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Portfolio ManyChat Automation for Lead Capture and Messaging This section shows how I use ManyChat to build simple but powerful conversational marketing systems. Instead of relying on basic auto-replies, I set up complete automation flows that help brands collect leads, qualify them, and respond instantly. The images walk through how Comment-to-DM triggers, message sequences, and logic-based workflows work together to turn social media engagement into real, high-intent leads that the business fully owns. 2 G I R B M O T H 3 I OR E M A The image (page 3) shows the main dashboard of the ManyChat interface. It displays different automation templates that help capture leads and engage users across platforms like Instagram and Messenger. From this view, you can launch quick automations for fast responses or build deeper conversational flows using the Flow Builder. The cards such as “Auto-DM links from comments” and “Grow followers from comments” highlight an effective comment growth strategy. By setting up these triggers, anyone who comments on a post can automatically receive a DM, turning simple interactions into real leads while boosting engagement at the same time. You can also see platform icons for Instagram and Messenger on the templates, showing how ManyChat supports cross-platform messaging. Whether someone interacts through an IG Story or a Facebook message, all conversations flow into one place, making it easier to track leads without missing any. There’s also an “Automate conversations with AI” module, which uses AI to handle questions naturally, reducing support workload and improving response quality. Finally, the “Send affiliate product links” template shows how ManyChat supports conversational commerce, helping increase clicks and conversions through personalized private messages. 4 G I R B M O T H 5 I OR E M A The image (page 5) shows the Automation Repository inside ManyChat, where all previous automations are stored, managed, and tracked. It gives a clear view of how different flows are set up using trigger-based actions across Instagram and Facebook. This setup helps turn public engagement—like comments—into private automated conversations that support lead generation and sales. One of the automations, “IG DM Automation…,” is triggered when a user comments on a specific post or Reel using the keyword “CULTURE.” This is an example of intent-based automation, where the system listens for certain words and immediately sends a DM with relevant content. This Comment-to-DM strategy boosts organic reach and brings more users into the funnel. On the right side, the data columns show the number of runs and CTR (Click-Through Rate). Seeing a “100%” CTR means the message sent in that automation was highly effective and matched the audience’s interest. This helps with ongoing funnel optimization and testing. The “LIVE” and “STOPPED” labels show which automations are active or paused, helping maintain clean and updated campaigns. Finally, the IG and Messenger icons confirm that the flows were built for different platforms, ensuring each audience gets the best experience possible. 6 G I R B M O T H 7 I OR E M A The image (page 7) shows the backend view of a ManyChat automation, where the trigger and action steps of the workflow are set up. It highlights how a “Comment-to-DM” automation is built for a recruitment campaign, turning Instagram comments into qualified leads automatically. The trigger is set to fire only when users comment with specific keywords like “apply,” “application,” or “interested.” This setup helps identify high-intent leads, making sure the system responds only to people who clearly want more information. It keeps lead quality high and avoids wasting messages on random comments. The “Public Replies” section is set to send random responses such as “Info sent!” or “Just sent you a DM.” Using different replies helps prevent the account from looking spammy and also boosts engagement on the post, which can improve visibility on Instagram’s algorithm. The workflow then connects to an “Instagram Send Message” action, where the DM includes application details and an email address. This helps move the user from the comment section into a private message, reducing friction and improving conversions. The green connector line between the trigger and the message block shows a clean and direct workflow, ensuring every interested user receives an instant automated response. 8 G I R B M O T H 9 I OR E M A The image (page 9) shows the Message Editor Interface in ManyChat, where the actual message sent to users is written and configured. In this example, the message is part of a recruitment automation that turns Instagram engagement into a simple, organized application process. The message text “Hi! Thanks for your interest… To apply, please email…” is an example of conversational copywriting. The script gives clear instructions and a short checklist (Resume, Confirmation, Transportation), helping filter out unqualified candidates early. This makes the screening process easier and ensures only serious applicants continue to the email stage. On the left, the “Edit Button” panel shows different logic tools like “AI Step,” “Condition,” “Randomizer,” and “Smart Delay.” Even though this step only sends one message, these tools show that the builder can create more advanced workflows, such as checking if someone has already applied or sending a follow-up reminder later to improve completion rates. The grey connector linking this message to the trigger shows how the user journey flows smoothly from the comment to the DM. The Instagram icon and “Send as Private Reply” label confirm the setup follows Instagram’s messaging rules while still converting public comments into private conversations, which is key for lead generation and recruitment automation. 10 G I R B M O T H 11 I OR E M A The image (page 11) shows the Visual Logic Map of a ManyChat automation. It highlights how the system connects a user’s public action (commenting on a post) to an automatic private response (DM). This setup is built on event-driven workflows, meaning everything runs on its own without manual effort. The “When…” block on the left is set to trigger when a user comments on a Post or Reel. This is the core of acquisition trigger setup. By listening for comments, the automation uses behavioral marketing to turn active engagement into instant leads. Anyone who shows interest publicly is immediately moved into a private conversation. The arrow leading from the Trigger to the “Instagram Send Message” step shows a smooth, frictionless user experience. The direct link ensures users get an immediate reply, so the system responds at the moment their interest is highest. The “Instagram Send Message” block contains the application details (“To apply, please email…”), which demonstrates operational automation. Instead of manually answering repetitive questions, the workflow sends clear instructions automatically, keeping the process fast and consistent. The Instagram icon and message preview confirm channel-native design, meaning the message is formatted correctly for Instagram DMs and follows platform rules while still delivering important information clearly. 12 summary ManyChat Automation for Lead Capture and Messaging In summary, these examples highlight how automated messaging and smart workflow design can create a smooth Automated Customer Experience (ACX). By combining clear logic with effective copy, I build systems that reduce manual work while increasing lead flow and engagement. Overall, this project demonstrates how simple interactions, like comments or messages, can be converted into a scalable, measurable sales pipeline through ManyChat automation. 14 thank you Appreciate you reading through.