Generative AI is a tool that can generate text and images in a broad array of styles and formats from simple text-based “prompts.” From creating a taco ad in the style of Salvador Dali to writing social copy for a new product launch, new generative AI tools can create sophisticated and personalized outputs quickly, pulling from a vast library of data about human language and aesthetic styles.
This makes marketing an arena where generative AI can drive massive transformation if implemented correctly. The ability to rapidly generate personalized, contextually relevant text and images offers the potential to achieve true personalization at scale for many marketing organizations. But the tools are not without their challenges and costs.
Is your organization ready to welcome generative AI as a creative partner in your next campaign? Here are five questions to consider first:
Each organization’s needs are different, hinging on its specific goals, budget, and planning horizon. Before you begin implementing generative AI, be sure you are crystal clear on what success looks like for your business. Is your goal to:
- Quickly scale more personalized experiences? Today’s customer wants an experience catered to their unique needs, and those needs are constantly evolving. AI tools can provide deeper consumer insights to inform and create scalable, highly personalized marketing campaigns.
- Stay ahead of the competition? AI can be a powerful tool to help identify and meet customer needs, find and target the right audiences, boost engagement, and more. Successful implementations can help organizations deepen brand loyalty and innovate to meet the future needs of your customer.
- Enhance productivity and reduce cost? Though there may always be an element of human oversight when using AI, these tools can help to automate repetitive tasks to drive efficiency and streamline processes so that people have more time and opportunity to do creative and strategic work.
- Win more customers? With more profound insights into customer preferences and behaviors at their fingertips, marketers can create experiences and content that engage the right customers at the right time in their journey.
Having a well-thought-out AI strategy that learns to adjust and interpret customer behaviors and desires in real-time will more likely be welcomed than rejected by your customers. To develop your AI strategy, consider these recommendations:
- Adjust to your audience. Personalization can provide powerful insights and allow for the development of relevant content for customers both on and off the website, but AI-driven advertising can also feel invasive. Make sure you understand where that line is for your target audience, and be prepared to track, measure, and adjust quickly if you notice negative feedback on your first efforts.
- Identify pockets where generative AI will be more accepted than others. Look for areas of your customer experience where the use of generative AI will more likely be accepted. Are your customers already accustomed to conversing with chatbots or other text-based components? This may be an area of existing trust that can be expanded on with AI.
- Give customers control. AI can provide more opportunities for organizations to hear directly from customers and use what they learn to drive increased engagement and loyalty. You can then use the data to build more effective and meaningful content to connect with your audience.
Use generative AI as a starting point for ideas instead of a final output for solutions. When tackling a challenging problem, AI can help creatives develop concepts to build on, but it shouldn’t replace creative jobs. Consider these recommendations:
- Use AI to develop creative ideas. Generative AI can be a catalyst for marketers as they brainstorm and visualize solutions to complex problems. When a situation seems too complex, a generative AI tool can serve as the first step to finding the right solution by compiling a wide variety of potential solutions to select from. Your creative team then plays the vital role of shaping and revising those outputs, providing guidance, quality control, and thoughtful prompt inputs to develop an effective overarching strategy.
- Identify innovative approaches to customer outreach. Using AI for customer modeling, targeting, and segmentation solutions helps to deliver highly qualified audiences for marketing activations. Additionally, generative AI can assist your team in developing new campaign outreach strategies. The bottom line is that generative AI can help, but real people are still needed to guide and validate the orchestration of its outputs into a strategic end-to-end solution.
- Include human judgment and empathy. AI’s ability to augment human creativity can spark new ways of working that blend the best of what machines do with what humans bring to the collaboration: judgment and empathy. Build processes so that humans stay in charge of decisions that require thoughtful judgment and emotional intelligence.
- Create twins and accelerators. In addition to helping iterate during the early stages of the creative process, generative AI can be used to create digital twins to simulate people and experiences; to develop personalized media in a variety of formats and resolutions; as an engineering accelerator for experience design and development; and as an efficiency tool across marketing operations functions.
Customers should be able to trust that the data they share will be used ethically and without bias by organizations and the AI algorithms they employ. By focusing on AI bias and emphasizing AI ethics, companies can help protect customer data—while building brand equity and customer trust. Deloitte’s Trustworthy AI Framework offers these guiding principles:
- Fair and impartial. Assess whether AI systems include internal and external checks to help enable equitable application across all participants and make a plan for how to implement those checks in a transparent and accessible way.
- Transparent and explainable. Help participants understand how their data can be used and how AI systems make decisions. Algorithms, attributes, and correlations should be open to inspection.
- Responsible and accountable. Put an organizational structure and policies in place that can help clearly determine who is responsible for the output of AI system decisions.
- Robust and reliable. Confirm that AI systems have the ability to learn from humans and other systems and produce consistent and reliable outputs.
- Respectful of privacy. Respect data privacy and avoid using AI to leverage customer data beyond its intended and stated use. Allow customers to opt in and out of sharing their data.
- Safe and secure. Protect AI systems from potential risks (including cyber risks) that may cause physical and digital harm.
Quantity of output does not equal quality of results. A successful implementation will need to carefully think through what KPIs will be your best signal of successful integration. Here are a few steps you can take to assess impact:
- Choose the right metrics to measure success. Identify key performance indicators to indicate success. This could be click-through rates, conversion rates, cost reduction and throughput increase, or any other relevant metric that aligns with business objectives and customer needs and expectations.
- Conduct A/B testing. Test different implementation versions to determine which types of content perform better. By using generative AI to create multiple different ad or email campaign versions, marketers can compare the results to determine which option performs better against a control.
- Monitor performance. Monitoring the performance of messaging and campaigns to measure their effectiveness is critical. To do so, marketers should track both individual campaigns and overall trends. Additionally, keep a close, human eye on what matters to the business and its customers to ensure the generative AI strategy is solving the right problems and generating the right responses over time.
Whatever your goals may be, implementing generative AI can have surprising impacts on many aspects of your organization. From delivering new operational efficiencies and helping your staff build new skillsets, to providing technology support or a new set of policy implementations, the opportunities are endless and you’ll need to have a clear and cohesive roadmap and change-management plan to ensure that your implementation is achieving its intended results.