Digital marketing has relied on cookies for years to track campaigns and show how spending pays off. But with privacy changes everywhere, the cookie jar is running empty! It's a big shift that leaves marketers wondering how to connect the dots or prove their work drives sales.
Tracking cookies is messy right now, no doubt about it. But rather than get frustrated, we need to see this cookie conundrum as a chance to upgrade our game. By getting creative with incrementality testing and statistical models, we can still map customer journeys and spend smart, even with crumblier cookies.
This article will break down:
- How cookies became marketing magic
- The new updates mucking up the works
- Impacts across social, search, and display channels
- Old school incrementality testing to the rescue
- Future fantasy: marketing mix models
- Key takeaways so your budgets don't go stale
Let's start by looking at why tracking cookies worked so well for growth hacking up until now.
Ways Primer can help
Securing the Bag with Cookies
In a nutshell, cookies are personalized text files websites place in your browser to remember who you are. They help sites serve up a consistent, tailored experience - kinda like how a bakery decorates your go-to cookie just the way you like it!
For digital marketing, third-party cookies offered even more powerful abilities. Platforms like Facebook dropped these cookies during website visits, which meant they could secretly follow you around the whole internet.
Creepy...but also extremely useful! Tracking cookies allowed Facebook to spot fans of yoga mats here, crossover SUVs there, and shoehorn people into ultra-specific ad audiences. Then, they'd tweak and test those groups to predict who was most likely to buy based on behavior.
So cookies fueled all kinds of audience wizardry, pinpoint targeting across sites, and the growth that came with it. Marketing teams could connect the dots to show spending led directly to more signups and sales. For the analytics geeks out there, the cookies made measuring channel attribution beautifully simple.
The Cookie Crumbles
Now imagine one day all the bakeries around you stopped making cookies altogether. That's just the thing that's happening to cookies in the digital world! Tracking cookies with all these privacy changes, updates, and new rules from Apple, Android, browsers, and such is nearly impossible now. It messed up the whole system that helped fuel crazy ad targeting and data collection.
On iPhones, IDFA codes that act like mini cookies are getting blocked, so Facebook and similar platforms go in blind, trying to connect your journey from ad view to actual purchase. Safari is shortening third-party cookie life spans from 90 days to just seven, so developers and analysts can't attribute long-term impact to different marketing campaigns anymore.
As a result, the percentage of traffic simply labeled "Direct" and "Organic" keeps ballooning. ulti-touch attribution across social, search, and display gets fragmented without tracking cookies. So suddenly, all that detailed data that helped prove the value of digital spending looks full of holes like a termite got to it!
Not awesome for showing the ROI and ironclad impact we want as marketers. When the CEO asks if we should renew big ad contracts, we scratch our heads, wondering if the analytics tell the whole story anymore.
In our article about surviving iOS 14 and the Cookie Apocalypse, we’ve highlighted the main challenges of new privacy-related restrictions and provided general recommendations on how to work around them.
Unique Fallout Across Channels
Nearly all digital ad channels rely at least partly on tracking cookies, so they collectively feel the sting. But specific platforms are getting a bit harder than others:
Facebook: Conversion pixels still optimize ads in-flight, but attribution data after the fact gets fuzzier. More sign-ups get marked as "Organic" since the dots between ad view and eventual form fill can't be connected anymore.
Google Ads: Search ads are less affected since Google links user profiles from services like Gmail more heavily to activity on their network. Tracking cookies isn't as critical for them to report on performances.
LinkedIn: Cost-per-metrics for leads and conversions look unreliable going forward. And LinkedIn's cookieless world means their platform struggles to apply past audiences or targeting traits to future campaigns.
Display/Programmatic: Display ads use cookie-dependent tactics like frequency capping, sequential narrative messaging, and retargeting, which now have huge blindspots. Performance analysis suffers, too, without the full picture.
The Testing Imperative
With all the holes appearing in customer journeys due to insufficient tracking cookies, marketers must get back to Marketing 101 with incrementality testing. Sometimes called lift testing or buy-in testing, the idea is to see performance lift uniquely attributable to a specific campaign.
It works like this: You pick a test market or ad account where you can flip a switch on or off for advertising to run. First is a business-as-usual period to baseline expected results when ads are paused. Then, you flip the switch and measure any uplift during the campaign flight. As long as performance spikes uniquely while a campaign runs, you can feel good crediting added revenue back to your spending even if multi-touch attribution falls short. In our article on “Cracking the B2B Marketing Attribution Code,” we explained the limitations of multi-touch attribution and how you can challenge them.
This style of isolated campaign testing has been around since the Mad Men days of advertising. Brands would run a TV campaign in certain test cities and then see if sales in those markets jumped compared to others. If so, they could safely assume the ads worked magic rather than some other random factor.
Zoom became masters of this testing methodology with their offline ads. They'd sponsor a billboard or run radio ads in select areas, then parse the data to see if web traffic and sales in those zip codes saw measurable lift over similar regions. They grew crazy fast with almost no tracking cookies and digital ads but were diligent about incrementally testing traditional channels.
The Crystal Ball
While incrementality testing saves the day for now, it does require manual effort and extended cycle times. Marketers might dream of the good old days when tracking cookies did that analytical work automatically!
The future offers hope of a new backbone to replace crumbling tracking cookies: marketing mix modeling. This uses big data and machine learning algorithms to uncover relationships between channels. By uploading a full history of spending, creatives, targeting, and performance data, we can train advanced models to estimate the causal impact of every variable.
The models output something like "Adding Facebook video ads causes a 2.3X lift in conversion rate on average historically." Rules of thumb like that help optimize budgets even with limited visibility into real-time attribution. No more flying blind on the value of each channel and campaign!
Marketing mix modeling requires heaps of quality data, rigorous analysis, and often outside specialists to build properly. For most marketing teams, it remains years away from feasible. But the concepts provide hope that even as cookies fade to black, mathematics and software can spotlight the levers driving growth.
Let's recap the key points so far into some practical tips for marketers navigating the crumbling tracking cookie landscape:
Know thy numbers (correctly). Cookiegeddon means reporting on channels can get wonky. Cost-per-conversion metrics will inflate; attribution models shift money to direct traffic. Make sure leadership knows to rebaseline expectations.
Apply special scrutiny for social. Channels like Facebook and LinkedIn lean heavily on third-party cookies for optimization and analytics. Measure their incrementality with added rigor.
Stay flexing those testing muscles. Regularly use on/off testing in isolated campaigns or regions to prove value. Helps keep budgets justified even as multi-touch models falter.
Explore modeling for the long run. Marketing mix modeling based on historical data offers a sequel to cookies. Start capturing the quality data now to feed the models of tomorrow.
Get sneaky with fakes. Marketers fight fire with fire, right? Serve up misleading fake personal data to browser extensions to maintain some tracking where you can.
Own the message. Rally teams around privacy changes are a chance to showcase marketing's versatility. Cookies ain't nothing but a word.
At the end of the day, marketing comes down to moving people: Inspiring them, understanding them, serving them. Tracking cookies happened to provide excellent fuel for that purpose over the past decade as digital matured. But the ingredients of success never relied on cookies alone.
Even if the precise tracking cookies enabled gets muddy going forward, the same foundations for great marketing remain:
- Researching customers' needs
- Crafting relevant and empathy-led messaging
- Finding avenues to get our voice heard
- Building tools to listen for feedback and optimize
- Testing and analyzing for continuous improvement
With initiative and spine flexible to what the future holds, marketers will continue finding ways to move audiences. And instead of cookies, new methods to quantify effectiveness will rise over time.
Use Primer to Reach High-Value Accounts Despite Crumbling Cookies
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