Marketers are no strangers to the power of AI. Artificial intelligence, especially AI-powered writing support, has assisted marketing workflows for over a decade, helping marketers perform common writing tasks and check their communication for accuracy and clarity.
However, recent developments in generative AI have ushered in a new era of these tools becoming more prominent in the workplace. A Forrester study commissioned by Grammarly shows that 70% of respondents use generative AI for most or all of their writing and editing at work. But that’s not the only way marketers can use AI to work smarter and create more effective marketing campaigns.
From market research to content generation, copywriting, and campaign analytics, secure, responsible AI is the modern marketer’s essential digital marketing partner. Read on for a step-by-step guide to leveraging AI technology to strengthen your marketing campaigns.
What is a marketing campaign?
A marketing campaign is a coordinated series of actions to promote a product or service. AI enhances campaigns by analyzing data for personalized targeting, predicting trends, and optimizing strategies and workflows, leading to more effective and efficient marketing efforts.
Plan an AI-driven marketing campaign in 7 steps
1 Set campaign goals with AI insights.
AI plays a crucial role in market analysis and setting campaign objectives by providing data-driven insights and predictions. With predictive analytics, marketers can set goals for sales, conversions, and ROI based on historical data and future predictions. AI-driven customer segmentation enables targeted campaigns, while sentiment analysis informs objectives related to customer satisfaction and brand perception.
AI-powered tools like Google Analytics, Adobe Analytics, and Salesforce Einstein help marketers understand website performance, consumer behavior, and customer data. For instance, you could use Google Analytics to identify underperforming web pages and aim to increase traffic or conversion rate by 20% in a quarter. Salesforce’s AI can help marketers analyze customer interaction data, predict churn risk, and implement targeted engagement strategies for high-risk segments.
2 Identify your target audiences with machine learning.
AI tools can help you define highly specific target audiences by analyzing large datasets to identify patterns, behaviors, and preferences. Tools like Adobe Analytics and Salesforce Einstein use advanced machine learning algorithms to sift through customer interaction data, social media engagement, purchase histories, and demographic information to create detailed audience segments.
Adobe Analytics leverages AI to track and analyze user behavior across websites and apps, enabling marketers to segment audiences based on online activities, content preferences, and engagement levels. This can lead to segments such as “Highly Engaged Website Visitors” or “Frequent Mobile App Users,” each with distinct characteristics and behaviors that inform tailored marketing approaches. Salesforce Einstein further integrates customer relationship management (CRM) data with AI, creating segments like “At-Risk Customers” based on predictive analytics related to customer satisfaction and churn risk.
A retailer might use Salesforce Einstein to identify a segment of “High-Value Repeat Customers” who make frequent purchases. Adobe Analytics could help an online publisher discover a segment of “Engaged Readers” who frequently consume content on specific topics and engage with it through comments and shares. These precise target audiences allow marketers to create more impactful content and campaigns that speak directly to a highly targeted group of people or customers.
3 Leverage AI to generate audience-centric content.
Armed with more specific target audiences, marketers can create campaign content that is more likely to resonate, especially since generative AI thrives off specific prompts. For example, let’s say a fashion retailer defined a target audience of consumers ages 25–40 who have shown interest in eco-friendly fashion trends through their browsing habits. The marketer could use AI-powered writing assistance, like Grammarly, to generate ideas for an email series highlighting the brand’s commitment to sustainability, stories behind its ethically sourced materials, and testimonials from customers who share the company’s passion for the environment.
Current generative AI technology works best for specific writing tasks, like subject lines, taglines, headlines, descriptions, and blog posts, especially when armed with specific product marketing information. Quickly turn value propositions into options for customer-facing taglines, or transform dense product messaging documents into creative briefs or first drafts of website copy, blog posts, or social media captions. It helps to include details like word count in your prompt. You can even add voice and tone guidance so the output sounds on-brand. Writing for websites? Add target search keywords to your prompt to make your content more SEO-friendly.
Content revisions are also easier thanks to Grammarly’s strategic, real-time writing feedback that considers the target audience, brand voice and tone, grammar correction, word choice, and more. Use AI writing assistance to revise underperforming web content or adapt copy for various channels, formats, and audiences.
AI-powered design tools like Adobe Creative Cloud Express and Canva allow marketers to generate graphics from text input. Thanks to AI-powered design interfaces, marketers can become powerful content creators for small business owners and agencies with little formal design experience. These graphics can also strengthen creative briefs for enterprise operations and ease collaboration with professional designers by creating richer first drafts, proofs of concept, or several creative options in a fraction of the time.
4 Personalize and customize the campaign.
If you’ve ever wondered how Netflix knows exactly what you should watch next, how Instagram predicts your next ad, or how Spotify knows your music tastes better than you do, it’s all about AI-driven personalization.
AI-driven personalization tools are pivotal in tailoring advertising messages to individual preferences, behaviors, and demographics. These tools analyze vast datasets to understand customer profiles, enabling hyper-personalized content. For instance, an e-commerce platform could use an AI-powered tool like Dynamic Yield to customize product recommendations based on a user’s browsing history, purchase behavior, and preferences. If the AI detects a customer frequently exploring running shoes and outdoor gear, the platform could deliver personalized ads featuring the latest running shoe releases, along with complementary products like moisture-wicking apparel and accessories.
Such personalization extends beyond product recommendations. Chatbots, powered by AI, can engage users in real-time conversations to understand their needs and preferences. A travel agency could use conversational AI, like Intercom, to interact with website visitors. If the AI identifies a user searching for family-friendly vacation destinations, the chatbot could provide personalized recommendations, share travel tips for families, and offer exclusive discounts on kid-friendly accommodations and activities. By leveraging AI-driven personalization tools, businesses can enhance user experiences, increase engagement, and ultimately improve the effectiveness of their advertising campaigns.
5 Use AI to optimize the budget, execute the campaign, and monitor and adjust in real time.
AI can revolutionize budget allocation across different advertising platforms by analyzing real-time performance data, market trends, and consumer behavior. Tools like Adobe Advertising Cloud use machine learning algorithms to identify which platforms and campaign strategies yield the highest ROI, adjusting budget distribution dynamically to favor the most effective channels. For instance, if AI analysis reveals that social media ads generate more leads than search engine marketing for a particular product launch, the system can automatically redirect more of the budget toward social media. This ensures that the marketing budget is always optimized for maximum impact, reducing waste on underperforming channels and reallocating resources to the most effective ones.
Read more: Guide to generative AI tools
6 Measure and report on campaign performance.
AI-driven analytics go beyond traditional metrics to offer deeper, more nuanced insights into campaign performance, enabling marketers to understand what happened, why it happened, and how to predict future trends. AI tools can sift through massive datasets—including social media interactions, website engagement metrics, customer feedback, and sales data—to identify patterns, trends, and correlations that might be invisible to the human eye. This level of analysis can reveal the underlying factors driving campaign success or failure, such as subtle shifts in consumer behavior, emerging market trends, or the impact of external events on audience engagement. Moreover, AI-driven sentiment analysis can gauge the emotional tone of customer feedback and social media mentions, offering insights into consumer perceptions and brand sentiment critical for adjusting campaign strategies and messaging.
Marketers can use AI-powered tools to measure campaign performance and evaluate ROI. With its advanced machine learning features, Google Analytics is indispensable for tracking website traffic, user behavior, and conversion metrics, offering a granular view of how digital campaigns drive online engagement. Adobe Analytics provides deep insights into customer journeys across digital touchpoints, enabling marketers to understand the paths that lead to conversion and identify opportunities for optimization.
For a comprehensive view that includes sales data and customer interactions across channels, Salesforce Einstein Analytics offers AI-powered insights that can help marketers measure the impact of their campaigns on revenue and customer retention. With built-in AI and analytics capabilities, HubSpot’s marketing hub is another powerful tool for tracking campaign performance, with detailed reporting features that allow marketers to evaluate the effectiveness of their content, email marketing, and inbound marketing strategies.
7 Adhere to brand values with responsible AI advertising.
Ethical AI in advertising is more important than ever now that AI is used in so many aspects of marketing. Businesses should be transparent about their use of AI and how it helps them create mutually beneficial relationships with their customers, employees, and partners. Using trusted, secure AI that respects your—and your customers’—data is critical for business success. Respecting original work by citing sources and avoiding generative AI that was trained using unlawfully acquired content will not only keep your company out of legal trouble but will trail-blaze the use of AI in a way that amplifies creativity and integrity.
Read more: Grammarly’s approach to responsible AI
Embracing AI in advertising campaigns holds immense potential for businesses seeking innovative and successful marketing strategies. AI technologies—including machine learning, data analytics, and generative content—enable marketers to analyze vast datasets, identify consumer trends, and produce and personalize content at scale. By automating repetitive tasks and optimizing ad placements in real time, AI enhances efficiency, allowing marketers to focus on strategic, creative initiatives. Moreover, AI-driven insights facilitate data-driven decision-making, enabling businesses to stay agile and adapt quickly to changing market dynamics.
