Three key trends underpin tech, media and telecom companies’ race to claim larger slices of the digitalization pie, through consolidation, cloud computing and machine learning.
As consumers and businesses around the world demand increased digitalization, companies in technology, media and telecommunications are pushing to expand their market reach and become bigger multiline platforms than ever before.
It’s one of the biggest takeaways from Morgan Stanley’s Tech, Media and Telecom Conference in San Francisco in the first week of March, where the firm’s bankers helped facilitate a gathering of companies and investors to learn about and discuss the industries’ most important trends, corporate outlooks and big debates.
“Companies are re-platforming their applications to engage with their customers in new ways,” says Melissa Knox, Head of Software Investing Banking at Morgan Stanley. “You have to engage customers wherever they are, by any channel.”
Gone are the days when the hottest Silicon Valley companies solved for just one customer problem. Three key themes from the conference illustrate how companies in these sectors are vying for more diversified slices of the digital market, whether through consolidation, or by using big data, cloud computing and machine learning in novel ways to capture new revenue streams and increased customer usage.
Streaming killed the cable TV bundle, and with consumer spending on digital content increasing, media companies are making strategic acquisitions to access a wide array of streaming ad dollars. Recent consolidation has helped companies offer over-the-top (OTT) advertising services in new markets; streaming music companies are breaking into podcasting, and online media players are widening their sights to small and midsized businesses for a piece of their marketing budgets. The name of the game is profiting from the delivery of paid content to audiences increasingly streaming audio or TV.
In e-commerce, meanwhile, tech companies that had once focused on a specific stage or transaction point have used acquisitions to expand their reach and insert themselves at virtually every step of the customer journey. For example, a digital payment specialist may now offer users price tracking, retail discounts or rewards, and your intent-driven searches may flow through an integrated platform that ends with online or offline points of sale. Consolidation among specialized online marketplaces has also helped niche retail platforms—of craft goods or consumer electronics, for instance—become multi-category competitors against larger e-commerce players.
“M&A activity had been continuing at a strong pace through 2019 and into 2020, and it didn’t look like it was going to take a break,” says Mike Wyatt, Head of Global Technology M&A at Morgan Stanley. “After things settle down a bit, the current market dislocation may actually lead to an increase in activity, as premium assets get repriced.”
Super apps allow users to perform many online actions on a single mobile-first platform. They most commonly originate from, and are used in, large cities in Asia, where consumers rely on them to perform everyday tasks, from booking doctors’ appointments and hailing rides, to messaging friends, paying for meals and playing games, all within one application.
Now, tech companies around the world aim to replicate some version of that super-app model. Starting with their core competencies, they are expanding their services and adding more types of transactions under their umbrella brands—even if they don’t claim to be a super app. One notable trend is to blur the lines between social media and search engines, which allows brands or influencers to create social profiles and content powered by search-function findability, tagging and customer data that exceeds what a standalone social platform can provide—thereby potentially boosting user conversions.
Many tech companies are exploring synergies from combining search and social platforms. E-commerce payment companies that cater to gig economy workers with multiple jobs, for example, are figuring out how to combine search algorithms and social profiles on existing apps to create one easy, streamlined way to be discovered by potential employers and get paid for commissioned work.
Artificial intelligence and machine learning can facilitate the automation of more, and different, types of work. Tech companies can offer business clients more efficient ways to improve customer touchpoints through automation, big-data computing and cloud storage and services.
Brands are also turning to AI to help them manage the proliferation of digital channels through which they engage customers, market to prospects and communicate with users. Whether it is owned mediums, such as email, chat, text and voice, or paid platforms, AI may hold the promise of a unified approach to reaching consumers through all of these streams, while providing data-driven, real-time coaching to support and sales representatives to improve their services.
Meanwhile, machine-learning algorithms are getting even better at matching ad content with appropriate audiences. Based on search and personalization data, advertisers can more intelligently automate targeted marketing campaigns. Media companies in particular, or tech firms looking to monetize their media channels, aim to develop ad-personalization platforms that can serve relevant content to audiences for streaming video, music and podcasts.
While long-term trends such as the transition to the cloud or 5G wireless remain intact, many investors asked corporate participants about their exposure to the global coronavirus outbreak and how they are reacting to the still-evolving risks and challenges. Companies that provide remote connectivity services, including online conferencing and gaming, said they expected increased traffic. Others took a wait-and-see approach, including those monitoring the shifting effects on their global supply chains.
Nevertheless, many said that market disruptions have sharpened their focus on digital transformation. Despite the now uncertain macro environment, they believe that funding remains intact for them to expand their reach, build mega-platforms and consolidate market share, while capitalizing on the latest developments in cloud computing, AI and machine learning.