While most companies struggle to prove a return on their AI investments, Estée Lauder's AI-powered scent advisor provides a clear win. By doubling the purchase rate for users, it serves as a rare, concrete example of an AI application that directly and measurably boosts revenue.
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With AI enabling precise control over media spend, key performance indicators are changing. Brands now move beyond simple Return on Ad Spend (ROAS) to more sophisticated metrics like incremental ROAS and contribution margin, reflecting a new emphasis on profitable growth rather than just volume.
The true ROI of AI lies in reallocating the time and resources saved from automation towards accelerating growth and innovation. Instead of simply cutting staff, companies should use the efficiency gains to pursue new initiatives that increase demand for their products or services.
Moonshot AI overcomes customer skepticism in its AI recommendations by focusing on quantifiable outcomes. Instead of explaining the technology, they demonstrate value by showing clients the direct increase in revenue from the AI's optimizations. Tangible financial results become the ultimate trust-builder.
Focusing on AI for cost savings yields incremental gains. The transformative value comes from rethinking entire workflows to drive top-line growth. This is achieved by either delivering a service much faster or by expanding a high-touch service to a vastly larger audience ("do more").
To evaluate AI's role in building relationships, marketers must look beyond transactional KPIs. Leading indicators of success include sustained engagement, customers volunteering more information, and recommending the experience to others. These metrics quantify brand trust and empathy—proving the brand is earning belief, not just attention.
A large-scale Wharton study found 75% of business leaders see positive ROI from AI, directly contradicting a widely-cited but methodologically questionable MIT report claiming 95% of pilots fail. This confirms that despite the hype, businesses are successfully generating tangible value from their AI investments.
Amazon has attached a specific, massive financial value to its AI assistant, Rufus. It's projected to generate over $10 billion in new sales annually by increasing conversion rates by 60%, proving the immediate and substantial ROI of embedding AI into the e-commerce customer journey.
When leadership demands ROI proof before an AI pilot has run, create a simple but compelling business case. Benchmark the exact time and money spent on a current workflow, then present a projected model of the savings after integrating specific AI tools. This tangible forecast makes it easier to secure approval.
Humans lack the precise vocabulary to describe abstract senses like smell. Google's AI for Estée Lauder overcame this by building a structured framework connecting ingredients to technical categories and then linking them to evocative, emotional descriptions, making the abstract understandable and marketable.
When leadership pays lip service to AI without committing resources, the root cause is a lack of understanding. Overcome this by empowering a small team to achieve a specific, measurable win (e.g., "we saved 150 hours and generated $1M in new revenue") and presenting it as a concise case study to prove value.
