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Anna Loverus

Anna Loverus

The difference between an offline and online audience

Understanding your online audience is a crucial step to reach online marketing success. 

If you fail at online marketing, you are usually doing one of these two things:

  1. You don’t know your audience
  2. You make things too complicated

And sometimes you do both at the same time.

Look:

Most of my clients have, at some point, asked me to help them build an online audience or create user segments.

They have tried on their own without success, and they’ve asked multiple media agencies to help them out.

And they always say:

“We have no idea what we are doing wrong, we’ve tried everything.”

But I see the same problems over and over.

Without the possibility to find and target the right people (with the right message, at the right time), you will have a hard time to make an impact.

Why is it so hard to build an online audience?

So, this is the case:

Most people in marketing today started long before online marketing was a thing.

And even though most things stay the same, moving from offline to online. Some things change. So, the key to success for most marketers today is to figure out what has changed and what hasn’t.

When looking at audiences and segmentation, building an online audience is very different from making an offline audience. This difference is simply due to new technology.

So, now, you might ask:

“What are they doing wrong?”

Let me tell you the most common mistake:

Most marketers think about an online audience in the same way they think about an audience used for print, out of home,  direct mail – or for other offline channels.

But since things are so different, using the same methods, you used to do when you created a “print audience” won’t create a successful online audience. You can’t translate one audience from one context to the other.

The big difference between an offline and an online audience is:

How you decide if a person should be in your audience or not.

Building your online audience always starts with a hypothesis

Here’s the deal:

Before you create an audience (to use in an advertising campaign), you usually have an idea of who you want the reach with your product. 

For example:

  • If you’re going to market a contraception app, spending your marketing budget on women between the age of 23-45 is probably wise.
  • But, if you try to sell fancy cheese, your audience is different and probably should consist of cheese lovers with making enough money to spend it on cheese.

So far, we’re all good.

But after this step, it’s starting to get messy. A lot of people makes the same mistake when building an online audience.

The BIG mistake in audience targeting

Here we go:

Let’s say you want to reach wealthy people.

(I’m not saying this is ethical targeting, but it is a simple case to use when making a point, so bear with me – it’s only an example).

You might ask:

“What are rich people interested in?”

You start to list the things you can think of:

  1. Sailboats
  2. Watches
  3. Fancy wine
  4. Sports cars

And based on these interests, you create an audience consisting of sailing sportscar drivers with expensive watches drinking fancy wine.

Sure, many of these probably have an income above average. But, would you say this is a good representation of “wealthy people” as a group.

Instead, wouldn’t it be convenient to use Income directly to create your audience? Everyone with an income above X should be in my audience if they have a lower income they should not.

Doesn’t that sound much simpler than trying to figure out the interests of wealthy people?

“Is this even possible you might ask?”

Yes.

With the cookie tracking made by online platforms (Facebook, Google, etc.), your income is straightforward to estimate. Just by looking at your browsing behaviour, they will know.

And in many places around the world, targeting on income is perfectly legal. In other situations, using income might not be permitted, but using the zip code is.

Once again, this example is used to make a point. I’m not suggesting you target based on income level. I find it unethical and sometimes also illegal. (Here’s a post about ethics in targeting if you are interested.)

But most things you can think of can be used for targeting.

Want to sell:

  • E-scooters? Target people interested in E-scooters.
  • Soap? Target people interested in soap.
  • Solar panels for small households? Target owners of small houses.

It’s all there.

Another essential thing to think about when creating an online audience

Often you have to take your business audience and translate it into an advertising audience.

There can be several reasons behind this, maybe:

  • You want to personalise your ads based on preferences, or age;
  • Or, because you have a small budget and want to make sure you spend it on those who are most likely to consume it.

So, we are taking your imaginative business audience and turning it into an advertising audience consisting of living human beings.

Sidenote: Some people work with personas in their marketing strategy work to get to know their audiences. But I try to avoid working with personas since I find it limiting.

I will save my take on personas for a separate post. But it’s safe to say that personas create a lot of trouble when people are trying to reach their “personas” with online ads.

Why offline audiences are bad

Let’s start with the bad:

In the offline world, you have very little information about people.

You might have some info, like:

  • the average income level in a zip code
  • a magazines rate of female readers
  • the average age of people watching a specific tv-show

But you don’t have rich profiles or detailed information about anyone.

Instead:

You choose a zip code where the average income level is similar to what you think your audience earn. Or you pick a magazine with mostly female readers in a relevant age span if this is the audience you want to reach.

Now you might wonder:

“Sure, but it’s always been like that, what’s the problem?”

The problem is: You will never know if the person seeing your ad likes cheese or is trying to get pregnant.

What is a "proxy" – and why do you need to know that?

Okay, now we are getting a bit technical:

In statistics – yes, building audiences is statistics – a proxy variable is: 

Proxy Variable – A variable that is not in itself directly relevant, but that serves in place of an unobservable or immeasurable variable.

Maybe it’s easier to think like this:

If you can’t use what you want to use, you have to use something close to it instead.

Some examples of proxy variables:

  • Zip code ≈ income
  • Women’s fashion magazine ≈ gender
  • Running magazine ≈ runners
  • Airport visitors ≈ travellers

Marketers try to find good proxies to make their advertising do better.

The thing is: 

It is hard to find relevant proxies for some products and services.

For example: Say you run a house cleaning service

You believe you should try to reach women because they feel more responsible for keeping the house clean (Bleh). 

But: you also want the women you spend your advertising money one, to have a high enough income to afford your service. 

So:

“How can you narrow it down further?”

Maybe, you would want to reach women with demanding and high paying jobs. Then you can advertise in a magazine with readers in this category.

But wait! There’s a big problem here:

This magazine sure seems like a good proxy for your audience. But you don’t know how many of the magazine readers who are potential customers.

Some women who read the magazine might have demanding and high-paying jobs, but they have husbands that do all the housework. Others might not have a high paying job yet but wish to have it one day, so they are reading the magazine as inspiration.

Spill-over in an offline audience

Look:

Among those you target with an offline audience, only some people are the ones you’re trying to reach. 

So you will always have “spill over” and reach people you’re not interested in.

Are you with me? Not really?

Spill-over is very simple to understand when it comes to “out of home” ads. 

You can advertise on bus stops in an area where you know the income level is high, but you will never know for sure if the lion share of people walking past them have high incomes.

The benefit of online audiences

You might wonder:

“What’s the good thing with an online audience?”

Look:
When you create audiences online, you have much more data about people. You can, for instance:

  • Have your own customer data (“first-party data”)
  • Use data from Facebook or Google (“secondary data”)
  • Buy data from someone else (“third-party data”)

Facebook and Google collect data all around the web and in apps through different scripts such as Facebook Like buttons or Google Analytics installations. This is why they know so much about their users, and this is why their advertising solutions are thriving online.

This is it:

When you have data about everyone online, you don’t need proxies.

Instead: You can target users on Facebook directly on income level. Or cheese interest, or if they are interested in contraceptive apps. 

This is why Facebook ads can become so relevant.

We don’t need to guess if the people interested in cleaning services are women or men, or if they are reading a specific type of magazine. We can target directly towards people interested in cleaning services.

Why your Facebook Audiences don't work

Look:

Everyone that talks to me about poorly performing online audiences, have built them incorrectly.

They have all the data they need but are using the data for the wrong thing – trying to be smart when they don’t have to.

This behaviour is even more prevalent when they are trying to build audiences based on fancy marketing personas from a strategy deck.

What I’m trying to say is this:

Don’t use a proxy when you can pinpoint the behaviour or interest you are trying to reach.

Doing this will create a massive detour when the algorithms serving your ads are trying to decide who is relevant and who isn’t.

Instead, try this:

  1. Start with defining what you actually think is the key characteristic in who you want to target and why. Is it age? Income? Location? Is it a combination of them?
  2. Stop trying to guess what your audience is interested in. You will most likely be wrong.
  3. Only add interests if it’s extremely relevant to your product. For instance, if you sell books, target on books
  4. Make sure to use the AND rule and not the OR rule if you combine interests
  5. Have correct optimisation goals and let the algorithm do the job in finding the best matches for your ad among the people you’ve selected above

Finally:

The use of proxy-based audiences for social media is widespread.

I’m continually meeting both media agencies and social media marketers that are doing this daily.

But it is much more work, that will create a worse result.

And since you know better now. I’d suggest you stop doing it from now on.

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