Machine learning and Digital marketing- Study of a Recent Trend

Machine learning is responsible for a slew of radical new advancements across many industries. Usage of machine learning is a very recent and hot topic in the digital marketing area. Advancements in machine learning, predictive analytics, big data and artificial intelligence aren’t limited to not only big giants but also now organizations of all sizes are capitalizing on the power, using this revolution.

ML is a part of Artificial Intelligence —it’s just something that has evolved over time, and gained considerable new strengths in recent years. Recent examples include online product recommendations, which use big data to make algorithmic suggestions to consumers. Google’s search browser also examples of ML: not only do search results themselves flex the power of machine-centric problem-solving to understand intent and speak to the searcher’s pain points, but Google routinely uses ML technology to make sense of search queries, such as when those queries are littered with spelling errors.

different brands are already started to use  ML to drive insights and operations that go well beyond text. For example, companies use ML to make brand email marketing more efficient and productive. Machine learning analyses consumer behaviors to determine when email delivery is most likely to draw engagement and conversions. By timing emails according to those insights, clients have seen double-digit increases in email-generated revenue (Source: Harvard Business Review).

As behavioral and contextual data becomes more available to brands, using ML technology these are trying to many hidden information from data.  If marketers are unable to put that data into context and drive insights from the information. ML picks up where those marketers and their analytics tools fall short, processing data at an enormous volume to leverage that information for valuable insights.

One of the most interesting examples of this, very recently Target’s marketing team able to learn of a teenager’s pregnancy before the girl’s parents. That realization came by examining her shopping history and giving it context based on past purchases from other consumers. Based on her shopping behavior, Target reached the conclusion she was likely pregnant, and the company shifted its marketing to specifically address her new pregnancy needs.

ML is already being utilized in marketing campaigns around the world, but the full force of its influence is yet to arrive. A recent prediction by market research experts, ML will soon move from its service at the individual consumer level to a larger role that considers large groups at once, and external factors as well as internal data.

Machine learning may sound futuristic to many people at this moment, but my belief, its usage in long run increase intelligent marketing and efficient customer interactions that benefit both customers and businesses. Marketing teams can adapt and evolve through exposure to new data quickly, and can accelerate business processes for the long run in future.