It is undeniable that personalisation no longer acts as an option in today’s world of increasingly rapid digitisation. It is definitely a must-have. Consumers expect a brand to know them better and talk to them in their own voice.
They desire experiences that are tailored just for them, and the use of generative AI has enabled marketers to create new, powerful tools to deliver that type of personalization on a large scale. Generative AI is not merely a buzzword; it is generating identifiable value. For instance- as per a recent article from McKinsey, generative AI could enhance productivity in the marketing function by anywhere from 5 to 15 per cent of total marketing expenditure.
The blog will discuss the role of generative AI in marketing, as well as how to implement this use properly and what to look out for, all backed with real-world data and insights.
Why Generative AI in Marketing Matters?
A larger number of marketing teams have been embracing AI marketing tools. Salesforce’s 2024 survey stated that 51% are currently using generative AI, and another 22% are going to very soon, which adds up to nearly three-quarters. Some statistics show that by 2025, “86% of brands improved personalization thanks to AI.
Personalization Expectations
Customer expectation goes much beyond asking for a brand’s opinion. One source states that 71% of consumers expect brands to engage with them on a personal level, while 80% are inclined to purchase from a brand when their expectations are fulfilled. Moreover, revenue from e-commerce accounts for 31% directly related to AI-driven recommendation engines.
How to Use Generative AI for Personalised Marketing?
A stepwise practical framework for practically applying generative AI into consumer-specific marketing. Let’s discuss key use cases, workflows, technology considerations, and best practices so that you can run the best AI-driven campaigns for your business.
Step 1: Gather and Prepare Your Data
Generative AI will thrive, but only with good data peeking behind the curtains; here is how to toe the line:
- Gather Customer Data: Demographics, purchasing history, browsing behaviour, engagement metrics, customer support interactions.
- Segmentation and Enrichment: Create meaningful segments of the customer universe (e.g. high-value, repeat, at-risk) and enrich these with (e.g. behavioural scores, preferences).
These steps will help you choose the right AI adoption strategies.
Step 2: Define Personalization Objectives & Use Cases
Generative AI can help in different aspects of marketing, but having your goals set will assist in directing the efforts. Some common examples are:
- Personalized content creation: AI can generate email copy, social-media posts, landing page text, blog drafts, or ad copy with a focus on segments or individuals.
- Dynamic creative & imagery: AI can create images (video), adapting according to user persona, past behaviour, or triggered by a campaign.
- Recommendation engines: AI suggests matches for products, services, or content to users, depending on user behaviour and affinities.
Step 3: Choose and Integrate the Right Generative AI Tools
Choosing the right tools and platforms is key for personalization with AI. Use models that have been pre-trained versus those that have undergone fine-tuning: Use generative tools straight off the shelf, such as those for content or imagery, and then fine-tune them on your brand/data for a better fit.
Look for multi-modal capabilities where a platform can handle texts, images, videos, or combinations thereof give more flexibility for personalization. Integration within the marketing stack of the enterprise is also important. The AI tool must fit into the CRM and the marketing automation, and the content management systems, as well as the analytics, where the output can easily flow into campaigns and be tracked.
Step 4: Develop Personalized Workflows and Content
Once those three things are defined, what follows is a series of building blocks for workflows:
- Segmentation personalization: For example, customers may be segmented based on purchase frequency, with different email templates being tailored using AI according to their behaviour.
- One-on-one personalisations: AI can create hyper-personalised content (name, past purchases, and expected interests) and deploy that content to the customers at different times based on the importance given to that customer.
- Dynamic content variations: Multiple variations of the content (header, image, offer) would be generated and applied dynamically depending on the user profile or on user behaviour seen in real-time. AI can automate this whole generation.
Step 5: Measure, Learn and Scale
First, understand key metrics and track their progress. Improvements in conversion rates, increases in click-through rates, increases in average order value, increases in costs associated with customer acquisition, improvements in customer retention rates, and time freed up for the team. To understand, and measure key metrics, we recommend availing the generative AI services from any reputed organization such as Webuters.
Example: Marketing data indicates that AI solutions produce returns of about 300% for marketing teams and an improvement in conversion rates of about 37% with AI targeting. In this case, running even just one test campaign or segment would give you enough of a result to measure and optimize before moving on to other segments and channels.
Real-World Insights & Practical Examples
Some concrete findings and examples show the use of generative AI at present in personalized marketing.
- According to one survey of marketers, 71% stated that generative AI would eliminate busy work and allow marketers to focus on strategic tasks.
- Regarding personalisation, brands using AI personalisation recorded metrics such as real-time product suggestion conversion rates that were higher by 29%, bounce rates on personalised landing pages that were lower by 33%, and retention rates that were higher by 27% for customers who received personalised experiences.
Best Practices & Pitfalls to Avoid While Using Generative AI in Marketing
First, start small, iterate faster. Choose specific use cases (e.g., personalized email campaigns) rather than aiming to transform everything simultaneously. Use human and AI both together. Use AI for scale and speed but keep oversight with humans for brand voice, creative nuance, and ethical checks.
Generative AI in marketing automation can only be relied upon to some extent. If a human editor does not check everything AI generates, it stands a very real chance of being off-brand messaging; messages lacking empathy or subtlety; or worse, messages that contain some error/bias. Personalized marketing touches on sensitive data. Ensure alignment with regulations (GDPR, CCPA, etc.) so as not to breach customer trust.
Looking Ahead: The Future of Personalised Marketing with Generative AI
As generative AI continues to grow, exciting avenues for personalized marketing are opening up. One such trend is hyper-personalization at scale. Individual-profile-based communications, not only segment-based, but tailored offers, content, visuals, and experiences in real time.
Increasingly, generative AI will combine text, image, audio, and video personalisation, so a user might see an ad, hear a message, or view a visual very specifically tailored to them, all dynamically generated.
According to McKinsey, marketing & sales functions are among the top domains expected to gain value from generative AI–$463 billion annually from productivity gains in marketing alone.
Conclusion
Generative AI in marketing for personalization isn’t a futuristic concept. It is here, and already data demonstrates that it works. Brands prepared to invest in data, develop specific use cases, pick appropriate tools, and execute vigorously and with reasonable oversight will see tangible upsides in engagement, conversions, customer relationships, and cost efficiencies. So what are you waiting for? Reach out to Webuters, to know how you can use generative AI for your business.
FAQs on Generative AI in Marketing
- How does generative AI improve personalized marketing?
Generative AI helps marketers create highly personalized content—emails, ads, and product recommendations—based on customer behavior, interests, and preferences, improving engagement and conversions.
- What are some examples of generative AI tools used in marketing?
Popular tools include ChatGPT, Jasper AI, Midjourney, and Adobe Firefly. These tools assist in generating text, images, and videos tailored to specific audiences.
- Is generative AI safe to use for customer data personalization?
Yes, if implemented responsibly. Always ensure compliance with privacy regulations like GDPR and CCPA and use anonymized or consent-based customer data to maintain trust.
Loading...