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Data-driven marketing is a process where marketers employ a process to gain insights into consumer behavior, including purchasing patterns, advert effectiveness, and browsing habits. Contemporary methods utilize big data strategies to collect and analyze information on consumer interactions and engagements, aiming to predict future behaviors. This analysis involves evaluating existing data, acquiring new data and systematically organizing and interpreting it to improve marketing strategies. The primary objective is to better understand and address customer needs. Market research provides a detailed understanding of consumer preferences
Contemporary data driven marketing can be traced back to the 1980s and the emergence of database marketing, which increased the ease of personalizing customer communications. [1]
Through the use of analytic tools, marketers attempt to understand customer behavior and make informed decisions based on the data. [2]
E-commerce retailers use data driven marketing to try and improve customer experience and increase sales. One example cited in the Harvard Business Review is Vineyard Vines, a fashion brand with brick-and-mortar stores and an online product catalog. The company has used an artificial intelligence (AI) platform to gain knowledge about its customers from actions taken or not taken on the e-commerce site. Email or social media communications are automatically triggered at certain points, such as cart abandonment. This information is also used to refine search engine marketing. [3]
In marketing, market segmentation or customer segmentation is the process of dividing a consumer or business market into meaningful sub-groups of current or potential customers known as segments. Its purpose is to identify profitable and growing segments that a company can target with distinct marketing strategies.
Personalized marketing, also known as one-to-one marketing or individual marketing, is a marketing strategy by which companies leverage data analysis and digital technology to deliver individualized messages and product offerings to current or prospective customers. Advancements in data collection methods, analytics, digital electronics, and digital economics, have enabled marketers to deploy more effective real-time and prolonged customer experience personalization tactics.
Analytics is the systematic computational analysis of data or statistics. It is used for the discovery, interpretation, and communication of meaningful patterns in data, which also falls under and directly relates to the umbrella term, data science. Analytics also entails applying data patterns toward effective decision-making. It can be valuable in areas rich with recorded information; analytics relies on the simultaneous application of statistics, computer programming, and operations research to quantify performance.
Database marketing is a form of direct marketing that uses databases of customers or potential customers to generate personalized communications in order to promote a product or service for marketing purposes. The method of communication can be any addressable medium, as in direct marketing.
Data management comprises all disciplines related to handling data as a valuable resource, it is the practice of managing an organization's data so it can be analyzed for decision making.
Marketing communications refers to the use of different marketing channels and tools in combination. Marketing communication channels focus on how businesses communicate a message to their desired market, or the market in general. It is also in charge of the internal communications of the organization. Marketing communication tools include advertising, personal selling, direct marketing, sponsorship, communication, public relations, social media, customer journey and promotion.
The target audience is the intended audience or readership of a publication, advertisement, or other message catered specifically to the previously intended audience. In marketing and advertising, the target audience is a particular group of consumer within the predetermined target market, identified as the targets or recipients for a particular advertisement or message.
Marketing effectiveness is the measure of how effective a given marketer's go to market strategy is toward meeting the goal of maximizing their spending to achieve positive results in both the short- and long-term. It is also related to marketing ROI and return on marketing investment (ROMI). In today's competitive business environment, effective marketing strategies play a pivotal role in promoting products or services to target audiences. The advent of digital platforms has further intensified competition among businesses, making it imperative for companies to employ innovative and impactful marketing techniques. This essay examines how various types of advertising methods can be utilized effectively to reach out to potential consumers
Digital marketing is the component of marketing that uses the Internet and online-based digital technologies such as desktop computers, mobile phones, and other digital media and platforms to promote products and services. It has significantly transformed the way brands and businesses utilize technology for marketing since the 1990s and 2000s. As digital platforms became increasingly incorporated into marketing plans and everyday life, and as people increasingly used digital devices instead of visiting physical shops, digital marketing campaigns have become prevalent, employing combinations of search engine optimization (SEO), search engine marketing (SEM), content marketing, influencer marketing, content automation, campaign marketing, data-driven marketing, e-commerce marketing, social media marketing, social media optimization, e-mail direct marketing, display advertising, e-books, and optical disks and games have become commonplace. Digital marketing extends to non-Internet channels that provide digital media, such as television, mobile phones, callbacks, and on-hold mobile ringtones. The extension to non-Internet channels differentiates digital marketing from online marketing.
Marketing Mix Modeling (MMM) is a forecasting methodology used to estimate the impact of various marketing tactic scenarios on product sales. MMMs use statistical models, such as multivariate regressions, and use sales and marketing time-series data. They are often used to optimize advertising mix and promotional tactics with respect to sales, revenue, or profit to maximize their return on investment.
Customer engagement is an interaction between an external consumer/customer and an organization through various online or offline channels. According to Hollebeek, Srivastava and Chen, customer engagement is "a customer’s motivationally driven, volitional investment of operant resources, and operand resources into brand interactions," which applies to online and offline engagement.
Customer analytics is a process by which data from customer behavior is used to help make key business decisions via market segmentation and predictive analytics. This information is used by businesses for direct marketing, site selection, and customer relationship management. Marketing provides services to satisfy customers. With that in mind, the productive system is considered from its beginning at the production level, to the end of the cycle at the consumer. Customer analytics plays an important role in the prediction of customer behavior.
A target market, also known as serviceable obtainable market (SOM), is a group of customers within a business's serviceable available market at which a business aims its marketing efforts and resources. A target market is a subset of the total market for a product or service.
Artificial intelligence marketing (AIM) is a form of marketing that uses artificial intelligence concepts and models such as machine learning, Natural process Languages, and Bayesian Networks to achieve marketing goals. The main difference between AIM and traditional forms of marketing resides in the reasoning, which is performed by a computer algorithm rather than a human.
Customer experience, sometimes abbreviated to CX, is the totality of cognitive, affective, sensory, and behavioral customer responses during all stages of the consumption process including pre-purchase, consumption, and post-purchase stages.
Dialogue marketing emerged in the early 2000s as companies engaged willing consumers in an ongoing dialogue to create lasting relationships. For example, based on data, marketers invite groups of likely consumers to connect with the company. The engagement process provides value to both the consumer and the company. Marketers use these opportunities as data collection points. The companies use the data to further customize their marketing messages and personalize the experience for their consumers and market segments. In exchange for sharing opinions, buying patterns, product preferences, etc., consumers receive perks such as discounts, tips, and free trials as well as appropriate messaging from the company.
The purchase funnel, or purchasing funnel, is a consumer-focused marketing model that illustrates the theoretical customer journey toward the purchase of a good or service.
In electronic commerce, conversion marketing is marketing with the intention of increasing conversions—that is, site visitors who are paying customers.
Marketing automation refers to software platforms and technologies designed for marketing departments and organizations automate repetitive tasks and consolidate multi-channel interactions, tracking and web analytics, lead scoring, campaign management and reporting into one system. It often integrates with customer relationship management (CRM) and customer data platform (CDP) software.
Customer data or consumer data refers to all personal, behavioural, and demographic data that is collected by marketing companies and departments from their customer base. To some extent, data collection from customers intrudes into customer privacy, the exact limits to the type and amount of data collected need to be regulated. The data collected is processed in customer analytics. The data collection is thus aimed at insights into customer behaviour and, eventually, profit maximization by consolidation and expansion of the customer base.