Marketers are living in unprecedented times. With the phasing-out of third-party cookies and a general tightening of online data regulations, finding ways to track consumer behavior is more complex than ever.
But adjusting to the new ‘privacy-first’ landscape is achievable. So in this blog, we’ll take a look at ways you can adapt your PPC strategies and campaigns to achieve the best possible returns.
How Are Privacy Changes Impacting PPC Tracking and Attribution?
To understand how marketers can overcome this challenge, we first need to understand what impact the privacy changes are having on PPC attribution and tracking
Alongside Google’s announcement of its intent to abolish third-party cookies, Apple has already altered the rules for its IDFAs (identifiers for advertisers). UK and EU businesses have also felt the impact of the GDPR directives on cookie use.
These changes have shifted the control of data back to consumers. They decide whether or not you can have their data, and how you can use it. So if, for example, users REJECT ALL or ignore the consent box altogether, well…yeah. All of the usual GA metrics you rely on to build PPC strategies and campaigns simply disappear.
This ‘invisibility’ of users also means it’s difficult to track visitor numbers, conversions AND, crucially, sales attribution. Not knowing where visitors are coming from leaves marketers in the dark about individual channel performance. And not knowing that makes it impossible to optimize the stuff that’s doing well, or fix what’s not.
What Are The Different PPC Attribution Models?
Marketers used to go by the rule of 7 – that it would take an average of 7 interactions with a brand before a purchase is made. It’s more than that now, with the sheer volume of ads we’re exposed to daily across various mediums, but the principle remains – that there are many touchpoints before purchase.
However, marketers need to know where the sale came from. So how do you measure it? Attribution models – the best way to measure PPC attribution in the privacy age.
Google defines attribution models as “the rule or set of rules, that determines how credit for sales and conversion is assigned to touchpoints in conversion paths.”
In English, attribution modeling gives marketers clearer data on what channels played the most important roles in converting a prospect.
Google has six:
Last Click Attribution
If you haven’t touched your attribution settings in your GA account, then, as the default setting, you’ll be using this model. ‘Last click’ is exactly what it sounds like – the last-clicked ad or keyword before the goal is reached.
Last-click attribution is not very useful for post-sale analysis because it doesn’t tell the whole story. It could make you think that other channels aren’t working very well when the reality is that they played a massive part in early-stage brand awareness!
That being said, it works well for simple ad campaigns without diverse remarketing lists.
First Click Attribution
The opposite of what we’ve just talked about, this credits the conversion to the ad or keyword that was first clicked.
The issues with this model are the same as the first-click model, except in reverse. It doesn’t factor in the multiple touchpoints that came after the initial click. It might have got their attention, but if you know it took other keywords for the conversion to happen, then clearly it wasn’t down to the first click.
This does work well, though, for awareness campaigns. High first-click rates indicate good engagement. It shows your ad or keyword was enticing enough to encourage a click.
This attribution model spreads the credit around equally across all interactions and gives you a good idea of what worked and what didn’t.
It’s suited to longer and more complex campaigns that require a multichannel approach. Campaigns targeting broader search terms, for example.
Time Decay Attribution
The Time Decay attribution model credits the actions that happened closer to the final conversion. Like the person crossing the ball and the person heading it into the net.
Again, this is a good model for longer-term campaigns. It helps you to understand how long your sales process is. But it’s not great for simple, short-term campaigns.
There’s an argument for this being the fairest model of attribution in how the credits are allocated. The two most influential clicks, the first and last, are given 40% each, with the remaining 20% being spread across the remaining interactions.
This model is great for understanding the combination of keywords that grabbed the most attention initially and which ones closed the sale.
The newest kid on the block, the Data-driven model uses machine learning to credit the keywords with the most influence on the conversion. It’s based directly on your account’s performance to date.
It’s probably the best of all the options because it removes chance and guesswork. But not everyone has access to it. You need a whole lot of clicks and conversions to be eligible – 3000 clicks and 300 conversions for a minimum 30-day period, to be precise.
How to Measure PPC Campaign Performance
Measuring campaign success needs good, clean data to begin with. With the phasing-out of third-party cookies, first-party data is essential to the marketing process. And the best way to get first-party data is by building trust with your customer base.
You may already be collecting it using tracking cookies across your website or app. In which case, get to know these customers better. Understand how you can use the data to personalize their customer experience.
Then think about ways to capture better quality data from customers – attributes that will help you to improve their experience. This in turn increases customer happiness and loyalty to your brand. Which means they’ll give you more data, and around we go.
If you’re not already collecting it, then start immediately. You can do this using:
- CRM platforms
- POS systems
- Retail apps
- Website analytics
- Affiliate marketing programs
Another way to ensure accurate measuring of PPC campaigns is highlighted by Andrew Hopkins, senior VP of customer acquisition and global products at Discover Financial Services.
He says, “We worked with partners, including Google, to set up a number of application programming interfaces (API) that delivered real-time data back to our marketing platforms so we could continuously optimize the messaging, cadence, and capping tactics on our live campaigns. We saw an immediate lift in marketing performance and efficiency, and increased our investments in the best performing channels.”
Bridging The Gap Between PPC and Other Marketing Channels.
Third-party data is gone for good. Its phasing-out will leave gaps in how GA reports on PPC performance. But there are tools out there that can help you (to an extent, otherwise what’s the point in new privacy regulation?) identify and fill them.
And it tracks visitor numbers, referral sources, and conversion numbers, which is handy.
We’ve already touched on the importance of first-party data in bridging the gap. And one thing is for certain: to acquire new customers, ads will need to be more data-driven than ever before. That means marketers need to do two things: get more of it and do more with it.
Here are a few ways you can do that:
- Ask for it. Sometimes, it’s easy to look past the obvious and miss what’s staring you in the face. But the most straightforward way to get more first-party data is simply to ask for it. If you’re providing a good user experience, you might be surprised at your loyal customer base’s willingness to share it with you.
- Build partnerships with companies where you can match first-party data.
- Consider using the data owned by Google, Facebook, Apple et al. Consumers use these platforms daily and so there is an opportunity to advertise and track within these environments.
- Use contextual targeting. “Like beer ads in a bar: go where your customers are. For consumers, contextual advertising, based on keywords or the webpage content, feels relevant and less creepy than third-party cookie-based retargeting.” – R&CSaatchi.
Measure PPC Performance On Real Users – Not Bots
One final thing to mention about your data.
It’s hard enough acquiring it as it is without bots undoing all your hard work and skewing marketing figures.
We mentioned earlier that clean data is the basis for optimizing the success of a campaign. Lunio provides a centralized protection against bots across all paid channels, ensuring your data stays clear of invalid clicks and other fraudulent activity.
Start a trial now to see it in action.