Why Running Ads Natively Doesn’t Cut It for Demand Gen Marketers

Mark Huber

Demand gen marketers have it really tough.

How can they target the right audience when people are using different devices and tracking technologies like third-party cookies are going away?

How can they use their budgets in the smartest way (without wasting money), knowing CEOs are pinching pennies?

How on earth can they determine what’s actually generating pipeline and revenue when they have 17 audiences and 122 ads running across campaigns on different ad channels?

Now that I say that, tough isn’t the right word; impossible seems more appropriate. 

But demand gen marketers will keep spending money on digital advertising and that spend keeps going up. By 2023, B2B digital ad spending is expected to approach $15b, up from less than $3b in 2015.

There’s just one problem: native ad channels aren’t good enough for today’s demand gen marketers.

Native channels aren’t intuitive, many are over-complicated and none of them meet the requirements of what demand gen marketers need to do today: generate pipeline and revenue. 

Not to mention, every channel makes more money when you spend more money. The whole model is broken. Let me explain why and how Metadata fixes this.

“I can’t imagine ever running paid campaigns natively ever again. It’d be like going back to dial-up internet.”
Andrew Harder
Senior Paid Media Manager, Webex Events

Here’s the problem with running ads natively

When Mark Zuckerberg launched Facebook Ads in 2007, he did it with the current state of the digital world in mind. 

The same for LinkedIn, Google, and every demand-side platform (DSP) out there.  

These ad channels were revolutionary (and are still powerful), but they don’t account for how buyers move between channels and what demand gen marketers are on the hook for: generating pipeline and revenue.

Native ad channels make money when you spend more money. The whole model is broken.

Let’s break this down at a high level: 

  • Campaign: The box all the way to the left represents your entire budget. By setting a budget of $100/day, you’re telling Facebook, LinkedIn, Google or the Display network to run your ads (creatives) until you reach that threshold. When you get there, your campaigns are paused and restarted the next day.
  • Audience: These are the people you want to see your ads. You can build your audiences with two different data sources: First-party data and third-party data. The first-party data is yours (like your customer or prospect list), while the third-party data comes from the individual platforms.
  • Creative: These are the ads that your audiences see. Simple as that. You can create as many as you want, testing different colors, headlines, CTAs, imagery, ad formats, and more. It’s up to you. 

This is generally how campaigns work, although it varies slightly within each channel.

The point of outlining this structure is to highlight where running ads natively goes wrong.

Let me explain:

In this example, you have three audiences and three creatives (ads), which means you have nine total combinations. 

Great. Variety is the spice of life. 

The problem is you can’t see which combinations drive pipeline and which ones burn through your budget.

This is because your budget sits at the campaign level, meaning you can’t isolate variables and allocate your budget towards the highest performing combinations.

So, for example, if your campaign is driving 2x more leads than your goal, you can’t drill down into the campaign and see which combination is driving the most conversions.

You just have three audiences, three creatives and nine combinations. 

Somewhere in there is the answer, but you can’t see it. See the problem?

Without the ability to drill down into each unique variable, you can’t really optimize for performance and efficiency (but you can try). This is where Metadata shines.

So, how does Metadata fill the gaps?

You can use Metadata to move beyond native ad channel capabilities and run better paid campaigns.

From targeting to automation to experimentation to revenue optimization – Metadata is the cheat code demand gen marketers didn’t know existed.

Let’s start nerding out.

Targeting

One of the fundamental gaps in native ad channels is they exist in siloes; you build your audiences for Facebook in Facebook, for LinkedIn in LinkedIn, and so on. Every channel has their own audience criteria, with limited flexibility, so good luck trying to target the same people across channels.

There’s a reason the term “walled garden” follows most of these channels around. It’s their way or the highway.

This is a problem for three reasons:

  1. It’s a huge time suck
  2. Targeting is limited to the individual channels
  3. They all operate in silos

Combine these problems and the most important aspect of your campaign (targeting) is on rocky ground. Not only do you spend a ton of time manually building and rebuilding every audience, but it gets that much more difficult to make smart optimizations.

How does Metadata solve this? With MetaMatch, our audience targeting capability.

With MetaMatch, you build all of your audiences in one place, using the same audience criteria with 22 different data sources. You can finally move beyond limited native targeting in each channel.

For example, you can use dynamic account targeting with your first party data from Salesforce, activate intent data from Qualified, G2, 6sense (and more), and use our proprietary database of 1.5 billion B2B profiles using firmographic and demographic criteria.

Once your audience is built, you can preview the first 100 rows and refine your criteria to make sure you’re targeting the right people— before you launch your campaign and blow through your budget.

The kind of targeting (and flexibility) every demand gen marketer dreams of.

P.S. MetaMatch is powered by emails, not cookies, which means when the latter goes away in 2023, MetaMatch won’t lose any of its power. 

Automation

The average B2B buyer, let alone a person, has too many devices. Because of this, cross-channel campaigns are no longer a pipedream. It’s an absolute requirement for demand gen marketers.

The only realistic way to move buyers from unaware to most aware, is to launch different types of campaigns across Facebook, LinkedIn, Google, and Display. Meeting your buyers exactly where they are in their journey.

Remember: The diagram above represents just one campaign on one channel. Each time you want to launch a new one, the complexity and resource drain grows exponentially. Your team wastes serious time building and rebuilding the same campaign experiment on each channel. 

Metadata ensures demand gen marketers can keep “button-pusher” off of their resume by allowing them to launch every campaign—and all of its experiments—across every channel with just a few clicks.

Launch LinkedIn, Google Ads, and Facebook campaigns from the same screen.

So, say goodbye to siloed campaigns and hello to freeing up your time so you can spend it on important tasks, like strategy, creative execution and experimentation. You can also bid farewell to the inevitable errors—albeit unintentional—that come with manual campaign creation in every native tool.

Experimentation

Unless you’re a mad demand gen scientist (or a clone of Silvio Perez), finding the right mix of targeting, creative, and budget will take some testing. If you’re a mad demand gen scientist, let’s chat. 

But time experimenting is time very well spent. 

Experimentation is your lifeblood and the only way to maximize the value of your campaigns. 

Here are examples of what you can find out with the right experimentation strategy:

  • Which messaging resonates with your audience?
  • Which audience converts at the highest clip?
  • Do ads with unpolished images of customers outperform ones with stock images?
  • Does a certain headline on a landing page convert people at a lower cost? 
  • Does Google or Facebook have a lower cost-per-opportunity?


Each of these experiments gives you an idea of what’s working and what’s not. From there, you can look at the performance metrics that matter to your business and double down on what’s generating the best business outcomes.

The problem is running all of these experiments in native ad channels requires a ton of manual work and even more spreadsheets. If you’re running experiments across channels, the complexity grows exponentially. 

It gets worse. 

Once your team (or agency) gets everything into the native ad channels and all of the variables are aligned, the curtain is closed, preventing you from truly seeing what’s working and what’s not.

Metadata opens that curtain, wide open.

Simply select the audiences (or keywords, if you’re running campaigns on Google), ads, and offers you want to test, and bam, you’re ready to go. Seriously, it’s that easy and there’s no limit to how much you can test. 

Want to test 10 audiences, five ads, and three offers on Facebook?

Sweet. The only thing standing between you and all of those experiments is a few clicks. 

At Metadata, we believe in using a 1-1-1 (audience, ad, and offer) approach to run paid campaigns. This hypersegmented, and automated approach lets you experiment within each ad channel at a much more granular level. 

Not only does this save your team serious time—and a ton of headaches—but it gives you a single source of truth you can rely on. The kind of insight you and your leadership team dream of.

Because Metadata gives you greater visibility at each level of your campaign using the 1-1-1 approach – you can truly see which unique campaign experiments drive pipeline and revenue.

With Metadata, you can track individual experiments from impression to closed won revenue. NBD but KBD.

Don’t forget: with native ad channels, your budget lies at the campaign level, which prevents you from optimizing experiments in a way that takes the performance of each variable into account. 

Revenue Optimization

Vanity metrics like impressions, clicks, and leads are so 2010. 

Unfortunately, vanity metrics are all you can see in native ad channels. Even worse, they’re the only options you can use to optimize your campaigns.

It’s 2022. Demand gen marketers need more or else they’ll be out of a job. 

Metadata gives you just that, by providing you the ability to drill down into post-conversion metrics, like opportunities created, cost per opportunity, and the holy grail: revenue created.

From there, you can get clarity on what works, what doesn’t, and what you need to optimize moving forward to get the most out of your paid campaigns.

With Metadata – your campaigns are optimized using data from your marketing automation platform, your CRM and our AI – without having to do any manual and repetitive work.

To get this level of reporting – you have a BI team or spend most days stitching together static reports.

Metadata vs. …Nothing

Both Metadata and native ad channels exist to help demand gen marketers do the same thing: get in front of potential buyers for whatever you’re selling.

But they do so in very different ways.

At first, native ad channels worked wonders for demand gen marketers. But they don’t help you get any closer to truly impacting your bottom line (and getting your CFO off your back).

Metadata lifts the veil on the advertising world that’s historically lacked the transparency and control needed to drive pipeline and revenue—while saving you a ton of time every week.

While some might see a choice here—Metadata vs Native Ad Channels—we titled this piece Metadata vs Nothing for a reason. Call us presumptuous, but there’s really only one right option here. Native ad channels don’t make the cut.

Metadata has what you need. If you don’t believe us, book a demo here and put Metadata to the test.

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The advertising platform to rule them all!
Metadata has been the most efficient platform for managing LinkedIn and Google ads all in one place. I can easily manage audiences, ads, creatives, offers, and more. The budget grouping allows me to control how much spend to allocate by campaigns, geos, and more.
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The ability to launch campaigns simultaneously across LinkedIn, Facebook, and Google Ads is incredible
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