Into the Great Unknown: Understanding and Leveraging Dark Social Traffic

The term "Dark Social" was originally coined back in 2012 by Alexis C. Madrigal of The Atlantic, to describe “untrackable” social content sharing through means like email, instant messages and even mobile applications. Dark Social traffic represents the sharing activity via private digital communication channels exclusive of referral headers and as a result, cannot be tracked by analytics tools. Most web analytics tools categorize Dark Social traffic as Direct, meaning grouping these content sharers together with users who reached a webpage by typing an exact page URL. 

However, it is highly unlikely that any user at all would type in long and “unfriendly” URLs, rendering the above categorization as misleading. But any other categorization is equally misleading, as with the lack of referral data, analytics tools are “in the dark” as to the origination of this “Dark Social”. 

However, Dark Social is too big to ignore. According to a 2014 Statista report, Dark Social accounts for the majority of all online shares.An additional hurdle to the tracking efforts is the increasing use of SSL by social media and community sites. By default, whenever someone is moving from a secure site to a non-secure site, no referrer data is recorded and transferred. And that's not all of it. Things get even more complicated on mobile; traffic just doesn’t flow as track-ably. 

Most mobile applications, including Facebook or Gmail, do not pass referral data. In fact, mobile traffic from Facebook was recently claimed to be the number one reason for Dark Social. Besides the usual Direct visits (visitors who type a website address directly into the browser, or click on untagged links from favorites and bookmarks), there are legitimate reasons why browsers do not always report where visits have come from. For example:

1. Clicking on untagged links via non web documents (e.g.: PDF files, documents, spreadsheets, presentations, etc.).
2. Clicking on untagged links from desktop email clients (e.g.: Microsoft Outlook).
3. Going through internal Meta Refresh and untrackable JavaScript redirects.
4. Clicks on links from social media Mobile apps like Twitter, Facebook, Pinterest, LinkedIn, as well as from QR code readers and many other applications.
5. Clicking on untagged links which include the "rel=noreferrer" attribute.
6. Some organic search traffic may also arrive with no referrer data (as recently reported by Gene McKenna of Groupon).
7. Going to a non-secure (http) page from a link on a secure (https) page.

Shedding Light on Dark Social

Luckily, as a marketer, there are several steps you can take to reveal the source of, and appropriately categorize, your Dark Social traffic:

1. Get smart with your URL tracking – Clean up some of your Direct traffic by properly tagging ALL of your marketing campaigns (this includes links in your email marketing campaigns, links posted on social media sites, links you can control on external sites, etc.) using custom campaign tracking parameters, such as the Google Analytics UTM tags.
2. Take control of your links – Implement advanced tagging mechanisms throughout your site. Develop and use easy-to-click smart share buttons that automatically attach proper tracking tags on each shared URL. Implement auto-tagging on sharing buttons, RSS feeds and even bookmarked links.
3. Use shortened tagged URLs – Wrap all branded sharing content using branded short links. Replace your long tagged links into short, branded and traceable links on your social media posts, email blasts, QR codes, offline campaigns, email signatures, text messages, etc.
4. Segment Dark Social audiences – Group your Direct traffic into different audiences; separate direct visits from desktop (including tablets) and mobile, but exclude those visitors who landed on the home page. In addition, some apps (such as Twitter and Facebook) include metadata to the User-Agent string that can be used to identify and segment mobile app traffic (iPhone as well as Android).
5. Eliminate analytics implementation errors and configuration issues – Make sure you're using server-side redirects (and not JavaScript and Meta Refresh redirects) and perform comprehensive tag audits and eliminate any tracking errors.
6. Get creative and develop ad-hoc solutions – Such as LunaMetrics’ opensource Directmonster.js solution (available on GitHub).

Acting On and Amplifying Dark Social Traffic

Now, once you’re able to recognize and segment some of your Dark Social traffic, you can leverage this opportunity to get ahead of the game by engaging this audience with custom tailored optimization initiatives. Here are just a few ideas for you to follow:

1. Engage Dark Social traffic with highly relevant recommendation widgets – Social media has become the epicenter of “pull marketing”, indirectly pulling and attracting natural visitors through interesting stories, deals, discounts and viral content. Leverage this “pull-mode” and reduce single page view visits by engaging Dark Social visits with targeted content recommendations. Turn the “pull-mode” into “push-mode” – by pushing highly engaging content towards people.
2. Implement behavioral exit-intent messages – Prompt subscription offers and tailored promotions to recurring Dark Social visitors upon display of exit intent. Personalize your messages and calls-to-action based on user interest and past behavior.
3. Retarget Dark Social visitors on Facebook and Twitter – Unlock new target audiences by utilizing programmatic media buying to retarget Dark Social visitors, directly on social media mobile applications.
4. Optimize social sharing based on contextual and behavioral signals – Tap into visitors’ natural desire to share popular and trending content by prompting sharing messages when a visitor views an article that is catching popularity.
5. Encourage sharing – Embrace the characteristics of this audience by offering them additional sharing tools that automatically include tagged links.

Clearly, the prevalence of Dark Social requires digital marketers, publishers and web analysts to take three major steps: (1) identify Dark Social traffic, (2) analyze and segment behaviors, (3) discover opportunities to engage with this audience. Source: Dynamic Yield

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Learn from the Experts: Instagram Tips

Instagram is still relatively new territory for marketers, but it’s quickly becoming one of *the* essential platforms for all sorts of businesses. The challenge is knowing how to create the sorts of content that will look appealing, and not too sales-y, in users’ feeds.

In today’s post we’ve gathered a handful of tips from Instagram pros that will help businesses gain traction on the photo- and video-sharing platform.

Ready?

#1: Be Consistent ~  Studio DIY/Jeff and Kelly Mindell

Know your brand inside and out! Create brand ‘filters’ or key identifiers for your account and stick to them. Start by defining a do’s and don’ts list to determine what your brand is and is not. For example, Studio DIY is bright, colorful photos with even composition and captions that highlight personality! We both keep to that aesthetic when sharing content which lends itself to a much more cohesive brand experience when visiting our Instagram feeds.

#2: Offer a Unique Perspective ~ Rebekah Radice

Whether you’re taking a picture of your latest event, product or creation, be unique in your content and perspective. Steer clear of simply throwing up pictures for the sake of it. Be strategic in what you share and engage your audience through appealing context that tells your distinct story. Every image has the power to connect your business to a new audience. Why not make your feed bold, beautiful, vibrant and perfectly aligned with your business or brand?

Highlight what’s special about your business, product, service or area.Christi with Love From the Oven is a perfect example of this in action. Every one of her pictures makes me drool. From buttery pretzel bites to mouth-watering peanut butter cheesecake bars, Christi makes me want to click through to her site and bake, bake, bake!

#3: Use Hashtags Strategically ~ Cyrissa @immersephotography &@sparkle.society

I love using hashtags to “move up the food chain!”  As a photographer, I’m up against a lot of competition and I always try to make it easy for my brides to find me!  If I’ve shot a wedding at a venue (or engagement session whose wedding will be at that venue), I’ll tag them in the photo, geotag their location, and use their hashtag.  All these things help my brides find me… because who do they usually book first?  The venue and the church!  Instagram makes it easier for me to reach my ideal clients.

#4: Use Scheduling Tools in Moderation ~ Christian Karasiewicz

One of the most requested features on Instagram is the ability to schedule Instagram posts. While Instagram doesn’t currently offer a native tool to allow you to schedule posts, there are a number of third-party tools available that can help with this.

Some of my favorites include: ScheduGram, Latergramme and TakeOff

When choosing between a scheduling tool remember, each of these tools has its own unique pricing and features so choose the tool that fits your situation, not just the tool that everyone else is recommending you use. Scheduling should be a part of your Instagram strategy, not your whole strategy.

I recommend scheduling content when you know you won’t be available to post. For example, if you’re attending a conference, giving a presentation, or writing a blog post.By scheduling Instagram posts in moderation, this allows you to keep fresh content in your channel to keep your audience engaged.

#5 Never Leave a Comment Behind ~  Sue B. Zimmerman

The best way to create authentic relationships on Instagram is to engage in conversation. I know this is time consuming but Instagram is where we grow our community the fastest and we want to respond to every question and comment to make our followers feel connected and valued. The same principles hold true for our company on Facebook, Twitter, and Youtube. (For more great tips from Sue, read our entire interview here.)

#6 Learn from the Experts ~  The Instagram Blog

On Instagram’s own blog you can learn how to perfect specific kinds of shots. In recent months there have been features on “Taking the Perfect Action Shot,” with tips from X Games photographers (@wilhelmvisualworks); “Capturing the Perfect Time-Lapse Video” with tips from Kevin Lu (@sweatengine), a New York based photographer who is on a quest to capture time-lapse videos on his iPhone; and “Cinematic Portraiture” with tips from Spanish photographer Lucia Fernandez Muniz (@luciafernandamuniz)

#7 Be Strategic with the One Link You’re Allowed in Your Bio ~ Jim Belosic, CEO, ShortStack

For personal use, Instagram is fun and spontaneous. But if you want to use it as a marketing tool, you have to be a little more calculating with it. I suspect the businesses that are really killing it on Instagram — Nordstrom, Starbucks, Nike, etc. — plan their posts well in advance. But even if you’re a smaller brand, or a one-man show, you can still develop a great presence on Instagram by using the link in your bio to connect to a landing page that holds the same posts you put on Instagram, but allows you to collect leads, promote your ecommerce site, gain subscribers to your blog, collect entries for a giveaway, etc.

Here’s what our bio link looks like: 

And when you click on the link, you’re taken to our Campaign, which looks like this:

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Does Social Media Sharing Matter?

On virtually every site you visit on the Internet, you’ll find social media sharing icons. Share! Pin! Tweet! Like!

Do these activities matter? Does all of that sharing create any kind of tangible benefit for the site? Instinct would say yes, but we cannot run a marketing department on instinct alone.

To answer this question, let’s put together a formal hypothesis: if sharing matters, there should be an association between the number of shares a page gets versus the number of page views that a page gets. While we cannot establish sequencing and causality, we can at least hypothesize that sharing a page should have a positive correlation to page views. Conversely, an unshared page should receive fewer page views.

It’s also important to note that we’re not examining clickthroughs on links or any other down-funnel metrics. We just want to prove or disprove a positive association between social media shares and page views.

Let’s first get our data. I’ll use data from my personal website so as to avoid revealing anything under NDA. I started by identifying the content to check. I’ll use my blog posts for the last 18 months:

From here I’ll load them into Excel, clean things up, and match them with the appropriate social shares using SHIFT’s proprietary social scanning software:

Now we do a Pearson correlation, plotting the total number of social shares on the x-axis and the total number of page views on the y-axis, then fit a trend line to the plot:

We do see a relationship, a reasonably strong one, between social shares and page views. The slope of the line is measured with a term named R-squared. R-squared is .61; if you take the square root of r-squared, you get an r-value, which in this case is .781. What does that value mean? The generally accepted meaning of r values is:

+.70 or higher Very strong positive relationship
+.40 to +.69 Strong positive relationship
+.20 to +.39 Moderate positive relationship
-.19 to +.19 No or weak relationship
-.20 to -.39 Moderate negative relationship
-.40 to -.69 Strong negative relationship
-.70 or lower Very strong negative relationship

Thus, we can say there’s a very strong positive relationship between social shares and page views. We cannot say which is the driver; does excellent content that garners page views in turn drive social media shares? Or do social media shares drive page views? The data cannot answer this question for us.

To dig a little deeper, which social network shows the greatest association between social shares and page views?

We see that for this data set, LinkedIn matters the most (r of .71), followed by Facebook (r of .65), then by Twitter (r of .39, a moderate positive relationship), and finally Google+ (r of .32). Across the board, there is a relationship between social shares and page views.

Social media shares matter; they simply matter unevenly. The discrepancy above means that sharing might matter more on some networks than others, or that some content resonates better with certain social audiences than others. Given that my site is a B2B-focused website and blog, it would make logical sense for strong affinity between LinkedIn and the content.

What would you do with this information? Test, of course! The first logical test would be to see if distribution matters more than content. I’d turn off my social posting for a week and see if it’s my social sharing that’s driving page views. If page views drop like a rock, then I’ve begun to establish causality. If page views remain constant, then I know it’s not my social sharing that’s driving page views, and I must develop a new hypothesis.

Alternately, if not sharing isn’t an option, I could increase the amount of sharing I do. Instead of sharing a blog post once a day, I could schedule it to be shared 2, 3, or even 4 times a day. This would test causality as well – if I saw page views increase by a proportional amount, I’d know that sharing was driving the results.

To get even more advanced, I could choose to increase sharing on the underperforming networks while leaving sharing the same on the networks that are performing well. I’d be looking for those networks to have more shares, and if I’ve established causality with page views from a previous experiment, I’d look for page views to increase commensurately.

Do the same level of data-driven analysis on your own content. Identify what content gets shared the most, which networks it is shared on, and what causes what. You’ll develop a strong understanding of what’s really working as you build your audience, create engagement, and ultimately drive business results.

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The Biggest Social Media Science Study: What 4.8 Million Tweets Say About the Best Time to Tweet

Imagine removing all guesswork when you schedule your tweets, knowing the times that work for maximum clicks and maximum engagement.

As someone who shares frequently to social media, this info would be fantastic to have! We’re always eager to dig up new research into social media best practices—things like length and frequency and timing.

The timing element, in particular, feels like one where we’d love to dig deeper. And we just so happen to have a host of data on this from the 2 million users who have signed up for Buffer!

With a big hand from our data team, we analyzed over 4.8 million tweets across 10,000 profiles, pulling the stats on how clicks and engagement and timing occur throughout the day and in different time zones. We’d love to share with you what we found!

The best time to tweet: Our 4.8 million-tweet research study

Our key learnings

Wow, we learned so much looking at the awesome stats from those who use Buffer! Here were some of the takeaways we came up with. I’d love to hear what catches your eye, too!

• Early mornings are the best time to tweet in order to get clicks.
• Evenings and late at night are the best time, on average, for total engagement with your tweets
• In some cases, the most popular times to post are opposite of the best times to post.
• Popular times and best times to tweet differ across time zones.

The most popular time to tweet:

Noon to 1:00 p.m.

We’ve taken the data from all tweets sent through Buffer to find the most popular times for posting to Twitter. Looking at all tweets sent across all major time zones, here is an overview of the most popular times to tweet.

• Noon to 1:00 p.m. local time, on average for each time zone, is the most popular time to tweet
• The highest volume of tweets occurs between 11:00 a.m. and 1:00 p.m., peaking between noon and 1:00 p.m.
• The fewest tweets are sent between 3:00 and 4:00 a.m.

Here’s the chart for the most popular times worldwide, taken from an average of 10 major time zones (the times represent local time).

Here is the graph for the most popular times to tweet in each of the four major U.S. time zones. 

(We normalized the data to account for daylight’s savings in the U.S. as well.)

Here are the charts for the major time zones in Europe and Africa.

(Note: The London (GMT) time zone used to be the default time zone for new Buffer users, so our data for GMT is not as clean as we would like it to be. We’ve omitted any takeaways for GMT from the research results here.)

Here are the charts for the major time zones in Asia and Australia.

It’s interesting to see how the most popular time to tweet varies across the time zones. We’ve shared Buffer’s 10 most popular time zones in the charts above. Here’s a list of each most popular hour for the 10 major time zones.

• Los Angeles, San Francisco, etc. (Pacific Time): 9:00 a.m.
• Denver (Mountain Time): noon
• Chicago (Central Time): noon
• New York, Boston, Atlanta, Miami, etc. (Eastern Time): noon
• Madrid, Rome, Paris, etc. (Central European): 4:00 p.m.
• Cape Town, Cairo, Helsinki, etc. (Eastern European): 8:00 p.m.
• Sydney (Australian Eastern): 10:00 p.m.
• Hong Kong (Hong Kong Time): 8:00 a.m.
• Tokyo (Japan Time): 2:00 a.m.
• Shanghai, Taipei, etc. (China Time): noon

For any clarification on this or the other research throughout this article, feel free to leave a comment and we’ll get right back to you.

Takeaways & thoughts:

• The most popular time to post could be due to a number of factors: This is when most people have access to Twitter (perhaps at a work computer), this is when online audiences are most likely to be connected (see Burrito Principle), etc.
• Should you post during the most popular times? That’s one possibility. Also, you may find success posting at non-peak times, when the volume of tweets is lower.
• If you have a large international audience on Twitter, you may wish to locate the particular part of the world where they’re from, and adjust your schedule accordingly. You can find the times when your audience may be online with tools like Followerwonk and Crowdfire.

The best times to tweet to get more clicks

We were excited to dig into the specific metrics for each of these tweets, too, in hopes of coming up with some recommendations and best practices to test out for your Twitter strategy.

First up, the best time to tweet for clicks.

Looking at the data, we found the following trends for maximizing your chance to get more clicks:

• Tweets sent between 2:00 and 3:00 a.m. earn the most clicks on average
• The highest number of clicks per tweet occurs between 2:00 a.m. and 4:00 a.m., peaking between 2:00 and 3:00 a.m.
• The fewest clicks per tweet happen in the morning (when tweet volume is particularly high), between 9:00 a.m. and 1:00 p.m..

The data in the below chart is the worldwide average, calculated for the local time in each time zone. So the peak at the 2:00 a.m. hour would hold true as the overall top time no matter which time zone you’re in—2:00 a.m. in Los Angeles, New York, Cape Town, Hong Kong, etc.

For the specifics on each of the best time to tweet for clicks in each of the major time zones in Buffer, here’s a breakdown.

• Los Angeles, San Francisco, etc. (Pacific Time): 2:00 a.m.
• Denver (Mountain Time): 7:00 p.m.
• Chicago (Central Time): 2:00 a.m.
• New York, Boston, Atlanta, Miami, etc. (Eastern Time): 11:00 p.m.
• Madrid, Rome, Paris, Berlin, etc. (Central European): 2:00 a.m.
• Cape Town, Cairo, Istanbul, etc. (Eastern European): 8:00 p.m.
• Sydney (Australian Eastern): 2:00 a.m.
• Hong Kong (Hong Kong Time): 5:00 a.m.
• Shanghai, Taipei, etc. (China Time): noon
• Tokyo (Japan Time): 8:00 a.m.

Takeaways & thoughts:

• Clicks was far and away the largest engagement metric that we tracked in this study (compared to retweets, replies, and favorites).
• Some of the recommended best times for individual time zones show thatnon-peak hours are the top time to tweet for clicks. This data may reflect some particularly high-achieving posts—some outliers—that bring up the average when the volume of tweets is lowest. Still, it’d be a great one to test for your profile to see what results you get.
• One neat thing to keep in mind is that a non-peak hour in, say, Los Angeles may correspond to a peak hour in London or Paris. The worldwide audience is definitely one to consider when finding the best time to tweet.

The best times for overall engagement with your tweet

We define engagement as clicks plus retweets, favorites, and replies. When looking at all these interactions together, we found the following trends formaximizing your chance to get the most engagement on your tweets:

• Tweets sent between 2:00 and 3:00 a.m. earn the most total engagement on average
• The highest amount of engagement per tweet occurs between 11:00 p.m. and 5:00 a.m., peaking between 2:00 and 3:00 a.m.
• The smallest amount of engagement happens during traditional work hours, between 9:00 a.m. and 5:00 p.m.

Takeaways & thoughts:

• The best times to tweet for engagement are quite the inverse of the most popular times to tweet. (The late-night infomercial effect—tweet when fewer people are tweeting—seems to be the case here.)

The best times for retweets and favorites on your tweets

Adding together two of the most common engagement metrics, we found some interesting trends for maximizing the retweets and favorites on your tweets, especially for those with a U.S. audience.

Looking at 1.1 million tweets from U.S. Buffer users from January through March 2015, here were some of the notable takeaways we found:

• Tweets sent at the 9:00 p.m. hour in the U.S. earn the most retweets and favorites on average
• The highest number of retweets and favorites occurs between 8:00 p.m. and 11:00 p.m., peaking between 9:00 and 10:00 p.m.
• The lowest retweet-favorite engagement happens at 3:00 a.m.

(Interesting to note, the takeaways from this data compared to the worldwide engagement data differ slightly for a couple reasons: 1) clicks represent a huge portion of overall engagement, and 2) the worldwide vs. US datasets vary.)

We’d love to make it easy for you to share these results with your audience, your friends, your clients—anyone you think might benefit from them.

>> Download every chart from this post (.zip) <<

The methodology for our research

We studied all tweets ever sent through Buffer—4.8 million tweets since October 2010!

Based on this sample set, we looked at the number of clicks per tweet, favorites per tweet, retweets per tweet, and replies per tweet, in accordance with the time of day that the tweet was posted to Twitter.

Further, we segmented the results according to time zones, based on the assumption that the learnings might be more actionable if they could be specific to exactly where you live and work.

We had an interesting opportunity to consider whether median or average would be the better metric to use for our insights. It turns out that so many tweets in the dataset receive minimal engagement that the median was often zero. For this reason, we chose to display the average.

Over to you: What are your takeaways?

We’re so grateful for the chance to dig into the stats from the many tweets that people choose to share with Buffer. The data is super insightful, both for sharing with others and for impacting our own social media marketing plans!

What did you notice from the stats here?

Did any of the results surprise you or get you thinking about your plans in a different way?

I’d love to hear your take on this! Feel free to share any thoughts at all in the comments!

Image sources: IconFinder, Blurgrounds, Death to the Stock Photo, UnSplash

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