AI Transformation for Digital Marketing


It’s here. AI is a transformative force in the digital marketing landscape this year. AI adoption continues to surpass expectations, and businesses are increasingly leveraging its capabilities to drive efficiency and enhance their marketing strategies. 

In this article, we will explore the practical applications of AI in digital marketing and showcase how to capture its transformative impact. 

We will delve into: 

  1. How to use scaled platforms like Adobe, Salesforce, and Google to integrate AI seamlessly.
  2. How to use the single-point solutions that utilize large language models to develop middleware for specific use cases.
  3. How to implement the right measurement strategy to effectively test and evaluate AI applications.
  4. How skill sets will evolve to ensure a human element in a post-AI era.

At Hero Digital, we’ve embraced AI to deliver more value to our clients and safely build a competitive edge in the ever-evolving digital world. We invite you to use AI to transform your organization’s digital marketing initiatives 

Scaled Platforms for AI

Many of the platforms you’re using have embedded AI capabilities waiting to be unlocked. Let’s dig into some key examples. 

AI for Google Ads

AI  allows marketers to make data-driven decisions and optimize their strategies with precision. AI capabilities that come native in an advertising platform like Google Ads are an example of this that you likely have access to but maybe don’t fully understand. 

Google has been leaning into automation and real-time decisioning for a while now, but with the adoption of Performance Max and its impact.

“Advertisers who use Performance Max achieve on average over 18% more conversions at a similar cost per action.”


Not everyone loves the idea of Performance Max because of the lack of visibility. But you have to test the capability.

Here is a list of other AI capabilities in Google Ads out of the box:

  1. Smart Bidding
  2. Responsive Ads
  3. Automated Insights (often overlooked – they have become much more valuable)
  4. Predictive Analytics
  5. Audience Targeting (Similar Audiences)
  6. Ad Performance Optimization
  7. Fraud Detection
  8. Language Translation
AI for Personalization

Personalization has become a cornerstone of successful marketing, and AI plays a pivotal role in achieving it. By analyzing vast amounts of customer data, AI-powered tools help identify opportunities for automated decision-making and enable marketers to deliver personalized content and offers at scale. 

Platforms like Adobe are driving scale with personalization by integrating GenAI across their product suites to drive results. Adobe’s Firefly generative AI is used to create unique, compelling, and on-brand content that is needed for personalization, while Adobe Sensei GenAI activates that content across channels, with end-to-end measurement and insights provided by Customer Journey Analytics.  Adobe’s GenStudio revolutionizes content management with AI, streamlining workflows for marketers, optimizing the content supply chain, and delivering precise, engaging content to consumers

Salesforce has enhanced the SF Marketing Cloud with cutting-edge AI: from engagement scoring and content management to deep customer insights. These tools empower marketers to craft targeted, impactful messaging, driving solid business results

This level of AI-powered personalization has the potential to significantly improve customer engagement and drive measurable results. 

Single-point AI Solutions

While the benefits of AI in digital marketing are undeniable, we must address potential counterarguments. Many may wonder how they can utilize AI if they don’t have access to big, expensive platforms. 

The good news is that AI is becoming more accessible, with a range of affordable solutions available in the market. Getting started may require some initial small investment, but the long-term benefits outweigh the costs. Middleware single-point solution tools and products that utilize Large Language Models (LLMs)— a form of generative AI  that is able to process and generate human-like text based on vast amounts of data it has been trained on—are growing at a rapid pace. 

These are tools like:

  • Jasper
  • Narrato

These tools are among the various options available for businesses and individuals looking to harness the power of AI for content creation, each bringing a unique set of features to the table. Some are built by and for SEO (Narrato), and others excel at long-form content creation/revising (like Jasper).

Of course, ChatGPT does a lot of this work, although the UI of some of the other tools (especially Jasper) is so intuitive and predictive, that it really has a chance to accelerate productivity for content creators of all types.

Ethical considerations are another aspect that cannot be ignored in the AI-driven marketing landscape. As marketers, we have a responsibility to ensure ethical practices, transparency, and data privacy. We must strike a balance between leveraging AI’s capabilities and respecting consumer trust.

AI Application Measurement 

It’s crucial to have the right measurement strategy in place to effectively test and evaluate these AI applications. This means going beyond traditional KPIs in digital marketing and measuring both efficacy and efficiency. Can your teams and partners do more with less? How do you measure that? Also—how can we ensure we continue to monitor that our customers are beyond satisfied? They should feel delighted with an AI-driven experience, right?  

We must ensure that AI-powered tools enhance our marketing efforts and contribute to personalized customer experiences. 

Here is how we think about the different categories of a true AI Impact Measurement Framework:

1. Efficacy in Campaign Performance:

Conversion Rates: Track the increase in conversion rates for campaigns using AI-driven personalization versus those that don’t.

Customer Engagement: Measure engagement metrics, such as click-through rates and time spent on page, before and after implementing AI.

ROI of Marketing Spend: Calculate the return on investment by comparing the costs of AI-powered campaigns against the revenue they generate.

Lead Quality: Use lead scoring models to assess the quality of leads generated with the help of AI tools.

Attribution Modeling: Implement advanced AI-driven attribution models to understand how different touchpoints contribute to conversions.

2. Overall Business Impact:

Sales Growth: Monitor sales metrics to see if AI-driven insights and automation lead to an increase in sales.

Market Share: Look at the growth in market share as a result of more targeted and effective AI-powered marketing strategies.

Innovation Index: Create an index or score that reflects the level of innovation in marketing strategies due to AI implementation.

3. Efficiency in Team Operations:

Time Savings: Quantify the time saved on tasks that AI now automates, such as data analysis, report generation, or content curation.

Scale of Operations: Evaluate how AI tools have enabled the team to manage larger-scale campaigns without proportionally increasing resources.

Resource Allocation: Assess how AI has allowed for reallocating team members from repetitive tasks to more strategic initiatives.

Error Reduction: Monitor the decrease in human errors in data-driven tasks, like data entry or targeting, thanks to AI automation.

4. Improvement in Customer Experience:

Customer Satisfaction: Use surveys and sentiment analysis to gauge customer satisfaction with AI-enhanced interactions.

Personalization Success: Monitor metrics associated with personalized content or offers, such as increased uptake of personalized recommendations.

Customer Retention Rates: Track changes in customer retention and lifetime value, as AI can help predict and prevent churn.

5. Better (and faster) insights from data:

Data Utilization: Evaluate how AI is enhancing the use of data, leading to new insights and data-driven decisions.

Predictive Analytics: Measure the accuracy and impact of predictive analytics in forecasting trends and customer behaviors.

6. Qualitative Feedback:

Team Feedback: Gather feedback from the marketing team on how AI tools have impacted their day-to-day activities and job satisfaction.

Stakeholder Reviews: Regular reviews with stakeholders to discuss the perceived benefits and areas for improvement can provide qualitative insights.

I’m envisioning a dashboard, how about you? By systematically measuring these areas, digital marketing leaders can obtain a comprehensive understanding of AI’s impact on the efficacy and efficiency of their marketing efforts and team dynamics. It is also essential to regularly review these metrics and adjust strategies accordingly to ensure continuous improvement and alignment with overarching business goals.

Remember: AI’s impact on key metrics might not be instant. It’s a two-way street—the model learns from you as much as you learn from it. You might notice operational efficiencies before seeing a tangible business impact. That’s why zeroing in on crucial metrics and launching targeted pilots is vital. Test, adapt, and scale your way to success.

Evolving Skill Sets

In the rapidly evolving world of technology, particularly AI, you must adapt or risk being left behind. Despite the buzz around AI potentially ousting humans from jobs, especially in Digital Marketing, we’re convinced that the human touch will become even more crucial in a post-AI era—assuming we’re still marketing to humans, not AIs. 

This means our teams must sharpen and expand their skills:

Strategic Insight: While AI excels at churning out tactical solutions like a high-speed vehicle, direction is vital. We need team members who can navigate the broader business strategy, driving the AI-powered marketing vehicle toward our long-term goals.

Critical Eye: Efficiency through AI is a double-edged sword. It can streamline tasks, but there’s a danger of overreliance, leading to complacency and potential mishaps. These mishaps, potentially more damaging with AI, could tarnish our reputation and hinder further AI adoption.

Prompt Engineering Prowess: The essence of powerful AI lies in crafting sharp, effective prompts—akin to coding, but in natural language. Mastery of this skill will set the future’s leading digital marketers apart from the pack.

Deep Industry Know-how: As AI models grow more specialized, understanding your industry inside and out becomes crucial. The ability to ask pointed questions, tailor AI prompts precisely, and assess outputs for relevance and fit will be indispensable.

Flexibility: We’re only at the dawn of AI’s impact. As it evolves, so must we. Those who embrace change and adapt swiftly will flourish in the AI age.

In short, the rise of AI doesn’t signal the redundancy of human roles in Digital Marketing but rather a shift towards more strategic, thoughtful, and adaptable skill sets.

Embrace AI Transformation 

The practical applications of AI in digital marketing continue to evolve and shape the industry. By safely embracing AI-powered solutions, businesses can enhance their marketing strategies, drive efficiency, and deliver personalized experiences at scale. 

As we navigate the AI landscape, we encourage you to stay mindful of the costs and ethical considerations. Connect with our expert problem solvers to explore AI-powered solutions for your marketing needs and unleash the full potential of this transformative technology.

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