Yahoo’s acquisition of Aviate should come as no surprise for anyone who is familiar with the mobile space. In order for Yahoo to compete with companies like Google for advertising money, Yahoo has to invest and solve their problems with mobile marketing. As we previously mentioned, the difficulty in tracking performance and the smaller screen size of mobile devices, has created a gap between where advertising money is spent and where people spend their time. Aviate helps Yahoo solve part of the screen estate problem with its predictive computing platform, by giving users what they want and when they want it. This acquisition confirms what most of us already know – predictive computing is the future of mobile.
Why is Predictive Computing the Future of Mobile
The simple answer is that consumers want it because it’s convenient. It’s also happens to be the right time because everything is already in place: the data, the infrastructure and the technology. Companies collect billions of data points from their customers each year and that individual’s data can be used to predict their actions in the future. With decreasing computing costs and the rise of cloud computing, a lot of the heavy duty computing has been moved to the server side from the client side. This makes predictive computing possible because the data analysis can take place, regardless of the computing power of mobile phones. Finally, over the past decade, because of the explosion of data, there has been a lot of progress in data analytics and predictive modeling. For instance, Microsoft is able to predict where a person will be 285 days from today. When considering all of these factors, it’s clear that predictive computing will become the future of mobile.
Huge Unexplored Opportunities
Given that mobile is the only media consumption that’s growing, there is no doubt that predictive computing will be a huge market and the ROI will be huge, so enterprise companies will be all over it. In essence, enterprises will be able to tailor their ads to customers at the moment they are about to make a decision. For instance, Starbucks can send targeted ads to you at 2:00pm on Mondays, if they know you usually buy coffee on that day and time. Even though there are many players in the marketing analytics industry, there are few, if any, in the predictive computing market. This represents a huge unexplored opportunity.
B2B Analytics and Marketing Companies Needs to Start Thinking about Predictive Computing Now
The digital marketing industry is a competitive industry with few entry barriers. B2B marketing and analytics companies should start looking into predictive computing, not only because it is a way to differentiate themselves from competitors, but also because the winners will be the ones who have the best predictive computing capabilities.
Below we have compiled a list of metrics that could be relevant for most B2B marketplaces and hope that it serves as a framework for tracking KPIs for success.