In short
Podcast Episode Summary
Podcast Title
Marketing School - Digital Marketing and Online Marketing Tips
Episode Title
Dark Social's False Attribution to 'Direct' Traffic
Episode Description
In episode #2622, Neil Patel and Eric Siu discuss the challenges associated with accurately tracking web traffic amid the rise of dark social. They highlight the misclassification of social referral traffic as direct traffic and the implications for marketers and website owners. With growing privacy concerns, traditional analytics tools like Google Analytics are becoming less reliable. The episode emphasizes investing in brand recall studies and qualitative data to enhance understanding of visitor origins.
Time-Stamped Show Notes
- (00:00) Introduction to the topic: Dark Social's False Attribution
- (00:40) Discussion on misclassification of social referral traffic as direct traffic
- (01:38) Explanation of dark social and attribution challenges
- (02:03) Impact of increasing privacy concerns on tracking web traffic
- (02:54) Shift towards traditional marketing models and multi-touch attribution
- (03:45) Strategies for capturing qualitative data and attributing leads
- (04:17) Importance of investing in brand recall studies
- (04:23) Challenges with data analysis using Google Analytics
- (05:23) Utilizing custom reports and daily dashboards for analytics
- (05:46) Conclusion and reminder to rate, review, and subscribe
Key Concepts and Discussions
- Misclassification of Traffic
- A major point discussed is how a significant portion of social media referral traffic is incorrectly recorded as direct traffic. This misattribution can skew analytics and impact marketing strategies.
- Understanding Dark Social
- Definition: Dark social refers to social media engagement that cannot be tracked or attributed, such as shares via messaging apps or private groups.
- Attribution Challenges: With traditional analytics systems failing to accurately capture this data, marketers face difficulties in understanding the true sources of their traffic.
- Privacy Concerns Impacting Tracking
- With rising privacy concerns, many users opt-out of tracking cookies, leading to a decline in the reliability of platforms like Google Analytics.
- The episode mentions that a substantial percentage of users (over 68%) decline tracking consent, further complicating data collection.
- Transitioning to Traditional Marketing Models
- The discussion suggests a shift back to more traditional marketing methodologies, such as media mixing models and multi-touch attribution, to comprehend the effectiveness of various marketing channels.
- Strategies for Capturing Qualitative Data
- Brand Recall Studies: Emphasized as crucial for understanding how customers first heard about a brand.
- Surveys: Suggestion to survey leads and customers to gather qualitative insights about their origins and decision-making processes.
- Challenges with Google Analytics
- The hosts express frustration with the complexity and usability of Google Analytics, noting it has become increasingly difficult to derive meaningful insights from the platform.
- They advocate the creation of custom reports and dashboards that better serve their specific analytical needs.
- Focus on Business Metrics
- The hosts reveal a shift in focus from purely tracking traffic metrics to understanding broader business metrics such as lead conversions, average sales cycles, and estimated lifetime value (LTV).
Key Takeaways
- Marketers should not solely rely on traditional analytics platforms due to rising inaccuracies in data attribution.
- Investing in brand recall studies and gathering qualitative data is essential to gain accurate insights into customer behavior.
- The landscape of digital marketing is evolving, necessitating adaptations in strategies and tools used for tracking performance.
Conclusion This episode of the Marketing School podcast provides valuable insights into the challenges of tracking web traffic in the context of dark social and privacy concerns. It encourages marketers to rethink their strategies and invest in more reliable methods of understanding their audience and optimizing marketing efforts.
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Additional Resources
- [Rand Fishkin Blog](https://sparktoro.com)
Connect with the Hosts
- [Neil Patel](https://www.neilpatel.com)
- [Eric Siu](https://www.singlegrain.com)
Feedback
- Suggestions for future topics are welcome in the comments below.
- If you enjoyed this episode, please leave a short review.
Written by AI. May contain mistakes. Listen to the episode to check what was said.
Transcript
Automatic transcript. May contain errors.0:00All right, so we're going to talk about how dark social falsely attributes significant percentage of web traffic as direct. So this is a post from Ran Fishkin. So he formerly, he founded Moz. He's the founder, one of the co-founders of SparkToro. And so Ran Fishkin over here, you can see on the SparkToro blog. So he basically says that at a high level that, actually, I'm going to pull, I'm going to go all the way down here. So takeaways, I'm going to go to takeaways over here. So takeaways, if you are a marketer or website owner relying on analytics platforms, Google analytics, or anything else to provide accurate, comprehensive information about where your visitors came from and how they found your website, we recommend revisiting those assumptions.
0:40A substantial portion of social traffic referral, social referral traffic comes without proper accurate referral data and is misclassified as direct. If you're attributing all direct visits to type in visitors, email, text message, offline, brand campaigns, or dark search because of dark social, you're almost certainly undercounting the impact of social media marketing, social referrals, and word of mouth networks. Now, Let me call out one more thing real quick before we move on here. So in this graph up here, you can see the results at a glance. You can see basically 100 % of TikTok traffic is attributed to direct.
1:14Same with Slack, same with Discord, same with Mastodon, if anybody uses that. WhatsApp is 100 % as well. Facebook Messenger, 75%. And Instagram is about 30 % or so. So let me explain dark social really quick. And then Neil, you can give your reaction. So dark social basically just means it's like the social media post that you post and you're basically not able to attribute it, which is why it's called dark. But you know, it's funny, you're gonna see even more direct traffic, because when people come to your website, typically you have consents. Like, do you allow cookies? Do you not do allow tracking?
1:49Do you not? Most people say no. Like we looked at our stats the other week, over 68 % say no. In essence, they're saying don't track me. That's a lot. Now that's over a week. It's not the whole web. And yes, our audience is marketers, but still, we have millions and millions of visitors a month. So the sample size is large enough. It's going to get worse and worse. We're going back to a model in marketing where you have to start doing things like media mixing models and things like that to figure out where you're getting an ROI and where you should be spending your money. People want more privacy.
2:27They want access or they want to control the rights to their data. And I'm not saying these are bad things at all. It's just changing the web and marketing landscape to being more of a traditional model where you got to start doing multi-touch attribution and figure out, all right, where are people coming from, brand recall studies, where are people actually buying from, And how can we go and take that data and figure out where to allocate our budgets? Yeah, like five, 10 years ago, everyone's like, everything's going digital. You have to be able to track everything. The reality now is things are becoming less trackable.
3:02And what you could do is you could, for example, when we have a lead that comes in through the single grain website, we'll ask them, hey, how did you hear about us? Like, where did you come from? We'll also see the first URL, which where they submitted or where they came in from. We'll then also see the URL, the last URL where they actually filled out the form. So we're looking at first and last touch attribution, multi-touch, more ideal. But then we're also asking which search term they put into whatever platform they came from. So we're trying to get that qualitative data. And then let's say you have people on your email list as well.
3:32You can also survey this list and say, hey, where did you first hear about us? So it's not like this stuff is completely opaque. There are ways for you to capture your audience. Like when the leads are coming through, you can just capture that data. Yep. Look, I think with marketing, you have to start doing, companies should. I think they need to make a much bigger investment in brand recall studies. Look to see where visitors are coming from and look to see where buyers are coming from. That'll give you a good understanding of where you should be investing your dollars. Don't just rely on analytics.
4:07The data is getting harder and harder to track and becoming accurate because of a lot of the laws and the changes that are coming, especially with the cookie list future that's happening soon enough right so you need to start investing in brand recall studies to figure out where you should be investing your money yeah i mean neil and i used to look at google analytics every day and now like i can't even look at it because it's so difficult to slice and dice it just makes me not want to log in anymore dude how when's the last time you logged in your google analytics i log in like maybe once every one two weeks or so because i do have reports set up but it's just like it's not easy like Like you can't even, you know how like you can use to be able to make the graph like it was sorted by daily where it was hard to read.
4:48So it didn't get sorted by weekly and then monthly. You can't even do that anymore. Yeah. Yeah, I haven't logged in in a long time. I probably haven't logged in in like two months. But on that counterpoint, I do have a daily dashboard that pulls in a lot of analytics data that I see every single day. So it's kind of like the same thing as logging in. It's just we've created our own custom reports that break down everything we need. So then I just look at that every single day and it's not just visitors for me. It looks at visitors, sources, lead conversion, pipe, pipe to close, average sales cycle, MRR, estimated LTV, etc.
5:23Yeah, it's interesting. The dashboards I look at now are either GDS or Looker dashboards. And then also we look at our HubSpot reports as well just to look at pipeline as well. So we're looking at more business side of things, I think. So I mean, maybe when we used to look at this stuff pretty hardcore 10 years ago, we were more focused on traffic. Now we're more focused on kind of general business. So time changes. So that is it for today. Please don't forget to rate, view, subscribe and we'll see you tomorrow.

