Using ML & AI to Drive Marketing
So what exactly is machine learning and artificial intelligence? In short, like other analytical tools, ML and AI transform data into knowledge. ML scours vast amounts of data to uncover an insight exposed in patterns and aims to identify the rules that seem to govern the data, then apply that learning to the query, and provide a model that can then be applied to other datasets.
In order to identify these rules, the algorithms in the model must learn from the inputs. Hence, the term Machine Learning. Artificial Intelligence, on the other hand, allows computers to discover underlying patterns in data without human intervention or explicit programming instructions, as such AI is considered “self-learning”.
For complex tasks and larger datasets, it is now possible to let a machine develop its own solution to a problem, whereas humans would find it impossible to detail all of the scenarios. In short, ML and AI leverage huge computational power in order to process vast datasets in real-time, resulting in an analysis that is way beyond human capabilities.
An obvious advantage of ML and AI is the ability to handle large and diverse data volumes with speed and accuracy. As business data volumes grow, with current data output at nearly 250,000 Billion pages of text per day, applied models can scale without diminishing performance. And as the data changes, with mixtures of structured/unstructured from multiple varieties (i.e. images, text, financials, voice), ML and AI can adapt without any human involvement. ML and AI can identify trends, patterns, and insights that an analyst could never observe, so the performance gains over non-assisted analytics is immeasurable.
ML and AI strategy allow businesses to stay ahead of their competition by analyzing customer, product, and industry trends as they are developing and solving complex problems before they fully materialize.
Organizations that continuously invest in AI can increase their competitive strategic advantage, and are well-suited to receive the benefits from other ML and AI-enabled performance multipliers.
Thanks to years of knowledge sharing from SEO practitioners, SEO analysis, and on and off-page practices, ML can now automate many SEO processes including tracking hundreds of ranking indicators and identifying variables such as tags, metadata, page types that can drastically increase the visibility and ranking of business websites.
With literally billions of active users, social media management is a requirement for any business. AI can help by automatically responding to critical reviews or complaints, maintaining trend awareness, identifying neglected and/or new opportunities (i.e. keywords, audiences), and mining the wealth of direct customer data posted each day that demands 24/7 attention.
One of the more popular AI applications used today are chatbots, which are always “live”, improve customer service, eliminate wait times, provide up-to-date product information, and help answer customer questions – all while building an ever-expanding dataset through the analysis of responses and threads.
AI can create valuable insights for a business by parsing through content from news sources, relevant blogs, or thousands of customer interactions across multiple channels, and focusing on a multitude of variables, such as sentiment, which can provide valuable insights into customers’ feedback, relevant trends, and churn risks.
Personalization is where the popularity of ML and AI all began. The poster child for this is Netflix, beginning with its recommendation engine for its movies and tv shows. Then its AI algorithm started serving up custom visuals to each customer, enticing them to try new offerings. For Netflix, utilizing AI for deeper personalization means more screen time, which translates to renewed subscriptions and increased revenue.
Predictive analytics has been a powerful tool since the 1940’s, but now with AI, marketers can analyze millions of customer interest variables, social interactions, and website touch-points in order to provide insights that are way beyond the abilities of analysts. This includes predicting the most profitable segments with greater accuracy and speed than traditional methods.
AI and ML have unparalleled optimization capabilities. In short, they help marketers reach more prospects with a lot less work. For example, they can significantly reduce manual work when creating an ad campaign, while simultaneously auto-optimizing its performance. For content marketing, models can optimize content for SEO, prioritize gaps, and automatically create product descriptions, tweets, and emails in less than a second.
When marketing automation took off in the 1990’s, newer technologies began to take advantage of the features in CRM and email platforms. Now, AI can inject the power of intelligent decision-making to automate every element of complex, large scale campaigns in order to dynamically serve an individual with accurate messaging at every touch point – transforming prospects into lifelong advocates.
Not sure what your strategy should look like? Or maybe you don’t have the time or bandwidth? Then connect with an Apex Theorem Marketing Acceleration Advisor. We’d be happy to discuss a customized ‘next level’ strategy with you, and show you where you stand on our proprietary Capability Maturity Model (CMM).
Article Written By: Jonathan Bonghi, Marketing Strategist at Apex IT, [email protected]