This article is inspired by “How Generative AI Can Boost Consumer Marketing”, written by Lisa Harkness, Kelsey Robinson, Eli Stein and Winnie Wu on McKinsey & Company Growth, Marketing & Sales Insights blog.
In today’s interconnected and rapidly evolving global economy, marketers face the challenge of delivering personalized and impactful messages to their target audience. With the advent of generative Artificial Intelligence (AI), this challenge is being met head-on. Generative AI has the potential to revolutionize consumer marketing by enabling marketers to create highly personalized and engaging campaigns, automate processes, and analyze vast amounts of data to identify new opportunities.
According to a McKinsey report, generative AI can generate up to $4.4 trillion in annual productivity. This value can be unlocked by leveraging generative AI in critical sectors such as software engineering, sales and marketing, customer operations, and product R&D. In particular; marketing productivity could increase by up to 15% of total marketing spend, equivalent to approximately $463 billion per year.
By harnessing the power of generative AI, marketers can streamline their processes, automate interactions with other departments, and gain valuable insights from analyzing customer data. This enables them to deliver highly personalized marketing campaigns, improve customer engagement, and drive business growth.
Generative AI offers numerous benefits for marketers, including:
Generative AI allows marketers to deepen customer engagement through personalized interactions. Marketers can create content that resonates with each segment by analyzing customer segments and their interactions with various messages. For example, Michaels Stores used generative AI to personalize their SMS and email campaigns, resulting in a 41% increase in click-through rates for SMS and a 25% increase for email campaigns.
Generative AI enables marketers to analyze unstructured customer data, such as feedback and reviews, to gain insights into customer behaviour and preferences. For example, companies like Stitch Fix and Instacart use generative AI to interpret customer feedback, make product recommendations, and provide personalized experiences.
Generative AI can automate interactions with other departments, such as service, sales, product development, and legal reviews. This streamlines internal processes, reduces response times, and improves overall efficiency. For example, a direct-to-customer retailer saw an 80% decrease in time to first response and a four-minute reduction in average time to resolve a ticket using generative AI for process automation.
Generative AI can analyze competitor moves, gauge consumer sentiment, and test new product opportunities. Companies like Mattel, Kellogg’s, and L’Oreal use generative AI to generate product concept images, analyze recipes and comments, and identify potential innovation opportunities.
While off-the-shelf generative AI models provide quick returns, companies can differentiate by customizing them with their data and specific requirements. By adjusting prepackaged models with task-oriented data sets, companies can achieve exponential gains in personalization and customization. This allows for creating unique content and tailored marketing campaigns that give companies a competitive edge.
For example, a telecoms company in Europe used generative AI to personalize outreach messages for 150 distinct segments. The company achieved higher response rates and reduced deployment costs by training the AI engine on demographic, regional, and linguistic data. Similarly, a beverage company in Asia used generative AI to gain user insights and accelerate the product development process. Leveraging generative AI, the company created 30 high-fidelity beverage concepts in one day, significantly reducing the time and cost of traditional product development.
As generative AI continues to advance, marketers can anticipate a future where almost all marketing projects are enhanced by AI. From content generation to research and customer experiences, generative AI has the potential to transform the way marketers operate. However, ensuring the responsible use of generative AI is crucial, as well as safeguarding privacy, avoiding biases, and respecting copyright laws.
To prepare for this future, marketers should craft a North Star vision and roadmap aligned with their overall marketing objectives. This includes assembling a dedicated team, conducting low-complexity pilots, and gradually scaling up the use of generative AI. Prioritizing data security and compliance, appointing responsible leaders, and establishing governance protocols are also important to mitigate risks.
In conclusion, generative AI can revolutionize consumer marketing by enabling personalized campaigns, automating processes, and unlocking valuable insights. By embracing generative AI and customising it to their specific needs, marketers can enhance customer experiences, drive growth, and stay ahead in today’s competitive landscape.
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