Facebook advertising has come a long way in the past few years, and it provides a highly profitable way for brands either to engage an existing audience or grow new ones.
Paid social media shares some common foundations with paid search, but there are some significant differences both in how its auction-based model works and in the interaction users have with its advertisements.
As such, this maturing-but-still-nascent form of advertising provides a huge amount of room for testing and innovation. It comes with its pitfalls too, as we have seen with the measurement scandals.
However, there are other challenges that affect paid social practitioners daily and they require novel solutions. Below, we have looked at what makes a successful campaign – and what to do when everything best practice tells us just doesn’t work.
The ABC of Facebook Advertising
A successful campaign can be broken down into 3 areas:
- Audiences: Deciding who you want to communicate with and how you want to utilize your audience lists and website visitor information.
- Bidding: Selecting to use manual or automated bids and choosing the metrics for your campaign, which will affect your campaign cost.
- Creative: Testing the right format for your audience since it will directly impact the effectiveness of the two categories above.
Let’s begin with the theory behind a best practice Facebook campaign across these three areas, with reference primarily to the auction that decides so much of how well our ads perform and how much they cost.
By way of contrast with AdWords, Facebook is inherently driven by images and their power to create an aspirational projection in the mind of the consumer.
AdWords works on a very pure, direct response model that is often based on text-based communication. A user types in a keyword and is met with a text-heavy response, although this stance is softening over time as results pages become more visually arresting.
Facebook allows a different approach to targeting, based on specific consumers rather than keywords. However, both are underpinned by an auction-based bidding system.
Facebook uses an auction for two main reasons: to create maximum value for advertisers and to improve the user’s experience. In an ideal world, this would see advertisers attract sales cost-effectively by providing a timely, relevant and enticing ad to the right consumers.
It is in understanding which aspects of this auction we can directly impact that we can start to affect our campaign costs.
Bids are defined by the bid value an advertiser sets (more on this below), multiplied by the percentage chance of their defined action being taken.
So if we want to bid on clicks as a metric, that value will be multiplied by Facebook’s estimated probability that that click will occur. Furthermore, bids in the same auction can target different outcomes: clicks vs. conversions, for example.
This is then combined with relevance and quality factors to come up with the final bid price and the auction winner. These last factors will be affected by things like image quality, negative comments on posts, and click-through rate. Note that this can change over time, affecting your costs on an ongoing basis as Facebook hoovers up more data on your performance.
An easier way to summarize and memorize this is B.E.A.R.:
These bids can be set as either manual or automatic. You are told to use automatic if you don’t know what you are willing to pay for that action. If you do have a price in mind, you are told to bid your “true value” of what your action is worth to you. For instance, if you can only afford to pay $30 to acquire a new user, Facebook suggests you set your manual bid at $30.
If setting it on manual, you can choose a maximum or an average bid. For maximum, the algorithm is stricter on the threshold and is supposed to only find conversions below your bid, but unfortunately this is not always the case.
For average bidding, it will find conversions above and below your bid to find one that will eventually even it out. As seen below, if your bid is $10, Facebook will find bids anywhere between $2 to $12 as long as it averages out to $10.
Regardless if bidding on maximum or on average, you should ensure to always have a budget that is five times your bid to give Facebook enough breathing room to learn.
But this theory doesn’t always hold true and best practice sometimes lets us down.
So, what are some of the most commonly-faced challenges, and how can we deal with them most effectively?
Hyper-targeting hampers performance
It seems counter-intuitive at first, but getting a bit too carried away with Facebook’s impressive targeting options can actually slow your progress.
It is best to provide Facebook with as much data as possible for each ad set so that its algorithms can find the optimal match between creative and audience. As such, it is advisable to avoid audience segmentation at this stage unless it has a clear and defined benefit to your campaign goals.
Ads stop showing
This issue can be caused by many different factors. The first port of call (after checking your bids and budget, of course), should be your website. Check the implementation of the pixel (the Chrome extension is very useful here) and look into Analytics to check conversion rates on key landing pages.
If all seems fine on the site, check the interactions your audience has been having with your ad sets in the past. If these are overwhelmingly negative, this could be enough to convince Facebook to stop showing the ads altogether.
Audiences stop performing
If there is excessive overlap between the audiences you are trying to target across different ad sets, Facebook will prevent the list with the lowest performance history from entering the auction. Excessive overlap can cause significant issues, but it can be avoided by using Facebook’s audience overlap tool.
The audience overlap tool will show the percentage overlap between lists (we recommend keeping it below 30%) and provide insight into where you should consider consolidating your lists.
The auction is increasingly competitive and CPMs are rising as a result. Therefore, sometimes that “true value” that Facebook advises us to bid just isn’t high enough to compete.
However, there are many ways to arrive at the same CPM, so it is worth trialling new campaign objectives such as link clicks. This can be risky, but if you are confident that your landing page will convert well, it can allow you to hit the same revenue targets (or better) for a lower campaign cost.
Another challenging area we encounter is with Facebook’s pixel. This needs to be implemented correctly at each stage of the conversion journey to give you the accurate data you need. It is also crucial to ensure that each of these events is tagged accurately.
This is a fundamental foundation if you plan to use sequential messaging to target your audience at different stages of their purchase journey.
Analyzing GA data
A challenging question – and one with no obvious, catch-all solution – is the attribution of Facebook conversions within a wider marketing strategy, particularly at impression level. The main symptom of this issue is conversion data on two everyday platforms (Facebook and Google Analytics) that simply don’t match up.
We could say that Facebook is rather generous in how it weights its own importance, with a 1-day view through and 28-day click through window as standard. Multiple clicks from the same user within a short timeframe will also be classified as separate sessions, unlike in Google Analytics.
Analytics and DoubleClick do not have access to Facebook impression data, meaning that it is difficult to square this circle comprehensively. We also need to accept that we simply aren’t comparing apples with apples; these two platforms facilitate a different form of advertising and, as such, their metrics will inevitably differ.
That said, a great way to mitigate this issue is to trial conversion lift testing. This works best retrospectively and requires some initial investment, but it does provide insight into the ‘true’ impact of a Facebook campaign.
This same logic applies to Facebook ad sets, if you want to understand the impact each is having on your overall performance.
There is some optimism to be found in Google’s data-driven attribution too which, although missing impression-level Facebook data, will still provide a clear view on clicks. Here, we would typically expect Facebook to appear higher in the funnel, demonstrating its importance as an assist channel.