LinkedIn Stories For Newbies (PERFORMANCE INSIGHTS AND WHAT IT MEANS FOR BUSINESS

Almost 6 months ago, I was invited to the official LinkedIn briefing in Australia for the launch of their ‘Stories’ product. After the briefing, I wrote this article to share everything LinkedIn told me about this product. Since the launch of the Stories product on LinkedIn, I’ve taken my standard Sally approach to experimentation including by routinely conducting comparative analyses of Stories across different social media platforms.

I promised I would share some insights on my experiments hence I have published this article. As context for any new readers with me, since the beginning of 2018 I’ve become arguably one of LinkedIn’s greatest self proclaimed students. I had an initial curiosity to understand how content on LinkedIn can create emotional reactions and then to further understand the impact of such passive and incidental emotional reactions on business(es). Almost three years later, I’ve had the honour of coaching and consulting to countless people and businesses on LinkedIn, content marketing and communications.

The purpose of this article is to disclose to you some insights in relation to the performance of Stories on LinkedIn VS Instagram VS Facebook. For those of you who may not be familiar with the Stories product on LinkedIn, or any other social media platform, and are wondering if I’m about to start analysing bedtime stories, let me provide a quick overview of what I mean when I refer to Stories within this article.

The Stories product (commonly referred to as a ‘Feature’) on LinkedIn, Facebook, Instagram and many other social media platforms, is a content function that allows users to share content in a reel manner. So if you think about an [old school] reel of film for a camera, the Stories function operates in effect like that - published sequentially and is consumed like one reel of content VS feed content which is most commonly consumed as stand alone pieces of content. Most social media platforms have a 24 hour hard expiration for Stories content which means that each piece of content published to your Story expires by default after 24 hours has passed. For most platforms, you can access the Stories product (to consume and publish) at the top of the Newsfeed and it is most commonly displayed on the interface as circles centred with the publishers profile photo and a coloured highlighted circle surrounding the round icon if there is new, unconsumed [by you] Story content. See below an example of what the Stories product looks like at the top of your LinkedIn Newsfeed.

Note: Stories on LinkedIn are not yet accessible via any device other than smartphones and subsequently on the LinkedIn smartphone application.

Note: Some social media platforms, such as Twitter and WhatsApp, have bespoke names for the Stories product.

Note: At the time of publishing, the LinkedIn Stories product may not be available to all countries.

When LinkedIn launched the Stories product, I immediately became intrigued by how it may perform. Unsurprisingly, there’s been a lot of confusion about Stories on LinkedIn largely subsequent to seemingly lower familiarity with the general purpose and functionality of a Stories product on a social media platform - this is certainly the feedback I’ve been receiving from within my community.

For several months I’ve been comparing performance of Stories across LinkedIn, Instagram and Facebook. For the purpose of keeping this article simple and quick to read, I’m sharing one case study that adequately represents the average comparative performance of Stories across the last few months on LinkedIn, Facebook and Instagram.

Case Study Story Post

In the interests of short attention spans, I am not going to share my detailed assessment of the performance of this Story and how it compares across the platforms.

As per the performance overview details shared above;

• If we focus on total view count for the Story in the first 22 hours and believe that the platform delivering the highest view count wins, then LinkedIn wins (629 views) with Facebook (226 views) in second place.
• But if we believe the platform where the highest percentage of followers (equiv) saw the post wins, then Instagram wins (c6.10%) with Facebook (c5.81%) in second place.

It's interesting to acknowledge that I have 92,129 more followers on LinkedIn than I do on Instagram and 90,745 more followers on LinkedIn than I do on Facebook yet in this Stories performance case study, my Instagram arguably performs better than my LinkedIn on at least one front and my Facebook arguably performs better than my LinkedIn on at least one front. Further, my Instagram has the least amount of followers across the three platforms yet manages to beat both Facebook and LinkedIn when it comes to [perceived] engagement retention with followers via Stories.

Upon quick assessment, it is blatant how crucial it is for us to know what data matters to us and our business. It is also critical for us to know what each metric means for us and our business. If we don’t understand what data matters and why, then it is indisputably near impossible for us to make the best investment decisions when it comes to marketing and subsequently we’ve minimal chance of being able to determine reliable return on investment insights.

For example, it is likely the case that ‘views’ of a Story for my business matters in the context of brand awareness and can be proportionately benchmarked to assess exposure and reach. And conversely, it is possible that the percentage of followers exposed to a Story for my business is most valuable of the metrics shared in the overview above on the basis that it provides more insight into engagement with existing community members (retained engagement, for example).

But what’s most fascinating, as you can likely detect by what I am saying, is that it is individuals that pick and choose what data they use (hopefully in accordance with weighting to business value). Data is an overwhelming function of business and life, and what’s becoming increasingly difficult is for businesses to know how to most effectively use data. Consider the above case study on the performance of Stories across LinkedIn, Facebook and Instagram and imagine you and I, with 7 other people, were responsible for marketing within an organisation. If there is no standardisation from the outset as to what data matters to us and what those data mean to our business, we’d really struggle to achieve anything effectively. We’d likely spend more time debating who picked the right metric contrary to deriving insights from the data that matters to our business (to be honest, I’ve been in this situation before and it is not good for business).

It’s called Data Maturity. The short story is that you want to mature your data strategy ASAP.

Yes, the purpose of this article is to provide insight to those who (do or are preparing to) use the Stories feature on LinkedIn, and other socials, however it would be inconsiderate of me to bypass a contemporaneous learning opportunity by highlighting the importance of clarity for your data strategy (whether as an individual or business).

This incidental learning, subsequent to this comparative performance analysis of Stories, produces a debate akin to the one I’ve argued for 2+ years in relation to feed content performance. To keep it short and sweet, I’ve always argued that your Content Engagement Rate (Likes + Comments + Shares as a % of Views) per content asset is the most effective way (not view count alone) to measure the performance of content on social media platforms on the basis that this metric provides you with a relative way to measure performance by focusing on incident based impact because feed content assets are typically consumed as standalone within a newsfeed and newsfeed configurations encourage feed consumption which means each piece of content is competing with other publishers (I.e. seldom does a user visit LinkedIn and specifically look at individual profiles to consume content). For more detail on this approach, read this short article. If you actively use coordinated inauthentic behaviour (commonly referred to as ‘engagement pods’ on LinkedIn), then that’s an entirely different debate - I’d argue that you’re artificially adjusting the majority of your performance so best of luck to you with deriving sustainable business value (unless you’re in a business that simply needs social proof, no matter how artificial it is - but then I’d argue there’s no true satisfaction in that, but anyway…).

I hope this has been helpful for you and if you know someone who would enjoy this article, please tag them in the comments below or share the article.

If you enjoyed this article, I’d encourage you to read further and discover the WHAT, WHY & HOW of LinkedIn Content, How To Increase Your Profile Views On LinkedIn, or How To LinkedIn. I’m not a natural brag, but there is sincerely a lot of information in those articles that you can take and apply immediately without investing countless dollars.

I’d love to hear your thoughts on Stories in the comments below.

Best,

Sally A Illingworth