Random Labs: Are Keywords or Hashtags Better for Reach on Instagram?

As we turn the page into 2025, we decided it was a great opportunity to open the year with another Random Labs experiment. This time, we focused our analysis on Instagram, a rapidly changing social media platform, to understand the impact that keywords or hashtags may or may not have on Instagram reach.

Do Hashtags Actually Increase Reach on Instagram?

There have been frequent arguments throughout Instagram's lifespan associating the use of hashtags with improved post exposure. If this was true, we would expect higher reach among these posts. However, questions about the effectiveness of this conventional aspect of social media posting have been increasing in recent times.

One rebuttal involves the idea that performance relative to captions is more attributed to the keywords themselves rather than strictly to hashtags. Adam Mosseri, the CEO of Instagram, has previously commented about his platform’s changing environment to user experience and content discovery, which may have seemed like an exclusive role to hashtags in the past. 

How We Tested the Effectiveness of Keywords

At Random, curiosity—one of our core values—often drives experimentation. With this in mind, we tested different caption strategies on our own Instagram content to evaluate this hypothesis. Below is an example of what the differences in captions looked like.

Keyword-Rich Instagram Caption:

View this post on Instagram

A post shared by That Random Agency (@thatrandomagency)

Hashtag-Rich Instagram Caption:

View this post on Instagram

A post shared by That Random Agency (@thatrandomagency)

To maintain an adequate sample size for this hypothesis testing, we also included zero-hashtag content that did not contain additional keywords. 

Performance metrics were analyzed on a per-month basis and compared with similar content types to further narrow down performance within the same time frame and context. For example, Instagram reach for reels will average significantly higher in this metric compared to single image posts so we compared reels without hashtags to reels with hashtags. There’s a lot of random (no pun intended) noise in the world of social media, so it’s essential that we fine-tune our testing. 

The Results: Are Keywords or Hashtags Better for Reach?

We utilized 8 of the 12 calendar months to create individual monthly comparisons of averages between no-hashtag content and hashtag content. The content we compared them to was pulled from a random sample of similar content within the same month and cleaned of any outliers or viral content. The following table summarizes the average results for each month:

MonthReach (No Hashtags)Reach (Hashtags)Difference
February24683+196.4%
April44644+913.6%
June14474+94.6%
August11459+93.2%
September11168+68.2%
October15299+53.5%
November45767+582.1%
December56139-59.7%

The table contains columns representing the months where the experiments were held, the average post reach of content with or without hashtags, and the percent difference between these averages. 

Interestingly, in 7 out of the 8 months tested, we observed that content without hashtags had a higher average reach. In several of these months, the differences in averages were in the triple-digit percentage range. Surprisingly, in 6 out of those 7 months, the posts without hashtags outperformed those with hashtags in reach. They also ranked as the top-performing posts for their respective months.

What Is the Significance of Our Results?

Before drawing any definitive conclusions, we need to establish some basic statistical boundaries. The majority of the tested content consists of reels, which inherently show greater variation in reach compared to other content. Other factors likely have a greater influence, including the topic, quality, timing, and various external elements. 

Additionally, this is a newer experiment, so a larger sample of posts still needs to be evaluated. However, the initial results align with the platform's general trend of decreasing reliance on hashtags.

So, how will hashtags be utilized on this platform in 2025? They will continue to serve their primary purpose of helping users manually discover content within specific categories. However, overloading posts with hashtags is unlikely to significantly impact reach and may even lead to negative returns. As we’ve often concluded in previous Random Labs sessions, every profile is unique. Be sure to base your evaluations on your own data.


Need a data-backed strategy to grow your digital results? Chat with our team today!

Random Labs: Does Geo-Tagging on Instagram Improve Performance?

Geotagging has long been a popular feature on Instagram, allowing brands and users to tag locations on their Instagram posts, thus enabling their followers to see where the content was created.

The general understanding is that enabling this feature on your Instagram content can potentially (and positively) impact the performance of said post. Some commonly cited benefits include higher engagement, increased reach, and improved discoverability of content. 

But we wondered…is this true? In this edition of Random Labs, we will be doing a basic comparison of metrics between content with geotagging enabled and content without geotagging to validate some of these hypotheses. 

What is a Geo-Tagged Instagram Post?

We will be evaluating organic content performance for Instagram from our awesome partners over at Trasca & Co Eatery and Ponte Vedra Tap Room. We tallied all the content posted on these Instagram channels over 2024, using geo-tagging as a separator. The following images show examples of Instagram posts that feature this:

View this post on Instagram

A post shared by Trasca & Co Eatery (@trascaandco)

Our Analysis of Geo-Tagged Instagram Posts

For the comparative analysis, we compiled a sample of approximately 150 posts from 2024 and compared the descriptive statistics of post metrics, using a simple identifier to separate the data: posts with geotagging versus those without. As it is generally difficult to obtain identical samples of both types of content throughout the year, we will use a similar method of comparing uneven samples, as we did in our previous Random Labs analysis on the performance impact of faces in social media content.

The following table compares the average metrics between the two types of Instagram content as well as the test results for each unique post metrics:

Once again, in this Random Labs analysis, we use hypothesis testing to statistically determine whether any Instagram performance metrics differ between content with or without geotags. 

A Quick Statistics Lesson

The sample size for each post type is denoted by n, a widely used standard notation in statistics. We also report the averages for both types of content (with and without geotags) along with the corresponding p-value from the test for each specific metric. 

A p-value helps you understand whether the result of an experiment happened by random chance or by something meaningful—geotagging, in our example. Furthermore, we need a way to decide whether the p-value is small enough to consider the result significant. 

This is where the alpha (α) level comes in. This alpha level is a threshold we set before the test to decide when we will be convinced that those results were meaningful. 0.05 is a commonly practiced threshold, which means in our example that we are willing to accept a 5% chance that our results happened by random chance. If our p-value is less than this threshold, we conclude a significant test for the metric. 

Should You Geo-Tag Your Instagram Posts?

Based on our tests, we did observe a few statistically significant impacts of geotagging

We found that Instagram posts featuring geotags did not significantly differ in terms of comments, saves, reach, or impressions compared to those without geotags. This may be due to a few hypotheses or constraints. Geotagging represents only one difference between the content being compared. Higher-weighted engagements, such as comments and saves, may be more influenced by factors like visuals, messaging, content type, seasonality, etc.

Additionally, the inclusion of geotagging alone may not result in increased post reach. But we believe this could vary depending on the specific location. Highly popular locations may yield different results.

On the flip side, we did observe significant results when comparing geotagged posts to non-geotagged posts in terms of likes. There was enough evidence to suggest that geotagging has a meaningful impact on the number of likes a post can receive. The difference in likes was also strong enough to conclude significance in overall engagement, as this metric typically has the highest volume of interactions compared to other engagement types. 

People may be more inclined to like posts related to places they are familiar with, as users are more likely to engage with content from their city or favorite spots. Additionally, there may be a psychological factor at play. Geotagging adds a sense of authenticity, making posts from real, specific locations feel more genuine.

Conclusion

Overall, the impact of geotagging may vary depending on your industry, location, audience, and other factors. However, it would be premature to assume that geotagging cannot have an impact on your content. It is important to frequently leverage the social media data available to your business. 


Need a data-backed strategy to grow your business? Chat with our team today!

Random Labs: Do Faces Boost Social Media Post Performance?

It’s often claimed that showing real people in social media posts helps to humanize a brand and potentially garner more engagement. But can the simple act of showing a face in a post actually boost post performance?

In this month’s edition of Random Labs, we explored the impact this basic human element has on post performance across various platforms. 

Our Methods to Test Post Performance

As we've reiterated in past experiments, modern social media platforms offer users a wealth of data on their own content, providing great opportunities to fine-tune and optimize strategies. (Check out our previous Random Labs blog on TikTok video length performance.) We will analyze the posts we have shared in 2024 so far on our own agency’s social media platforms.

In our experiment, we focused primarily on image content. 

Short-form videos and Reels have become highly effective content formats across most platforms. We've observed that a large percentage of this type of content already features people within the posts themselves. 

We will utilize multiple hypothesis testing across three major platforms (Facebook, Instagram, and LinkedIn) to answer a series of questions: Is there a statistically significant difference between posts with faces and those without? If so, what metrics are primarily affected?

How We Set Up Our Experiment to Test Post Performance

Before we deep dive and answer these questions, we will make the following data assumptions and preparation disclaimers across all platforms:

Let’s take a look at some Random content!

How Do Posts with Faces Perform on Facebook?

Content w/ FacesContent w/ No Faces
Average Engagement: 5.12
Likes:  2.52
Comments: 0.20
Shares: 0.08
Average Impressions: 38.08
Average Engagement: 4.05
Likes: 2.50
Comments: 0.06
Shares: 0.03
Average Impressions: 32.47
Hypothesis Testing Results:
Engagement: No statistically significant difference between the averages of the two datasets at the 95% confidence level.
(P-value: 0.402 > 0.05)
Likes: No statistically significant difference between the averages of the two datasets at the 95% confidence level.
(P-value: 0.323 > 0.05)
Comments: No statistically significant difference between the averages of the two datasets at the 95% confidence level.
(P-value: 0.245 > 0.05)
Shares: No statistically significant difference between the averages of the two datasets at the 95% confidence level.
(P-value: 0.195 > 0.05)
Impressions: No statistically significant difference between the averages of the two datasets at the 95% confidence level.
(P-value: 0.127 > 0.05)
Methodology explained: In our statistical method, think of the p-value as a measure of surprise. It shows how likely your data could occur by random chance if there’s no real effect. The alpha level (usually 0.05) is the cutoff we set to decide how much surprise we're okay with. If the p-value is less than alpha, it means the result is surprising enough to believe something is happening (significant). If it’s higher, we assume it's just random chance (not significant).

What Do These Results Mean?

In summary, Facebook differed significantly from the other two platforms we analyzed by showing no statistically significant differences in metrics between the two content types. Whether posts had faces or no faces on this platform, there is not enough evidence to suggest its presence has any impact on post performance. Although the averages may seem to show some differences at first glance, hypothesis testing reveals that these differences are neither justified nor consistent. 

We have some external hypotheses that may potentially support these results, including the year-over-year trend of a general decline in organic engagement on the platform. During this period, Facebook has shifted its focus significantly towards an algorithm centered around advertising, and paid content has disproportionately outperformed organic content based on our observations. 

Additionally, we are just one account within a single industry. These results can vary depending on factors such as objectives, follower size, and more.

How Do Posts with Faces Perform on Instagram?

Content w/ FacesContent w/ No Faces
Average Engagement: 22.45
Likes:  19.94
Comments: 1.61
Average Impressions: 153.61
Average Engagement: 12.53
Likes: 11.58
Comments: 0.28
Average Impressions: 81.88
Hypothesis Testing Results:
Engagement: Statistically significant difference between the averages of the two datasets at the 95% confidence level.
(P-value: 0.006 < 0.05)
Likes: Statistically significant difference between the averages of the two datasets at the 95% confidence level.
(P-value: 0.0096 < 0.05)
Comments: Statistically significant difference between the averages of the two datasets at the 95% confidence level.
(P-value: 0.0005 < 0.05)
Impressions: Statistically significant difference between the averages of the two datasets at the 95% confidence level.
(P-value: 0.0062 < 0.05)
Methodology explained: When a p-value is really close to zero, it suggests that the difference between the averages is highly unlikely to be due to random chance. In simpler terms, it means the data is showing a very strong signal that there’s a real difference between the two groups (face vs. no face content) you’re comparing. The closer the p-value is to zero, the more confident we can be that the observed difference is meaningful and not just a fluke.

On Instagram, our statistical tests showed significant differences in average metrics between content types. Nearly every test indicated a strong bias toward content featuring faces, with those posts consistently outperforming posts without faces, as confirmed by the statistical analyses.

This was an easy assumption considering the nature of Instagram, a highly visual platform. On Instagram, users are more drawn to emotionally engaging, personal, and relatable content, which faces provide. Faces capture attention more effectively. As additional support beyond the content we tested, the majority of high-performing Reels also tended to feature faces—this was so evident on our end that we didn’t feel the need to specifically test this content type.

How Do Posts with Faces Perform on LinkedIn?

Content w/ FacesContent w/ No Faces
Average Engagement: 17.28
Likes: 5.44
Clicks: 11.44
Average Impressions: 121.25
Average Engagement: 11.63
Likes: 3.70
Clicks: 7.75
Average Impressions: 94.22
Hypothesis Testing Results:
Engagement: Statistically significant difference between the averages of the two datasets at the 95% confidence level.
(P-value: 0.014 < 0.05)
Likes: Statistically significant difference between the averages of the two datasets at the 95% confidence level.
(P-value: 0.012 < 0.05)
Clicks: No statistically significant difference between the averages of the two datasets at the 95% confidence level.
(P-value: 0.063 > 0.05)
Impressions: Statistically significant difference between the averages of the two datasets at the 95% confidence level.
(P-value: 0.037 < 0.05)
Methodology explained: Based on the previous channels, since we generally concluded significance across Likes and Shares in tandem, we test an engagement type in clicks which is more highly prevalent on LinkedIn.

In terms of total engagement and impressions, we observe similar patterns on LinkedIn as on Instagram. The average overall engagement, including likes and impressions, is significantly higher for content featuring faces, with a high level of statistical confidence. Interestingly for post clicks, a highly prevalent engagement type for LinkedIn, there was no significant difference in the averages between both content types. 

Clicks often represent a more intentional action, such as wanting to learn more or visit a website. Users might engage with content featuring faces by liking or viewing it without necessarily clicking through, especially if they find it visually appealing but not informative enough to warrant further action. LinkedIn users might be more likely to click on content with a strong call to action (CTA) or business-related context, which may or may not always include faces.

Bottom Line: Include More Faces in Your Posts

In summary, both Instagram and LinkedIn demonstrated strong performance across multiple metrics when content featured faces, with Instagram showing a more pronounced disparity. This raises several potential explanations, such as an algorithmic boost for this type of content, increased visual appeal, or a heightened sense of human connection.

Try testing more posts on your Instagram and LinkedIn that feature real people–whether that be your team members, customers, or clients–to start increasing your post performance.

As a reminder, results can vary across different industries and strategies, highlighting the importance of refining a strategy tailored specifically to your business needs.

Want us to bring statistically backed results for your strategy? Send us a message!

Random Labs: Does Video Length on TikTok Matter?

With TikTok's rapid growth and the countless videos uploaded daily, one question remains: Does video length matter? Is a short, snappy clip more effective than a longer, more detailed one? 

Like most major platforms, TikTok empowers users to analyze their own performance data directly, providing valuable insights into their marketing strategies. At That Random Agency, we leverage this capability daily to optimize our campaigns. 

So we were curious - could we use performance data to analyze what video lengths on TikTok provide the best metrics?

Let’s put on our lab coats and dive into our first Random experiment.

Our Methods to Determine Best TikTok Length

Video length has been a prevalent topic of discussion for TikTok videos over the years. Specifically, is length a variable that may impact content performance?

The general recommendation? Shorter videos tend to perform better in terms of views. 

However, the issue with general recommendations is that they often pool results across a broad range of accounts. These vary significantly in terms of audience type, audience size, content strategy, industry, and more. 

We have evaluated how consistently results vary across different platforms based on individual accounts. To better understand this general trend, we will compartmentalize our analysis of TikTok video length by industry. This will help us assess video performance more accurately. 

Here are five different industries sampled among clients anonymously who have seen some marketing success in the platform. 

(Disclaimer: These results are samples of larger industries and are not meant to guarantee improved performance for your personal accounts.)

Best TikTok Length for Marketing Brands

We'll begin with an industry which we happen to be rather passionate about: marketing. We randomly selected a large sample of our own TikTok video performance data and chose to eliminate extreme outliers due to the platform's viral tendencies. We generated the following output when plotting average video view performance (in seconds) in relation to video length at different intervals.

Nothing in this output came as much of a surprise to us. A video length of 30 seconds is a recommendation we consistently hear. Most of our video analytics from the year to date show a central tendency of video length between 30 and 90 seconds. Additionally, the relatively higher average for videos between 0 and 10 seconds is a key observation for future analysis.

Best TikTok Length for Food Brands

We output a similar chart utilizing video performance for TikTok accounts within the food or restaurant industry. 

We observed a similar pattern in the video data for this industry, noting that the average number of video views increases beyond the 30-second threshold. While the maximum interval in seconds can still be classified as a “short” video at around 80 seconds, we noticed a larger increase in average video views even beyond a minute long. We can consider the storytelling nature of food preparation that could keep viewers engaged as a potential element for this pattern. 

Best TikTok Length for Keynote Speakers

Another industry in which we are well-versed is the keynote speaking industry. If you're specifically involved in the keynote speaking business, feel free to check out our upcoming SPEAKR  event to amplify your speaking career! 

In terms of video length to video views performance in this industry, we are once again observing consistent behavior with a moving average once videos exceed 30 seconds. However, there is a significantly higher increase in average video views for videos within the 0 to 10-second range. This variation may be attributed to the nature of keynote speaking videos, which often include short, memorable quotes or soundbites in brief clips, or longer videos that expand on compelling or educational topics.

Best TikTok Length for Automotive Brands

We also work with clients in the automotive industry. Some immediate observations when evaluating video performance data for this category reveal a tendency for videos to skew towards shorter lengths. This is likely due to the nature of the industry. Automotive videos are often action-focused and visually dynamic, making shorter content more common and effective. 

We account for the natural tendency toward shorter video lengths in this industry by analyzing 5-second intervals. Interestingly, a more positive linear trend emerges as videos approach 30 seconds, likely due to these shorter intervals. Videos reaching at least 30 seconds continue to mark a significant threshold for increased average views.

Best TikTok Lengths for Health Brands

The final industry we will evaluate in this analysis is the Health industry, specifically in the non-profit sector. We see a bit more variability in the ranging video views in the chart due to some difference in the video quantity as well as audience size. 

Relative to the other industries we have analyzed so far, we are still able to depict a consistent pattern when we key into the 30 second threshold for video length. Including the 30 to 40 second intervals itself, 3 of the top intervals by average video views were apparent for videos that extended beyond this half minute threshold. Content wise, videos under this industry can use a combination of educational, attention-grabbing research along with a versatile range of visuals. 

Summary

After evaluating the TikTok video view performance from the five different industries, we are able to conclude some insights. 

Most notably, for all industries, average video views were significantly higher for video intervals longer than 30 seconds as opposed to the first 30 seconds. 30 to 90 seconds seems like a general sweet spot based on our data. This aligns with multiple general recommendations that we have observed. 

In a few industries, videos shorter than 10 seconds had a notably high average view count. This could be due to a systematic reason: video replays are automatic and contribute to view metrics. As a result, videos of this length are more likely to loop repeatedly, boosting their view counts.

In summary, although video length on TikTok showed some significance in view differences, it shouldn't take priority over other important aspects such as crafting engaging content, relevance, sounds, storytelling, and more. Additionally, like other major platforms, TikTok is constantly evolving, with longer-form content and new content types (such as carousels) emerging. Staying updated on new trends, alongside analyzing the best performance strategies tailored to your account, will be crucial.

Need a data-backed strategy to grow your TikTok? Chat with our team today! 

The Truth Behind Social Media Verification: Is It Worth the Price?

The History of Social Media Verification

Many long-time social media users may be aware that social media verification was historically free. 

In those earlier days, the guidelines for verification were simpler:

The Switch to Paid Social Media Verification

For the most part, many of these perks still highlight the primary benefits of social media verification today, perhaps even more so with the significant surge of bots across all channels over the last decade. However, with the added paywalls behind these verifications, essentially mimicking subscription services, verification is no longer limited to just viral accounts. 

As a result, some new features are now being promised. Here are a few of the newer features:

Oftentimes, social media users want to evaluate if this monetary investment in verification will result in an increase in their post performance. We’re here to evaluate a couple major platforms practicing this system, specifically Meta and X, and give our evaluations of the services accompanying the blue checkmark. 

Meta Verified (Facebook and Instagram):

It's rather appropriate to begin our critique with Facebook and Instagram, as they are likely the most prominent platforms for their massive user base and seemingly high verification rates. 

Meta introduced its “Meta Verified” program which introduces the following plans as of August 2024: 

Chart showing the 5 different levels of Meta Verified along with their pricing and benefits

Of the two verification systems we are evaluating today, the Meta Verified program comes at a steeper price point, ranging up to $349.99 a month for the Business Max plan. The Standard plan would be the bare minimum price point to receive the blue checkmark, the very same checkmark that social media enthusiasts would try to seek over decades. 

Based on our observations and data from accounts across various verification plans, we found no convincing or statistically significant evidence that any of these plans impact post performance, such as reach

Numerous individual case studies by users across Meta have consistently shown that performance changes are due to normal fluctuations in social media rather than any immediate benefits from the verification plans.

This may not fully reflect the overall value of the verification program or the potential for strong performance on the respective platforms. 

For example, starting from the Business Plus tier, your account gains the added functionality of including links in your reel content. Reels are a content type we've found to consistently perform better across all platforms that feature them, including Meta. 

You also gain advantages in search optimization, where your profile can appear higher in search results. Although, this does not materialistically correlate to an increase in post performance as a significant majority in post reach is skewed towards feeds. 

X (Formerly Twitter)

X has undergone significant changes in recent years, most notably its rebranding. These changes also include an overhaul of the criteria for verification, along with the introduction of a tier-based subscription model similar to what we’ve seen with Meta. 

During its time as Twitter, the verification process was generally free and focused on identifying accounts that were notable, authentic, and active:

The criteria for verification on X (formerly Twitter) have changed significantly. Now, only accounts subscribed to X Premium can receive the blue checkmark. The current price points for X Premium are as follows: 

Chart showing the three options of X Premium subscriptions, including their prices and benefits

The minimum price point for achieving verification status on X under these plans is $7 a month with X Premium. Comparatively, this makes the verification entry about half the cost of Meta Verified when evaluating the cost of the piece alone. 

Along with the checkmark, you are also granted pretty significant functionalities within the account such as analytics. Feel free to read more about that here

Mimicking our observations with verified accounts, X also shows no convincing evidence that verification status affects post performance. 

Since the verification overhaul is still relatively new, more data needs to be analyzed to determine if this will change in the future. 

However, general impressions of the platform have seen a steady decrease, as expected during its transitional period away from Twitter. Unlike Meta, it's generally more difficult to pinpoint a clear correlation during that offset of the platform. But we are not too optimistic that paying for verification will benefit your post performance for either platform at this time. 

Is Verification Worth the Price?

Based on our observations shared with industry experts and social media enthusiasts, it is clear that the significance of the checkmarks has diminished over the years. 

We strongly believe that the allure of having a profile checkmark itself should not serve as the basis for investing in the subscription options presented today. Additionally, investment in these plans for the purposes of post performance should also not be a consideration as evidence is lackluster at best. 

The decision to pay for verification should consider a more holistic view of the benefits to your social account. You might receive enhanced authenticity, improved customer support, and possible access to early platform features. The return on investment may vary based on the account.

Need to know if any of these verifications are worthwhile for your business? Send us a message

Is X Premium Worth Paying For?

If you're a social media enthusiast like us, you’ve likely noticed some changes involving X and its subscription services. Although the platform has consistently hinted at various premium services since Elon Musk acquired it a few years ago, a covert update to restrict basic access to your page's analytics took effect in mid-June.

Phone screen shows a folder of social media apps, including Facebook, Messenger, Instagram, WhatsApp, and X

Where Did X Analytics Go?

Social media analytics provide critical knowledge about your audience, content performance, and the overall effectiveness of your social media strategy. They empower data-driven decisions, benchmarking, and continuous improvement (something we exercise every day at Random). 

Previously, you could access the necessary information and data through one of the basic profile features or a direct link, such as www.analytics.twitter.com. Since transitioning to X, there has been a gradual reduction in methods to access this interface and instances of missing data points - likely a byproduct of the constant construction of the new analytics environment.

Accessing the provided link on a regular account will now prompt a message suggesting an upgrade to one of X's subscription services. The once-free analytics feature is now locked behind their mid-tier Premium paywall, requiring users to purchase this tier to access it through the direct analytics link.

Screenshot displaying the three different tiers of X Premium, with the $7 per month plan highlighted

Is X Premium Worth It?

So, is this Premium service worth the monthly cost? We're here to dive deeper into the new analytics feature, highlight what's new and what's missing, and ultimately help you decide if it's right for you or your business.

One of the more immediate and obvious changes we noticed is the navigation path to accessing the analytics feature. If the account is logged in as a X Premium account, you will notice the slightly bolder 'Premium' text towards the left where all the platform features are listed. If subscribed, it will then introduce additional features in the main portion of the interface, including a direct path to your profile’s analytics.

Screenshot showing the X Premium tab on the X interface, with the Analytics line circled in red.

Upon accessing the X Premium analytics feature, you will be introduced to the overview tab. Much like other social media platforms providing analytics, the overview is typically the central interface. You will usually see line graphs summarizing data (typically in days by default) as well as totals for those accumulated metrics, along with percentage changes relative to the preceding period.

Screenshot showing the analytics tab overview, with a line graph and boxes displaying Impressions, Engagement rate, Profile visits, and more.

Here is a summary of differences we have noticed having closely worked with the older, previously free, interface over the years: 

Improvements

What’s Missing

The new analytics interface includes an overview and a tab for content performance. Clicking on this tab will show your recent posts and their corresponding metrics.

Screenshot showing analytics tab where each post is displayed along with date, impressions, likes, bookmarks, and quotes.

Similar to the overview portion of the analytics, we were able to pinpoint some key differences:

Improvements

What’s Missing

So the million-dollar (or really, seven-dollar) question remains: Is X Premium worth it for your business? It depends.

If your business heavily relies on X as its primary platform, this subscription may be a necessary investment. Social media analytics will always be better than having no analytics at all, but you should also consider the other premium features, such as claims of increased post performance, creator controls, early access to new features, and more. However, the return on investment may vary if X serves as a secondary platform for your brand. 

Feel free to contact us if you want our expert recommendations on whether X Premium is right for your business or if you need help navigating this ever-changing social media landscape!

Here Are The Latest TikTok Benchmarks for 2024

Still wondering if TikTok is worth your brand's attention? The latest Rival IQ report reveals the platform's impressive growth and continued user engagement, making it a prime target for social media strategies in 2024.

We’re jumping into the key points from their report and how you can use them to analyze your own TikTok metrics. 

Firstly: What is Benchmarking?

Benchmarking is a part of the analytics process that compares your social media results to industry and competitor standards. How do your campaign results - like engagements, engagement rate, clicks, and more - hold up against other brands’ campaigns on the same channel?

Benchmarking is a key component of strategy. Understanding how your brand stacks up against competitors and industry leaders on TikTok can be useful for optimizing content strategy, setting realistic goals and expectations, and identifying areas for improvement. 

Many benchmarking reports emphasize the importance of analyzing your own data alongside industry benchmarks. This allows you to track your progress and measure the effectiveness of your specific social media strategy. 

What Does the TikTok Benchmark Report Cover?

Recently, Rival IQ released their 2024 TikTok Benchmark Report, analyzing key metrics commonly observed across many of today's social media platforms. Some of these key benchmarks, such as engagement rate, are frequently used as key performance indicators (KPIs) for many brands. 

To better understand the one way intersection between metrics and KPIs, or to have a baseline understanding of reading benchmark reports, check out this blog

In this 2024 iteration of the TikTok Benchmark Report, the following metrics are assessed:

Engagement

Reach

Other

What are the 2024 TikTok Benchmarks?

Knowing that engagement rate is one of the most important metrics to track - more on that later - here are the industry benchmarks for engagement rate by view. 

Sports Teams: 9.2%

Nonprofits: 5.2%

Influencers: 4.9%

Alcohol: 4.3%

Higher Education: 4.1%

Media: 3.8% 

Travel: 3.0%

Tech & Software: 2.9%

Fashion: 2.7% 

Health & Beauty: 2.7% 

Retail: 2.6% 

Food & Beverage: 2.6% 

Home Decor: 2.5% 

Financial Services: 1.9% 

You can check out the full list of benchmarks in the report here

What Metrics Should My Brand Track on TikTok?

After considering this long list of metrics, brands should evaluate which ones are most suitable as KPIs to fulfill their overall TikTok strategies. 

Rival IQ emphasizes engagement rate - a metric used to measure how much a social media audience interacts with a piece of content - as one of the most prevalent metrics for them when benchmarking brands across many industries. Engagement rate is a versatile KPI, ideal for brands with diverse objectives like boosting brand affinity, awareness, and even sales conversions.

TikTok is a highly engaged platform in general, so it is also important to understand the context of how this percentage is shifting non-linearly when it comes to both engagement rate by followers and engagement rate by views. 

The data shown in Rival IQ’s articles suggests that engagement rate by follower count skews higher for accounts with smaller follower buckets, left-skewed distribution in statistics terms. As Rival IQ suggests, high-follower accounts might have a lower average views per follower compared to smaller accounts. 

This means a smaller portion of their total followers actually see their content (due to the algorithm or other factors). This can also be attributed from basic mathematical effects: if engagement is still happening (likes, comments, shares) but on a smaller subset of viewers (lower views per follower), the engagement rate per follower will naturally be lower since the denominator (total followers) is much larger. 

Many brands might be tempted to prioritize follower growth as their main KPI, but in reality, we often categorize this as a primary vanity metric. A vanity metric is a statistic that looks impressive at first glance but doesn't necessarily translate to any meaningful business results when observed in isolation. 

Our Perspective on Vanity Metrics:

We typically observe follower growth as a byproduct of high engagement across many different platforms, and TikTok definitely follows that trend. 

On TikTok, prioritize engagement rate as your key performance indicator (KPI). 

Track follower growth as a secondary metric, as a strong correlation often exists between the two. 

This allows you to focus on creating high-quality content that fosters engagement, which will likely lead to organic follower growth over time. This can further trickle down to utilizing the other metrics such as videos per week, hashtags per video, and videos with mentions, which can also contribute to overall optimization strategies. 

Newly arriving brands into the platform, or newer accounts in general, may want to consider engagement rates per view over followers because of the mathematical inflation that is likely to occur when adding follower counts into the mix. A high engagement rate by followers with a very small audience might not be a true reflection of your content's overall effectiveness. It simply means a small group of followers is highly engaged, but it doesn't necessarily indicate broad appeal. 

As your follower base grows, you can start tracking both engagement rate by view and engagement rate by follower. This provides a more balanced view of your content's effectiveness. You can also start comparing your engagement rate by follower to industry averages - but it is also important to consider research on follower buckets for accounts as we have discussed the impact of follower counts on these percentages.

As a disclaimer, nothing will outweigh the importance of leveraging your own benchmarks. Industry reports offer a starting point and can help you understand your performance on a broader TikTok landscape. Focusing solely on industry benchmarks can be discouraging if your numbers fall short initially. Tracking your own progress allows you to celebrate improvements and measure your success based on your own growth trajectory.

Want us to bring both personalized and industry benchmarking into your brand? Send us a message!

Are All Social Media Metrics Created Equal?

There is more to analyzing social media posts than just counting the number of likes a post might have or seeing how many views your video may have received. The significant growth of the data analysis industry has extended to social media, and the demand for its implementation is crucial for executing digital marketing strategies. Optimization techniques in social media marketing are frequently implemented through the use of metrics.

Before diving deeper into the application of metrics in the world of social media, it would be appropriate to define what a metric is. 

A metric can be generally defined as measurements used to evaluate performance. In the context of social media, metrics can give us insight to how well a particular post, channel, or campaign is performing. Some of the most commonly observed ones in measuring social media content are as follows:

EngagementThe number of interactions in a post. These interactions can come in the form of likes, comments, shares, etc. 
ImpressionsThe number of times the content has appeared to users. 
ReachThe number of unique users that saw the content. 
Click-Through Rate (CTR)Percentage of users who clicked on a link compared to its audience exposure. Usually divided over impressions.  

The overall pool of metrics used in social media is vast and highly dependent on objectives, platforms, and the level of analysis. Today, we aim to answer the specific question of which social media metrics carry more weight when it comes to analyzing performance.

We will take a look at each of the most prominent metrics used to analyze social media performance and analyze them on a platform-by-platform basis.

How Social Platforms Weigh Metrics Differently 

Engagement is likely the most commonly used metric to measure performance on every social platform. This metric generally accumulates all the different interactions that are unique to their respective platform to create a holistic measurement of content relevancy and how well the audiences are resonating with a post.

On Meta platforms, specifically Facebook and Instagram, engagement is considered a significant variable when it comes to prioritizing a post's ability to spread to a broader audience. Among different types of engagement, both platforms heavily prioritizes likes, comments, and shares when it comes to fueling this visibility. Engagement on Facebook is also thought to be more personal, considering the network's tendency for personal connections with friends and family. 

On Instagram, as a platform with a greater emphasis on visuals and a robust influencer culture, engagement takes a similar form to that on Facebook (likes, comments, and shares). However, on this platform, engagement may be derived more from what the viewer finds visually appealing.

The metrics themselves, when it comes to engagement, may start to take a different form when we start comparing platforms such as LinkedIn and X (formerly Twitter). 

For example, LinkedIn includes 'Post Clicks' and 'Follows' as additional metrics when calculating the total engagement for each piece of content. These 'Post Clicks' differ from Meta's 'Link Clicks' as they record not only direct user interactions with any given links but also interactions with any clickable elements within a post (such as images or profiles). The trade-off with this method of recording clicks is that it can inflate the click-through rate (CTR) and complicate efforts to standardize clicks across different platforms. This is an important factor to consider when understanding why total engagement may appear in larger quantities for this platform. When it comes to weighing various forms of engagement metrics, LinkedIn's 'Follows' can indicate a higher level of engagement, as they demonstrate users' intent to see more of your content in their feeds.

At its current stage of rebranding, X may be the most challenging platform to analyze. Formerly known as Twitter, the platform's users have become accustomed to its posts, which were normalized as 'Tweets,' aligning well with the platform's name. Due to its ongoing changes, X might undergo a renaming process that incorporates metrics along with post names. Content on X consistently prioritizes trending topics and timely information, resulting in a high level of engagement through the 'Retweet' metric. They are often used as a measure of how viral or shareable a tweet is, and they contribute to the overall engagement level of a tweet. Clicks on X may carry less weight compared to the previously mentioned platforms, as recent studies indicate that this platform has the lowest average percentage in click-through rate (CTR). This could be a result of the skewness towards higher impressions per tweet. Additionally, differences in ad performance between platforms might also contribute to this phenomenon.

Navigating this sea of metrics is a complex yet necessary task. With each platform having its unique metrics landscape, understanding the significance and weight of these metrics can provide valuable insights tailored to the context of each platform.

Which Metrics Should I Prioritize? 

When evaluating which metrics to prioritize in regards to measuring success for a campaign or post, it's highly important to factor in key performance indicators (KPIs). KPIs help measure the success of content as they are quantifiable metrics that provide a clear understanding of how well a campaign or post is performing in relation to those goals. It's important to note that all KPIs are metrics, but not all metrics are KPIs. 

When thinking about a social media post, metrics can cover a wide range of engagements and impressions. Let's say we're creating a promotional post with the goal of attracting more users to visit a website through the link in the description. A good KPI to measure the success of our objective would be clicks (or CTR). Other forms of engagement, such as likes or comments, might not be weighted as heavily as they are usually not going to correlate to an increase in website traffic. Being able to align social media posts with an objective allows you to transform any of these metrics into a measurable KPI. These will greatly enhance your understanding of how effective your social media strategy is and whether you're reaching your goals.

Below are a few more examples of common social media objectives, along with some of their corresponding KPIs:

Objective: Website Traffic KPIs: Clicks, Click-Through Rate (CTR)
Objective: Brand AwarenessKPIs: Reach, Impressions
Objective: Showcase New ProductKPIs: Likes, Comments, Shares
Objective: Build CommunityKPIs: Page Likes, Follower Increase

Our experts at Random are ready to create data-backed digital campaigns for your business! Reach out to us below to learn more about how we can work together.