AI is transforming the way brands approach and execute marketing activities. Starting with the creative process, which can be democratized to allow consumers to produce their own personalized collateral: for example, at this year’s French Open, fans could pick a past memory of Rafael Nadal, and type a text prompt in a simple generative AI interface to generate a poster in a matter of seconds.
Generate Your #RafaForever Artwork
Gimmicks apart, the technology can bring immense value to sales and marketing:
AI is believed to be one of four areas that together will garner 75 percent of the US $2.6 trillion to US $4.4 trillion annual value creation expected from generative AI.
Broadly speaking, that value will manifest as higher marketing efficiency, more effective engagement, and accelerated business growth.
Higher Marketing Efficiency
AI can save cost, time, and effort by automating scores of laborious tasks, from media buying to content creation.
By 2025, 30 percent of marketing messages sent out by large companies will be AI-generated.
AI tools can also be trained to build creatives in conformance with brand guidelines, including color, font, and tone of voice. Using AI for conceptualizing and generating content can free up five to ten percent of marketing bandwidth. AI can also boost efficiency by analyzing various performance data and triggering an appropriate response in real-time. Together, the outputs of AI – content & creatives, data-driven recommendations, and performance insights – can optimize marketing campaigns to yield solid double-digit cost savings.
Effective Engagement
Marketers have talked up hyper-personalization for years. But it is only now, with the advances in AI and generative AI (GenAI) in particular, that they can put it into practice. The latest AI solutions can understand customer preferences and behavior, and speaking in the customer’s language, offer relevant recommendations to create highly personalized, memorable experiences that engage more effectively on every channel. For example, clients have leveraged our AI-amplified marketing suite to increase the number of repeat buyers by as much as 50 percent.
By providing real-time visibility into promotions, AI enables brand marketers to take informed, timely decisions. It also provides granular information – for example, what worked or didn’t in a particular campaign – that marketers can act on to make their marketing strategies more effective in the future. Other effectiveness-building AI use cases favored by marketers include ad targeting, optimizing email send-times, and calculating conversion likelihood.
Accelerated Business Growth
AI provides customer insights that sales teams can use to identify the rights leads, as well as cross-selling and upselling opportunities to increase revenue per customer. Other analytical insights help to enhance channel conversion, demand capture, and repeat purchasing rates. Right from determining the pricing strategy for a new launch to designing market-leading loyalty programs, marketers can capitalize on the insights of AI to grow the business faster.
At the same time, sales executives, who could discover new opportunities only by spending long months in the market, can accelerate the journey to new revenue by using generative AI for picking up cues from client conversations and immediately suggesting products meeting their needs.
A payment processing firm and some e-commerce platforms have integrated a chatbot and virtual assistant in their solutions to offer online shoppers curated product recommendations and targeted advice.
AI is data
Brand marketers have barely scratched the surface of AI potential. For companies that get it right – all of it right – the rewards are stupendous. But the opposite is equally true; thoughtless implementation, especially of gen AI, can lead to chaos, even disaster. The first prerequisite for success is a robust (structured and unstructured) data foundation, since clearly, the output of an algorithm is only as good as the data it is trained on. Apart from being clean, accurate, and unbiased, the data needs to be ready for AI integration.
Here are some ways that marketers can make their data absolutely AI-ready:
- Add layers of context: Hygienic data will lead to acceptable algorithmic outcomes, but superior outcomes result when there is context. Take the earlier example of generating creatives with gen AI; information additional to brand guidelines, such as the content attributes sought by different roles and personas – simple & straightforward, or original & attention-grabbing – can reduce the need for iteration and produce exactly the kind of content the user is looking for.
- Down the silos: Less is more when it comes to provisioning AI solutions. If there are multiple disparate solutions working in isolation with independent datasets, each tool could end up using different data on the same customer, resulting in incoherent, contradictory outcomes. A “single source of truth” data fabric, and a unified AI solution suite, is essential for successful AI integration.
- Use responsibly: Marketers must use data and AI responsibly to protect their customers’ and their own interests. Ensuring data privacy, security, and confidentiality is paramount. The use of AI must also follow ethical principles, for example, clearly indicating when content is AI-generated, using customer data for training purposes only with consent, creating transparent, explainable models, and making sure training data is free of bias.
AI can drive valuable marketing outcomes, including efficiency, engagement, and growth. But marketers need to leverage it thoughtfully and responsibly to extract its full potential.
