How to Implement Generative AI in Your Marketing Strategy

Generative AI has been making waves in the news as a groundbreaking technology, particularly in the marketing sector. In fact, according to a recent survey, 29% of Gen Z, 28% of Gen X, and 27% of Millennials are already using generative AI tools in their office.

Marketing teams that can harness the power of generative AI can develop engaging content at scale and in half the time. However, implementing generative AI can be challenging, as the technology is still new and rapidly evolving.

If you are looking to create content at scale, develop new and innovative campaigns, or hyper-personalise your content, read on. In this article, we will delve into the essential steps you can take to successfully incorporate generative AI into your marketing strategies.

We've consulted with several generative AI experts who have shared their insights below. You can hear from these experts in person at the upcoming Generative AI for Marketing Summit 2024.Be sure to check out the schedule and register for the event to learn more about the impact of generative AI on marketing.

What are the benefits of generative AI on marketing strategies?

First of all, let's explore the benefits of generative AI in marketing strategies. We spoke to Janis Thomas, Managing Director of Look Fabulous Forever, about the most effective ways to use generative AI. Here's what she had to say:

“I think AI brings huge opportunities for marketers to be more creative. It is fantastic to inspire fresh ideas. Additionally, it is great at giving you alternative perspectives, or coming up with suggestions when you’re stuck. Lastly, it is brilliant from a visual creative perspective, particularly in ecommerce, being able to take a flat product shot and quickly turn it into an appealing lifestyle image."

“It’s brilliant as a jumping off point to get my creative juices flowing. For me, there’s nothing worse than staring at a blank screen and being stuck for inspiration. It’s surprising how often even suggestions that are completely wrong can challenge you to think about why they’re wrong, which leads to what would work better instead.”

Generative AI technology has extensive applications in a wide range of fields. In marketing, it's most commonly used for generating articles, images, video, and ideas. However, it can also be an excellent resource for streamlining administrative tasks, aiding in data analytics, and campaign creation.

Here are some examples of how generative AI can benefit marketers:

● Increased Content Generation: Generative AI can be used to create unique content at scale, such as articles, video, and image-based content.

● Cost Efficiency: Generative AI significantly reduces the number of hours employees spend on creating content and designing marketing campaigns, leading to increased productivity and efficiency.

● Fresh Output: One of the most impactful uses for generative AI is its ability to enhance creativity and foster original marketing ideas.

● Data Analytics: Marketing teams can use Generative AI to delve deep into data analysis and extract valuable insights into new trends, angles, and patterns.

● Customisability and Personalisation: Generative AI-based content can be tailored to specific audiences, offering highly personalised engagement.

● Time Efficiency: AI can create content or generate outputs at all hours of the day, unlike human employees.

● Democratisation: Time-consuming or technical skills, such as data analysis, video creation, image creation, can be made more accessible with generative AI technology.

Key steps to take for implementing generative AI in marketing strategy

According to a study by Gartner, 71% of Chief Marketing Officers (CMOs) do not have enough funding to implement their plans to the fullest. In today's market, where businesses are under pressure to create content, and engage with audiences using personalised messaging, generative AI appears to be the solution for marketing materials and increasing productivity. On how generative AI can support marketing strategies, David Granger, Content Director at Cinch said:

“I’ll be looking at how it can support marketing efforts, where it can make our campaigns and our teams more efficient and effective. The key for content teams will be to know when to use AI and when to use their creativity – and where to blend the two. As long as we retain our sense of innovation, and don’t solely rely on GenAI, it will make our lives easier and improve our output.”

Here are key considers you can take to effectively use generative AI in marketing strategies.

● Define your marketing goals: Integrating generative AI into your company's workflow can be a challenging undertaking, as with all major technology implementations. It is essential to understand your business challenges and how generative AI can provide solutions. Consider the target audience, the topics you want to cover, the tone and style of the content and other factors when deciding what types of content to create.

● Be open to experimentation: The capabilities of generative AI are growing every day, and it's essential to explore its full potential through experimentation instead of solely relying on it for common use cases. Marketing teams should encourage research and experimentation with small scale case uses for AI tools to deepen their understanding of the technology. This will help them identify and prioritise large scale use cases that can be enhanced with generative AI.

● Gather data: Gather all the necessary data you need, which can include audience and customer data, content data, market research and more to help train the model. Ensure that the data is diverse and representative, to help you generate engagement marketing materials.

● Select a model: The market has many generative AI tools, so it is important to research and choose the best one for your content needs, as each has its strengths. For example, ChatGPT generates human-like text, GPT-4 is multimodal and provides control over tone and style, DALL-E2 generates realistic images, Designs.ai offers graphic design solutions, and Copy.ai is designed for professional writers and streamlines content creation.

● Training generative AI to use data: This process includes feeding the model with data, enabling it to learn patterns and trends that are critical for content generation and formulating marketing strategies.

● Implement generative in campaigns: Once you have your generative AI model selected, you can use it in marketing campaigns that align with your objectives. Paul North, Head of AI at Big Group says

“AI should be implemented pretty much everywhere within marketing team workflows: admin, research, ideation, strategy, creation, measurement, reporting and so on. Team roles and structure should also change to place humans where they are most valuable, leaving the AIs to handle the rest.”

Incorporating generative AI into your marketing strategies: Tips for your team

What are some ways in which your teams can deploy generative AI in marketing strategies?

Martin Musiol, Generative AI Expert at GenerativeaI.net explains:

“While the full potential is still emerging, hyper-personalisation could be realised by generating client-specific content—both text and images. A robust framework that incorporates feedback would be necessary for continuous model improvement."

“Effective prompt engineering, context awareness, and the right toolset are key. For instance, Perplexity AI can be employed for effective web searches. ChatGPT and its ecosystem of plug-ins can further streamline activities like data analytics or vacation planning, with integrations like those offered by Kayak.”

Here are some additional avenues to consider:

● Personalised marketing: Creating content can be a time-consuming task, whether you're working on articles, social media posts, emails or visual content such as images and videos. Fortunately, generative AI has the potential to streamline the process by generating content that caters to specific audiences. If time is of the essence, you can adjust the output parameters of generative AI technology and easily create dynamic content tailored to various segments.

● Targeting and segmentation: With the help of generative AI, marketers can effectively segment and target their audiences. By analysing historical data to identify patterns and trends, new campaigns can be developed around these insights.

● Ideation: Generative AI can be a gold mind for generative creative ideas for marketing campaigns. By inputting marketing goals and target audience characteristics, AI can suggest templates or outlines to entire marketing strategies that are aligned with your business objectives. On using generative AI for ideation, David Granger adds:

“By ensuring it’s used in the right part of the production process and used to make ideation and production more efficient. Clear prompts and instructions will kickstart both the creative and the production process and – for that functional marketing content – will fit easily into processes.”

● Chatbots: If your organisation intends to deploy chatbots, or already has, consider using generative AI to gain a deeper understanding of customer needs. By doing so, you can provide more tailored solutions that accurately reflect customer requirements.

● Forecasting: Generative AI can be a valuable tool for boosting future performance in marketing strategies. It can help determine how content or marketing materials will perform with different audiences or content types.

● Repurposing content: If you already have a library of established content, you can breathe new life into them by using generative AI to repurpose it for new campaigns. For example, you can spin long blog posts into brief articles, transform articles into text for infographics, reformat content and create data visualisations from text data.

● Customer feedback: By using AI, organisations can gather valuable feedback directly from customers, which can be used to increase engagement and loyalty. The data obtained can then be utilised to create more effective and meaningful content that resonates with your audience.

● Templates: With the help of generative AI tools, creating marketing content can be quick and effortless. You can now generate a wide range of materials from scratch, by using a text-to-design template function that assists users in creating a vast array of marketing materials in seconds.

How to tackle challenges in implementing generative AI in marketing

To fully take advantage of generative AI, it's crucial that both customers and employees feel comfortable using it. One key aspect is adhering to ethical guidelines, such as safeguarding sensitive data. By doing so, we can ensure that the technology is used responsibly and effectively. This starts from the top as noted by Janis Thomas:

“It’s really important for senior leadership to use AI themselves and fully understand how their company both is and could use AI. It’s vital to involve everyone in the organisation to understand the scope of their roles and where they could be using AI and where they shouldn’t. If the governance framework isn’t practical or doesn’t have a complete understanding of the specifics of people’s roles, then they will ignore it or find ways around it. That’s a fast path to disaster.”

Here are more actions you can take to ensure that generative AI meets the expectations of your marketing teams.

● Choose the right metrics: When assessing the impact of generative AI on marketing, track engagement rates, conversion rates, and ROI. Engagement rates, such as click-through rates and social media interactions, indicate how well the AI-generated content resonates with audiences.

● Iteratively test and measure the performance of generative AI tools: To assess the effectiveness of generative AI technology, it's important to measure the quality and number of ideas generated, the time between idea generation and execution, and user satisfaction.

● A/B testing: One of the ways generative AI can benefit marketers is by creating multiple versions of marketing assets that can be tested through A/B testing. By testing these variations, marketers can determine which resonates the most with their target audience, and improve their campaigns through an iterative process.

● Maintain a strong ethics posture: Protecting both customer and company data is of the utmost importance. Be sure to take measures to prevent any misuse of sensitive data, such as using it as an input for generative AI. Mike Taylor, AI Expert at Prompt Engineering explains in more detail:

“The really important topics are model provenance, safety monitoring, and contribution disclosure. Many models are trained on questionable data, so it's important to research what your model was trained on, and whether you're comfortable with that in your organisation. You need to define what sort of outputs are brand safe, and not violating copyright or NSFW content. Automated and manual monitoring is difficult but essential to set up."

“Lastly, you need to define what will be disclosed to your audience, for example will you say in the blog post that it was partially AI generated? Do you tell your clients? What wording do you use here? How do you inform your users how their data is being used?”

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