Digital Marketing - Study Notes:
Personalization and segmentation using AI
Recent advances in AI technology have fundamentally changed how organizations approach audience segmentation with a view to developing highly personalized messages and experiences. Through machine learning algorithms, AI can automatically determine the most relevant variables for different customer groups, helping to tailor marketing messages or campaigns more precisely than traditional methods. For example, Spotify uses AI-driven personalization in its music recommendations. In this way, marketing becomes a blend of science and art.
L’Oreal uses AI to segment its audience and recommend relevant products. It captures data from users through surveys and website analytics to understand their age, skin type, and skin concerns. It then uses this data to create a variety of audience segments, each united by a distinct set of preferences. As a result, each visit to L’Oreal’s web properties can be tailored to the current visitor.
Integrating AI data insights with human intuition
AI can complete many tasks effectively, but it can’t do everything. This is why it is so important to take a balanced approach when using AI for data interpretation. This is why L’Oréal insists on human oversight of all its AI-driven digital marketing decisions.
While AI offers unparalleled data analysis capabilities, the integration of these insights with human intuition and contextual understanding creates a more holistic and effective strategy.
- AI can provide the ‘what’. What has happened? What is the data telling you? For example, the data might show that only 5% of female customers under the age of 30 in Australia buy from you more than once.
- Humans are often needed to understand the ‘why’ behind the data. Why did this happen? Why do people feel this way? For example, analyzing the data might reveal that the content that was targeted at female customers failed to resonate with them.
Predictive analytics for sales forecasting
AI algorithms analyze historical sales data, market trends, and external factors to predict future sales performance. Organizations can then make informed decisions about inventory levels, marketing strategies, and resource allocation based on accurate forecasts. This helps them to reduce waste and maximizing revenue.
Walmart uses predictive analytics to anticipate demand for products. This enables it to stock shelves appropriately and minimize out-of-stock situations.
Operational efficiency optimization
AI examines operational data to identify bottlenecks and inefficiencies in processes, such as manufacturing or supply chain management. Organizations can then streamline operations, reduce costs, and improve service delivery by implementing AI-driven recommendations.
General Electric uses AI to monitor industrial equipment and predict maintenance needs. This enhances operational efficiency and minimizes downtime.
Optimizing marketing spend with AI
One of the most pressing challenges for marketers is to justify and optimize their budget allocation. AI-driven analytics platforms can track the performance of every dollar spent across channels in real-time, enabling dynamic adjustments.
Skai’s AI platform for omnichannel marketing connects data from multiple channels to provide visibility into real-time performance. This empowers marketers to shift budget away from low-performing campaigns. For instance, if a Bing campaign is performing poorly, the budget can be moved to Amazon or Google where results may be better.
This transforms marketing spend into an investment optimized for the highest returns. And this, in turn, helps you to refine the strategic decision-making process.
Risk assessment and management
AI analyzes various risk factors, including market conditions, historical data, and financial indicators, to assess potential risks. Organizations can make more informed decisions regarding investments, lending, and compliance. This helps them to minimize their exposure to financial risks.
JPMorganChase uses AI-driven risk assessment models to evaluate creditworthiness. This allows it to make better lending decisions and reduce default rates.
Back to TopClark Boyd
Clark Boyd is CEO and founder of marketing simulations company Novela. He is also a digital strategy consultant, author, and trainer. Over the last 12 years, he has devised and implemented international marketing strategies for brands including American Express, Adidas, and General Motors.
Today, Clark works with business schools at the University of Cambridge, Imperial College London, and Columbia University to design and deliver their executive-education courses on data analytics and digital marketing.
Clark is a certified Google trainer and runs Google workshops across Europe and the Middle East. This year, he has delivered keynote speeches at leadership events in Latin America, Europe, and the US. You can find him on X (formerly Twitter), LinkedIn, and Slideshare. He writes regularly on Medium and you can subscribe to his email newsletter, hi, tech.
Cathal Melinn
Cathal Melinn is a well-known Digital Marketing Director, commercial analyst, and eommerce specialist with over 15 years’ experience.
Cathal is a respected international conference speaker, course lecturer, and digital trainer. He specializes in driving complete understanding from students across a number of digital marketing disciplines including: paid and organic search (PPC and SEO), analytics, strategy and planning, social media, reporting, and optimization. Cathal works with digital professionals in over 80 countries and teaches at all levels of experience from beginner to advanced.
Alongside his training and course work, Cathal runs his own digital marketing agency and is considered an analytics and revenue-generating guru - at enterprise level. He has extensive local and international experience working with top B2B and B2C brands across multiple industries.
Over his career, Cathal has worked client-side too, with digital marketing agencies and media owners, for brands including HSBC, Amazon, Apple, Red Bull, Dell, Vodafone, Compare the Market, Aer Lingus, and Expedia.
He can be reached on LinkedIn here.
