A Platform Strategy is Incomplete without Machine Learning
In today’s digitalized world, platforms have transformed the way we connect, exchange products and services, and access information. Whether it’s social media platforms like Facebook, e-commerce platforms like Alibaba, or ride-sharing platforms like Uber, these platforms have revolutionized business models and created immense value for both individuals and organizations. However, a platform strategy alone is not enough to guarantee success. In order to thrive in the rapidly evolving landscape, one key aspect that sets apart successful platforms is the integration of machine learning capabilities.
Platform businesses are growing at an unprecedented pace and wielding significant power. We have witnessed how a single tweet from a president caused a drastic impact on the market capitalization of Amazon. Instead of solely focusing on facilitating relationships and interactions, businesses must prioritize serving users with the right products and services. Facebook, Uber, Airbnb, Alibaba, and others have demonstrated the transformative potential of platforms. However, not all platforms are created equal. Machine learning plays a pivotal role in determining the success of a platform strategy. It empowers users to generate intelligent business solutions using various techniques, even with minimal technical knowledge, while providing transparency in the process.
Network-based business models are not new. We had recruiters before LinkedIn, message boards before Twitter, and matchmakers before Match.com. The shift to online platforms has undoubtedly brought about significant advancements, enabling rapid and cost-effective scaling. However, managing large-scale platforms with simple algorithms becomes increasingly challenging when faced with overwhelming amounts of data, such as resumes, dating profiles, or thoughts expressed in short posts. The data becomes unmanageable, and the potential for manipulation and misuse arises. To address this complexity, intelligent algorithms powered by machine learning come to the rescue. Machine learning allows platforms to organize vast amounts of data and deliver specific results tailored to users’ needs. It enhances the user experience by providing better organization and personalized recommendations. By utilizing machine learning platforms, technology becomes accessible to all, driving innovation and value creation across industries.
The effectiveness of machine learning distinguishes a good platform from a mediocre one. Many platforms rely on curation to elevate content based on simple rules like up-voting. However, this approach puts the onus on users to sift through a vast amount of content to find what they truly desire. Unfortunately, this content can be easily manipulated and fails to cater to the diverse needs of users. On the other hand, platforms that harness machine learning excel in organizing data and delivering customized experiences. These platforms prioritize serving users better rather than merely passing along information.
For example, consider the case of Monster.com, an online job board that was once a pioneer in the 90s. While it provided a platform for job seekers, the sheer volume of resumes made it challenging for users to find the best opportunities. The reliance on simple algorithms fell short in meeting users’ needs effectively. As a result, new players like LinkedIn and Glassdoor emerged, offering curated professional networks and revolutionizing the job search experience. Companies that failed to adapt and innovate, such as Craigslist, lost market share to newcomers like Offer-Up and Facebook. Adopting a machine learning platform as a service can provide a significant advantage to organizations seeking to stay competitive and deliver value.
A successful platform creates a space for connection and enhances users’ lives. By leveraging machine learning, platforms like LinkedIn can gain valuable insights about their users, enabling them to deliver a superior experience. Data storage is no longer a challenge, but rather bringing accurate and relevant information to users becomes the primary focus. Machine learning, combined with data, helps platforms learn more about their users and deliver personalized recommendations. Artificial intelligence is now employed in nearly every aspect of these platforms to enhance user satisfaction.
If we examine companies that are outperforming their peers, we notice that the use of AI is a common thread. Netflix, founded around the same time as Monster.com, has flourished by curating personalized content recommendations through machine learning. Netflix keeps AI at the forefront, utilizing it to monitor bandwidth issues and ensure smooth streaming experiences, especially in emerging markets.
Additionally, platform companies employ machine learning to detect and prevent misuse of their networks. Understanding the patterns and data generated by the network allows them to identify and counter criminal, abusive, and fraudulent behavior. Platforms like Twitter, Facebook, Yelp, and LinkedIn have taken active measures to protect user data and prevent misuse. The complexity of these platforms requires automated solutions, and artificial intelligence and machine learning are essential tools for managing content safely and effectively.
If you are considering a platform strategy and aiming to leverage network effects, curation becomes a critical component of your journey. Never underestimate the power of machine learning in achieving your goals. Small organizations with limited resources can benefit greatly from adopting machine learning platforms that efficiently manage and maintain the value of their organizations. Machine learning can swiftly generate customized results for users and alleviate concerns surrounding the customer experience. In the pursuit of a successful business model or platform strategy, the integration of machine learning is paramount in addressing a wide range of user and business challenges. Embracing AI has become an indispensable part of platform strategies for organizations seeking growth and innovation.