For the last several years, Messaging Apps have been experiencing a meteoric growth, both in terms of number of users and the average time spent by a user within his or her favourite Messaging App. Already, there is a steady move away from aspiring to stand out publicly in the News Feeds and Streams of the major Social Media Apps to engaging privately, as social activity increasingly transitions to communities, groups and particularly messaging apps. As interactions and engagements move away from news feeds and timelines to one-to-many or one-to-one messaging, the rise of the dark social will challenge a lot of things that we have learned about social media in the last decade. This transformation will open up major challenges and opportunities for individuals, marketers and brands and will have major implications for apps (including messaging apps), bots and AI driven chatbots. We will briefly look at some of these scenarios in this particular post.
Smartphone software is currently in a state of flux. Download numbers are still growing but the app economy is rapidly approaching maturity. The twenty most successful apps account for over half of the total revenues from apps in Apple's app store. As users find downloading apps and navigating between them a hassle, their enthusiasm about doing so is clearly waning. A quarter of all downloaded apps are abandoned after a single use. Only instant messaging bucks this trend with over 2.5 billion people having at least one messaging app installed on their smartphone. Facebook Messenger & WhatsApp currently lead the pack. Activate estimates that within a couple of years, this number will reach about 3.6 billion or about half of humanity. Growing numbers of teenagers are now spending more time on messaging apps, sending messages, rather than posting or perusing content on social media networks. When it comes to sharing, private messaging already dominates, with over 70% of all referrals coming from dark social. Dark social channels typically include messaging apps, email and private browsing.
Let us now cast a glance at chatbots and start with defining what they are. Simply put, chatbots are computer programs that allow businesses to build automated response systems, capable of interacting with potential customers on a one-on-one basis, using the current advances in Artificial Intelligence (AI) and Deep Learning. Chatbots are changing the ways users interact with the internet, creating an all-inclusive environment often within messaging apps. For example, while going on a trip, users will no longer have to download multiple apps to perform different activities. Typically, they should be able to book a flight, hail a cab and book a table at a restaurant all within one messaging platform. Put another way, chatbots have the potential to replace individual apps altogether. Messaging apps, together with their bots, will provide the environment for direct, instant and multi-pronged interactions with potential customers. From customer service to purchasing products, the entire ecosystem will now become easier and seamless as there will no longer be a need to download a separate app, sign up, and create a separate account for a one-time transaction. Thus, by simplifying the entire process, brands will make it easier for potential customers to engage with them and buy their products or services.
Over a period of time, bots will come to be known as the new breed of 'invisible apps'. Typically, installation will take mere seconds and switching between bots will not involve tapping on yet another app icon. In quite a few cases, talking to a bot may be more appealing than interacting with the customer service agent of a bank or an airline and, as messaging apps keep growing in popularity, engaging with the bots on their platforms will become commonplace. Much of course will depend on 'Killer Bots' which essentially will be hugely popular services that work best in the form of bots. Businesses, over a period of time, won't just have phone numbers and web pages but their own bots too. In the healthcare segment, bots could deal with routine ailments and only direct difficult ones to a doctor. Similarly, restaurants could take orders via instant messaging, as some already do in China. Of course bots will need a lot of experimentation to find their rightful place and this, in turn, will depend on how well providers manage their platforms.
Among the several brands taking the dive into Dark Social, the senior director of global brand communications for Adidas Football had this to say:
"As long as the dark social platforms continue to innovate, we'll find new ways to use the technology. In the past you could only send text but now, you can send video and image, which has opened doors. Using a mix of content, we can reward advocacy with personalized approaches like inviting customers to a dialogue with Adidas stars, offering live coverage from events or simply handle customers service queries. There is excitement about the opportunity dark social presents and how it can help Adidas become the most personal brand, so we expect it to play an increasingly important role in our strategy."
The piece on this in The Drum, can be read here.
AI in social media networks is primarily being used as an efficient way to sort through large clusters of user-generated information. The term 'Deep Learning', often used in this context, signifies a high-level knowledge arrived at by analyzing and establishing patterns in large data sets. For social media, this means that AI can help with anything from personalized product suggestions, based on previous engagements, to image and voice recognition, to deep sentiment analysis.
AI will also impact the social media analytics business in a major way. It's going to affect a number of areas, ranging from the analysis itself to certain recommendations that can be offered to users. For example, one can say that a particular tweet from an influencer is likely to be further amplified with a certain promotional. One can then go on to recommend that, if promoted, it will likely be amplified by say 10 times than what it is now. Recommendations of this kind can create a major impact.
AI can also help ingest proprietary corporate data, like chat logs, more efficiently, and be able to then sort through that data, make sense of it, and gain new insights through analysis.