AI Agents for Marketing: A New Era of Automation

Marketing has become like a speed race today—think jet powered. The speed at which the marketplace operates is so fast that many traditional teams simply cannot keep up with the pace of today's events. As you are likely sleeping at night, others have already deployed AI agents to assist with prospecting—these agents will work 24 hours a day without limitation so they are constantly identifying leads and creating hyper-customized offers for those leads and closing on those leads without emotion or taking breaks.

I saw this first hand when I assisted with a variety of the leading crypto activities including the likes of 1inch or MultiversX. Automation will cost you 10% of your budget for every delayed transaction after you receive the first confirmation. Do you remember the awful evening of October 11, 2020, when the cryptocurrency trading market lost $22B in less than 60 minutes? Everyone on your team was looking for a way to manually determine what was happening and you were all panicking. Our team, ASCN, was using our AI agents to find arbitrage opportunities with pricing differences of up to 40% between exchanges, which resulted in making clients hundreds of thousands of dollars. There are extraordinary and amazing examples like this, but by the time you notice them, the event has already taken place.

The impact of this is pure raw strength.

"Traditional marketing can take hours to perform the analysis, while our AI agents can provide the same result in less than 10 seconds using Web3 data that ChatGPT and Grok do not have access to."

In three months from one project, our CAC decreased by 34%—the best we've seen in five years!

What Are AI Agents and How Do They Function in Marketing?

Definition & Role of AI Agents:

AI agents are virtual colleagues that you can count on to work 24 hours a day, 7 days a week. They analyze people's buying habits, assist with creating personalized emails and offers, sort through your projects, and create reports for you—no sleep, no vacation. Unlike traditional scripts, AI agents analyze the context surrounding each customer when responding to an "I want to buy"; they look at not just a customer's past purchases, but also look at current offers, the time of day, etc. Then they determine what the customer needs.

Traditional marketing tools such as CRM systems and basic email service providers work based on the rules they have been programmed with. For example, if the user has not opened an email after three days, then the system will automatically send another related email without understanding why the user has not opened; this is similar to sending exactly the same email to every customer in your database. In contrast, AI agents act as a psychologist would; AI agents learn about the customer through their social media activity, past purchases, and when they typically check their email; they will send an appropriate marketing message on Instagram to a customer who uses Instagram but has yet to open an email, taking into consideration the customer's preferences.

Traditional Marketing Tools vs. AI Marketing Tools

Understanding how both methods work in relation to each other helps determine which option provides the best opportunity to build strong relationships with the target audience. Compare an AI system with traditional marketing tools with respect to the following characteristics:

1. Decision-Making:
   • In traditional marketing, the decision-making process is rigidly defined by countless rules.
   • AI marketers can analyze the entire context in which the decision must occur.
2. Language Processing:
   • In traditional marketing, the language used is comprised of keywords.
   • With AI marketers, the system will identify the person's intention through natural language processing.
3. Personalization:
   • Traditional marketing uses general segments to identify a customer.
   • AI marketers will analyze the historical data about the customer and establish an individual approach.
4. Training:
   • Training for a traditional marketer is usually manual.
   • AI training occurs automatically through self-learning.
5. Reaction Time:
   • The average traditional marketer can take minutes to respond.
   • An AI marketer can respond in seconds.
6. Scaling Cost:
   • A traditional marketer will require additional personnel, so the cost is linear to scale.
   • An AI marketer has a fixed cost structure, so a single agent can complete thousands of tasks without increasing costs.

With an AI marketing agent, managers will no longer be required to manually filter and decide on leads. An AI marketing agent will filter and present the hottest deals available to the manager, along with a brief overview of critical deal elements. For example: "John is trying to buy product X for $5,000 and is able to receive a call when he becomes available on Friday at 15:00."

Types of AI Marketing Agents

Chatbots and Virtual Assistants.

The chatbot and virtual assistant are the initial points of contact between the client and the business. The bot has a real understanding of what it is talking about; can carry on a complex dialogue; and can switch to a live person when required. Unlike a simple FAQ using an instruction manual, the chatbot can answer simple questions just like a traditional marketing person by asking, "What method of withdrawal are you seeking?, What amount will you be withdrawing?, What is the limit on your current account?"

At ASCN.AI's Telegram Agent, the average response time for all crypto-blockchain-related queries is approximately 10 seconds, and the bot has extended knowledge of Web3 data that neither ChatGPT nor Grok possess. The response to the query about Solana (What caused the rise of Solana?) by artificial intelligence will access information from blockchain activities, social media analytics and articles to provide a succinct, current, and relevant answer.

When you ask an AI "What is the reason for the rise in Solana?" it will be able to find answers both on-chain and off-chain (including news articles, social media, etc.) to provide you with up-to-date and structured information.

Virtual assistants do more than just solve problems; they also follow & remember clients through the funnel process while encouraging the client to complete their purchase. For instance, if a customer leaves items in their cart, the virtual assistant will say to that customer, "Hey John, you have left a concern item in the cart! You have 10% off today."

This type of small improvement will raise conversion rates by 15-25%.

Personalization & Recommendation System

These virtual assistants will track the clicking habits of their users, what has been purchased and what other social networking sites were visited. They will have access to trading strategies, time frame and indicators of crypto currencies and therefore will send a signal based on these variables to entries and exits of those trades and will increase conversions to 22% for the first month. There are various technologies for this type of tracking: collaborative filtering, content analysis and hybrid models that guess at what you want now 85-90% of the time.

Agent Systems for Data Analysis & Forecasting

There are also several agents that can provide analysis of billions and billions of pieces of data, create demand forecasts and identify anomalies. These agents can be used to create optimizations for advertising campaigns, create budgets for required Customer Acquisition Costs (CAC) and identify true profitable areas.

I remember on the night of October 11, ASCN.AI had agents that scanned and analyzed order books, in real-time and that identified arbitrage opportunities with a difference of almost 40% between traditional exchanges and decentralized exchanges. The users that were able to act on time would close their deals 15-20 minutes earlier than when stabilization happened and would not have been able to do so if they would have had to do manually.

The models for prediction are based on regressions, neural networks and gradient boosting. This all relies on having very high-quality data and having different sources from Web3 connected to each other; therefore the level of accuracy is much higher than using universal AIs.

Machine Learning (ML) And Deep Learning (DL) Are The Technologies Behind AI Agents

ML is when systems learn through experience and therefore improved performance and accuracy has increased based on experience. In marketing, ML provides user segmentation data, prediction of churn, optimization of bids, and precision of personalization for each user. DL is a type of ML that has many levels of their neural network structure in order to help systems recognize text and emotion in a particular text and to generate that same type of content. The agent called ASCN.AI is using Web3 data (transactions, DeFi activities, community data, etc.) to generate insights that a chatbot using anything but Web3 data will be unable to provide to an end-user.

NLP Is The Way Agents Understand And Communicate With A Human

NLP allows agents to comprehend written words and respond as if they were a human being. By using NLP, agents can identify a person's emotional state (happy, angry, etc.), underlining the important points from their inquiry (if any exist), categorizing their inquiry into a known type of request, and composing an appropriate response based on those factors. For example, if a user were to provide an inquiry stating "I cannot access my account," the NLP will automatically identify that the user is having a password-related issue and provide them with a link to recover their password. In the context of ASCN.AI, NLP is used to report on the sentiment of the crypto community about a particular token or coin, prior to identifying whether to purchase or sell a certain token or coin.

RPA/Integration Is The Process Automation Software/Services Used To Develop AI Applications

RPA is the use of robots for repetitive and predictable tasks such as filling out forms, transferring data, and creating reports. However, these "robot" AI applications do not only perform the tasks they are programmed to perform; they will make decisions based on context and take action based on the same. In order for these AI applications to operate at their fullest capabilities, they must be integrated to Customer Relationship Management (CRM), Email Service Provider (ESP), Messenger Services, and Advertising Platforms. For example, ASCN.AI has an easy-to-use, no-code/low-code workflow editor that allows the user to seamlessly connect Telegram, Google Sheets, and Exchange APIs without needing to hire programming resources. The use of robotic technology has cut down the time it takes to complete tasks by around three-quarters and has virtually eliminated errors in completing those tasks.

AI Agent Use Cases in Different Marketing Activities.

Customer Support/Interaction/Sales Support

AI agents provide the first line of communication for potential customers by immediately checking leads, answering common customer questions, and only forwarding the hottest leads to the sales manager. For cryptocurrency projects, AI Agents analyze tokenomics, current issues in the news, and how people are currently feeling about the cryptocurrency on social media to help traders determine whether they should invest in an asset in seconds versus waiting hours to do so.

Content Marketing & Automated Communication

AI Agents create draft articles, create e-mail campaigns and adapt marketing communications for different audiences. For example, when you add a new product to the system, the agent will automatically create an SEO title as well as an SEO description and create/format the various messages once the approval process is completed. The system sends emails to customers at a personalized level by using an open and click rate to select the specific messages to send right to their inboxes. The agent will send you reminders via text message or another messaging service, as well as sending you alerts about upcoming promotions, or providing you with a unique promo code for your use.

Customer Behavioral Analytics/Customer Segmentation

AI Agents use demographic information (age, gender, location), purchase history, and activity to build larger groups of customers and to discover patterns related to those groups of customers. Instead of sending mass marketing email campaigns, companies can now target their marketing messages specifically to their customers, therefore providing a higher rate of conversion. A major benefit to having an AI Agent is the ability to predict when a customer may not continue to do business with them. When the AI Agent observes that a customer has decreased engagement with the company, it will automatically send that customer an email with a reactivation incentive that costs approximately 5-7 times less than acquiring a new customer.

Benefits of Using AI Agents for Marketing

Improving Productivity & Reducing Costs

Unlike people, AI Agents do not tire and can process thousands of customer interactions simultaneously - creating the effect of a team of 10 - 20 marketing representatives. According to the Salesforce report 2024, 78 percent of all buyers prefer to receive replies within a maximum of a few seconds; five minutes of service downtime, will result in a one-third reduction in the likelihood that a purchase will be made. Operating costs can be reduced by 30%–50% with AI, as a result of greater efficiency and faster work performance from fewer mistakes.

Enhancing Personalization and Customer Experience

Personalization refers to meaningful offers and recommendations based on the totality of a customer's profile/message. Agents will modify their service style based on customers' moods, provide useful assistance when needed and inform the customer if there is an issue. Accenture demonstrated in a study in 2023 that 91 percent of consumers prefer brands that personalize their service experiences, and as a result create greater loyalty to that brand and increase customer lifetime value (LTV) to that brand.

Scaling Quickly with AI and Fast Decision-Making

AI facilitates the rapid scaling of products and services without needing additional staff. Being able to react quickly to market shifts presents businesses with a competitive edge. In the crypto market example, ASCN.AI is able to evaluate prices and find entry/exit points for trades within two seconds; therefore clients have an advantage over competitors.

Successful AI Agent Implementation Examples

Case 1: ASCN.AI Making Money from the October 11 Crypto Crash

On the evening of October 11, 2020 there was a sudden decline in the value of cryptocurrencies. Within seconds after this decline, ASCN.AI agents were able to scan through dozens of different exchanges to find price discrepancies of up to 40% for arbitrage opportunities. Customers following ASCN.AI generated between $1,000 and $50,000 in profit within seconds of the initial alert. This level of speed is not achievable through manual processes.

Case 2 - Falcon Finance - Token Drop Warning

As soon as the Falcon Finance token price had dropped significantly, agents of ASCN.AI were quick to gather information from the blockchain activity, Telegram and Twitter activity, trading activity and large holders within a 10 second period. This analytical information allowed investors who had received this summary to exit their positions and limit their losses to a maximum of 60% of the total amount invested in that token. The analytics also allowed the investors to act in a calm and rational manner rather than running around in a panic stricken state.

Case 3 - Alert Personalization for a Crypto Exchange

For a crypto exchange, an agent was implemented to monitor each client's trading strategy and provide them with personal notifications whenever any key events occurred; for example, BTC breakout levels. Because of the personal alerts, conversion rate for the exchange grew by 22%, while churn rate decreased by 15% for the first month after the implementation of the agents.

An Overview of Leading Marketing AI Agents

Below is a brief overview of popular marketing AI agents and their relevant features:

A key differentiator with ASCN.AI is its ability to provide insight into what lies within the DeepWeb3 data space (which is unavailable to non-blockchain-based AI models such as ChatGPT), whereas ChatGPT is limited to information from publicly available sources.

Pricing Models for Marketing AI Solutions

ASCN.AI NoCode

This service offers three payment models:

• Basic (from $29)*: basic scenario builder, limited number of integrations and request limits.
• Professional (from $99)*: adds additional functionality vs. the basic tier, allows users to create more scenarios, provides an expanded request limit and has priority support and crypto analytics features.
• Enterprise (from $499)*: complete access to ASCN.AI's no-code platform, with the added benefit of a complete API for integration into other systems, along with a personal manager dedicated to serving their needs.

• HubSpot AI — Starts at $800/monthly.
• Drift — Starts at $2,500/monthly.
• ChatGPT — Plus version starts at $20/month, additional charges apply to use of API if applicable.

Consider starting with the basic package to determine what you require and avoid overpaying for features you will not utilize.

AI Marketing Agent User Reviews

"ASCN.AI is more than software; it is an analyst available 24/7 for me. It takes about 10 seconds for the agent to pull data that took me hours. Without it on the night of October 11, I would have missed a 40 per cent arbitrage."

"I have tried ChatGPT to analyse tokens and found its answers were general and very surface-level. ASCN.AI provides on-chain data completely unavailable elsewhere. It's as if you're trying to compare Wikipedia to exclusive inside knowledge."

"After implementing the chatbot, the process of responding to requests has increased five times and conversions have improved by 18%. As a result, managers receive all hot leads, meaning the work has become far more efficient."

Implementing AI Agent in Marketing: Step-by-Step

1. What to Automate: Decide which processes you want to automate. Examples are handling telegram messages, creating reports, personalizing emails, or qualifying leads.
2. Configuration & Integration: For cryptocurrency and no-code, ASCN.AI is the best choice. By simply registering at ascn.ai, you have access to the workflow editor where you can construct the triggers, logic, and AI agents just like building blocks.
3. Logical Flow: Set up a trigger (e.g., new telegram message), apply the logic (analyse the text), if any conditions are satisfied, then set the action (e.g., send price list, save the contact to Google Sheets, notify a manager).
4. Security: Add API tokens for your telegram, Google Sheets or CRM in the "Secrets" section for security.
5. Launch: When you are ready to try the workflow, send a message and launch it; the agent will run 24/7.
6. Monitor: Track your metrics and continue to refine and improve the logic.

Frequently Asked Questions

How do I choose an AI Agent for marketing? First, analyse your business and budget. A universal AI agent will fit many tasks, but a specialised AI agent will fit one specific market, such as cryptocurrencies. Always demo before you buy.

What are the constraints and risks with using AI? AI will never replace humans' roles for complicated or emotional situations. If anything is wrong with your data, (e.g., an error) AI will also most likely provide you with incorrect results. However it is possible to over-automate; hence some industries, like medicine or finance, would require some legal regulations to be adhered to.

Conclusion and Future Prospects

Marketing without automation is similar to walking to win an Olympic event. AI is going to save you between 30% and 50% on your marketing cost, increase conversions between 18% and 35%, and enable your business to grow without hiring half a team. If you are in the cryptocurrency world where everything is changing every few minutes, you have no choice but to automate. The marketers who implement AI now will be years ahead in their marketing effectiveness.

Choose one process to automate, test it, expand from there, and keep in touch with the latest in marketing trends.