How to Track Sales and Sentiment from Meta Ads Message Campaigns (No CRM Needed)

Is there a tool that tracks all Facebook & Instagram conversations for deep analysis (without replying)?

We’re running a lot of Meta ads with Messages as the campaign goal.

Right now we process 50+ messages per day with 2 people answering and closing sales directly in DMs.

We use Meta Business Suite for replying, but it is very limited when it comes to analytics.
I’m looking for (or thinking about building) a tool that could:

• Track sentiment in conversations – are people satisfied or not with our service/products?
• Show how many conversations are still open so we can follow up before they go cold
• Extract statistics about sold products from messages
• Extract data about products people are asking for but we currently don’t stock (so we can spot demand)
• Give us a bunch of other analytics: average time to first response, tone of messages, conversation volume by day/hour, etc.

I don’t need another chatbot. I just want a read-only analytics dashboard that pulls all message data from Meta (Facebook + Instagram), organizes it, and gives actionable insights.

Does anyone know if a tool like this exists?

The short answer is:

The long answer is:

What you’re looking for is a classic business intelligence setup, and you can create a powerful one with a few key components.

The core idea is to intercept the message data Meta is already sending, process it, and then send it to a dashboard you control.

It sounds more complicated than it is.

First, you’d use the Meta Messenger Platform API.

It has a feature called webhooks.

This means every time someone messages your Facebook or Instagram page, Meta can instantly send a packet of data – the message text, who sent it, when they sent it – to a URL that you own.

This is the raw data source for your entire system.

Next, you need a place to receive and process that data.

This is where server-side Google Tag Manager comes in, hosted on a service like Stape or Google Cloud Platform.

Stape is often easier and very cost-effective to start with.

You give your Stape container URL to Meta as your webhook destination.

Now, all your message data flows into your private GTM container.

Inside this container, you can write logic to analyze the messages.

For example, to track sales, you could instruct your team to type a keyword like “sold_item_123_price_99” in the chat after a sale.

Your server can be set up to spot this keyword, extract the item and price, and log it as a sale.

You can even send this back to Meta as a Purchase standard event via the Facebook Conversions API to improve your ad targeting.

For tracking demand, you can use a similar system.

When a customer asks for a product you don’t have, your team can type “request_blue_widget”.

Your server logs this request.

To handle sentiment, your server-side GTM container can automatically send the text of each incoming message to a third-party service like Google’s Natural Language API, which will return a sentiment score – positive, negative, or neutral – that you can log.

Finally, you need to see all this data.

Your server-side container sends all this neatly processed information – sales, product requests, sentiment scores, message timestamps, conversation volume – into a data warehouse like Google BigQuery.

The free tier for BigQuery is very generous and likely all you’d need.

Then, you connect Looker Studio, which is a completely free tool from Google, to your BigQuery data.

In Looker Studio, you can build your dream dashboard.

You can create charts for conversation volume by hour, tables of top requested products, gauges for overall customer sentiment, and a list of conversations that haven’t received a reply in a certain amount of time.

This entire setup gives you the powerful, read-only analytics tool you described, with full control and at a very low operational cost.

About The Author