Why are some firms better and faster than others at adapting their use of customer data to respond to changing or uncertain marketing conditions? A common thread across faster-acting firms is the use of AI models to predict outcomes at various stages of the customer journey. These firms are using AI to predict which customers are likely to churn, while their competitors react after the customers have already left. And when their predictions go off track because of external changes or market conditions, they use that feedback to quickly reorient and redirect their marketing and sales efforts. Using AI models to predict customer response has translated, in effect, to designing and running a large number of digital experiments that helped these firms respond to market changes faster than firms not using those tools. And while AI tools are far from infallible, they could reshape how we make decisions in functions such as marketing and sales and maintain a competitive advantage.

Jim McHugh is the CEO of Mperativ, the revenue marketing platform that connects go-to-market strategy to the revenue operations engine. Today, there is greater demand than ever for better and more quantifiable connections between marketing budgets and how they drive business outcomes. Even with thousands of marketing technology products available, it has been difficult for them to clearly show the impact of marketing initiatives and spend on revenue outcomes, paving the way for new technologies to rise up to this challenge and create the future of marketing science. This year, we'll begin to see go-to-market teams establish a new realm of marketing science that brings together siloed data to quantify how marketing drives results, setting the stage for continuous, bitemporal data models that will unlock the true benefits of AI and ML for marketing. Connect marketing to revenue and predict business outcomes.

Digital marketing is a term that has emerged to describe the usage of the Internet and digital media to support marketing. By using digital technologies, marketing teams achieve marketing objectives defined in the organization. As more consumers, customers and prospects are present and active on different online platforms, digital marketing needs to encompass different kinds of media channels. Paid media, earned media and owned media needs to be considered in the competitive and complex buying environment of today's market. Paid media are channels where investment is put forward to pay for visitors through ads or search ranking.

Summary: 99% of our application of NLP has to do with chatbots or translation. This is a very interesting story about expanding the bounds of NLP and feature creation to predict bestselling novels. The authors created over 20,000 NLP features, about 2,700 of which proved to be predictive with a 90% accuracy rate in predicting NYT bestsellers. It's a pretty rare individual who hasn't had a personal experience with NLP (Natural Language Processing). About 99% of those experiences are in the form of chatbots or translators, either text or speech in, and text or speech out. This has proved to be one of the hottest and most economically valuable applications of deep learning but it's not the whole story.

As attention spans wane, contract and become more sparse, always-on optimisation has become the Holy Grail for marketers. Here, Leah Pope describes the profound uplifts AI stands to deliver marketers who are willing to invest the time and understanding. Customer journeys are becoming increasingly complex due to the growing number of channels and touchpoints. At the same time, according to a Dentsu Aegis report, marketing is getting a bigger seat in the boardroom with record-high technology budgets that are expected to surpass those of CIOs this year. In fact, technology now accounts for 29% of the total marketing budget, making martech (marketing technology) the largest investment in terms of marketing resources and programs, according to Gartner.

Brands that communicate with their audiences with a 2-way communication that engages and excites the prospective clientele without shying of from creating appreciative content and embrace digital technologies, are the once who will survive in 2019! We live in an era where "Digital" and "Marketing" are terminologies, that are changing its essence & meaning, every single day. Users that brands wish to engage with have a different set of expectations and are paying attention only to brands who are communicating content that they want to hear. Gone are the days of one-way communication, where a brands Target Audiences' Consumer Journeys are based on "ADVERTISEMENTS" Since we've entered digital era and have been communicating with our audiences in 2-way conversations, audiences have been interested in a brand, only if the brand talks to them'things' (content) that they want to hear. But as we move towards the future, in 2019 what also matters is how you're keeping them engaged. Hence, how a brand takes this content, what mediums they use and how well do they exploit digital technologies, matter.

Businesses are constantly looking for ways to reduce their overhead cost and at the same time increase their revenue. One way of doing this has been cutting down on traditional advertising and using a tiny fraction of the marketing budget to advertise on social media. Another viable option has been to reduce the human workforce and replacing it with AI. Now, what happens when these two- AI and social media- combine? This article sheds more light on the AI and social media interaction, and how AI has impacted social media marketing.

Though flashy advertising campaigns tend to get most of the attention, in reality, data science is what will ultimately have the biggest impact in ensuring effective customer acquisition. Just how valuable can big data be for a business? Some analysts believe that simply increasing data accessibility by 10 percent can help the average Fortune 1000 company generate an additional $65 million in income. Quality data can be even more valuable for new startups. When you have a limited marketing budget, you can't afford to let your customer acquisition efforts go to waste -- especially when in many industries, companies spend hundreds of dollars to acquire a single customer.

Though flashy advertising campaigns tend to get most of the attention, in reality, data science is what will ultimately have the biggest impact in ensuring effective customer acquisition. Just how valuable can big data be for a business? Some analysts believe that simply increasing data accessibility by 10 percent can help the average Fortune 1000 company generate an additional $65 million in income. Quality data can be even more valuable for new startups. When you have a limited marketing budget, you can't afford to let your customer acquisition efforts go to waste -- especially when in many industries, companies spend hundreds of dollars to acquire a single customer.

Chief marketing officers (CMOs) are increasingly considering leveraging Artificial Intelligence (AI) to manage their marketing budgets. Marketing spends on digital channels have increased by 20 percent per annum as per industry estimates. Digital marketing itself has incorporated AI by skipping a generation of intermediate system development. Modern marketing automation platforms already include chatbots for customer interaction, voice recognition/translation in their websites and semantic search in their product catalogues. However, the shift from traditional marketing to digital marketing was driven by the very fact that one could drive more personalised and segmented messaging to customers to drive up conversion rates.