical Use of AI in Customer Retention

While AI offers immense potential for improving customer retention, it also raises important ethical questions, particularly around data privacy and transparency.

Data Privacy and Ethical Considerations

Retailers must handle customer data responsibly when using AI. Customers are increasingly aware of how their data is being used, and any misuse can erode trust. Adhering to strict data privacy regulations, such as GDPR in Europe, is essential.

Building Trust Through Transparent AI Practices

Transparency is key to maintaining customer trust. Retailers should be upfront about how they are using AI and customer data, ensuring that AI-driven recommendations and strategies are clear and understandable.

Conclusion

AI has the potential to revolutionize customer retention strategies in the retail sector. From personalization and predictive analytics to automated customer support and loyalty programs, AI empowers retailers to build stronger, more enduring relationships with their customers. As the future of retail becomes increasingly data-driven, businesses that adopt AI-powered retention strategies will stand out in the competitive markets.

Retailers must begin embracing AI now, not just to stay ahead but to meet evolving customer expectations and create seamless, personalized experiences that foster long-term loyalty.

Frequently Asked Questions (FAQs)

1. How can AI improve customer retention in retail?

AI enhances customer retention by leveraging AI-Powered Retention Strategies that analyze customer behavior and predict churn risks. Through AI-Driven Predictive Analytics, retailers can proactively address potential issues by offering tailored solutions before the customer leaves. AI-Powered Predictive Models enable retailers to forecast trends and preferences, ensuring personalized customer experiences, which boosts loyalty. AI-driven insights can also optimize engagement timing, ensuring promotions and communications hit at the right moment, improving overall retention rates. By integrating AI-Driven Systems, retailers can continuously refine strategies based on real-time data, improving long-term customer satisfaction.

2. What role do AI-driven loyalty programs play in customer retention?

AI-Driven Loyalty Programs personalize rewards based on individual preferences, enhancing the customer experience and fostering long-term relationships. By utilizing AI-Driven Recommendations and Strategies, these programs adapt in real-time to customer behaviors, offering more relevant rewards and incentives. This targeted approach increases engagement, encouraging repeat business. Additionally, AI-Powered Predictive Models help identify trends and preferences, enabling retailers to offer timely, valuable rewards that resonate with customers. Ultimately, such programs drive customer satisfaction and loyalty, reducing churn rates while increasing retention through personalized, AI-driven interactions.

3. How does AI-driven customer support improve retention?

AI-Driven Customer Support solutions, such as AI-Powered Chatbots, offer instant, 24/7 assistance, significantly improving customer satisfaction. By analyzing common queries and preferences, AI can deliver more relevant responses and faster resolutions. Through the integration of AI-Driven Systems, support platforms can predict potential issues and proactively address them before they escalate, improving overall customer experience. This real-time, adaptive support helps retailers resolve issues quickly, reducing the likelihood of customer churn. Moreover, seamless and efficient support strengthens customer loyalty, contributing to improved retention rates.

4. How do AI-driven recommendations enhance customer loyalty?

AI-Driven Recommendations and Strategies offer personalized product suggestions based on customer preferences and browsing history. By utilizing AI-Powered Predictive Models, retailers can predict customer needs and preferences, delivering highly relevant recommendations that increase the likelihood of purchases. These personalized interactions make customers feel valued, driving repeat purchases and building brand loyalty. Furthermore, AI can adapt to changing customer behaviors, refining recommendations to maintain engagement over time. This personalized, dynamic approach to customer interaction plays a crucial role in fostering long-term loyalty and improving overall retention in retail.

5. Can predictive analytics help improve customer retention?

Yes, AI-Driven Predictive Analytics helps retailers anticipate customer needs, predict churn, and identify opportunities to enhance engagement. By analyzing vast amounts of customer data, these models provide actionable insights into behavior patterns and trends. Retailers can leverage this data to implement AI-Powered Retention Strategies that proactively address issues or offer personalized experiences that keep customers engaged. Additionally, AI-Powered Predictive Models enable retailers to optimize timing for promotional offers, communications, or product recommendations, further improving retention rates by aligning with customer preferences and behavior.

6. How do AI-powered chatbots influence customer retention?

AI-Powered Chatbots provide customers with instant, 24/7 support, improving satisfaction and retention rates. By integrating AI-Driven Systems, chatbots can learn from past interactions, offering more personalized and accurate responses over time. These bots reduce customer wait times, resolve issues efficiently, and provide seamless communication across multiple platforms, enhancing the overall customer experience. In addition, AI-Powered Predictive Models allow chatbots to anticipate customer needs and offer proactive assistance, preventing potential churn. The continuous improvement of these systems strengthens customer loyalty, ultimately contributing to higher retention rates.

7. How can AI improve the timing of customer engagements?

Through AI-Driven Predictive Analytics, retailers can optimize the timing of promotions, product recommendations, and communication based on customer behavior and engagement patterns. AI-Powered Predictive Models analyze real-time data to determine when a customer is most likely to engage with specific content, allowing for more effective outreach. By delivering timely, relevant interactions, retailers can improve customer satisfaction and drive repeat business. These AI-Powered Retention Strategies ensure that each touchpoint is meaningful and engaging, enhancing customer loyalty and reducing churn.

Original source : https://bit.ly/3ztz8mM

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Unlock AI-Powered Topic Recommendations for Targeted Traffic

The Role of Data in AI-Powered Recommendations Harnessing the Power of Data for Personalized Suggestions In the era of digital transformation, data serves as the cornerstone for driving AI-powered recommendations. Through the analysis of user behavior, preferences, and historical data, businesses can derive invaluable insights to offer personalized suggestions. This not only enriches the user…

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How Intelligent Recommendation Engines Reshape Choices?

Intelligent recommendation engines have become important tools that are changing how we make decisions in the era of excessive information. These engines evaluate enormous volumes of data and offer individualized recommendations based on user preferences. They are powered by sophisticated algorithms and machine learning. These recommendation engines are transforming the way that people make decisions, from streaming services to online retailers.

Reducing the overwhelming number of options available to users is one important way intelligent recommendation engines change decisions. These engines serve as individualized curators in a world overflowing with goods and entertainment, sifting through the clutter and presenting users with options that suit their tastes. This offers options that are more likely to resonate with the user, which not only saves time but also increases satisfaction.

Recommendation engines also facilitate the discovery of new interests. These systems can present users with material or products they might not have found on their own by examining user behavior and preferences. Because it constantly broadens users' horizons, this serendipitous element encourages a sense of discovery and keeps them interested.

Enhancing user engagement and retention is another important function of intelligent recommendation engines. These engines can modify and improve their recommendations over time by learning about the behavior of their users, resulting in a dynamic and customized user experience. This guarantees that users stay engaged with the site and encourages loyalty.

In summary, there is no denying the impact of sophisticated recommendation engines on molding decisions. These engines have become indispensable for navigating the wide array of possibilities available in our digital environment, from streamlining decision-making processes to encouraging inquiry and interaction. Recommendation engines will probably have a greater impact as technology develops, radically altering the way people make decisions in many spheres of their lives.

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Revolutionize Your E-Commerce Site Search with Wizzy - Request a Free Demo

Discover the power of AI-driven search optimization for your e-commerce store! Request a free demo of Wizzy and see how it boosts conversions and user engagement. Don’t miss this opportunity to transform your customer experience - learn about smarter search today!

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How NexMind Automates SEO Tasks for Top Rankings 2023

NexMind, an innovative AI-powered application that transforms how you run SEO duties and create content, can help you achieve extraordinary marketing success. Are you tired of doing keyword searches manually especially when you have a lot of work to do? Finding the right keyword for Google to rank for is not easy. It requires a lot of hard work in this fast-paced world. That’s why NexMind comes…

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Book 7, Chapter 7, Episode 103

Malleus made a zombieland lmao

Ok so remember last episode that mom mentioned that Ortho has a time limit of 20 minutes? Yeah, Malleus' magic is so complicated that it takes a super computer like Ortho 17 minutes to gather data. He's pressed on time, so he gets to work... UNTIL

???: "My my... And I was wondering what anomaly might be happening in my domain..."

Malleus: "You... Your appearance has changed, but you are the Littler Shroud, are you not?"

Ortho: "Malleus Draconia..! I knew it... So you did overblot."

Doggy 1: "GRRRR..."

Malleus wonders what Ortho was doing there, because he was quite sure the boy's sleeping soundly at Diasomnia. Ortho explains that it's too bad for Malleus because that body's already empty. He's escaped through the school's wireless LAN.

Ortho: "I'm just a self-driven AI program data... But even if I say that, you wouldn't really understand right."

Malleus: "In other words, your consciousness is that of a ghost that left its body to settle into another vessel... Did I get that right?"

Ortho: "Oh~! So that's how fairies would interpret data transmission!"

(HELP? WHAT KIND OF CONVERSATION IS THIS)

Ortho confirms that yeaaaah, that's basically how it works. So he can move through electronic waves to basically anywhere, even outer space! He also explains that he probed through underwater cables too, but everything was blocked by magic... but through his desperation he realized that wireless waves were accessible to him because

"Magic is the power of one's imagination. You need to understand something to conjure it... So naturally, you can't do something about things "you don't know about"."

Ortho found Malleus' weakness and exploited it! Malleus knows what cables are, but he doesn't know about the concept of wifi. He got outsmarted because of his ignorance omfg.

Ortho: "Aren't your cybersecurity awareness a bit dull? I recommend setting up a UTM in your magic domain."

LITTLE BOY'S DISSING THE OLD MAN OMFG!! FUCKING BURNED SDAKNJSDAKLAS

Malleus: "Yuuteeehm... Is that some sort of abbreviation for a technique?"

(He's actually talking to him in a civil manner??? Malleus is surprisingly in control of the clarity of his intellect...)

Ortho: "Ehh~ you don't know what that is? That's why you're getting tricked by a junior like me. You're one of the top 5 mages in the realm and a master of unknown ancient magic but... It doesn't matter."

HE'S SO MEAN??

"I WON'T FALL ASLEEP UNDER YOUR SPELL!"

Malleus: "Hm... I see. Well, then..."

Malleus: "An unsleeping, noisy mechanical doll can be silenced by shattering it to pieces."

HE'S SUDDENLY SO MORBID

Ortho: "If you try to do that, then... "I'll show you STYX's... Humanity's greatest technological power!"

Ortho notes to himself that Malleus seems to be ignoring the data-collecting machines he's brought with him. He has 13 minutes left before the data gathering completes, so he MUST buy time until then!

Malleus: "May I ask all uninvited guests to leave at once."

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Enhance your retail strategy with AI-powered systems that optimize retention through personalized customer journeys and real-time insights.

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Enhance your retail strategy with AI-powered systems that optimize retention through personalized customer journeys and real-time insights.

[rubylogan15]

See how AI-powered chatbots can boost customer retention by enhancing support and delivering personalized shopping experiences.