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Here's what most brands don't know: Meta doesn't always process pause commands immediately through the API. Sometimes an ad you "paused" last night is still spending this morning.
That's why I check twice. Morning and evening. Every day.
The brands losing money on Meta aren't always running bad ads. Sometimes they're running paused ads that never actually stopped.
Daily monitoring isn't optional. It's the whole job.
If nobody is checking your account every day someone should be.
DM me.
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Your support team goes home at 6. Your customers don't. An online retailer we worked with had a simple problem.
Shoppers asked questions at 11pm, on weekends, on holidays.
The answers came the next morning, and by then a lot of them had bought somewhere else.
We built a 24/7 AI chat into their store. Not a FAQ bot that says "I didn't understand that" three times.
It handles the common questions on its own, recommends products inside the conversation, and drops every chat into their CRM with the full customer context.
When a person does step in, they aren't starting from zero. → 50% more conversions → 35% faster response time → 40% less support workload The part people underestimate is the CRM link.
A chat that sells but forgets who the customer is just moves the problem to your team. Support and sales turned out to be the same conversation.
Question for ecommerce founders. What share of your support questions come in outside working hours? Have you ever checked? It's usually the first number I ask for.
Founders, your visitors don't read websites.
They scan them in 3 seconds and decide.
One good bento card explains more in that scan than three paragraphs explain in a full read.
A great bento section instantly answers:
What your product does
Why it matters
Why they should trust you
Less text. More clarity.
That's how SaaS landing pages actually convert.
This project solves a common small-business pain point: inventory running out silently because no one's watching stock levels in real time.
Trigger 1 — Order processing: A webhook receives new orders (supporting multiple items per order). Each item is split out individually, matched to its corresponding row in a Google Sheets inventory log by SKU, and the stock count is automatically decremented — with the "Last Updated" timestamp refreshed on every change.
Trigger 2 — Daily stock monitoring: A scheduled trigger runs once a day, scans the entire inventory sheet, and checks every item's current stock against its own custom reorder threshold. Any item running low automatically triggers a Slack alert listing the item name, SKU, current stock, and threshold — so restocking decisions happen before a customer ever notices a shortage.
I'd test two orders hitting the same SKU at once, since both can read the same stock count before either writes back to Sheets. Are you serializing stock updates per SKU, or using another way to prevent a lost decrement?