There have been some fundamental shifts in the digital marketing landscape in recent years. In his recent webinar Rand Fishkin he explored how marketers can keep up with 2024’s biggest issues in digital marketing. 

It’s clear there has been a massive impact by AI on digital marketing but that’s not all. Old, reliable tactics (such as the performance advertising barrage, the SEO + content flywheel, the influencer marketing takeover, and the big, splashy media launch) simply don’t cut it any more.

At the same time, other forces have become far more influential. We’ll break down each of these, examining the stats and challenges, and offer key takeaways to continue your marketing success.

• The death of trackable martech
• The rise of dark traffic
• The big lie of marketing attribution
• The end of the rising tide 
• Living in a zero-click world
• Email: the last channel standing
• Other channels to consider

Watch the full webinar below.▶

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” You probably have noticed if you’re in marketing that a lot of the strategies we used as successful don’t work no more “– Rand Fishkin

The death of trackable martech

Marketing technology once promised to track and attribute the entire customer journey, from discovery to purchase, allowing marketers to assign dollar values to each step. However, this trackability has significantly declined due to data privacy laws, increased use of ad blockers, and changes in cookie effectiveness. Multi-device journeys and the combination of apps and websites have further complicated tracking, making it difficult to accurately attribute marketing efforts to sales.

The decline in trackable data has made it challenging for marketers to justify investments in content, SEO, and other marketing initiatives. Google’s monopoly power has led to an increase in ‘zero-click’ searches (where users find answers directly on the search results page without visiting websites). This trend is particularly pronounced in the EU, where nearly two-thirds of searches end without a click, and it’s only slightly lower in the US.

” Running ads without getting scammed has become a full-time job for marketers. “– Rand Fishkin

Major platforms like Meta (Facebook and Instagram) and Google do not proactively notify advertisers of overcharges or false clicks, requiring constant manual auditing to avoid wasting ad spend. This situation has made it necessary for many businesses to employ agencies, consultants, or dedicated team members to monitor and audit their advertising efforts regularly.

Key takeaways

1. AdTech is less trackable, and less reliable than in years past. Make sure you’re building and testing your own models. 
2. Fraud, misleading attribution, and easy overspending mean it’s critical to regularly conduct ad audits, and manually file complaints with your ad providers.
3. If you currently run ads that rely on third-party cookies (in other words, almost everything outside Apple’s ecosystem), prepare for a massive shakeup in the next year, probably including higher ad prices.

The rise of dark traffic

The rise of dark traffic, also known as dark social, is a significant trend affecting marketers’ ability to track and attribute website visits accurately. Many companies find that their marketing efforts often involve people hearing about them through podcasts, webinars, or social media posts. However, when these individuals eventually visit the company’s website, the traffic is typically attributed to direct visits or organic search, masking the true sources of influence.

For instance, SparkToro’s own analytics show that 76% of their visitors come from direct traffic and 13% from organic search, accounting for 90% of their total traffic. However, this data is misleading as it doesn’t reflect the actual sources that led users to search for or directly type in the company’s URL. In reality, much of this traffic likely originates from various platforms like WhatsApp, Slack, LinkedIn, Instagram, Facebook, TikTok, and Discord, where people discuss and share links to the company’s content.

An experiment conducted with Steve Lamar from Really Good Data revealed that many traffic sources are incorrectly marked as direct. For example, traffic from Slack communities, both private and public, is often misattributed because the referral string is removed. This issue is particularly prevalent in B2B contexts, where discussions and link sharing in private channels lead to website visits that cannot be accurately traced back to their origin. As a result, companies are unable to see and measure the impact of these important traffic sources.

” We are getting traffic from WhatsApp, from Slack, messages and boards, from LinkedIn and Instagram and Facebook and all these places where people are talking about us and linking to our posts. And the referral data is hidden. “– Rand Fishkin

Key takeaways

1. If you’ve moved away from social media investments because you can no longer see the referral traffic, you’re likely losing out to smarter teams who focus on reach and attribution. 
2. If you need to track search and social for your client or boss, it’s time to revisit so-called ‘vanity metrics’, because they’re the only things that can show you relative reach and engagement.
3. Investing in sources that send indirect or un-attributable traffic doesn’t have to mean un-trackable! You can build time-series or geographic measurement systems to see the results of dark traffic channels.

The big lie of marketing attribution

We’ve seen cases where companies like Airbnb have drastically reduced or eliminated their advertising budgets without experiencing a decline in results. This phenomenon calls into question the effectiveness of traditional advertising and our ability to accurately attribute marketing efforts.

To illustrate this problem, consider this story about a pizzeria owner in Milan who hired three teenagers to distribute flyers with discount codes. One teenager appeared highly successful, but it was later discovered he was simply handing out flyers to people already heading to the pizzeria. This anecdote parallels how companies like Google and Facebook might be taking credit for sales that would have happened anyway, using their vast data to target ads at people who were likely to make a purchase regardless.

Attribution modeling has always been flawed and is becoming increasingly unreliable due to factors such as privacy laws, the use of multiple devices and browsers, and the rise of dark traffic. 

Despite claims from martech vendors about improved attribution through AI and machine learning, it’s impossible to build attribution models accurate enough to precisely credit all touchpoints in a customer’s journey, especially given the complexities of our modern digital landscape.