A well-organized supply chain has always been a powerful source of competitive advantage. In today's interconnected economy it very essential. With the development of Artificial Intelligence (AI) solutions, logistics departments can solve many complex problems. For example, optimization, forecasting errors, reducing losses in sales caused by product unavailability, etc. This information is according to a recent paper by McKinsey Global Institute.
Imagine you are a company selling a fast-moving consumer good in the market. Let's assume that the customer would follow the given journey to make the final purchase: These are the states at which the customer would be at any point in the purchase journey. Now, how to find out in which state the customers would be after 6 months? Markov Chain comes to the rescue!! Let's first understand what Markov Chain is. Let's delve a little deeper.
The year brought AI into the mainstream where numerous businesses warmed up to it, embraced it and reaped handsome results. Digital Marketing, being immensely data driven, has been one of the early adopters of AI and witnessed tremendous impact. Digital Marketing is all about harnessing the power of data to create campaigns that are personalized to fit the desires and interests of the customers. Interacting with the customers at the right time on the right platform with the right message is critical to a campaign's success. The competitive edge for a marketer is based on how quickly one can analyze the incoming data and recalibrate a campaign to outmaneuver the competition.
Maintaining digital relevance is a priority for most brands, however, according to recent research by Capterra, SMB brands are struggling in this area. The study surveyed over 700 SMB leaders, 47 percent of respondents said they factor technology trends and advancements into their strategic planning. However, choosing the right technology solution is proving to be a top business challenge, with 19 percent citing this as their number one challenge. Moreover, SMBs are failing to adopt chatbots, artificial intelligence (AI) and Internet of Things (IoT) marketing into their business strategies -- despite consumer expectations. The Capterra report identified the following three areas that SMBs are struggling to get to grips with.
Digital marketing is an ever-changing landscape, thanks to the strides in digital technology. The prevalence of smartphones and tablets, along with internet penetration, have added more power to digital marketing. Going digital means using the entire gamut of technologies - from the use of artificial intelligence to wearables. As a brand, making an impact on every customer (internal or external), and opening up multiple channels of communication for customers is no more a luxury, but a necessity. Businesses know that the present and future of marketing is undoubtedly digital.
Artificial intelligence has already made a huge difference in how brands interact with consumers and how marketing strategies are managed. In such a rapidly changing environment, it's difficult to predict what the future holds, but there are certainly some clues to what we might expect in the coming year. As we near the end of the year and look forward into 2019, here are some of the biggest AI-related digital marketing trends to look out for. We've already seen how chatbots can have all sorts of applications from dealing with basic customer service inquiries, to driving sales. Consumers have already become used to chatbots and feel comfortable talking to them, thanks to the growing popularity of virtual assistants like Siri and Alexa.
We have expected artificial intelligence (AI) will become part of our everyday lives for quite some time. Already, businesses are starting to utilise AI. For example, we built a basic chatbot utilising an AI platform in a week-and-a-half. The other great thing is large enterprises aren't leading the way – anyone can be involved. Companies are now making their AI tools accessible and easy to use, and we will see more rapid experimentation and innovation from smaller businesses as a result.
The High-Level Expert Group on Artificial Intelligence (AI HLEG) will have as a general objective to support the implementation of the European strategy on Artificial Intelligence. This will include the elaboration of recommendations on future-related policy development and on ethical, legal and societal issues related to AI, including socio-economic challenges. Moreover, the AI HLEG will serve as the steering group for the European AI Alliance's work, interact with other initiatives, help stimulate a multi-stakeholder dialogue, gather participants' views and reflect them in its analysis and reports. Advise the Commission on next steps addressing AI-related mid to long-term challenges and opportunities through recommendations which will feed into the policy development process, the legislative evaluation process and the development of a next-generation digital strategy. In May 2019, the AI HLEG will also put forward policy & investment recommendation on how to strengthen Europe's competitiveness in AI, including guidance for a strategic research agenda on AI and on the establishment of a network of AI excellence centres.
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.
Leading-edge marketing organizations are shifting both strategy and culture to prioritize data storage and application to produce actionable insights. Results from a recent survey conducted by MIT Technology Review Insights in association with Google showed that "leaders" (companies that have experienced significant growth in revenue or market share) are more likely than "laggard" organizations to leverage machine learning (ML) to help their marketers better understand customer intent. Armed with insight into customer behaviors, marketers can focus on those customers with high lifetime value, providing the personalized and relevant offers they seek. ML assists marketers in extracting intelligence from the enormous amounts of data their organizations generate daily, enabling certain customers to view the performance of specific marketing campaigns during specific time periods. ML is a powerful tool that uses empirical data to allow marketers to quickly respond to changing market conditions and customer needs by making informed decisions in real time.