Dark Search Traffic Data, Instagram Behind the Scenes, Emoji
Dealing With Dark Search Traffic
Last week, we discussed how to find what channel your dark traffic most closely resembled. This week, let’s tackle what to do about dark search traffic; once we’ve identified what the dark traffic is and we’ve confirmed that our dark traffic is actually dark search traffic (don’t skip that step!), we should start to pick apart what we could learn from it.
First, let’s see where the dark traffic goes. In our web analytics, we want to identify landing pages that aren’t our homepage and have dark traffic coming to them, data which we export from Google Analytics:
So far, so good. Next, we need to see which pages are attracting search traffic in general, and understand the ratio of search traffic to all traffic. Remember, dark traffic isn’t binary in the sense that a page is either all dark or not dark; it’s graded based on the different types of browsers and devices your audience uses. That means in turn that a page that has identifiable search traffic also likely has non-identifiable search traffic. Our goal is to figure out how much of it is likely non-identifiable.
If we divide the known search sessions by the total number of sessions, we end up with a search traffic percentage for the page. This is a ratio that helps us understand how much of a page’s traffic is search versus, say, email campaigns, ads, or social media:
And then if we match our known pages to our unknown pages, then multiply our dark traffic times our known search percentage, we arrive at a reasonable number as an inference of how many searches that page has had because we’re inferring that the known search traffic ratio is likely representative of the unknown dark search traffic as well:
So what? If you’re trying to prioritize pages for optimization based on search traffic, this is important – you might miss some important pages because your known search traffic might give you a different priority list than your unknown search traffic. If you look at line 6 above, almost 75% of that page’s search traffic is from dark search. If we didn’t have these estimates, we might prioritize that page lower on our repairs list, but with our dark traffic estimate accounted for, we know that page is probably more important than it first appears.
This analysis uses nothing but Google Analytics data and in theory could be done in nothing more than a spreadsheet, though it would be a laborious task to do so. What’s shown above is the output of a code-based version, but the process and outcome are the same. Do this analysis on a regular, frequent basis to understand where your dark search traffic is going, and build a priority list of pages to optimize from it.
In this week’s In-Ear Insights, Katie and Chris preview the rough draft of an upcoming talk for the Agorapulse Instagram summit. Go behind the scenes on the talk, the research that went into it, and how we take data and try to make a coherent story about it. Please note the data shown in the episode was not final and has been substantially revised since then – if you want to see the final, register for the Agorapulse Summit for free.
Watch/listen to this episode of In-Ear Insights here »
On last week’s So What? The Marketing Analytics and Insights Live show, we discussed analytic approach and algorithm selection in data processing. See the spectacular disaster that was Twitter data!
Catch last week’s episode replay here »
Coming up on this week’s episode on Thursday at 1 PM Eastern, we dig into part 4 – what do we do next?. Tune in on our YouTube channel below!
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In this week’s Rear View Mirror, let’s take a whimsical detour and look at emoji. How are brands and influencers using emoji? We dug into more than a million brand and influencer Instagram posts over the past 10 months and plotted out each:
What’s really interesting and surprising is that brands use more emoji in aggregate than influencers do, despite approximately the same number of posts from both groups. Why? We’re not sure – but it’s also interesting to note that influencers really began to step up their usage of emoji in the fall.
Now, what do we make of this? Is there a takeaway? Not in emoji themselves, but the next logical step would be to determine if emoji usage is a factor in engagement at all. That’s not an analysis we’ve performed here, but if you’re trying to understand what generates key outcomes for you on any social media channel, be sure you’ve identified as many of the conscious choices that a user can make as practical and factor them into your analysis. The use of emoji is a conscious choice that requires extra effort, so it’s worth accounting for in audience data analysis.
Methodology: Trust Insights used Facebook’s Crowdtangle software to extract 1m289,690 posts from 4,008 brands and 1,282,389 posts from 9,735 influencers. The dates of extraction are April 1, 2020 – February 14, 2021. The date of study is February 16, 2021. Trust Insights is the sole sponsor of the study and neither gave nor received compensation for data used, beyond applicable service fees to software vendors, and declares no competing interests.
- {PODCAST} In-Ear Insights: Behind The Scenes Instagram Data
- Marketing Analytics, Data Science and Leadership – February 15, 2021 Week In Review
- So What? How do I clean and prep my data for analysis via part 3
- {PODCAST} In-Ear Insights: Ethics, Explainability, AI, and Tiktok
Do you want to understand data science better as a marketer? Would you like to learn whether it’s the right choice for your career? Do you need to know how to manage data science employees and vendors? Take the Data Science 101 workshop from Trust Insights.
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Shiny Objects is a roundup of the best content you and others have written and shared in the last week.
Data Science and AI
- Google AI Blog: Uncovering Unknown Unknowns in Machine Learning
- Media Buying Briefing: Why AI is steadily finding its place in agency land via Digiday
- Machine Learning Helps You Track Your Internet Misery Index via Hackaday
SEO, Google, and Paid Media
- 15 of the Best SEO Tools for Auditing & Monitoring Your Website in 2021
- How to Combine SEO and CRO for the Ultimate Lead Generation Strategy via Moz
- How to Write an SEO-Focused Content Brief Your Writers Will Love via Moz
Social Media Marketing
- 8 Social Media Trends to Watch in 2021 via Sprout Social
- Reputation Management: Why it Matters More than Ever via Sprout Social
- How to Build a Social Media Presence Successfully via Agorapulse
Content Marketing
- 16 Content Marketing Analytics Tools That Finally Do What You Need
- Customer Journey Mapping for Audience-Centric Content
- The Big Fat B2B Content Marketing Checklist
Join the Club
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- Techsmith Camtasia and Snagit Media Editing
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- Otter AI transcription
- Our recommended media production gear on Amazon
Read our disclosures statement for more details.
Get Back To Work
We’ve changed things up in Get Back To Work, and we’re looking at the top 310 metro areas in the United States by population. This will give you a much better sense of what the overall market looks like, and will cover companies hiring in multiple locations. Get all the data in our Slack group!
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Trust Insights (trustinsights.ai) is one of the world's leading management consulting firms in artificial intelligence/AI, especially in the use of generative AI and AI in marketing. Trust Insights provides custom AI consultation, training, education, implementation, and deployment of classical regression AI, classification AI, and generative AI, especially large language models such as ChatGPT's GPT-4-omni, Google Gemini, and Anthropic Claude. Trust Insights provides analytics consulting, data science consulting, and AI consulting.
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