Marketing is one of the high-cost activities for any online platform. With the increase in the number of customers, it is crucial to understand customers based on their dynamic behaviors to design effective marketing strategies. Customer segmentation is a widely used approach to group customers into different categories and design the marketing strategy targeting each group individually. Therefore, in this paper, we propose an end-to-end pipeline RE-RFME for segmenting customers into 4 groups: high value, promising, need attention, and need activation. Concretely, we propose a novel RFME (Recency, Frequency, Monetary and Engagement) model to track behavioral features of customers and segment them into different categories. Finally, we train the K-means clustering algorithm to cluster the user into one of the 4 categories. We show the effectiveness of the proposed approach on real-world Housing.com datasets for both website and mobile application users.

As the digital era evolves, so does marketing. The recent boom in artificial intelligence (AI), machine learning (ML) and big data analytics have led to a new wave of opportunities for those looking to refine their customer engagement strategies. AI is taking over much of the decision-making process for marketers, which has helped eliminate many of the traditional challenges that come with marketing. While AI has been used successfully by marketers for years now, it's only recently that these systems have become powerful enough to take on more complex tasks such as predictive analytics and machine learning. For example, an email service provider can use AI to determine what time a person is most likely to read their emails and send out messages accordingly.

Artificial Intelligence in digital marketing is a concept many B2B marketers struggle to get their heads around. We've put together this informative guide to artificial intelligence (AI) including a jargon busting glossary of key concepts you're likely to see joining the marketing vernacular. Put simply, artificial intelligence (AI) is intelligence generated by machines which allows us to efficiently and effectively delve into all available data. AI has the ability to provide far greater amounts of more relevant data which, along with the best B2B digital marketing activities to support this, can lead to outstanding results. A computer or robot will think and work like a human, performing tasks which normally require the natural intelligence element that they were once perceived not to hold.

Click here to learn more about Gilad David Maayan. What Is Artificial Intelligence Marketing? In marketing, artificial intelligence (AI) is the process of using data models, mathematics, and algorithms to generate insights that marketers can use. Marketers use insights gained from AI to guide future decisions on event spending, strategy, and content topics. AI also makes it possible to measure and optimize marketing activities without human intervention.

In today's business environment, a company may employ a mix of many marketing activities (e.g., free samples, discount coupons, weekly specials and advertisements) to attract new customers, enhance customer loyalty, and induce sales. Given a marketing plan with a mix of marketing activities, each activity may be allowed a spend level that results in corresponding outcome. The company often needs to adjust the resource allocated to marketing activities due to various reasons (e.g., marketing budget change, change in scope of targeted audience, geographies and products, product demand and/or supply changes, and activity cost and/or performance changes), aiming to optimize the revenue, profit, or other goals of the company. In practice, the company may desire such adjustments to be planned and executed by considering resource availability for executing changes, contractual obligations, etc. Due to minimum incremental investments required for certain marketing activities (e.g., minimum cost of a targeted rating point in TV advertisements or minimum cost of implementing a promotional discount), there is a need to impose a minimum change in spend (investment) constraint for a marketing activity. Since resources will be required to implement changes in marketing activities and resources available are limited, a constraint on the maximum to number of activities with spend changes is also imposed. Therefore, to guarantee that the outcome of a marketing mix optimization (MMO) is feasible for practical implementation, there is a need to solve the MMO problem with these added constraints. Given an existing marketing plan (typically from a previous period), our MMO problem aims to adjust spend allocations on marketing activities with an objective of maximizing revenue subject to four sets of constraints: bounds on activity spend, total budget limits, the minimum change in spend for an activity, and the maximum number of activities associated with spend change.

Marketing mix models (MMMs) are statistical models for measuring the effectiveness of various marketing activities such as promotion, media advertisement, etc. In this research, we propose a comprehensive marketing mix model that captures the hierarchical structure and the carryover, shape and scale effects of certain marketing activities, as well as sign restrictions on certain coefficients that are consistent with common business sense. In contrast to commonly adopted approaches in practice, which estimate parameters in a multi-stage process, the proposed approach estimates all the unknown parameters/coefficients simultaneously using a constrained maximum likelihood approach and solved with the Hamiltonian Monte Carlo algorithm. We present results on real datasets to illustrate the use of the proposed solution algorithm.

AI-marketing Personalization, Video Marketing, Audience Analysis, Podcasts will be big trends for 2020. Every year - better to say, every week - there is something new in the digital marketing trends. Just as it happens with fashion, marketing knows different directions every year. Many of this year's trends are not a new entry at all. Many of them are around for a couple of years now. So, who knows what to expect from the future? That's why we have created for you our list and a beautiful calendar to handle all of these trends with success! We are not able to say which one will be what, but we can start this new decade with 12 most promising marketing trends for the new year - and, who knows, maybe for much longer than that! Our list is a list of those expectations for the new year. We expect that AI will grow its importance.

Digital Marketing is constantly changing and evolving and 2019 was no different. We can see new trends in digital marketing, new products, tools and technologies. Below I'm presenting 20 digital marketing ideas for you and your business and some tips on how to effectively use them to improve your marketing efforts in 2020. Pick and choose ideas that suit you and your business the most for the best results. Creating a website is an obvious thing to do for everybody that is doing digital marketing.

Artificial Intelligence (AI) is no longer the next big thing, it is now a big thing now in digital marketing. All digital marketing operations are now affected by AI-powered tools. From startups to large firms are opting for AI-powered digital marketing tools to enhance campaign planning & decision making. AI-based tools are now a flourishing market, with a drastic change in demand. According to most of the digital marketers AI enhancing all the areas where the predictive analysis, decision making & automation efforts required.

Do you know why your CMO needs artificial intelligence NOW? Because: CMOs must show measurable financial results for the budget they invested! Wonder how AI relates to financial results? I'm not surprised since the answer may not be obvious. With an ever-increasing number of smart devices, apps and methods, consumers have more and more ways to get information and create content digitally. In the process, they create an explosion of data for marketers to track and analyze.