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Getting replies is not the goal. Getting clarity is.
When someone answers your message, whether it’s a “Yes,” a “No,” or a vague “Tell me more”, your real job begins: understanding what that reply means. Are they genuinely interested? Are they curious but not a fit? Are they just being polite?
Qualifying is the process of answering one simple question: Is this lead worth pursuing further? Your ability to read and qualify these replies correctly is what separates random conversations from real pipeline.
Here are a few typical cases you’ll face:
Qualification is not just for salespeople looking to book meetings. It helps you prioritize, personalize, and just as importantly, disqualify when needed.
Unqualified leads can kill your focus. Qualified ones? They drive your results.
La Growth Machine doesn’t use rigid labels like “Positive” or “Disqualified.” Instead, it offers a flexible workspace that adapts to your use case.
Here’s how it works:
Tags are tied to campaigns
Each lead can only have one qualification tag per campaign. If the same person replies to two different campaigns, they can receive different tags in each, allowing you to evaluate success campaign by campaign.
Qualification begins with “To Qualify”
As soon as a lead replies to your campaign, they are automatically tagged as “To Qualify.” This is your signal to manually assign a more specific tag based on the content of their reply.
Available tags include:
These tags are grouped under categories like Replied, Won, and Lost, which you can use to measure campaign outcomes. For example: “Out of 150 replies, 30 leads were tagged as Interested → 20% win ratio.”
Qualification directly from the Inbox
You can tag leads directly from the Inbox view, and the tag will be linked to the last campaign that contacted the lead. This allows you to qualify in real-time as you handle replies, without switching interfaces.
Tags trigger actions
Out-of-Office automation
LGM detects Out-of-Office replies and automatically tags those leads. The sequence pauses until three days after their return date (if available), or indefinitely if not.
In short, qualifying your leads with tags lets you organize your replies with real sales meaning, accurately measure your campaign performance and automate follow-ups and CRM syncs.
It’s not just about knowing who replied. It’s about knowing what to do with each reply.
Before analyzing your results, start with a basic but critical question: did your messages reach anyone?
You can’t optimize what hasn’t been seen.
Globally, “reach” refers to how successfully your outreach gets delivered and seen across both LinkedIn and email. This includes:
A campaign with poor reach doesn’t necessarily mean your messaging is off, it could mean your domain isn’t warmed up, your LinkedIn profile isn’t optimized, or your list is outdated. If people don’t see your messages, they can’t reply.
In La Growth Machine, you can get reach insights by exporting your campaign data. The export provides detailed line-by-line information, including:
This gives you the ability to segment your campaigns not just by volume, but by real exposure. You’ll know exactly where the friction starts before the performance phase even begins.
Once you’ve confirmed that people are seeing your messages, it’s time to assess how they’re reacting.
There are two types of stats in outbound:
In the early stages, it’s the top that tells you where things break:
These numbers are not just KPIs, they’re feedback loops. They tell you what needs fixing.
But don’t drown in data. Focus on what actually drives learning:
Once you’ve got a baseline, dig deeper:
La Growth Machine gives you access to this level of granularity through its filters and campaign exports. By analyzing step-by-step reply data, per channel and per lead, you can track what works, where, and for whom.
In LGM csv exports, you’ll find columns for:
You can even layer this with qualification tags (e.g. “Interested,” “Not Interested”) to understand not just who replied, but who’s converting.
Most important of all: reading stats should lead to actions.
If a sequence underperforms, don’t just watch it fail — adjust.
Change your message. Rethink your timing. Shift channels. Test a new angle.
Stats aren’t reports. They’re diagnostic tools for better decisions.
Now, let’s move on to Chapter 3 : Optimising your statistics!
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