Marketing Information Systems
Introduction
Philip Kotler, ‘Father of Modern Marketing’ and MIT PhD Economist, offers the most concise definition of the marketing information system: “A marketing information system is a continuing and interacting system of people, equipment, and procedures to gather, sort, analyse, evaluate, and distribute the pertinent, timely, and accurate information for use by marketing decision-makers to improve their marketing planning, implementation, and control” (Kotler, 1997).
It’s the humble, understated marketing system that provides the foundation for the striking, colourful, exciting advertising that latches onto the hearts and minds of television viewers, video and audio streamers, shoppers, and blog readers around the world, creating hype, igniting trends, and sparking conversation, leading to interest, purchase, and sometimes lifelong relationships with brands, occasionally extending beyond the individual consumer to friends and family through referral, or online communities and vloggers sharing a common brand or product obsession, with their tips, tutorials, hacks, and other UGC.
Beginnings
Bournemouth University (Defining Marketing: A brief history of marketing, n.d.) describes three main periods in the development of modern marketing practices: production orientation during the Industrial Revolution, sales orientation from the end of WWII to the late 1950s, and marketing orientation as markets became saturated from the 1960s and the marketing department was formed. It was the sales orientation period that saw the first significant marketing tool developed in the paper-based Rolodex of 1953, invented and patented by Danish engineer Hildaur Neilsen (Google Patents n.d.), to allow for contacts to be stored and accessed. The Rolodex remained a staple among professionals throughout the personal computer era until the 1990s as PC digital storage gained significantly in size and popularity.
Development
Philip Kotler not only defined the marketing information system, he recommended a framework for such a system in his seminal publication, Marketing Management: Analysis, Planning, and Control (1967), including four components: Internal Records System; Marketing Intelligence System; Marketing Research System; and Marketing Decision Support System (DSS). Within the Internal Records System component, two different domains of marketing information systems initially evolved to overlap with the DSS: Sales Force Automation (SFA) managing lead generation and customer acquisition, and Customer Relationship Management (CRM) managing customer engagement and retention, and today both domains are increasingly integrated into one solution.
Business computing took hold across most industries during the 1970s and 1980s and marketing departments and managers adopted generic software such as databases, spreadsheets, and documents to perform SFA activities such as recording and analysing client, sales, and advertising data, and comparing results against set goals (see, for example, OpenFlow, n.d.).
Over time, those who used these solutions on a daily basis started seeing the challenges presented by this approach (see Salesforce, n.d.), and in the 1990s through to the early 2000s, some of the major marketing software solutions that we know today were launched. Unica’s Enterprise Marketing Management in 1992 (Kane, 2024) was designed for marketing campaign management focused on lead generation (ibid.). Before long, the popular SAP R/3 ERP integrated marketing and sales into its software, followed by the launch of Siebel Sales Enterprise in 1995 (Business Insider, 2020), Omniture Web Analytics in 1996 (Crunchbase, Organisation - Omniture), and Salesforce SFA and then CRM in 1999 (Salesforce, 2025).
in the early to mid-2000s, when the popularisation of the Internet was swiftly followed by social media innovation, before the mobile phone, each of the smaller players in this pioneering set were eventually acquired by larger companies, and in their place emerged a small number of marketing software startups that have over time become large, successful companies in themselves, led by HubSpot in 2006.
HubSpot was founded by MIT MBA students, Brian Halligan and Dharmesh Shah, to address changing consumer needs in advertising, and now serving over 248,000 business customers around the world (ibid.). HubSpot launched its AI assistant, Breeze, comprised of a Copilot and Agent, with over 80 AI features embedded across the customer platform, on 18 September 2024 at their Fall INBOUND conference (HubSpot, 2024). Along with the other major marketing software players in Salesforce, Microsoft, SAP, Oracle, Adobe, and IBM, HubSpot use their decades of industry experience to continue to forge a path into the age of AI today.
State of the Art
Amongst this group, Salesforce and Microsoft compete closely to take the lead in the area of Sales Force Automation, the CRM, and staying ahead of technological developments, while Adobe strengthens its own positioning in the experience domain, SAP and Oracle sharpen their Sales Cloud offering with intelligent features, and HubSpot continues to develop tools and features for smaller business.
Salesforce launched Agentforce and Agentforce Atlas Reasoning Engine in September 2024 (Salesforce, 2024), and AgentExchange on 4 March 2025 (Salesforce, 2025b), which respectively allows organisations to build, customise, and deploy their own agents easily; autonomously analyses data, makes decisions, and completes tasks reliably and accurately (Salesforce, 2024); and provides a marketplace for developers to monetise their agentic AI components and for businesses to select and deploy any of these agents within their own work environment (Salesforce, 2025b).
Microsoft is also moving fast with incorporating AI into its software, including Dynamics 365, launching 10 autonomous agents for Dynamics Business Central 365 in 2024 (Microsoft, 2024), and on 5 March 2025 announcing two new agents - Sales and Sales Chat - and Microsoft AI Accelerator for Sales, to help businesses more easily and quickly transform their sales organisation with Microsoft Copilot and agents (Microsoft, 2025b).
In March 2023 Adobe introduced Adobe Sensei GenAI for Experience Cloud (Adobe, 2023), which aims to act as a “marketer’s copilot” (ibid.) to “deliver personalised experiences at scale” (ibid.) through integrating AI into Experience Cloud, with the promised benefits of transforming data into deep and actionable insights using advanced marketing measurements, predicting customer behaviour, generating and personalising content, making campaigns more meaningful, and automating digital workflows, resulting in greater overall return on marketing investment (Adobe, 2025).
Possibilities
Gaarlandt et. al (2025), writing for the Harvard Business Review on the impact of ongoing AI developments on marketing and retail, suggest that gen AI could “fundamentally transform the landscape, much like ecommerce before it.” McKinsey Digital (2024), the arm of the renowned consultancy that helps business with AI integration and technology modernisation, and MarTech (2025), a content producer within the portfolio of leading visibility management SaaS platform, Semrush, that focuses on the intersection of marketing and technology, make similar observations on how marketing practices will be comprehensively shaped by gen AI and AI agents in the near future.
McKinsey Digital (2024) describe that the value of AI agents stems from their ability to automate complex tasks comprised of highly variable inputs and outputs, which can be challenging for a business to address effectively, through three capabilities: managing multiplicity and adapting to dynamicity in workflows and processes which are not easily codified and easily broken in conventional automation; being directed by natural language rather than programming, so that even the most complex workflows can be encoded quickly and without technical expertise; and their ability to work with existing software tools and platforms to communicate across the digital ecosystem in carrying out tasks.
In marketing, they suggest this could enable advanced integration and coordination between the software tools, applications, and platforms involved in marketing campaign management; a conversational collaboration with an agent system to develop, test, and iterate marketing campaign ideas, as well as generating content, copy, and design, essentially automating tasks that would otherwise be tedious and time-consuming; and a digital marketing strategy agent to analyse data, surveys, and activity recorded in CRMs and market research platforms to craft schemes using multimodal foundational models; with each of these agents working together toward continuous improvement.
Summary
The marketing information system has evolved from the Rolodex through to today’s conversational AI interfaces that continually learn about and adapt to customers’ needs, preferences, and behaviours, and use that data to generate insights that can be applied by marketing teams in campaign strategy, planning, and implementation. Characteristic of the development of the marketing information system is that it seems to have been led not by problem-solving technologists, visionaries, or inventors, but by the consumer and their changing circumstances and expectations, with marketing teams closely following and anticipating these expectations in order to create the best solutions. As Kotler’s early framework made clear, the most effective marketing systems are those that allow brands to see, understand, and respond to their customers, and the brands that best integrate insight, resonance, and reach will be those that continue to win hearts, minds, and market share.
***This article has been edited on 21 February 2026 to reduce wordcount - improving readability, as well as to update information to reflect technological advancements since original publication in December 2024.
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