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The Basics of Crafting an Effective AI Marketing Strategy

The Basics of Crafting an Effective AI Marketing Strategy

This may sound nerdy, but hear me out: using AI to create a marketing strategy is exciting. Think about how you'd explain this to your past self. We're having the robots do the hard work so we can focus on other things? 

Sign me up.

Interestingly enough, marketing stands to reap the most significant rewards from AI. Marketing's fundamental tasks involve:

  • Understanding customer needs.
  • Aligning them with products and services.
  • Persuading individuals to make purchases—all areas where AI can make a transformative impact.

To harness AI's potential, we first need to understand the current AI landscape when it comes to applications in marketing. Read on to start your journey into the wonderful world of AI.

The Current AI Landscape

In marketing, AI is used to handle several jobs. It can simplify complex tasks, from taking specific, well-defined functions like digital ad placement (programmatic buying) to enhancing prediction accuracy, such as sales forecasts. It can even help in areas such as customer service. 

Some examples of what AI can do are: 

  • Chatbots for lead development, customer support, and cross-selling or upselling.
  • Inbound call analysis and routing.
  • Real-time geolocation data for personalized product or service offers.
  • Programmatic digital ad buying to serve ads instantaneously to users.
  • Customer service bots capable of escalating issues and suggesting responses.
  • Post-sale support through AI-enabled service agents.

To put it simply, AI comes in handy.

The Framework

Marketing AI can be classified based on two key dimensions: the level of intelligence it exhibits and whether it operates as a stand-alone entity or integrates into a broader platform. While certain technologies like chatbots or recommendation engines may traverse multiple categories, their classification hinges on their specific implementation within an application.

Intelligence Levels

Not all AI programs are the same. We could get into the details, but that gets complicated. Instead, here's a brief overview.

Task Automation

These applications execute repetitive, structured tasks with limited intelligence, following predefined rules or sequences based on input. Examples include systems sending welcome emails to new customers or basic chatbots guiding users through decision trees.

Machine Learning

These algorithms, trained on extensive data, make more complex predictions and decisions. They can recognize images, analyze text, segment customers, and anticipate responses to initiatives like promotions. Machine learning powers programmatic ad buying, e-commerce recommendation engines, and sales propensity models.

Integration Levels

Levels of intelligence aren't the only thing that we have to keep in mind. 

Stand-Alone Applications

These distinct, isolated AI programs require users to access them separately from primary channels. Users, be they customers or employees, must take an extra step to engage with AI.

Integrated Applications

Embedded within existing systems, these AI applications are less conspicuous to users. They operate within customers, marketers, and sales teams' primary channels.

Four Categories of Marketing AI

Different kinds of marketing require different types of AI programs.

Less advanced, stand-alone AI

This category includes stand-alone task automation apps, such as basic customer service chatbots or email automation systems.

Less advanced, integrated AI

These encompass integrated task automation apps like inbound customer call routing and CRM-linked marketing automation systems.

More advanced, stand-alone AI

This category includes stand-alone machine-learning apps like Olay's Skin Advisor, Behr's color-discovery app, and Vee24's chatbot.

More advanced, integrated AI

Integrated machine-learning apps like predictive sales-led scoring, CRM-based sales coaching, e-commerce product recommendations, and programmatic digital ad buying are grouped here.

A Stepwise Approach

While integrated machine-learning applications hold the most significant potential value, beginning with more straightforward, rule-based task-automation applications is advisable for companies new to AI. Organizations can transition from task automation to machine learning as they acquire AI proficiency and accumulate data. 

For instance, Stitch Fix employs machine learning to curate clothing offers based on customer preferences, improving effectiveness through customer interaction data.

Firms should progressively shift toward integrating AI within existing marketing systems, moving beyond stand-alone applications. This shift aligns with the direction many companies are taking, with 74% of global AI executives in a 2020 Deloitte survey anticipating AI integration into all enterprise applications within three years.

Embracing Automation

As organizations grow proficient with AI, they increasingly automate decisions, especially for high-speed, repetitive tasks like programmatic ad buying. Enhanced automation leads to higher returns from marketing AI.

Challenges and Risks

Implementing AI, even for basic applications, may pose configuration challenges. Stand-alone task automation AI requires suitable AI expertise to customize specific workflows. Human-AI integration necessitates careful planning to ensure AI enhances rather than irritates customer interactions. 

As AI becomes more integrated, complexities may arise, particularly when incorporating third-party platforms. Companies must also address privacy, security, and data ownership concerns to maintain customer trust.

AI holds immense promise for marketing, yet CMOs must acknowledge its current limitations. AI can handle specific tasks but cannot replace an entire marketing function. Nevertheless, it already delivers substantial benefits and is indispensable in certain marketing activities, with its capabilities continuously evolving. 

Building AI capabilities and addressing potential risks should be a long-term focus for marketing and supporting departments like IT. They're a great tool to have when you're crafting an effective marketing strategy. So go forth! Harness the power of the robots, and get ready to elevate your marketing to the next level.

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