7 best types of lead magnets for DTC brands

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Most DTC brands I speak to do have a lead magnet.

A quiz.
A guide.
A discount pop-up.
Something.

It “works” in the sense that it captures emails.

But then nothing really happens.

No clear increase in purchase intent.
No obvious lift in revenue.
No feeling that these leads are any closer to buying.

So the instinctive conclusion is: “We need a better lead magnet.”

That’s usually wrong.

In most cases, the problem isn’t what you built. It’s when you’re showing it.

A lead magnet only works when it shows up at the exact moment your customer is ready for that conversation.

The mistake most DTC brands make is building one lead magnet and pushing it everywhere. Regardless of whether the customer:

If you’re running a lead magnet, it probably isn’t underperforming.
It’s just speaking to the wrong belief.

I put together a short guide that breaks this down properly. Not by traditional marketing funnel stages, but by customer awareness.

It walks through:

If you’ve ever felt like your lead magnet is “fine” but not moving the needle, this will likely explain why.

You can download the guide here:
👉 7 Best Lead Magnet Plays…And When to Use Each

Google’s AI optimization works best with more data. One campaign with 10,000 impressions beats 10 campaigns with 1,000 each.

For years, advertisers split keywords tightly by intent. Gym bags, hiking bags, running bags. Each had its own ad group, ad copy, and page. That worked when bidding was manual.

In 2025, this structure breaks learning. Each ad group gets too little volume for Google’s AI to understand what converts.

The better move is to merge related keywords into one theme, like athletic bags. All impressions, clicks, and conversions flow into one place. Responsive Search Ads then test combinations and route traffic to what performs best.

Rule of thumb:
If an ad group can’t generate enough conversions to teach the algorithm, merge it so the data compounds instead of fragmenting.

How to Decide What to Merge (With a Real Example)

Consider the hypothetical laptop-computer campaign below with eight ad groups and 90 days of performance data.

In the example above,  of eight ad groups, only Laptop Bags has real signal
💠55 clicks
💠10 conversions
💠174% ROAS

Everything else is starving.
Three ad groups haven’t even crossed 10 clicks.
Half have one conversion or none. Google can’t learn from that.

So the move isn’t to “fix” every ad group.
It’s to pick anchors.

Eight ad groups → three.

The point isn’t that this is the only right structure.
It’s that you consolidate around the few places where data already exists, so the algorithm can actually learn.

These decisions are subjective. Monitor closely after condensing. Performance usually improves, but if it declines, revert and analyze.

Credit - Practical Ecommerce

Brands usually use post-purchase surveys to ask safe questions.

Kanga Coolers asked a better one.

After checkout, they asked customers: "What almost stopped you from buying today?"

That one question did the work. And what they discovered was that it wasn’t price or shipping that was making them hesitate, but TRUST.

A meaningful chunk of customers weren’t convinced the “iceless cooler” claim actually worked. They bought anyway, but with hesitation.

Kanga used it to:

They also noticed repeated feedback around colors and designs, and launched new variants based on that input.

Result:

That’s how important post-purchase surveys are.

Here’s a tool that helps with customer surveys of various types— Post-purchase, pre-purchase, NPS, on-site, email and SMS

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