How AI is Changing Marketing: Must Know for Leaders

Picture a future where marketing is not just personalized, but hyper-personalized. A future where AI-powered predictive analytics predict customer needs, allowing real-time tailoring of messages – from automated content generation to hyper-targeted advertising. Well, this is no longer a futuristic concept, but a game-changing potential of AI in marketing.

In fact, a survey conducted in the US revealed 52% of marketing professionals using AI tools in marketing witnessed enhanced efficiency, speed, and data processing. This shows the power of AI, creating abundant opportunities for marketing teams to do more of what they already do best - understanding customers' needs, matching them to the right products and services, and influencing purchasing decisions.

5 golden rules of applying Gen AI in marketing

While AI tools accelerate, augment, and streamline the marketing strategies, here are a few rules that marketing leaders can follow to make the most of generative AI.

1. Prioritize the customer in every steps

Prioritizing customer experience is not just a noble goal – it's a proven business strategy that drives measurable results. McKinsey studies reveal that improving the customer experience can increase sales revenue by 2-7% and profitability by 1-2%, illustrating the direct financial impact of a customer-centric approach.

Hence, as a marketing leader, while integrating generative AI into your strategies, it's crucial to focus on ways the tech can enrich customer interaction and improve their experience, rather than solely focusing on cost-cutting or process efficiency.

You can view it as a generational opportunity to redefine ways to engage with audiences, foster deep connections, and drive profitability.

2. Go beyond creative application

To truly harness the full potential of AI in marketing, go beyond creative content generation like copy and imagery. Instead, use AI to optimize and scale end-to-end marketing, specifically:

• Data analysis: Analyze customer data and deliver highly personalized marketing messages.
• Internal marketing operations: Streamline internal operations by automating routine tasks (like data entry and report generation).
• Performance measurement: Analyze the effectiveness of campaigns in a more focused way with vast amounts of data.
• Testing & experimenting: Frequently test different marketing strategies and measure their impact in real-time.
• Insight extraction: Extract and use valuable insights from unstructured data (like social media posts, reviews, and mentions) to refine audience targeting.

Adopting such a holistic AI marketing approach helps deliver a consistent customer experience, encouraging them to stay loyal and repeat business.

Additionally, it fosters interdepartmental collaboration, ensuring alignment and efficiency – leading to improved decision-making and overall campaign performance.

3. Run quick wins and complex projects parallelly

Marketing teams can apply GenAI to attain smaller, low-risk quick wins while iteratively refining AI models and identifying potential challenges before moving on to more complex projects.

Meanwhile, tackling complex projects early can reveal the need for robust data infrastructures, AI platforms, and specialized talent to support future AI initiatives.

By pursuing both in parallel, your team can:

🤚Gain hands-on experience with various tools and techniques – from simple automation to advanced machine learning.

🚀Build confidence with early success from quick wins, encouraging further investments in AI.

🧠Gain valuable insights from complex projects and identify new opportunities for innovation.

Practical Tips:

• Start with smaller low-risk projects (automating email, generating social media content) to build confidence. Then invest in complex projects (personalized AI marketing, customer retention strategies, and sentiment analysis) to understand long-term strategic advantages.
• Ensure your data is clean, accurate, and up-to-date to get reliable AI outputs. After that, implement robust data privacy and security measures to protect sensitive customer information.
• Test different AI tools and techniques continuously to find the best fit for your marketing needs. Adapt and refine your approach as technology evolves.

4. Manage the highest priority use cases internally

While plenty of vendors like Google offer generative AI with general efficiency, in-house solutions are essential for addressing your unique challenges.

Here are some ways to ensure priority use cases stay in-house:

✅Avoid relying on generic AI tools for tasks that demand customization and innovation specific to your brand.

✅ Outsource repetitive tasks (like drafting emails and creating simple content) but keep business-critical tasks (such as customer acquisition and engagement) within your team to maintain control.

✅ Invest in custom solutions for areas that give your business a competitive edge, like personalized marketing campaigns.

✅ Integrate marketing AI with your long-term business objectives to enable greater flexibility and control over your marketing outcomes.

5. The CMO is perfectly suited to lead an AI driven change

As a CMO, you must balance protecting the brand and fostering innovation while leveraging AI to showcase marketing's strategic impact across the organization.

For that:

• Ensure Gen AI drives transformation while aligning with the brand's values and ethical standards.
• Work with legal teams to establish guidelines for intellectual property, data protection, and compliance to minimize risks.
• Develop systems to swiftly detect and rectify issues when the interaction between AI and customers doesn't go as planned.
• Embrace a culture that supports creativity and experimentation with AI, and ensure protection measures do not stifle AI-driven innovations.
• Use marketing as a proving ground for generative AI’s capabilities and utilize its strategic values for broader organizational benefits like product management and customer experience.

How to achieve success with AI in marketing: 5 use cases

From content creation, personalization, and data collection, here are five use cases where AI and GenAI shows maximum impact.

1. Data collection

To scale Gen AI successfully in the future, marketers can only partially rely on GenAI models. You'll have to focus on proprietary models that ensure data alignment and brand safety and embrace multi-model AI capable of handling diverse inputs and outputs.

These models can collect and process diverse data formats including text, images, videos, animation, and audio. Then convert complex inputs into machine-readable formats through techniques like image-to-text, video-to-text, and audio-to-text, making it possible to handle a wide range of data efficiently.

These AI models also help collect and analyze data tailored to specific use cases, such as customer profiles, product pricing, campaign performance, and consumer preferences.

Tips for Leaders: How to scale data collection

Develop and optimize proprietary AI models

● Partner with data science teams to fine-tune models using specific datasets such as brand guidelines, tone of voice, customer persona, and product data.

● Frequently update the model by integrating market learnings, ensuring to “unlearn” outdated information.

Prioritize data quality and management

● Establish disciplined processes for data cleansing, rationalization, taxonomy building, and comprehensive tagging of assets.

● Used structured and unstructured data to train models

● Fill data gaps using synthetic data to ensure a holistic dataset.

Focus on personalization and customer engagement

● Use AI-powered tools to analyze customer preferences and behavior to create tailored content recommendations.

2. Content creation

Marketers are leveraging AI to produce and automate content creation across socials, blogs, and email marketing – without losing quality.

In fact, among companies using gen AI for content creation, 58% of marketers said increased performance is the top benefit, highlighting its potential to enhance efficiencies and outcomes in content strategies.

The AI offers various advantages including:

• Brainstorming ideas offering creative suggestions and alternative perspectives.
• Drafting content that marketers can refine and personalize.
• Updating existing content by offering valuable insights and suggestions for improvement.
• Generating visuals to enhance storytelling and presentation.
• Generating highly personalized campaigns by analyzing vast data.

💡Take inspiration from Coca-Cola  

The legendary beverage maker collaborated with OpenAI, inviting creators to participate in its Create Real Magic Contest, where participants generated artwork using GPT-4 and DALL·E. The selected artist's creations were featured on Coca-Cola's digital billboards — an excellent example of user-generated content.  

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Best practices to leverage GenAI in content creation:

• Balance generative AI and human creativity. You can always utilize AI-generated content as a starting point but add your knowledge to ensure it adheres to your brand’s core principles and appeals to your target market.
• Use only licensed or original content to respect legal restrictions and avoid copyright infringement. Confirm ethical standards, obtain the required data usage consent, and be open and honest with your audience about using AI in content development.
• Keep evaluating the performance of AI-generated content by monitoring engagement metrics, conversion rates, and audience comments to spot areas for improvement.

👉Bonus: Compare 8 Best AI-powered Social Media Content Creation Tools

3. Hyper-personalization

Hyper-personalization is the new expectation of customers from brands. According to Deloitte, 80% of consumers purchase from companies that offer more personalized experiences. This is where AI in marketing can help you uplevel.

• It processes large datasets from multiple sources like social media, browsing history, and purchase patterns to uncover insights about customer preferences and create a comprehensive customer profile.
• It ensures marketing efforts are directed toward the right audience by refining audience segmentation and analyzing data at a granular level. Then, it helps predict their future actions, enabling proactive strategies.

3 Marketing elements to hyper-personalize

✅ Customer journeys: Use AI-driven funnel and flow analytics tools to gain insights into your customers’ behaviors across different touch points. These tools can help you visualize the entire customer journey from the first interaction to conversion, and spot drop-off points and optimize your strategies to guide them to the next step.

✅ Website/app browsing experience: Incorporate AI-powered chatbots that use NLP and ML to engage customers with personalized real-time conversation. These chatbots can understand customer intent and offer tailored product suggestions, answer queries, and provide support based on past interactions.

✅ Visual elements: Use AI to create variants of visual elements like CTA buttons, typography, ad placements and more. Then, use A/B testing to analyze their performance results in real time. This helps you identify what works best with your audience and refine your strategies accordingly.

Netflix uses A/B testing by randomly assigning users to different groups. It then compares key metrics like user engagement or content discovery, helping it to identify small yet impactful changes. This further enables Netflix to tweak the UI or improve content discovery enhancing the overall user experience. 

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4. Trust and governance

AI models rely heavily on high-quality and consistent data, often including sensitive customer information. However, if there’s no proper governance, there arises the risk of data inconsistency, compliance failures, and decision-making errors that hinder AI’s effectiveness.

Effective data governance maintains the quality and consistency of data used to train AI models and secures its accessibility to the right people, protecting it from unauthorized access and breaches.

Compliance with legal and prevent biased or discriminatory decisions, foster trust with customers, and drive better results.

Quick tips to achieve AI success in marketing

• Implement centralized and decentralized data access models in your organization based on your team structure to prevent the risk of data misuse.
• To protect data, adhere to local regulations like GDPR. You can also collaborate with vendors who already comply with the standards.
• Ensure alignment between data, marketing, and executive teams on the data collection strategy, government policies, and AI initiatives.
• Continuously refine your AI models and data governance practices based on feedback from stakeholders, and evolving business needs.
• Verify that your AI tools offer transparent data usage policies and compliance badges. For example, Sprinklr’s AI-powered marketing platform assures data privacy and protection to its customers and users. The Sprinklr platform is built with cyber security and data privacy in its design. Visit our Trust Center to get details on Sprinklr’s extensive security and privacy program including policies, procedures, and standards.

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5. Marketing operations

The core of contemporary marketing strategies in marketing operations was mostly concentrated on process management, technological integration, and performance measurement to guarantee the effectiveness and efficiency of marketing initiatives. But AI has given marketing ops a new level of scalability.

For instance, AI-powered journey orchestration helps MOps manage customer interaction across channels by prioritizing actions according to the in-the-moment needs of the customer or lead, leading to better engagement and retention.

It analyzes customer interactions and adjusts workflows dynamically, creating a feedback loop that improves processes like audience segmentation, content delivery, and channel optimization.

Moreover, AI enables operations teams to use advanced attribution tools to trace the customer journey and measure the effectiveness of marketing campaigns. This help in:

• Optimizing ad spend and performance by identifying best-performing channels.
• Improving customer engagement strategies with granular insights into behavior and sentiment.

To effectively integrate AI into your marketing operations.

1. Identify challenges AI can solve like generating content, analyzing datasets, and predicting customer churn. Then select the tools based on scalability, integration, user-friendliness, privacy, and security. 
2. Identify the bottleneck and resource gaps of existing workflow and remove overlapping tasks and duplicate tools. 
3. Invest in data management tools to maintain accurate, accessible, and well-organized data. 
4. Implement change management strategies to facilitate the adoption of new workflows and processes. Further, invest in training programs to equip your team with the necessary skills. 

Marketing AI tools that can solve business use cases

1. AI tool for audience research: Sprinklr

Sprinklr is a customer support management platform that leverages industry-leading AI and generative AI offers a comprehensive view of customer behavior, sentiment, and trends with 90% accuracy.

It helps capture customer feedback in real time and benchmark it against competitors, providing you with actionable recommendations.

📈Struggling to aggregate data from siloed sources? 

Sprinklr unifies data from over 30 channels, 400k+ media sources, and over 1 billion websites to unlock insights for better decision-making. Get real-time insights into customers, competitors, and market trends with outstanding precision with Sprinklr Insights. 

• Understand customers' pain points and sentiments. 
• Track your brand mentions, sentiments, and emerging trends. 
• Understand your competitors’ KPIs. 
• Save time and resources by automating social media reporting and insights generation. 

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 2. AI tool for visuals: Canva

Canva is a design platform for users to create, edit, and share high-quality visuals.

Its intuitive drag-and-drop interface offers a wide range of templates and tools for creating: Social media posts, logos and videos, thumbnails, presentations, and more.

It offers both free and premium features catering to individuals, businesses, teams, and nonprofits tailored to their specific needs.

3. AI tool for content creation: Jasper

Jasper is an advanced AI writing tool designed to help marketers generate engaging content at scale.

It offers various features, such as auto-correction, content generation, and style improvement, that make the writing process efficient.

Hence, it quickly turns your ideas into action, empowering your strategy.

4. AI tool for marketing automation: Zapier

Zapier is a web automation tool that connects various apps and services and creates a workflow called Zap, which automates repetitive workflows without having to code.

It automates actions like saving email attachments to cloud storage or sending notifications to teams.

It’s easy integration with various tools like Slack, Google Sheets, and others makes it a versatile option for different business needs.

Ready to harness AI for marketing?

Sprinklr’s solution for marketing teams is powered by AI and GenAI to create impactful campaigns, engage customer efficiency, and deliver outstanding brand experiences. It leverages AI-powered tools and a unified platform, helping businesses achieve 50% higher ROI while reducing operational costs.

How Sprinklr AI can help in marketing & advertising

1. End-to-end campaign orchestration 

• Listen: Track relevant conversations across 30+ data sources including websites, social media, media sources and more
• Engage: Deliver hyper-personalized content tailored to each target demographic, region, etc. for maximized engagement
• Amplify: Boost reach and visibility by combining paid and organic tactics, user generated content, and influencers on social media
• Serve: Deliver timely customer support on channels your audience prefers, fostering trust and loyalty
• Analyze: See performance, listening and benchmarking insights on one unified dashboard.

2.Granular customer and competitor insights

• Monitors social channels, new blogs, and forums to track user behavior trends and insights.
• Track KPIs, trends, and influencers while gaining insights into your audience's demographics and preferences.
• Assess your market standing, track competitors, and identify areas for improvement with battle cards.

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3. Timely crisis management  

• Track industry specific reputation metrics to detect anomalies early with AI-powered alerts.
• Use dashboards, visualizations, AI summaries, and sentiment analysis to pinpoint crisis causes and patterns.
• Streamline case management, optimize ads, and drive targeted engagement – all in one platform.

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Curious to see Sprinklr in action? Grab a free demo today!