Monday Morning Learning – 4th February 2020
Published on 05 Feb '20
Half-life of Content Across Platforms
The half-life of a content piece is the time it takes for it to reach 50% of its overall expected engagement.
Twitter: 20 minutes
Twitter utilizes short-form content, simple “tweets” and small comments to relay information across users. So content spreads the fastest on this platform.
Facebook: 5 hours
While Facebook has over 2 billion active users daily, it has a large number of ways information can be relayed. For eg. pictures, videos, written content, stories, comments, shares, etc. Also, due to the traffic on Facebook, it takes a relatively long time for content to reach its half-life.
Instagram: 20 hours
Instagram is a lot slower in relaying content amongst its users. While its algorithm tries to boost pictures at all times, its main focus remains to be visually compelling and most of its user interface is filled with space-consuming pictures that increase the average half-life of any content shared on the platform.
LinkedIn: 24 hours
LinkedIn is for professionals, for the most part, and there isn’t a lot of traffic on the platform, so content pieces should have a low half-life. But on the other hand, LinkedIn is mostly used for job searching, profiling and lead generation. It doesn’t focus on boosting content on the feed but rather boosting companies on its job portal.
YouTube: 20 days
In the case of YouTube, such a long half-life is because of two reasons: 1. The high volume of traffic and 2. Even higher volume of videos. With a market as saturated as YouTube, videos are bound to take their time to reach their half-life.
Pinterest: 4 months
Pinterest is a huge platform cataloging millions of creatives and pictures, but the lack of social experience has only gotten it low traffic and a high bounce rate.
Blog post: 2 yrs
The only way blogs get traction organically is through SEO. But for any blog post, there may be 50 other blogs with the same keyword that may have the same content strength or may exist on a domain far older and stronger. SEO is a long-term strategy game that only gets better through testing, experience, and patience.
Ref: https://twitter.com/anutopiaa/status/1222314236791197696
Shopper Marketing Trends for 2020
- Know everything there is to know about your target audience.
- Invest wisely and appropriately in the right channels.
- Optimization (content and SEO) across platforms is key.
- Create a seamless shopping experience.
- Showcase on shoppable social sites.
- Leverage user-generated content.
- Utilize new age technology like chatbots.
- Connect with customers on a personal note.
Twitter Rolls Out Conversation Threads on iOS
Twitter is bringing a new ‘threaded’ conversation update to its iOS app, which more clearly defines replies from people you know on any given tweet.
Ref: https://www.socialmediatoday.com/news/twitter-rolls-out-conversation-threads-on-ios/571529/
Instagram is Testing Emoji Reactions for Direct Messages
As with Twitter’s recently launched DM reactions tools, given the availability of similar response functionality on other messaging platforms, it makes sense for Instagram to move in-step, tapping into habitual messaging behavior in order to facilitate more engagement. It’s worth noting that Instagram also already has a ‘quick reactions’ emoji response process for Stories.
Ref: https://www.socialmediatoday.com/news/instagrams-testing-emoji-reactions-for-direct-messages/571460/
Instagram Officially Begins Testing of DMs in its Desktop Version
After being spotted in testing months ago, Instagram is now officially launching a test of direct message access in its desktop version and is going to slowly roll out to the public.
Instagram is Adding a New Way to Find and Share Stories that Mention Your Profile
Instagram has added a new Stories @ mention option, which highlights any Stories that mention your profile, and enables you to easily re-share them into your own Stories stream.
Google is Working on Chatbots Which Can Engage in a More Genuine, Human Conversation
Google has built a new chatbot model called Meena, which is trained on a 2.6 billion parameter end-to-end neural conversational model and can conduct conversations that are more sensible and specific than existing bots.
