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Using Facebook Lead Ads to Reduce the Impact of iOS 14

by Digital MarketingFacebookLead GenerationPatient Recruitment

There’s been a lot of consternation in the world of digital marketing regarding the imminent impact of Apple’s iOS 14 ATT (App Tracking Transparency) update. For those of us who specialize in patient recruitment – as well as any business who relies on generating leads and sales through targeting people online – two of the main areas that will be affected are those of audience building and retargeting. Using Facebook Lead Ads could help to circumvent the problems that will be caused in these two areas – which I’ll outline below.

Firstly, let’s have a look at what’s happening with the ATT update and what the effects will be for Facebook Ads.

Apple’s iOS 14 ATT Update

Apple announced in early 2021 that it would be updating its latest operating system – iOS 14 – with what it calls its ATT policy. ATT stands for App Tracking Transparency and essentially means that when anyone visits a website or opens an app using their Apple device, they will be presented with a popup window that asks them to choose whether to allow a record of them visiting to be tracked by another website/app or not. (Tracking in this instance being for advertising purposes, such as determining that a website visitor has visited a particular website, then showing them relevant adverts on eg Facebook).

Despite the best efforts of those of us in marketing over the years, it’s highly likely that the majority of people will choose the option to not be tracked. Which means they will not be able to be included in an audience of people with specific Interests, in the way that they would be previously. Nor will they be able to be included in an audience of people who visited our own website. Both of which make it more difficult for us to target or retarget them with our Facebook Ads.

The crux of the issue is that – where Facebook used to be able to store data about website visitors using the Facebook Pixel, then target or retarget them with adverts when those people were logged in to Facebook, the ATT prompt will now lead to a large number of people opting out of this functionality.

You might think that it isn’t going to have all that much of an effect, based on the fact your website traffic might be predominantly made up of people on desktop devices or mobile devices powered by Android, rather than Apple’s iOS 14. However, the industry is very much heading in the direction of increased levels of data privacy anyway. (For instance, with Google announcing that Chrome will no longer support 3rd party cookies from sometime in 2022).

Plus, Facebook has already implemented a confusing and somewhat unsatisfactory update to its advertising system, in order to try and counteract the effects of increased data privacy. Which means your ads will be affected even if you don’t have many iOS 14 users.

All of which brings me to an already-existing function within Facebook Advertising that doesn’t fall foul of those data privacy issues and will be unaffected by such things as the iOS 14 ATT prompt or forthcoming 3rd party cookie deprecation.

Enter Facebook Lead Ads

Here’s why Facebook Lead Ads should be valuable for audience building and retargeting in the post iOS 14 world:

– They operate purely within the confines of Facebook itself.

Anyone who uses Facebook has already signed-up to a privacy policy that entitles Facebook to show ads to them. (Whether unwittingly or otherwise). Which means that even if you are logged in to Facebook using an iOS 14 device, then, the ATT policy does not apply to this type of ad.

– People don’t know they’re going to be presented with a Lead Form when they click the Call To Action button.

The most common – and usually most effective – CTA button on a Facebook Ad is ‘Learn More’. When people click this, they might expect to be taken to a website. But, in the case of a Lead Ad, they will actually click through to the next page of the ad – the Form. Which means that, for your audience, the experience of seeing and clicking the ad is initially the same as it would be for a standard ‘click to website’ ad.

– Custom Audiences can be built from people who Open and/or Submit the Form.

Facebook defines a Custom Audience made up of people who engaged with your Lead Ad Forms as being a type of Engagement Audience. This type of audience does not rely on data from the Pixel, as all the engagement takes place within Facebook.

You can setup a Custom Audience that is made up of people who have clicked your CTA button (eg ‘Learn More’) and thus Opened the Form. This audience will be the equivalent of an audience of people who had clicked through to your website from an ad and be classed as a visitor by the Facebook Pixel on your website. People who Submit the Form can make up a further audience of ‘qualified leads’ – ie the same as people who would have filled in a form on your website.

You can then retarget ads to either or both of these audiences – in the same way you would retarget to an audience of people who had visited your website. You can also create a Lookalike audience of people who ‘look like’ the people in these audiences – in the same way you would create a Lookalike audience of website visitors or qualified leads.

– Form fields can be pre-filled, so it’s no big effort for people to submit them.

Having the form fields pre-filled with contact data makes it very easy for people to submit them, so you are potentially more likely to receive email addresses through Lead Ads than you would through a website form.

– Building a list based on email addresses is unaffected by iOS 14 or 3rd party cookies.

With a list of email addresses that you collect through the form, you have another means of creating an audience within Facebook. Again, you would be able to use this audience for the creation of Lookalikes and for Retargeting.

Downsides of Using Lead Ads

One of the downsides of relying on Lead Ads for patient recruitment is you are not allowed to ask specific health-related questions on a Lead Form. Which means you can’t incorporate inclusion/exclusion criteria in the way you could with a form on your website. What you can do, though, is specify who you’re looking for in the text that appears above the form, which should help to filter out people who don’t fit the relevant criteria.

Another downside to this strategy is that all the data is contained and only works within Facebook itself. You can’t, for instance, build a Custom Audience of people who Opened but Didn’t Submit the Form, then use that audience to target them on Google or LinkedIn – you can only target them on Facebook.

However, my experience of patient recruitment for clinical trials has shown me that Facebook is by far the most effective platform for generating patient leads, so you’ll be able to reach the vast majority of your potential audience through Facebook anyway. If that situation changes, I’ll be among the first to be recommending a different platform to advertise on. (I don’t expect Facebook’s effectiveness to significantly diminish anytime soon, but I’ll certainly be keenly interested in the effects of the forthcoming changes, so I can continue to maximise the number of patients I help recruit for trials).

Conclusion

If you use Facebook Advertising as part of your marketing strategy – and, for patient recruitment or other forms of lead generation, I certainly recommend that you do – Facebook Lead Ads could help reduce the potentially negative impact of the iOS 14 ATT policy change.

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Drop and Give Me 20 – 20 Powerful Insights for Facebook Ads for Patient Recruitment

by Digital MarketingFacebookPatient Recruitment

I recently re-read the excellent book, The Business of Expertise, by David C Baker. One of the things he talks about is the ability to demonstrate your expertise in a particular subject through being able to come up with 20 facts about your specialist subject matter that even people engaged in the field might find they didn’t know. (He describes this as the equivalent of a military instructor or sports coach getting someone to ‘drop and give me 20’).

Once I’d done the exercise for myself, it occurred to me to turn it into a blog post re: the kind of insights I’ve picked up from my experience promoting clinical trials using Facebook Ads.

1) Facebook doesn’t care whether you spend money with it or not. This concept is one of the hardest things to grasp for ‘old school’ businesspeople and marketers – who believe that spending advertising dollars with Facebook should give them some kind of authority over the organisation. In reality, Facebook’s whole ethos is built around keeping its users happy, not keeping its advertisers happy. And with 10 million advertisers using their service, the people at Facebook really don’t care if you spend money with them or not.

2) The ability to share adverts is one of the key drivers of registrations for clinical trials. Even if someone in your target audience isn’t on Facebook when you’re showing your ads, they are likely to have a friend or family member who is. That person can share the ad with others, thus helping get your message in front of the right people. As well as this, if some members of your target audience are not on Facebook at all, they will almost certainly know someone who is. That person can see your ad and alert their connection regarding the existence of the trial. Which means you can reach both people on Facebook and people not on Facebook with a Facebook ad.

3) Targeting within Facebook is not just based on demographic information and the location of the user. Interest targeting was pretty much Facebook’s original ‘killer app’ – enabling you to target people based on their behaviour online. (ie Facebook tracks what people are doing online and can show them relevant adverts accordingly – something you can tap into for promoting your trials).

4) Point 3 notwithstanding, Interest targeting is only half the story when it comes to targeting people on Facebook. The actual content of the ad itself is a form of targeting as well. For example, when you’re browsing magazines on a newsstand, you will likely ignore the headlines for topics you’re not interested in and be drawn to the magazine headlines and images that relate to topics you are interested in. The same applies with Facebook ads, where if you or someone you know is living with a particular condition, the mention of that condition in the ad headline will likely draw your attention.

5) As well as demographics, Interest, and content targeting, Facebook allows you to develop Lookalike audiences – based on people who visit your website or an existing contact list. Which means that, if you have a database of people who have been in touch with you to express their interest in a particular clinical trial – either through visiting a relevant page on your website or through having submitted a contact form – you can use this audience to develop a new audience of people that ‘look like’ your ideal target audience – allowing Facebook to show your ads to people who are more likely to be interested in your trial.

6) Another of Facebook’s ‘killer apps’ is the ability to retarget people with your ads. We’ve all seen adverts that seem to follow us around the internet. For example, if you look at a particular garden tool on a shopping website, you may see lots of adverts for the same tool – or a different brand – when you’re next online. This is an example of Retargeting in action. For the purpose of patient recruitment, there are many reasons why someone might not go through with submitting the registration form – the phone or doorbell ringing, becoming distracted by something else they’re viewing online etc. Which is where showing them an ad for the trial when they’re next online might be just the reminder they need to go through with the registration.

7) The ‘killer apps’ and targeting methods mentioned in the previous points actually forced Google to ‘up its game’ when it comes to targeting, such that their system is now much more similar in functionality to what Facebook can provide.

8) You don’t have to send people away from Facebook to a landing page in order to capture their contact details in a registration form. Facebook Lead Ads allow people to express their interest in your trials with a simple button click. The form can be pre-populated with their contact details, so all the person has to do is click the Submit button. This way they don’t have to leave Facebook, which leads to a higher volume of leads being generated. The quality of these leads isn’t generally as high as for leads that come from a landing page that features trial exclusion criteria. But the quantity can make up for this – and ultimately you’re targeting the same people anyway.

9) Swift follow up of leads is the key to success for converting people from initial enquiry through to randomized patients. Within 24 hours is what you should be aiming for – with ideally a follow up phone call being made within an hour of the person submitting the registration form. (Note: if your leads have come from Facebook Lead Ads, as in point 8 above, you will need to do all the screening questions in your follow up call, as Facebook does not allow health-related questions in Lead Ads).

10) Long forms on landing pages are generally thought to put people off. However, in the field of patient recruitment for clinical trials, people have shown they are prepared to answer a large number of quite in-depth questions. I’ve seen as many as 25-30 questions on a web screening form work well, without seeming to put people off by the number of questions they have to fill in.

11) Despite what web developers and techie people might try to tell you, I’ve found that when tracking conversions online – ie the number of successful registrations or contact form submissions – it’s always best to have a separate Thankyou/Success page. Identifying that the tracking code or pixel has been fired when someone visits this page is always more accurate than any other method of tracking conversions.

12) Single image ads are still the most widely used and effective form of advert on Facebook. Though video ads are certainly valuable and are gaining in popularity all the time, ads featuring a single image have consistently outperformed any other type of ad for patient recruitment campaigns.

13) You can enhance the results of your Facebook Ads campaign by complementing it with a Google Ads campaign. There are always going to be people who will see your ad on Facebook and try to check you out on Google for credibility. Having a ‘brand name’ campaign within Google Ads – based on the name of the Facebook Page you’re showing your Facebook Ads through – is an inexpensive and potentially valuable way to capitalise on this kind of ‘credibility search’. (You may want to link these Google Ads to a landing page relevant for the specific trial you’re advertising on Facebook, in order to maximise the potential results).

14) Your Facebook ads for clinical trials will attract comments from people on Facebook. In particular, they will attract the type of negative comments you might more readily associate with trolls on Twitter. References to ‘guinea pigs’ or ‘Bill Gates’ have always been around, but have certainly increased during the Covid pandemic. Somewhat unbelievably, the most common type of comment I’ve seen on ads for Alzheimer’s trials has been of a supposedly humorous nature – such as “I can’t remember if I applied or not…”. Hiding these comments can work to stop them putting other people off. Or, and perhaps more usefully, responding to them in a professional manner can also be useful for boosting credibility.

15) As well as negative comments, your ads will also attract positive, and sometimes even uplifting ones. It’s well worth responding to these comments, too, as the people making them may be suitable for becoming advocates for your trials, or be able to provide a testimonial.

16) You can use Facebook Ads for building a database of potential trial participants. If you’re not promoting a specific trial, you can avoid the necessity for IRB/EC approval for your ad content. Thus enabling you to target people with a specific condition, get them to register their interest, then contacting them in the future when a suitable trial comes available.

17) Talking of IRB/EC approvals, Facebook’s own rules on content are equally as strict when it comes to healthcare ads. For instance, you have to be quite generic in what you say and not highlight an individual’s personal characteristics. Such that ‘We’re looking for people with psoriasis’ should be approved rather than making a direct assumption about something personal related to the user, eg ‘Do you have psoriasis?’ Further to this, you’re not allowed to mention prescription drugs by name in your ads or on your landing pages.

18) The majority of web traffic – and in particular Facebook traffic – now comes through people using smartphones. For this reason, you should ensure your landing pages are mobile-friendly. (Which is pretty much the standard nowadays anyway). And if you have a screening form with multiple questions, you might decide to check the option to only show Ads to people browsing their phones while connected to wi-fi. This allows you to target people who are more likely to be stationary in one place and thus have sufficient time to fill in your forms, rather than while they’re on the go.

19) Despite the obvious sophistication of Facebook and other digital advertising platforms, the type of A/B or Split Testing that would be familiar to olden day advertisers such as Claud C Hopkins still forms the basis for every successful digital ad campaign. ‘Beat the control’ is still the most useful tool for improving your Ads’ performance – a tool with its roots in the principles of tracking coupon advertising from over a hundred years ago.

20) Building on these principles of Split Testing and ‘Beat the Control’, Facebook’s machine learning capabilities will always be able to far outstrip those of any human being. With billions of data points to work with, Facebook’s internal algorithms are an extraordinarily valuable tool that you should tap into with your patient recruitment ads. Giving Facebook’s machine learning a head start by setting things up well in the first place, then managing them in the right way ongoing, is how best to make use of the power of this tool. It’s by adding the human traits of creativity and experience to Facebook’s machine learning functionality that you’ll achieve the best possible results overall.

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Testing Significant Differences is the Key to Optimizing Your Digital Ads

by Digital MarketingFacebookPatient Recruitment

Split testing, or A/B testing, is a well-known concept in digital advertising and marketing in general. However, the way I mostly see people do it in practice is the equivalent of tinkering around the edges, rather than delivering the kind of significant improvements you should be after.

Significant Differences versus Minor Differences in Ad Content

Consider these two potential headlines that could be used in a Facebook Ad:

Psoriasis Clinical Study

Help with Medical Research

These two headlines are quite different in tone and content, with the first doing ‘exactly what it says on the tin’ by promoting a clinical study for psoriasis. Whereas the second is more general and has a softer element to it – the headline encouraging people to be helpful, rather than simply being matter of fact about what the advert is promoting.

Which of these is likely to work best from the point of view of attracting patients to register to participate in clinical trials? From my experience, I’d say the first one is highly likely to perform best. But I only know that through having tested headlines like that one against headlines like the second one. And even with the level of experience I have, it’s never certain that the current campaign I’m working on will perform the same as the previous ones. Which is why you can only really tell which headline might work best by testing them against each other.

Notice here I haven’t suggested testing simple word swaps – eg ‘Trial’ for ‘Study’ in the first headline. The reason being that these are not significant enough differences to register all that much with the target audience. (See below for an additional look at this idea).

Of course, it is possible that people respond better to the word ‘Trial’ rather than ‘Study’. But it is highly unlikely to be in especially large numbers – which is the kind of significant improvement we’re trying to achieve when we run a split test.

That is, when we first set up our ads and start seeing results, we want to be able to deliver big improvements as far as possible. Once we’ve got to a point where we’re comfortable that our ‘control’ ad is made up of the best-performing elements, it’s only then that we might look at tinkering with the smaller changes to potentially squeeze even better results from a winning ad.

Testing out a Minor Difference

Once you’ve determined which type of messaging works best for attracting the right sort of people – ie those who will register their interest in participating in your trial (or whatever else you’re looking to achieve with your ads) – you can then get on to testing the sort of minor differences that I often see people concerning themselves with from the outset.

It’s worth reiterating this point – testing minor differences, such as slight word changes or images that are similar but slightly different, will not give you the kind of significant improvement in performance that you’re looking for from your test.

This minor level of testing should only be performed to generate ongoing incremental improvements, once you’re already satisfied that the basics of the imagery and messaging you have in your ads are the right ones for your audience.

When I’m talking about a minor difference in imagery, it would be the difference between having a middle-aged man looking to camera versus featuring a different middle-aged man looking to camera. A significant difference, on the other hand, would be a middle-aged man versus an obviously older or younger man, or a middle-aged man versus a middle-aged woman; or featuring someone obviously visiting the doctor versus someone obviously going about their life as normal.

IRB and EC Approvals of Copy

Of course, within the world of clinical trials advertising, when we’re working on a specific trial we have the regulations imposed by the IRB/EC to contend with. Which means there isn’t a lot of room for adding in marketing-led copy to our adverts, so there might not be much in the way of a significant difference that can be tested. In this instance, it may be that minor variations do actually prove valuable for attracting a person’s attention. For example, with these two potential Facebook Ad headlines:

Psoriasis Clinical Study

Psoriasis Clinical Trial

– there isn’t enough of a difference between the word ‘study’ and the word ‘trial’ to imagine it would have much of an effect if you were to test one against the other. However, by including the word ‘research’ in the first headline:

Psoriasis Clinical Research Study

– we not only take up more space in the ad with the headline, which may help to attract attention, we also subliminally reassure the person viewing the ad of the legitimacy of the trial being promoted. (‘Research’ being a word people will usually associate with laboratories, academics, clinicians and the like).

Ongoing Testing

Of course, once you’ve got your ‘control’ ad setup and are engaged in testing smaller differences for incremental improvements, it’s always worth also trying a major difference from time to time. Audiences and tastes can change, so if you’ve had your main ‘control’ ad content running for a while with only minor testing being done, I recommend you also bung in an ad that’s totally different in style. Maybe a cartoon image compared to the real people imagery you’re currently using. Or a completely different tone of voice in the headline and body copy.

Sometimes, I’ve even gone back to a style of ad that was initially well-beaten by the current ‘control’ and relaunched it – only to be surprised that it starts to perform better than it did originally so is worth including in the mix for testing again.

Conclusion

When developing split tests for your Facebook Ads and other forms of digital advertising, ask yourself if the differences you’re making are really significant, or if you’re simply tinkering around the edges with such things as replacing one word for another that effectively means the same thing.

It’s only through testing elements that are significantly different that you’ll be able to achieve significant improvements in results. Save the minor changes for a future stage when you’re looking for incremental improvements from an ad that’s already performing well.

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Machine Learning is the Future (and Present) of Digital Advertising

by Behaviour TargetingDigital MarketingFacebook

An outline of machine learning capabilities within the field of digital advertising. And what it means for your patient recruitment campaigns – both in the future and right now.

First of all, let’s have a look at what machine learning is and how it’s used by Facebook – the king of utilizing machine learning for digital advertising purposes.

What is Machine Learning?

Facebook and other digital platforms have access to lots of information about how users behave while on the internet. In Facebook’s case, this comes from their enormous user base and how people behave while engaged with Facebook itself. Plus the huge amount of data they’ve gathered about how people behave on other sites that have the Facebook Pixel installed.

Using complex algorithms, Facebook analyses this data in order to improve the results it delivers, based on learning from experience. It’s literally a ‘machine’ – the hardware, software and algorithms that come together to create Facebook – that is ‘learning’ from the data it has access to.

How Does Facebook Use this Data?

Facebook looks at what you want to achieve with your campaign – for example, generating potential patient leads for clinical trials – then shows your ads to people who are most likely to perform the action that you want them to. Such that, where Facebook can see that people who match up to a particular set of data points are the ones who usually perform this action, they will then try to target other people who, from their previous behaviours, match those same data points.

Having seen the results over many campaigns I’ve been involved with, I’m convinced that, over time Facebook would be able to use its machine learning capabilities to target the right people, even without any manual optimization at all during the period the campaign was running. (As long as you understand and set your goals correctly within the Facebook system). That is, the ongoing interpretation of the new data by Facebook itself would be continually improving the results of your campaign, without requiring any input from you.

Of course, as a Facebook ads specialist, that conjures up the possibility of me being done out of a job by the very system I’m an expert in. However, what it really means is that the tools I’m working with have become so sophisticated, that the combination of expert human-devised strategy, with enhanced machine learning functionality, helps to deliver the best possible results.

Where previously I might have spent a lot more time interpreting the data provided to try and match my targeting to the right sort of people; now I can put more effort into experimenting with and optimising elements such as audiences, creatives, and different parts of the funnel along the patient journey. Plus I can give the system a ‘head start’ through using my experience and knowledge of the best methods for getting the most out of machine learning. Which leads to better results overall and maximises the return from your ad spend.

Working with Machine Learning for Optimal Results

Marketers such as myself, who have a strong background in the way things were done in ‘the olden days’ (ie more than five years ago), are usually well-versed in the methodologies of such things as ‘split testing’ and ‘beat the control’. (Things that originally date all the way back to the earliest days of advertising as a proper profession). Indeed, I’d suggest that, were Claude C Hopkins (one of the founding fathers of the methods of modern marketing) around today, he’d understand the basic principles behind digital advertising as being essentially the same as those he wrote about in his classic text ‘Scientific Advertising’.

The difference nowadays is that Claude C Hopkins and people like myself were experienced in analysing and managing campaigns manually – that is, interpreting the data for ourselves and making adjustments accordingly. Facebook and the other main digital advertising platforms have taken that basic idea and automated it to a level that would have been inconceivable even just ten years ago.

Fundamentally, the amount of data that Facebook has to work with now is so enormous, that a single individual – even one as skilled as Mr Hopkins – would never be able to get anywhere near to being as accurate with their predictions of how people will behave. Which is why Facebook’s machine learning capabilities help to keep it head and shoulders above any other advertising platform out there.

Of course, the system is only as good as the information you provide to it. One of the easily-overlooked elements for success when working with machine learning is that you have to give the machine the right parameters to work with in the first place. Thus ensuring that the ongoing optimisation through the algorithm is actually targeting the right sort of people – those who are most likely to register their interest in participating in a clinical trial. (Or whatever it is you’re trying to achieve with your ads).

Conclusion

Machine learning is not something from the future as imagined in science fiction. It’s here today, and has been for many years in one form or another. In order to deliver the best possible results from your patient recruitment digital advertising campaigns (and indeed, any form of digital advertising campaign), you need to embrace this fact and incorporate the possibilities of machine learning into your strategy. Which will ultimately provide for much better outcomes than could be achieved without it.

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Podcast Interview with Dan Sfera – The Clinical Trials Guru

by FacebookPatient Recruitment

Following the release of my book – Patient Recruitment for Clinical Trials Using Facebook Ads – Dan Sfera, The Clinical Trials Guru, interviewed me for his podcast.

We discussed my background in digital marketing and how that led me to my specialism in patient recruitment from 2015 onwards, plus explore some strategies and techniques for successful recruitment using Facebook Ads.

You can watch the YouTube video above, or listen to the podcast below.

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Understanding the Key Metrics in Facebook Advertising for Clinical Trials

by Digital MarketingFacebookPatient Recruitment

Having worked on many patient recruitment campaigns using Facebook Ads, I’m well used to the confusion that can exist when it comes to interpreting the different metrics that are reported. It’s certainly not uncommon for clients to only have a vague idea of the true definition of things like Reach, Unique Clicks, Click Through Rate etc.

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Reviewing a Facebook Ads Account for Optimal Results

by Digital MarketingFacebookLead Generation

I’ve reviewed and audited dozens of digital advertising accounts over the years, including many designed for lead generation or promoting clinical trials. I’ve also always agreed with the idea that a ‘fresh pair of eyes’ looking over things can often help uncover new and potentially profitable approaches. Which is why I regularly bring in other Facebook specialists to have a look over what I’m doing – giving my clients the benefit of ‘2 wise heads’ working on their campaigns.

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Facebook Advertising Chat Support – Tips for Getting an Effective Response

by Facebook

Facebook Advertising Chat Support – Tips for Getting an Effective Response

Anyone who’s been involved with Facebook advertising for any length of time will almost certainly have had to deal with Facebook’s Chat Support service to try and resolve some of the issues that inevitably come up.

Unfortunately – and I believe this is by no means unique to Facebook, but a common trait for online support services – the experience can be somewhat frustrating (to say the least!)