@Sunil A Thanks a lot! I agree it’s all about learning, sharing, and growing together. Excited to connect with you and see what we can build together here

@Anna Birchenko Thank you, Anna! I’m really glad to be here and looking forward to engaging with everyone in the community.

I’ve run into similar issues with outbound agent setups. What’s happening here is that the outbound call request is going through, but the dynamic variables aren’t being passed into the session context. That’s why your agent is defaulting to a “blind” call. A couple of things to check: - Make sure the variables are being sent in the body as JSON, not just in the query string. ElevenLabs usually expects them under a variables or metadata object depending on the endpoint. - Confirm that the phone number ID you’re referencing is the correct one tied to outbound flows. Sometimes inbound and outbound share a visible number, but behind the scenes they map to different IDs. - For debugging, try sending a minimal test payload (just the phone number ID + one variable) to see if it’s accepted before scaling up to your full JSON. 👉 If you’d like, I can take a look at your HTTP request structure and help you reformat it so the variables actually pass through to your outbound agent correctly.

@Maurice Erie Hey Maurice, just checking in. Did you manage to get the outbound setup working, or is it still giving you trouble? If not, I can still take a look.

Nice work, personalized outreach with a Loom video is already a strong start. A couple of tips that might help: - Keep the video under 2 minutes so it’s quick to watch. - Add a short text summary in the email so they know what to expect before clicking. - End with a clear CTA (e.g., “Would you be open to a quick 10-minute chat this week?”). 👉 If you’d like, I can share a couple of proven outreach templates I’ve used that pair well with Loom. Just let me know.

@Sam Dervish, that’s great, you already added a CTA, which makes a huge difference. I’ll send over a couple of the templates I’ve used so you can adapt them for your outreach. Hope they help streamline your process!

I’ve seen this happen before when using a merge node, the behavior depends on the merge mode you select. By default, many tools (like n8n or Make) will only output the last incoming execution rather than combining them. That’s why you’re only seeing your WhatsApp data and not the web chat widget data. 👉 If you’d like, I can help you restructure your workflow so that both WhatsApp and web chat widget data consistently pass through and get handled by your agent.

Great question—there are workflows you can use to automate this kind of influencer analysis. A simple approach would be: 1. Data extraction – Use tools like Apify, Phantombuster, or direct API access (where available) to pull profile details (followers, name, ID, profile image). 2. Profile analysis – Run the data through sentiment analysis or keyword tagging to see how they position themselves and what niches they cover. 3. Post analysis – Collect recent posts and evaluate engagement rates, reach, and audience interaction trends. 👉 I’ve built similar workflows using Make.com, n8n, and Python scripts to streamline influencer research. If you’d like, I can map out a step-by-step workflow (or record a short demo) to help you get started.