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What to do with the Facebook Meta Pixel

Facebook Meta Pixel Lead Image

In this article we discuss what a Facebook Pixel is and why it’s so powerful for charities marketing online. We look at why you use it, why it needs data, and what mitigating steps you can take when it comes to reducing the amount of personally identifiable data being captured.

I have tried to keep this focused on facts and clear information, and where opinion or recommendations are offered they have been labelled as such. As a charity-focussed digital media agency, we understand the concerns and considerations charities and nonprofits must consider when it comes to personally identifiable information and marketing sensitive topics.

It’s important to say that no UK organisation has been fined by ICO (Information Commissioner’s Office) due to its use of the Facebook Pixel. In addition, the recent fine issued by Ireland’s Data Protection Commission (DPC) related to concerns that whilst EU user data is protected by law in the US – it could still be accessed by US intelligence agencies. This ruling has no impact on Facebook in the UK.

This article starts with introducing the pixel, what it does and why you use it. So for those among you who just want to know how they can tailor it and the recommendations going forward, you can jump further down: 

 

1. What is the Meta Pixel (formerly the Facebook Pixel)

The Meta pixel is a piece of code which is placed on a website, in order to track the actions users take on your site, such as viewing a page, pushing a button or making a purchase. It allows you to optimise and measure the performance of your campaigns across Facebook and Instagram.

It’s worth noting that the Meta pixel is gradually being phased out, with Facebook recommending you use the new conversion API. We will cover this new API later on.

 

2. Why you use it

So why do organisations such as charities and nonprofits use the Meta Pixel? Primarily, it’s down to performance in your marketing campaigns. We understand that charities are under continual pressure to ensure every penny of marketing budget is spent wisely and efficiently; and the Meta Pixel allows that. 

Its power comes from conversion tracking, where you define actions on your site which are core to your business and then review your performance against those actions. 

With enough data, the Meta Pixel can even optimise itself towards those conversions using signals and data to show your ad to people more likely to take those actions. You can then enhance it further by feeding it data such as revenue (donation amounts for example), and it can optimise towards getting higher value conversions.

Reporting on performance

The pixel allows you to measure the performance of your campaigns. It gives you real time feedback on what is working, what needs improving and what needs stopping. This means you can avoid wasted spend and improve your ROI.

Directly within the interface you can see which ads and audiences are hitting your KPIs and which ones aren’t. You can then use that data to make decisions to improve your campaigns, making you more likely to hit key KPIs such as revenue targets, volunteer sign ups or legacy gifts.

Optimising performance

As mentioned above, the pixel can use the data it collects to optimise its performance to hit specific KPIs. This makes your marketing more efficient, and more likely to hit relevant targets.

For example, if you ask the pixel to get volunteer sign ups at no more than £20 per sign up, it will use its data and understanding of your users to help achieve that for you. Spending more on users it thinks are more likely to convert, and less on those it’s more unsure of.

It’s important to note that it can only do this with a sufficient data set. Typically, this is around 9 conversions per day, and more than 50 in total.

Strategic planning

This data can be used on conversions, to help you plan for next year, or the next run of the campaign. You can review where performance exceeded targets and where you can make savings without impacting your KPIs.

Without access to valuable data such as this, it’s much more challenging to identify areas for improvement in your marketing (much like more traditional offline advertising). Offline, often you know there are improvements and optimisations to be made, but you don’t really know where they are. 

As we continue through a cost of living crisis, and pressure on marketing budgets increases, many charities could very likely see marketing budgets being cut by larger amounts than the targets you set. Having access to data on what works and what doesn’t can be vital to your organisation hitting its targets and objectives in the coming months.

 

Facebook Meta Pixel - Analysing Data

3. How it works

It might seem scary, and most of the information out there is borderline scare mongering, but it’s important to understand the pixel in order to be able to make a decision on how to best use it for your organisation. 

Data is its power

From a marketing perspective, utilising the pixel can be incredibly powerful. It enables Facebook to connect actions on your website with its vast database of users. 

This allows it to understand the characteristics of those converters. What they like. What they don’t like. Where they live. What content they consume. Their age range. Crucially though, this isn’t data you can use at an individual user level but it’s aggregated, and data used in mass, which gives it more weight.

The pixel helps you understand your audience. It could be that those users who like Waitrose tend to donate more money to your campaigns compared to those who like Sainsbury’s. This allows you to steer your digital media and can also help impact future out of home marketing activity, such as billboard placements. 

Ultimately if used efficiently and strategically, the pixel can help charities save money and become more efficient in their spending – which is what we all want!

This power has been limited in recent years

Everyone in the charity and nonprofit sector has felt the impact of the increased audience restrictions from Meta. It has pushed up the price charities need to pay per click for advertising on their platforms, and therefore has had a real impact on the perceived performance of those campaigns. 

On the face of it, those changes were a positive move forward in protecting sensitive audiences and user characteristics. The idea that corporate organisations could use the fact that users liked mental health charities in order to sell them products or similar, is horrifying. But we know that those audiences were also vital for a lot of charities, allowing them to reach those who might be in need as well as potential new supporters. 

The removal of this specific targeting doesn’t mean those users won’t get to see those ads; you can still use other characteristics to narrow down your targeting. It just means that your ads are less efficient, and more money is spent on audiences which are less likely to convert or resonate with your cause.

The power has also been restricted due to a move towards opting-in to user cookie tracking. The language used at the point of request often steers users to opt-out of sharing that data without really knowing what it is or why an organisation might need it.

Reduced data has led to reduced performance

For those of you who haven’t read Will’s fantastic analysis of paid media performance for charities across the festive periodFacebook (and Instagram) advertising is getting more expensive. Less targeting options has increased competition on what remains, pushing up cost per click (CPC). 

However, the remaining options don’t provide as relevant targeting – meaning lower user conversion rates. This can lead to your cost per action (CPA) skyrocketing. We personally saw up to 4x the CPA for Christmas 2022 v previous years and, unfortunately, this is likely to rise.

With costs continuing to climb, it’s more important than ever to be able to accurately identify successful elements of your campaigns to make them as efficient as possible. Currently the only way to do this is with the Facebook pixel. Without it you’re stabbing in the dark, in an environment in which costs are spiralling – it would be hard to justify and make it viable.

Hashing and grouping to store personally identifiable information.

What is hashing, you ask? Hashing is when you take data gathered from a site, and run it through a generalising algorithm to anonymise and abstract the data so it is no longer directly identifiable. 

Example diagram of how hashing anonymises data to protect user's personally identifiable information.

Hashing is similar to encryption. The main difference is that hashing is never intended to be translated back into the original data. Many different inputs can have the same output which makes it near-impossible to know exactly what the original data was.

This means that data is not viewable to you as a marketer or anyone else within the platform. For example, although it may read a user’s date of birth as 02/10/1999, it wouldn’t collect and send that data. Instead it would categorise this user as falling into the 18-25 age bracket.

Meta also has systems which try to spot and remove ‘hidden’ personable information such as when names or email addresses are passed through urls. It also says it tries to stop the collection of data from users on what it deems as ‘sensitive topic’ pages. However, it’s unclear how this is managed.

4. How to tailor it your needs

Ensure your tags are connected to your cookie policy.

This can take numerous forms, but the most popular tools (such as One Trust and CIVIC) allow Google Tag Manager integration in some form.

Typically this is done through ‘consent_given’ or ‘consent_not_given’ variables. You can then connect these to all your marketing tags and ensure that what a user agrees to is what they actually experience on the website. 

If you are using Google Tag Manager (which we recommend), you could also consider using Google’s Beta test of ‘consent mode’ which will fire a tag when the desired action has taken place, but remove anything personable to that user in what it sends. As this is still in beta, you may wish to wait for it to be fully released before utilising it – but it is certainly an intriguing development.

Focus on Cookie Policy wording

A lot of focus is given to the wording on your policy page (and rightfully so), but actually you should be focusing on the consent prompt itself. Ensure that this is aligned with your organisational policy as well as ensuring that you present enough information to give users an informed decision. If you have the room, it’s always worthwhile explaining the ‘why’ to.

In the long term, it would be worth considering running tests to discover the impact of your wording. Can you test longer or shorter text? Different colour schemes? Ultimately you want to try and move the dial towards increasing the number of people who consciously consent to your tracking.

Move to server-side tracking

This is where we get a bit more technical, but I’ll do my best to keep it light. Server-side tracking will be necessary for future Meta Pixels and is now recommended by Google Analytics.

Currently the vast majority of pixel and tag tracking is done in the user browser, leaving organisations with little control over what is sent or isn’t sent by those pixels(or tags). In essence if you add the pixel, they receive everything they want in any way they want.

There is a shift in this though, as organisations look for more control on specific aspects of that data. In essence, they are happy to share some of it, but not all of it. And those platforms are responding.

Google and Meta both already recommend using a server container to run your tracking, and I’m sure this will soon become the default. A server container doesn’t run in the user’s browser or on their phone. Instead, it runs on a server that you control, and only you have access to the data in the server until you choose to send it elsewhere.

For Meta, utilising a server container means the platform only gets data you have chosen to pass on, enabling you to have more control over the data shared. This allows you to identify anomalies or block data before it’s sent to Meta. 

Facebook is actively encouraging users to move over to its conversion API tracking methodology – which is only available via server-side implementation.

Exclude specific users and actions

If you are worried about utilising your pixel alongside users who view sensitive content or take sensitive actions on the site, you don’t need to review the pixel entirely.

If you fire your Meta Pixel through Google Tag Manager, you can use exception rules to stop tags from firing on specific pages. This includes removing those users from remarketing ads – so you don’t have the situation of someone who is looking up support content asked to give a donation.

Within Meta itself you can remove the Universal Event Tracking (UET) element of the tag, which will mean that the pixel will only record actions taken on site that you specifically set up tags for. This again means you can avoid collecting information on things such as links or forms which are a constant presence in footers for example.

Be aware

Whilst you can take these steps to remove data points, be conscious of the fact that it’s this data which drives the power of Meta marketing. Removing any of those data points will have an impact – this could be small, but it could also be substantial. It should therefore be discussed and agreed across teams before you start to limit the data being collected.

 

Facebook Meta Pixel - Next Step Recommendations

5. Recommended next steps

There’s a lot to unpack here. But it’s definitely valuable as these things are constantly under scrutiny, so it helps to take a step back and look at what it does and why it does it. I wanted to lay out 5 key recommendations to take away with you, and help you navigate the ever developing world of the Meta pixel.

  • Move to server-side tracking using a server container. Google Tag Manager has a server-side variant which is the way we would recommend going. Unfortunately server-side tracking will likely come with a cost for you as you do need to host the container on a server, but this methodology for running marketing pixels will be the default (and maybe only) way very soon.
  • Review your cookie management tool. Ensure that your tag firing rules match the policy, and are managed in such a way that the users preference do impact on their firing/non-firing. The amount of websites I’ve been on where I refuse consent, and yet still get tracked is worryingly high!
  • Test using ‘consent mode’. As mentioned above, this is a way of still sending conversion data to your marketing platforms without sending any personally identifiable information. It’s still in Beta but definitely one to keep an eye on and we would recommend testing.
  • Ensure you discuss your marketing needs alongside the need for data protection. it could be that you can find a compromise which helps mitigate personal information being passed and minimises impact on your campaign performance. Especially with the use of server-side tracking it should be very rare that you need to remove the pixel entirely from your website, to satisfy a desire to protect users information.
  • Constantly be looking to test and optimise. Test the wording on your cookie policies, test using new channels to grow awareness, test different settings or structures, and test using ‘consent mode’ on Google Tag Manager.

Have any questions?

We’ll be advising our clients to move to server-side tracking across the next couple of months (once everybody gets over the grieving of Universal Analytics). So if you have any questions on the best way forward for you and your organisation, or any questions about the above, we’d love to hear from you. 

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    Facebook Ads: How to reduce CPAs

    Reducing CPAs for Facebook Ads - Blog Lead Image

    How can charities improve Facebook Ads performance

    In our last blog we discussed our predictions for paid media in 2023, which included a bleak outlook of the Facebook Ads landscape, with CPAs continuing to rise. However, it’s not all doom and gloom.

    The most significant reason for rising CPAs is due to a general decline in third-party cookies, especially following the iOS 14 changes, whereby loss of data has resulted in less precise targeting and worse machine learning.

    We’ve therefore shared some of our best tips and tricks you can start employing in your own campaigns, with the aim of reducing the cost of your Facebook Ads whilst actually improving results. We’ll touch on both settings and strategies to utilise on the platform which largely aim to help improve Meta’s own AI, by playing to its strengths.

    Below are some questions for you to consider about your current Facebook Ad campaigns.

    Are you maximising opportunities with automation?

    As third-party cookies have declined, so has performance on Facebook Ads, meaning advertisers have reduced their reliance on the platform. Meta have since invested heavily into improving their AI, and developing their automation offerings – as seen by the frequent new automation features (labelled advantage+) in 2022

    The general theory is, the more you resist the way Meta wants you to run your campaigns, the more your ads will be penalised. So these features have to be considered. They should be actively considered in your strategy, and not simply pushed aside. 

    That being said, you don’t need to adopt every single feature. Take the time to understand what each release can do, and whether it really is going to limit your campaign overall. Meta push the importance of the Power 5, so we would recommend starting here: Graphic on how to reduce CPAs

    This suite of tools includes:

    • Auto advanced matching (this can be toggled in Events Manager)
    • Campaign budget optimization
    • Automatic placements
    • Dynamic ads
    • Simplified account structure

    While the last point isn’t exactly a feature, Facebook advise against splitting out into multiple campaigns and ad sets, where the objective is the same. This approach allows for greater data pools per campaign/ad set, which improves machine learning, by reducing the ‘learning phase’. Exactly how broad or granular can be dependent on the situation and is something we highly recommend still testing. We will discuss this in more detail later though.

    Can you pivot the campaign to utilise lead-gen forms?

    The loss of data following the iOS14 changes has impacted Meta’s ability to effectively optimise. At least for click or conversion-optimised campaigns that rely on the pixel. Using a campaign format like lead-generation, can help minimise this impact.

    By keeping your users and data on the platform, their data will not be subjected to cookie-policies. This greater quality data pool can improve the machine learning as well as build better first-party audiences. 

    Lead focussed generation strategies Facebook ads

    Lead-generation focussed strategies do still need to be relevant to the objective, and rely on a good email strategy. For charities, we have found gift in will or legacy campaigns to work particularly well using this format.

    Are you leveraging first party data where possible?

    Remarketing or re-engagement is an extremely salient component of paid-social advertising. It’s vital to ensure these are well set-up and appropriately used. This includes audiences built on the platform, via the pixel or conversion API, as well as customer upload files from a CRM. This could be website visitors, Facebook engagers or previous sign-ups for example.

    Using high quality, first-party data to create lookalikes is still a great place to start when prospecting and scaling ad campaigns.

    Whilst ensuring your pixel is set-up to capture first-party data, it’s worth mentioning Aggregated Event Measurement. This is Meta’s protocol designed to allow for the measurement of events from (and improve delivery and reporting of) users on iOS14.5+ devices. If you haven’t already, it’s highly recommended you verify your domain and prioritise your AEM Events.

    Are your audiences too granular?

    We have historically adopted a highly granular and insight focussed approach, however, this is becoming increasingly challenging. Given the trend over the last year or so, we expect audience interests to be further decimated, and trying to target granularly, will start to seriously limit your reach and ability to effectively optimise, and may not even be possible. Allowing machine learning to tap into a wider pool of users speeds up the learning phase and improves results faster.

    Sure, we’re moving away from singular interest ad sets and multiple lookalike segments. But we still like to keep some level of granularity within our ad sets, where creative can be tailored (e.g. for remarketing).

    This is not a fixed rule though. We highly recommend testing and will continue to do so ourselves. Using entirely broad or run of network audiences will be more applicable in certain cases. One example could be if you are simply trying to reach a niche audience but relevant interests aren’t available. Another case could be you have large budgets available and need to scale. Or, you may have limited first-party data to create lookalikes.

    Are you utilising all creative formats?

    Different users need different messages, and may engage with content very differently depending on their format and placement. It’s key to ensure you’re offering Meta the greatest chance to test, learn and optimise messages for the right user.

    This extends to all standard formats (single images, carousels and video). You should also ensure you have placement-specific sizes, in particular for stories and reels. This is essential for optimal user engagement, which can ultimately impact how competitive you can be in an auction environment. If your CTR suffers, so does your CPC/CPM, and thus raising your costs.

    Examples of multiple creatives for Facebook Ads

    Are you reusing the same creative? 

    We can’t stress enough the importance of ensuring the creative concept and assets designed are high quality. Your technical set-up and Facebook strategy is only as good as the ad being run.  

    The best creatives are bespoke, stand-out and work in harmony with the ad as a whole and landing page. Poor quality and over-used creatives will receive poor engagement and increase overall costs. Similarly, if your fundraising message simply doesn’t resonate with your audience, you will be fighting a losing battle. We’re happy to recommend additional creative agencies who can help, so please do reach out to us.

    Have you tried alternative attribution settings?

    In response to limited data after the iOS14 changes, Meta also updated how their reporting worked. This included changes to attribution and conversion windows, which determine whether a conversion is recorded depending on how soon after a user clicked or viewed your ad.

    Attribution windows were reduced across the board, from 28-day click +1-day view as the default to 7-day click + 1-day view attribution. This means a conversion will be counted (and used for optimisation) if it falls either within 7-day after the ad was clicked, or 1 day after the ad was seen. However, due to reporting delays, the inclusion of the 1-day view makes use of statistical-modelling, which doesn’t always benefit Meta’s optimisation due to lower quality data being fed back.

    Testing click attribution for Facebook Ads

    There is a growing argument to suggest moving to a 7-day click only attribution setting, as this can drive higher volumes of quality traffic, and benefit performance in the long-run. This is especially effective when the consideration period for the service being advertised e.g. a donation, can be short, and the post-click performance (checking GA data) is fairly strong.

    Our above recommendations focus on in-platform changes. Yet, it’s worth noting that Facebook Ad performance is dependent on other factors, such as landing pages and general website. Considering your SEO, CRO and UX is extremely important (and are all services we’re keen to support on!) although that’s a post for another day!

    Want to optimise your Facebook Ads?

    We’d recommend testing our above suggestions to see what works best for your specific charity. Although, it might not be long until Meta make many of the automation-based suggestions compulsory anyway…

    If you’d like support to make the most out of your Paid Media budget for Facebook Ads, then we’d love to help you! You can contact us or send us an email at hello@upriseup.co.uk. We can’t wait to hear from you.

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      How to successfully run responsive search ads (RSAs)

      Not long ago Google announced the end of an era for expanded text ads. As of June 30th 2022, you will no longer be able to create or edit expanded text ads. 

      The announcement surfaced last year and here at Uprise Up, we’ve been preparing our client’s accounts ever since. Introducing responsive search ads (RSAs) into each of our ad groups ahead of June 30th. To help you also get ahead and be fully prepared for the change, we’ve jotted down our top tips in this blog for running successful responsive search ads. 

      First things first, what are responsive search ads?

      Responsive search ads (RSAs) are another step in the direction towards automation from Google. Expanded text ads (ETAs) had a set of 3 headlines and 2 descriptions that are shown statically, whereas RSAs allow us to select up to 15 headlines and 4 descriptions. Google then automatically tests the different combinations of these headlines and descriptions to give the user the ‘best’ performing combinations. 

      Ok, so what are the potential benefits of RSAs?

      • Improved performance. According to Google, advertisers that add RSAs to their ad groups achieve up to 10% more clicks and conversions. From our experience, we’ve also seen RSAs often out-perform existing ETAs when added into our accounts. 
      • Increase ad relevance and reach. More headlines and descriptions mean Google can serve more relevant combinations to the user. With more keywords in your ad copy, you’ll be entered into more auctions for relevant searches. 
      • They’re a time saver. Instead of needing to set up multiple variations of ETAs to test and learn, you only need the one responsive search ad which will test the combinations automatically.

      One thing to note is that while Google’s auto suggestions can often be useful, they are equally often not so useful. We’d advise taking a cautious approach when applying these.

      So, on the flip side, what are the potential downsides to RSAs?

      • Less control. Your ability to specify how an ad is formatted and reads overall is limited, due to the nature of the machine learning testing various combinations. This may lead to headlines appearing together which don’t necessarily work well or make sense to a user, or for your brand.
      • Reduced learnings. You cannot see as easily which headlines and descriptions have the best CTR and conversion rate, and therefore might work well outside of Paid Search.
      • Can actually take more time to select headlines and descriptions that work well together, but are unique enough, while also assessing whether to make use of the pinning feature (discussed below) can actually be more time-consuming than creating a standard ETA.
      • Beware of auto-suggestions. Google will be missing important context, so not all suggestions will be relevant.

       

      How to Run Responsive Search Ads Successfully

      Top tip time:

      • Include keywords in your headlines. To reach those good and excellent ad strengths you’ll need to make sure you have headlines relevant to your keywords. You can also use dynamic keyword insertions to insert your keyword into headlines, from experience this will help to optimise your ad strength. 
      • Include unique headlines. To give Google the variation it needs to test and optimise your RSA, you’ll need to keep your headlines unique. Try using a variety of calls to action and offers to improve headline uniqueness. 
      • Have a combination of short and long headlines. ‘Long’ headlines being within the 30 character cap.
      • Use all the headline and description fields available. If you can aim to fill out all 15 headlines and 4 descriptions, at a minimum include 10 headlines. 
      • Pay attention to ‘ad strength’. Google will offer you suggestions to improve the ad strength of your RSAs. You’ll want to get the ad strength up to at least “Good” but ideally aiming for “Excellent”.

       

      To pin or not to pin, that is the question.

      Responsive search ads are far from perfect, we’ll still quite often see Google pair similar headlines together as the highest serving combination (e.g. two branded headlines rather than a branded headline and a CTA). There’s definitely still questions to be answered. 

      Our biggest one is around the pinning feature. When setting up your RSA, you have the option to pin a headline or description so that they only appear in a certain position. While this sounds great (especially for controlling brand messaging), the ad strength of the ad is very much affected by the use of pinning. A lower ad strength may impact your achievable impressions share and your CPC, and may result in lower impressions/clicks as a result.

      With that in mind, you may be wondering: 

      • What is the actual impact of a lower ad strength on the total impressions?
      • Does this impact outweigh the benefits of improved brand messaging?
      • How do we best use pins to balance this impact?

      Fortunately, we have sought-out to find the answers!

       

      What we’re testing

      We’ve set up an experiment to test the pinning feature specifically. We’re running A/B experiments to test RSAs with no pinning, fully pinned, and a balance of pinning. 

      Specifically one thing we’re testing, is how the number of pins effects ad strength. For example will pinning 4-5 headlines in a single headline position still allow for a stronger ad strength compared to 1-2? 

      We’ll also be testing the impact of losing an ‘excellent’ ad strength in favour of pinning, looking at the effects on impression share against conversions. 

       

      We’ll be running this test over the next few months and look forward to sharing the results once they’re in.

      Here’s some examples of the types of variations we’re testing:

      Excellent

       

      Good

      Average

      Poor

       

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