How to Begin Using AI in Marketing

What is generative AI

Generative AI is the savvy marketer's new best friend. Generative AI, or GenAI, refers to artificial intelligence systems that can generate entirely new content, rather than just analyzing existing data. This content can take the form of text, images, audio, code, and more. Generative AI uses machine learning models that are trained on massive datasets to identify patterns and learn the underlying rules and logic. It can then leverage this training to produce original, human-like output when given a text prompt or other input data.

How Can AI Be Used for Marketing?

Generative AI is transforming marketing by automating and enhancing core tasks, enabling marketers to quickly create high-quality content and leverage actionable insights from unstructured data. The result? Marketers who use AI are able to make strategic decisions, and deliver higher quality work in a shorter amount of time. 

Content Creation: Generative AI allows marketers to create high-quality image and text content efficiently and at scale. AI tools can produce blog posts, social media updates, email campaigns, product descriptions, and visual content like images and videos. This assistance both saves time and ensures consistency in brand messaging.

Actionable Insights: AI excels at identifying patterns in large datasets and can assist marketers in pinpointing emerging trends, seasonal shifts, and customer sentiments. These insights enable marketers to make smarter, faster decisions, optimizing their strategies and improving ROI.

Most marketing professionals interact with generative AI through LLMs (large language models), which are primarily text-based, and diffusion models, which are primarily image-based. Let's quickly review these two types of models, and how marketing professionals can leverage them to produce higher-quality work more efficiently. 

What is an LLM

A large language model (LLM) is a type of artificial intelligence system that is trained on vast amounts of text data to understand and generate human-like language. LLMs use deep learning techniques, specifically transformer-based neural network architectures, to analyze and find patterns in the training data.

Some key characteristics of LLMs include:

Massive Scale: LLMs are exceptionally large neural networks with billions or even trillions of parameters. This allows them to ingest and learn from incredibly large datasets containing terabytes or petabytes of text from the internet and other sources.

Generalization: Once trained, LLMs can apply their learned knowledge to understand and generate text on virtually any topic, not just what they were explicitly trained on. This allows broad generalization.

Open-Ended Generation: LLMs do not simply retrieve trained responses, but leverage their understanding to dynamically generate relevant, contextual, and coherent language outputs based on the given inputs.

Few-Shot Learning: They can quickly adapt to new tasks like question-answering or summarization by being shown just a few examples, without having to fully retrain.

As LLMs grow even larger and more capable, they will underpin increasingly human-like artificial general intelligence (AGI).

Most Popular LLMs

While ChatGPT is currently the most recognizable LLM, there are plenty of AI models out there, each that excel in their own ways at different tasks. The following LLMs are a great starting point for someone to begin using AI.

ChatGPT (OpenAI)

Pros:

• Versatile AI for various marketing tasks, from copywriting to brainstorming
• User-friendly interface ideal for AI beginners in marketing
• Free version available for testing AI marketing applications

Cons:

• May produce outdated marketing information due to knowledge cutoff
• Requires careful prompting for marketing-specific outputs
• Potential for generating biased or inaccurate marketing content

Price:

• Free version available, or $20/month for ChatGPT Plus with more features

Bing Chat (Microsoft)

Pros:

• Integrates AI with real-time web search for up-to-date marketing insights
• Visual search capabilities useful for marketing trend analysis
• Free and accessible within the Bing search engine

Cons:

• Limited availability compared to other AI marketing tools
• May prioritize Microsoft products in marketing-related recommendations
• Less customizable for specific marketing needs

Price:

• Free to use with a Microsoft account

Claude (Anthropic)

Pros:

• Excels at long-form marketing content creation and analysis
• Strong ethical considerations beneficial for brand safety in marketing
• Capable of processing and analyzing lengthy marketing documents

Cons:

• May require more specific prompting for marketing tasks
• Limited integration with other marketing tools
• Less versatile for general marketing tasks compared to ChatGPT

Price:

• Free trials available on some platforms

Perplexity

Pros:

• Specializes in real-time information gathering for market research
• Provides citations, enhancing credibility of marketing insights
• User-friendly interface for quick marketing queries

Cons:

• May overwhelm users with information in complex marketing queries
• Limited content generation capabilities for marketing materials

Price:

• Free to use, with a paid Pro plan for additional features

Over time you may find yourself gravitating towards certain LLMs for certain tasks. Claude, for example, is a much more creative LLM than ChatGPT, while Perplexity's knowledge base is much more recent than both Claude and ChatGPT. There is no wrong place to start, so pick one and get started! 

What is a Diffusion Model 

A diffusion model is a type of artificial intelligence system trained on large datasets of images to generate new, high-quality images from text descriptions or other inputs. These models use a process inspired by thermodynamics, starting with random noise and gradually refining it into a coherent image.

Some key characteristics of diffusion models include:

Iterative Process: The model starts with random noise and iteratively refines it, removing noise in each step until a clear image emerges.

Text-to-Image Generation: Most diffusion models can create images based on text prompts, allowing for creative and specific image generation.

Style Transfer: They can apply artistic styles to existing images or generate images in specific artistic styles.

Image Editing: Many diffusion models can modify existing images, adding or removing elements based on text instructions.

High-Quality Output: These models can produce photorealistic images as well as highly creative and artistic visuals.

As diffusion models continue to improve, they're becoming increasingly important in fields like graphic design, digital art, and visual content creation.

Most Popular Diffusion Models

While DALL-E 2 gained significant attention, there are several powerful diffusion models available, each with unique strengths. Here are some of the most popular options for those looking to start with AI image generation:

Midjourney

Pros:

• Excels at creating artistic visuals
• Ideal for generating unique social media content and ad creatives
• Strong community support for marketing professionals learning AI tools

Cons:

• Steep learning curve for prompt engineering in marketing contexts
• Output style may not always align with conservative brand guidelines
• Subscription required for commercial use

Price:

• Subscription-based, starting at $10/month

DALL-E 2 (OpenAI)

Pros:

• Produces highly realistic images suitable for product mockups and marketing collateral
• Offers image editing features useful for brand asset creation and modification
• Integrates well with other OpenAI tools for comprehensive AI marketing solutions

Cons:

• Usage costs can add up quickly for large-scale marketing projects
• May struggle with specific brand logo or product accuracy in generated images
• Limited control over image details compared to traditional graphic design

Price:

• Credit-based system, with free credits upon signup

Stability.ai

Pros:

• Open-source nature allows for customization to specific marketing needs
• Can be run locally, ensuring data privacy for sensitive marketing materials
• Offers flexibility in creating diverse marketing visuals from product images to infographics

Cons:

• Requires technical expertise to set up and optimize for marketing use
• May produce inconsistent results without fine-tuning for brand-specific imagery
• Less user-friendly interface compared to other AI marketing tools

Price:

• Free for local use, paid options for cloud services

Adobe Firefly

Pros:

• Seamless integration with Adobe Creative Suite
• Designed with commercial use in mind, addressing copyright concerns for marketers
• Offers features like generative fill in Photoshop, enhancing workflow efficiency

Cons:

• Requires a costly Adobe Creative Cloud subscription
• Currently in beta, so features may be limited or subject to changes
• Generated content might have a recognizable "Adobe" style, potentially limiting uniqueness

Price:

• Included at no additional cost for Creative Cloud subscribers

Each of these models has its strengths, and the best choice depends on your specific needs. Midjourney is popular for artistic creations, DALL-E 2 for versatile and realistic images, and Stable Diffusion for those who want more control and customization. As with LLMs, there's no wrong place to start – choose one that interests you and begin exploring the world of AI-generated images!

AI for copywriting

Large Language Models (LLMs) like ChatGPT and Claude have revolutionized the copywriting process, offering marketers powerful tools to generate, refine, and optimize written content. Additionally, there are a plethora of AI tools popping up, made specifically for text-based marketing tasks. 

Copywriting Tasks to Outsource to AI Tools:

• Draft captions for social media posts
• Write blog posts
• Brainstorm headlines, taglines, names and jingles
• Optimize landing page copy
• Create outreach emails and responses
• Template customer service responses
• Rewrite existing documents
• Turn internal communication into external assets

Key Considerations:

Hallucinations and Fact-Checking. LLMs can sometimes generate false or inconsistent information, known as "hallucinations." Some AI tools guarantee to safeguard against hallucinations, which is something to keep in mind when comparing AI copywriting tools. If you are using an LLM like ChatGPT, always fact-check content, especially for:

• Statistics and numerical data
• Historical facts and dates
• Product specifications
• Company information

Providing Context and Data. To improve accuracy and relevance, provide the AI with:

• Brand guidelines and tone of voice documents
• Relevant market research or customer data
• Links to authoritative sources or company materials
• Specific product information or technical details

Example prompt

"I'm going to provide you with our brand guidelines and some market research. Please use this information to write a product description for our new eco-friendly pool floatie."

There are some very convenient AI tools that you can "train" on your brand guidelines and data, so that it retains knowledge and context. This creates a more efficient workflow, as it enables you to receive highly tailored outputs, without needing to provide the AI with extensive context for each request.

Prompting for Source-Based Content: To create content based on reputable sources,

1. Provide the sources upfront: "Using the following research papers [insert links], write a blog post about the most environmentally-friendly pool float materials."
2. Ask the AI to cite sources: "Write a summary of the latest trends in poolside recreation. Please cite reputable sources for each trend you mention."
3. Request a specific format with citations: "Create a whitepaper on foam versus inflatable pool floats. Format it with proper sections, including an introduction, main body, conclusion, and a reference list using APA style."

Best Practices:

• Use AI as a starting point or for ideation, then refine and personalize the content.
• Combine AI-generated content with human creativity and expertise.
• Always review and edit AI-generated copy for brand voice, accuracy, and style consistency.
• Use AI to generate multiple versions, then select and refine the best options.

Popular AI Tools for Copywriting

Copy.ai

Pros:

• User-friendly interface suitable for AI beginners
• Wide range of templates for different marketing copy needs
• Offers a free plan to test the service

Cons:

• Output quality can vary depending on input
• May lack depth for more complex copywriting tasks

Price:

• Limited free plans, or $59 a month

Writesonic

Pros:

• Focuses on SEO-optimized content
• Offers features like content rephrasing and expansion
• Competitive pricing with a free trial

Cons:

• Some users report inconsistent quality across different types of copy
• Learning curve for optimal use of all features

Price:

• Free trial, then tiers of plans starting at $19 a month

Jasper.ai

Pros:

• Specializes in marketing copy across various formats
• Offers templates for specific marketing tasks (e.g., product descriptions, ad copy)
• Integrates with other marketing tools

Cons:

• Higher pricing compared to some alternatives
• May require fine-tuning for brand voice consistency

Price:

• $49 a month

Remember, while AI is a powerful tool for copywriting, it should enhance rather than replace human creativity and expertise. The most effective approach combines AI efficiency with human insight and brand understanding.

AI for SEO (Search Engine Optimization)

Here's a fun fact, most people don't know: ChatGPT doesn't know keyword search volumes. We talk to a lot (a LOT!) of people who ask ChatGPT for keyword suggestions, and don't realize that the suggestions they are receiving are not connected to search volume data (i.e., they are hallucinations). However, Artificial Intelligence is transforming the landscape of Search Engine Optimization (SEO), and there are AI tools that will perform keyword research for you, among other SEO tasks. Here's how marketers can leverage AI for more effective SEO.

SEO Tasks to Perform with AI:

1. Perform keyword research
2. Get AI insights from keywords
3. Get AI insights from a SERP analysis
4. Plan a content strategy to rank
5. Generate search-optimized content

Key Considerations:

Keyword Research: What keyword data is most important for your needs? Consider what platforms you are trying to rank on (organic search, Youtube, paid search ads, Amazon, etc.), and choose an AI tool that is able to provide the data you care about such as

• Keyword volume
• Competition/difficulty
• MoM or YoY growth
• Estimated CPC

Insights and Strategy: While nearly any AI tool can create a blog post optimized for a keyword, look for AI marketing tools that go above & beyond by providing smart insights into your data. Artificial intelligence excels at finding patterns in large, unstructured datasets, and the strategic marketer should be leveraging these strengths. Look for AI SEO tools that provide:

• SERP analysis insights and takeaways
• Marketing strategies to promote your SEO content
• Audience insights to create content that resonates

Future-forward: This tool should anticipate and leverage how search behavior and search engines will evolve in the next 3-5 years, to set your business up for success in the long run. Key areas include:

• Trends in voice-assisted search on mobile and in-home, smart devices
• Question-based search queries
• AI-written search results such as Google's SGE (Search Generative Experience), and Perplexity Pages

Best Practices:

• Use artificial intelligence to mine for elusive high-volume, long-tail keywords that would otherwise be difficult to discover
• With any new AI tool, check for hallucinations and validate key data such as search volumes and estimated CPC 
• Use AI to identify search trends and opportunities, then create unique, valuable content around these insights.

Popular AI Tools for SEO:

Spok

Pros:

• Specializes in mining keyword data to discover new and highly relevant keywords
• Analyzes SERPs to return key takeaways and next steps for your content strategy
• Suggests integrated marketing strategies to promote your SEO content

Cons:

• Recently released from beta, can be rough around the edges
• Focuses on new content creation, rather than existing content optimization

Price:

• Starting at $59 per month

SurferSEO

Pros:

• Specialized in AI-driven on-page SEO optimization
• User-friendly content editor with real-time SEO suggestions
• SERP analyzer provides actionable insights for content creation

Cons:

• Limited keyword research capabilities compared to comprehensive SEO tools
• Primarily focused on content optimization, lacking in other SEO areas

Price:

• Starting at $219 per month

SEMrush

Pros:

• AI content generator integrated within a familiar SEO platform
• Leverages SEMrush's vast keyword and SERP data for content creation
• Provides SEO recommendations alongside content generation

Cons:

• AI content generator is a newer feature, may still be evolving
• Content generation feature may not be as advanced as dedicated AI writing tools

Price:

• Starting at $130 a month

Remember, while it is relatively easy for AI to generate mountains of content, it takes a truly savvy, strategic marketer to create content that converts. 90% of landing pages on the internet receive zero traffic. Avoid yelling into the void with an AI tool like Spok, that both helps you generate search-optimized content, and provides the strategic insights so you know with whom, when and where to implement your content.

AI for Brand and Design

Diffusion models are revolutionizing visual creativity in marketing, enabling rapid ideation, demonstration, and iteration across various visual tasks. These AI tools can help marketers quickly generate concepts for graphic design, video storyboarding, product photography, branding, mood boards, and more.

Design Tasks to Enhance with AI:

1. Graphic Design: Generate multiple design ideas for logos, posters, and social media graphics. Quickly explore various color schemes and layouts, or create custom illustrations and icons.
2. Video Storyboarding: Visualize scenes and shot compositions, generate concept art for characters or settings, and create visual representations of complex ideas or abstract concepts
3. Product Photography Concepts: Idete different product placement and styling options, explore various backgrounds and lighting scenarios, and generate mockups for product packaging designs
4. Branding Elements: Create mood boards for brand identity, generate ideas for brand mascots or characters, and explore various typography and color palette options
5. Ad Campaign Visuals: Quickly generate visual concepts for ad campaigns, create multiple variations of ad layouts, and visualize different emotional tones for campaigns

Key Considerations:

Prompt Engineering: Learn to craft effective prompts to get the desired visual outputs. For example, prompts can include:

• Camera angle and type
• Lighting angle and type
• Artistic or photographic style
• Aspect ratio

Style Consistency: You will quickly notice that diffusion models such as Midjourney and Dall-E struggle to replicate specific visual elements consistently across multiple images. This requires marketers to either use style transfer techniques to maintain brand consistency across AI-generated visuals, or select an AI tool with built-in features to help with this.

Copyright and Ownership: Be aware of the legal implications of using AI-generated images, especially for commercial purposes. Always check the specific license terms of the AI tool you're using. Some platforms, like Midjourney, offer commercial licenses, while others may restrict commercial use. However, in most cases, you don't own exclusive rights to AI-generated images. Tools like Adobe Firefly emphasize using only licensed content in their training data to mitigate this risk.

Iteration Process: Use AI as a starting point, then refine and customize the outputs. Remember that AI-generated visuals often include extra fingers, missing doorknobs, floating objects, and misrendered text. Almost all AI images need human refinement before professional use. 

Best Practices:

• Use AI to generate a wide range of initial concepts quickly, then select the most promising for further development.
• Use AI tools for concept generation, then work with designers for final, unique assets.
• Leverage AI for rapid prototyping and A/B testing of visual concepts.
• Use AI to explore unconventional ideas that might not have been considered otherwise.
• Always review AI-generated visuals for brand alignment and make necessary adjustments.

Popular AI Tools for Brand and Design:

Designs.ai

Pros:

• All-in-one platform for logo, video, social media, and website design
• AI-powered brand kit generation for consistent branding
• Suitable for users with minimal design experience

Cons:

• Limited advanced customization options compared to professional design software
• AI-generated designs may sometimes lack uniqueness

Price:

• Starts at $29/month (billed annually)

Canva's Magic Studio

Pros:

• Integrated within Canva's familiar, user-friendly interface
• Text-to-image generation feature
• Vast library of templates and stock assets

Cons:

• Generated designs may feel template-driven
• Limited to Canva's ecosystem
• May lack some advanced design capabilities

Price:

• Included in Canva Pro at $12.99/month per user (billed annually)

Dream Studio by Stability.ai

Pros:

• High-quality image generation capabilities
• Offers fine-tuning options for more control over output
• Allows for image-to-image transformations, supports inpainting and outpainting features

Cons:

• Limited built-in editing tools compared to full graphic design suites
• Potential legal uncertainties around copyright of AI-generated images

Price:

• Pay-as-you-go model starting at $10 for 1000 credits

Remember, while AI can significantly speed up the visual ideation process, the human eye for design, brand understanding, and creative intuition remain crucial. The most effective approach combines AI's rapid generation capabilities with human creativity and strategic thinking to produce visually compelling marketing materials.

AI for Market Research

Artificial Intelligence is transforming market research, enabling marketers to gather, analyze, and interpret vast amounts of data more efficiently than ever before. AI tools can help with everything from sentiment analysis to trend prediction, offering deeper insights and faster turnaround times.

Market Research Tasks to Enhance with AI:

1. Sentiment Analysis: Analyze social media posts, reviews, and customer feedback to gauge public opinion about brands or products.
2. Trend Forecasting: Identify emerging market trends by analyzing large datasets from various sources, including social media, news articles, and online searches.
3. Customer Segmentation: Use AI clustering algorithms to identify distinct customer groups based on behavior, preferences, and demographics.
4. Competitive Analysis: Monitor competitors' online presence, pricing strategies, and customer sentiment automatically.
5. Survey Design and Analysis: Generate more effective survey questions and analyze responses, including open-ended questions, at scale.
6. Predictive Analytics: Forecast future market conditions, consumer behavior, and sales trends based on historical data and current market indicators.

Key Considerations:

1. Data Quality: Ensure the AI tools are fed high-quality, relevant data to produce accurate insights.
2. Bias Mitigation: Be aware of potential biases in AI algorithms and take steps to mitigate them for fair and representative results.
3. Integration with Existing Systems: Consider how AI market research tools will integrate with your current data management and analysis systems.
4. Privacy and Compliance: Ensure all AI-driven market research complies with data protection regulations like GDPR or CCPA.
5. Interpretation Skills: While AI can process vast amounts of data, human expertise is crucial for interpreting results in the context of your business.

Best Practices:

• Regularly validate AI findings against real-world observations and expert knowledge.
• Use AI to identify unexpected patterns or correlations that human researchers might overlook.
• Invest in training for your team to effectively use and interpret AI-driven market research tools.

Popular AI Tools for Market Research:

Crayon

Pros:

• Real-time tracking of competitors' digital footprints
• Detailed market trend analysis to identify emerging trends
• Advanced sentiment analysis of customer reviews and social media

Cons:

• Requires a learning curve
• Volume of data can be overwhelming

Price:

• Custom pricing

Brand24

Pros:

• Monitor mentions in 108 different languages across the web
• Deep insights into consumer sentiment
• Instant notifications for brand mentions

Cons:

• The lower-tier plans have limitations on the number of keywords you can track, and real-time updates

Price:

• Starts at $69 per month (billed annually)

Browse.ai

Pros:

• Stay updated with real-time monitoring and notifications for any changes in tracked web data, helping you stay ahead of market trends
• Tailor the data extraction process to meet specific market research needs

Cons:

• May lack some advanced functionalities found in more comprehensive AI market research tools

Price:

• Limited free tier, with plans starting at $39 per month

AI is revolutionizing market research by enabling marketing professionals to efficiently gather, analyze, and interpret vast amounts of data. Tools like Crayon, Brand24, and Browse.ai facilitate sentiment analysis, trend forecasting, customer segmentation, competitive analysis, survey design, and predictive analytics, providing deeper insights and faster turnaround times. These tools, starting at affordable monthly rates, offer multilingual monitoring, real-time alerts, and comprehensive data analysis, making them suitable for businesses of all sizes. However, it's crucial to ensure data quality, mitigate biases, integrate with existing systems, and comply with data regulations while combining AI's capabilities with human expertise for optimal results.

AI for Analytics

Artificial intelligence is dramatically enhancing the field of analytics, allowing marketing professionals to delve deeper into data and uncover actionable insights with unprecedented speed and accuracy. AI-powered analytics tools can process vast amounts of data from various sources, enabling more informed decision-making and strategic planning.

How AI Enhances Analytics in Marketing

• Automated Data Collection: AI tools can automatically gather data from multiple sources such as social media, websites, CRM systems, and more, integrating them into a unified view. This saves time and ensures that no relevant data is overlooked.
• Data Cleaning and Preparation: AI algorithms can clean and preprocess data, removing duplicates, filling in missing values, and normalizing data formats. This enhances the quality and reliability of the data, making subsequent analysis more accurate.

• Forecasting: AI can analyze historical data to predict future trends and customer behaviors. For instance, predictive models can forecast sales, customer churn, and market trends, enabling proactive strategy adjustments.

• Efficiency: AI can help marketers create queries in SQL, customize javascript, write RegEx, and produce the HTML needed to quickly complete analytics tasks throughout various data platforms.

Key Considerations for Using AI in Analytics

1. Integration with Existing Systems: Choose AI analytics tools that can seamlessly integrate with your existing data management and business intelligence systems to streamline workflows.
2. Privacy and Compliance: Ensure that your use of AI complies with data protection regulations such as GDPR and CCPA. This includes managing data privacy and securing sensitive information.
3. Human Expertise: While AI can process and analyze data at scale, human expertise is crucial for interpreting the results and making strategic decisions. Combine AI insights with human judgment for the best outcomes.

Popular AI Tools for Analytics

Tableau

Pros:

• Real-time tracking of competitors' digital footprints
• Detailed market trend analysis to identify emerging trends
• Advanced sentiment analysis of customer reviews and social media

Cons:

• Requires a learning curve
• Volume of data can be overwhelming

Price:

• Custom pricing

Metabase

Pros:

• Monitor mentions in 108 different languages across the web
• Deep insights into consumer sentiment
• Instant notifications for brand mentions

Cons:

• The lower-tier plans have limitations on the number of keywords you can track, and real-time updates

Price:

• Starts at $69 per month (billed annually)

Power BI

Pros:

• Stay updated with real-time monitoring and notifications for any changes in tracked web data, helping you stay ahead of market trends
• Tailor the data extraction process to meet specific market research needs

Cons:

• May lack some advanced functionalities found in more comprehensive AI market research tools

Price:

• Limited free tier, with plans starting at $39 per month

AI-powered analytics tools are transforming the way marketing professionals handle data, offering deeper insights, faster analysis, and more accurate predictions. By integrating these tools into your marketing workflows, you can enhance your ability to make data-driven decisions, optimize campaigns, and achieve better results. Remember to focus on data quality, mitigate biases, ensure compliance, and combine AI insights with human expertise for the best outcomes.

How Will AI Change the Future of Marketing?

Artificial intelligence is set to revolutionize the future of marketing in numerous ways. Predictive analytics will become even more accurate, allowing marketers to anticipate customer needs and trends with unprecedented precision. AI will enable hyper-personalization at scale, tailoring marketing messages to individual preferences and behaviors in real-time. Additionally, AI-driven automation will streamline various marketing processes, from content creation to campaign management, significantly boosting efficiency and productivity.

However, it remains to be seen how these leaps forward will affect the marketing profession as a whole. Undoubtedly, some companies will no longer see the value in their copywriters or graphic designers, convinced they can outsource creative work to AI. We believe this would be a poorly-made decision, likely made by someone who doesn't use AI, understand copywriting, or graphic design. This is because time and time again, artificial intelligence has been used most effectively to enhance a worker's output, rather than replace the worker themselves. The businesses that adopt AI most successfully, then, will be the businesses that encourage (require!) the integration of AI into their teams' workflows, and will be delighted to find a dramatic  increase in productivity and quality as a result.

AI in Marketing: Crumbl Cookies

Crumbl Cookies, a rapidly growing cookie company, is one of our favorite examples of a business using AI in their marketing strategy. Using Hive3, an AI-powered platform, Crumbl sponsored a design challenge to reinvent their existing cookie ads, and received over 250 unique campaign ideas in just five days.

Key Takeaways:

• Innovative Ideation: AI facilitated access to a diverse talent pool, resulting in a high volume of fresh, innovative ideas.
• Reflective Process: Evaluating submissions allowed Crumbl to refine their creative brief, identifying truly important elements.
• Exploring New Directions: The variety of submissions enabled Crumbl to consider new visual directions previously unexplored.
• Foundational Assets: While none of the submissions were final assets, they were handed off to the design team for further iteration and development.

As Mai Pham, EVP of Growth at Crumbl, noted,

"The next frontier of marketing is generative AI."

Advice for Future-Forward Marketing Teams

Marketing teams looking to stay ahead should start integrating artificial intelligence into their workflows now. Begin by using AI tools for drafting copy, ideating visuals, and brainstorming campaigns. These tools can help generate high-quality content quickly and efficiently, allowing your team to focus on strategy and creative refinement. Embrace AI for data analysis to gain actionable insights and make smarter, faster decisions. And take a critical look at your own team's unique challenges, opportunities, and skill sets. Identify key areas where artificial intelligence could significantly improve or enhance workflows and outcomes. Then get to work! By integrating AI gradually starting today, your team can adapt to new technologies and optimize your marketing efforts.

‍

By embracing AI, marketers can unlock new levels of creativity, efficiency, and strategic insight, positioning their brands for success in the rapidly evolving digital landscape. So was this blog post written by AI, or a person? It was a collaborative effort 😉