Big Data: The Last Mile
It’s no secret that the amount of data available to us today is growing exponentially. Much has been written about the rapid growth of Big Data and the progress being made in artificial intelligence. Analytical research is enabling us to extract even more meaningful insights from this data. However, in order to truly exploit the full potential the growing investments in big data, we must also look at the last mile: the suite of technologies used in translating data-driven insights into consumer action.
IBM determined that 90% of all current data in the world was created over the last two years. That’s not so difficult to imagine when looking around at today’s connected, real-time world. With all of our social interactions online, our communication is public and exponentially multiplied in frequency. Instead of interacting with a select group of close friends over the course of a week, we now interact with a much broader group of hundreds of friends online daily. As a result, Facebook has already seen more than 9 billion LIKES on its platforms to date. With regard to dating, for instance, we are no longer set up on a date by a mutual friend, but instead, we swipe through hundreds of profiles and faces without meeting or speaking to the person on the other side of the screen. The Tinder Dating application has 1.5 billion profiles swiped per day.
While traditional poker players played around 75,000 hands offline per year, today’s online pros can play two million hands a year with the same time investment. As a result, a 23-year-old online poker pro is likely a more experienced player than the 60-year-old sitting across from him when playing in person. Additionally, everyday devices are becoming more connected. The Internet of Things (IoT) revolution is a reality, with over 6 billion “things” already connected and another 20 billion devices expected to join by 2020. Studies suggest also that 6 billion mobile phones will be in operation over the next 5 years, which is nearly the entire human population. These connected devices are stacked with data is increasingly generated by private companies. For the first time in history, private businesses possess more data than public institutions. With so much available data, marketers sometimes find it challenging to extract meaningful, actionable insights, sparking more than one debate around the ROI of Big Data investments.
Luckily, the impact of Moore’s Law coupled with the development of more advanced data-processing algorithms is here to save the day. Today’s cell phones boast hundreds of times more computational power than Deep Blue, the Supercomputer made famous for beating chess world champion Gary Kasparov in 1997. They also cost a fraction of the price and fit in our pockets.
IBM’s Watson was made famous through its Jeopardy triumph in 2011. Each day Watson helps companies improve business processes, identify actionable customer behaviors, and address latent client needs by making connections that were previously invisible. Google’s success in beating Go world champion Lee Sedol represents a new beachhead in our ability to extract insights from vast amounts of data. The immense complexity of Go has made brute force computational approaches impossible (in order to write out the number of variants of the game, you would need to use a 1 followed by 170 zeros). New machine learning approaches have managed to extract insights from this vast mountain of data. These rich insights, together with the rise of insight-driven marketing, are aligning entire organizations around data-driven projects, aiming to monetize and capitalize on the investments made. But if the customers aren’t listening, success may be elusive.
Much like the other parts of the value chain, where automation was an essential part of handling the extreme complexity of data collection and analysis, automation is also becoming a critical component for the success of the last mile in the value chain: Communications. Marketing automation technologies have enabled marketers to effectively drive high volumes of leads through their funnels while applying complex rules and insights. Mail merge made it possible to apply different rules and approaches to each individual lead or customer. Programmatic ad buying has made it possible to manage media campaigns across a highly complex landscape of networks and platforms. Translating insights into personal emails or hyper-targeted banner ads may be a good start. However, these media all fall short on storytelling and customer engagement. The one medium that consistently beats out the competition on all engagement metrics is video. High production costs and long timelines to deploy have made this an unsuitable medium for anything other than broadcast messages aimed at very broad audiences.
However, recent technological developments in the realm of real-time video rendering are finally making video accessible to insight-driven and results-oriented marketers. Companies are now able to deliver engaging and highly personalized campaigns to their customers using personalized video. Consider the case of a US Telco Carrier we worked with on addressing one of their CEO’s main concerns: extremely high churn. Our client employed a cross-functional approach using data-driven analysis to extract meaningful insights regarding the pain points experienced during the customer onboarding journey. These insights were then used to create a series of 10 videos, delivered at strategic points during the onboarding journey. These videos were personalized to each customer using data such as their location, billing plans, device, optional packages, data usage, and interactions with customer care. The end result obtained was a 37% reduction in early churn, far above our client’s expectations! This success was partly due to the strong and effective insights of planning. It was also due to the video communication channel selected to translate these insights into actions. In this specific case, 13% of customers engaged with the video. According to Silverpop’s Email Marketing Metrics Benchmark Study, on average 3.2% of customers interact with an email message sent to them. Therefore, it is estimated that using advanced communications technologies was responsible for 75% of the value creation in this project.
Big Data is here to stay. It will be understood best when sorted as Data collection, Cloud uploading, and Video Communication. 56% of enterprises plan to increase their investments in big data in the next 3 years. 3 out of 4 CMOs believe that their CEOs would say that “marketers are always asking for more money, but can rarely explain how much incremental business this money will generate.” These are clear indications that that ROI debate around these ever-growing investments is set to continue. Machine-generated insights require machine-driven campaigns across all mediums. Employing the latest video personalization and automation technologies will ensure that growing investments in big data will translate into real market value.