Consumer applications provide ample opportunities to surface and communicate various forms of content to users. From promotional campaigns for new features or subscriptions, to evergreen nudges for engagement, or personalised recommendations; across e-mails, push notifications, and in-app surfaces. The conventional approach to orchestration for communication relies heavily on labour-intensive manual marketer work, and inhibits effective personalisation of content, timing, frequency, and copy-writing. We formulate this task under a sequential decision-making framework, where we aim to optimise a modular decision-making policy that maximises incremental engagement for any funnel event. Our approach leverages a Difference-in-Differences design for Individual Treatment Effect estimation, and Thompson sampling to balance the explore-exploit trade-off. We present results from a multi-service application, where our methodology has resulted in significant increases to a variety of goal events across several product features, and is currently deployed across 150 million users.

As more businesses come online and marketing efforts increase, there is more demand for content. Creating that content takes more resources. However, several AI tools are available in the market today to generate content. But how good are these tools and the content generated by these tools? Capterra recently conducted a study to gain some insights.

With supply chain challenges and the ongoing global pandemic regularly introducing new obstacles, sales and marketing professionals must continue to move at the speed of business regardless of where they currently work. According to McKinsey, our new way of working during the pandemic inspired ten years of digital innovation in three months. To ensure no opportunities are missed in this rapidly changing landscape, sales and marketing teams need data to unearth new, actionable insights that they can use to identify in-market prospects and customers at scale. Over three-fourths of CEOs say that marketing leaders are the key to driving future growth. But they can't do it alone – technology will be an essential component fostering that progression.

AI has been around in digital marketing for a long time, but there are some pretty significant limitations-such as the need to be trained by humans. This is where Quantum AI comes in to help out! It can learn on its own, without any human input whatsoever. And it can even come up with new ideas on its own. In the article, I will explain how Quantum AI is making its way into the world of digital marketing, why it's happening now, and what this means for companies.

Excelsior has been engaged exclusively to conduct a search for this innovative technology company growing their New York operation. This really is a unique career opportunity to join a fast-growing and innovative Artificial Intelligence (AI) fintech company that is pioneering the deployment of next generation process automation solutions for banks through the use of artificial intelligence / machine learning technologies. This international firm has already had a lot of US success with refence-able banks as clients, and following Series A investment they're taking their US operation to the next level. Reporting to the Head of Marketing based in Europe, this is a newly created NYC position for a marketing professional to take the lead role in execution of the company's US marketing, with go-to-market strategies for new products and market areas. As their first marketing professional in the US working closely with the sales team this means taking the marketing plan from the strategic – business drivers, positioning, solution messaging and value propositions, through to tactical operations – content, campaigns, demand generation, events and PR etc.

Today's marketers are challenged to adapt to new technologies, consumer habits and practices, channels, and methods of engagement arguably faster than any other generation. One of the hottest areas of interest is artificial intelligence. How can AI be leveraged to understand, interact with, and generate loyalty with consumers? Raj Venkatesan (Darden Business School), co-author of The AI Marketing Canvas: A Five-Stage Road Map to Implementing Artificial Intelligence in Marketing with Jim Lecinski (Kellogg Business School), shares insight on how marketers must upskill to address the changing marketing landscape. Kimberly Whitler: How has marketing evolved?

There is no question that 2020 has been a pivotal year in history, but how it will affect the future largely remains to be seen. In digital marketing, we are noticing the continuation and acceleration of many trends. Marketing professionals believe that the digital transformation boost represents the biggest opportunity born of the current situation, giving us an indication of what the future might look like. Which trends are changing the face of the marketing industry? This question is no less relevant in 2021 – especially now that the pace of digitalization has accelerated in many sectors as a result of COVID-19.

Artificial Intelligence in Marketing Course is a practical guide for business leaders who are passionate about leveraging machine intelligence to enhance the productivity of their organizations. If you love to drive innovation by combining data, technology, design, and people, and to solve real problems at an enterprise scale, this is your course. This AI in marketing course will help you grow your business & save time! Let's talk about what you're getting with this Artificial intelligence in marketing course. We will teach you how to lead successful AI initiatives by prioritizing the right opportunities and designing business solutions to benefit your organization.

Marketers are increasingly using machine learning technology to help implement campaign strategies. But the introduction of machine learning can raise programming concerns, concerns which many marketing professionals may only have a surface-level understanding of. If you are a marketing professional who finds themselves in this situation, understanding pipelines is a good place to start learning without being overwhelmed. Pipelines are process steps necessary in building a machine learning algorithm. "Pipeline" is used by developers to describe the series of events which feed one into the other from source code and on into a production environment.

To help brands ensure that each and every customer interaction is data driven, Oracle has announced a series of new data-first updates across Oracle Customer Experience (CX) Cloud. The latest updates include new digital assistants for sales, customer service and marketing professionals, new data enriched B2B sales capabilities, and new industry solutions for telecom and media, financial services, and public sector. "The latest updates to Oracle CX Cloud are fueled by data and machine learning to help our customers take advantage of powerful data insights to get ahead of customer needs and ensure a positive, unforgettable customer experience" Rob Tarkoff, executive vice president, Oracle CX Cloud and Oracle Data Cloud said. Oracle CX is an integrated set of applications across marketing, sales, service and commerce. The latest updates to Oracle CX include enhancements to Oracle CX Unity, Oracle's enterprise-class customer data management platform, as well as: In addition, service teams leveraging Oracle Intelligent Advisor to model and deploy interactive advice can use the Oracle Digital Assistant's conversational UI to deliver rich data-connected self-service on chat channels.