Guide To Finding Your Audience on the Display Network

This article relates to the Google Display Network (GDN) and advertising through Google AdWords. There are alternatives available, but this guide is designed for businesses who currently use the above Google products. The post focuses on generic display campaigns where audiences and demographic targeting are used. This guide does not include Remarketing which will be the subject of another post in the near future. This article also assumes that you have Google Analytics Demographic reporting switched on.

Google Display Network

The Google Display Network is a monster. A vast ocean of websites which allow third-party ad serving (3PAS) through their use of AdSense – Google’s own exchange. It’s very easy to spend a lot of your advertising budget quickly if campaigns aren’t setup correctly. Incorrect bidding strategy, high daily budgets and a lack of understanding often contribute to businesses having a negative view of this channel. The reality, as with all campaigns, is that careful planning and knowing your audience can yield great results.

The GDN is not necessarily a revenue channel. Display campaigns are designed to help increase awareness of your business and products to a wider audience. Revenue can be generated from Display, but in most cases, the volumes are unlikely to ‘beat’ the Search network. Unless you have an offer that really can’t be refused, it’s best to use the GDN for its intended use.

The real returns are visible through Attribution modelling and understanding of this concept is key.

Finding Your Audience

Many companies already know who to target, they have comprehensive studies carried out on their customers which enable them to build buyer personas.

You may have heard things like “Sara is our customer, she is 25 – 35 years old, likes socialising with her friends, drinks fine wine, and eats at popular restaurants.”

The above statement already contains most of the audience targeting information; investing your budget into audiences that fit this buyer persona is the most logical thing to do and the most likely to yield results.

  • Gender = Female
  • Age = 25 – 35
  • Interested in Food and Drink

If you don’t have this information, Google Analytics Demographics and Interest reports are your ticket to success.

Demographics

Let’s have a look at my analytics account, and choose Audience → Demographics → Overview.

Ensure your Key Metric is set to Sessions and you are reviewing data from All Users. My preferred date range is the last 90 days, but this is a developed account with a lot of data. You will need to work out what works best for you, to give you a data set that you are confident with.

The above bar and pie charts indicate that of the 62% of sessions used to generate the data, the highest percentage of users who visit the site are between 45 – 54 years old and 70% of them are Male. You could assume that this is my most popular demographic, but what happens if we change the Key Metric to Avg. Session Duration? Does the above demographic also spend the most time on my site?

The answer to that is, No. Users who are 55 and above tend to spend the longest time on my site. Granted, still mostly male at 74%.

From the data above, we can conclude that Males between 45 – 54 tend to visit my site most often, but Males over the age of 55 spend the most time once they get there.

Conversions

What about conversions? We already know who visits the site most and also what segment engages more. But does this equate to people completing my desired action?

Let’s assume that my desired action is getting a user to fill out my Contact form. We’ll call this ‘Contact Us Enquiry’.

Let’s check out what our data told us about the Age of users who complete this goal.

Go to Audience → Demographics → Age

Now, this is interesting!

It seems that users aged 45 – 54 and users 55+ have a similar conversion rate and together make 43% of my total conversions.

Let’s check out the Gender too:

Not so clear this time, as the conversion rates are identical for both Males and Females. You could argue that 72% of conversions came from Males. But we already know that most of our traffic is of this gender, therefore this is expected.

That said, I think we’ve got some solid data to confirm we’re on the right track from an Age and Gender perspective. Our current plan looks like this:

  • Gender = Males
  • Age = 45 – 54 and 55+.

But, if we set up a Display campaign with just the above targeting, you would likely spend your budget within an hour or less! Or risk having some undesirable results like a very high bounce rate or low engagement.

Interests

Let’s use the Interests report to improve our targeting even further. Google segments its audiences by category, allowing advertisers to choose from Affinity, In-Market or ‘Other’ audiences.

Affinity Audiences are wide reaching; they contain users who display behaviour that can be seen as having a particular interest such as TV Lovers, Technophiles and Outdoor Enthusiasts. These audiences were built for businesses currently running a TV ad who would like to extend the reach of a TV campaign online cost-effectively.

In-Market Audiences are a little more targeted, they contain users who show buying behaviour against a particular vertical such as ‘Travel & Hotels’, ‘Autos & Vehicles’ or ‘Real Estate’. These audiences are designed for advertisers focused on getting conversions from consumers most likely to make a purchase.

Go to Audience → Interests → Overview

Set the Key Metric to Sessions. After all, we want to see how Google classifies our visiting users.

The above data tells us that our top Affinity category is ‘Shoppers/Shopaholics’. Well, this makes sense as my website is predominantly trying to sell a product. Next on the list is ‘Movie Lovers’ and ‘Travel Buffs’.

Ok great, so my users like to shop, they love to watch movies and like to travel. We’re building up a bit of a persona here…

Affinity

Let’s consider this with a bit more depth. Go to Audience → Interests → Affinity Categories

Focusing on the above data, conversion rates are identical with much of my Contact Us Enquiries coming from users in the categories discussed above. But how interesting that Auto Enthusiasts have the highest conversion rates!

And In-Market audiences, how do they fare with the above?

Ah interesting, so a lot of my traffic is from users who are currently in the market for a vehicle and maybe interested in a holiday (aren’t we all?). Great stuff, let’s dig a bit deeper…

Goal Completions

This time I’m going to sort my data by Goal completions, as I want to see which audience gives me the most Contact Us Enquiries.

Just as I thought, users who are in-market for ‘Autos & Vehicles’ and ‘Travel’ send me the most enquiries. I think I know who I want to spend my money on…

Let’s summarise the above. That’s quite a lot of data, but it’s only actually taken about half an hour to get the data I needed.

Summarising

Remember how we started off with no idea who to target, let alone which audiences I should go for?

We can now assume the following:

My Target Audience

  • Gender = Males
  • Age = 45 – 54 and 55+
  • Have an affinity for shopping, movies and TV
  • Interested in automotive and travel
  • Like to spend money on vehicles and holidays

Therefore, we can assume a buyer persona. “Geoff is our customer, he is above 45 years old and likes to watch movies and TV. He likes shopping, in particular, he likes cars and holidays.”

With this data, I can go ahead and build my Display campaign ensuring that I use the above data as my targeting method.

When you attempt a campaign build yourself, remember to use Google Display Planner to determine your initial bids and please, make sure you have a conservative daily budget. It’s easier to increase a daily budget than to decrease it once the money has already been spent!

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