The 3 Measures of ROI for AI

Artificial Intelligence (AI) is becoming a critical component of digital marketing.  AI in marketing can be particularly revelatory, often delivering valuable insights that marketers can use to develop personalized content, drive conversions, and improve customer experience. Such insights help develop effective marketing strategies, which increase Return on Investment (ROI) for AI implementations.

However, it can be very difficult to measure the ROI of AI. As a result, many digital marketers are struggling to make gains from AI investments. In this article, we present an approach to measure the ROI of the AI adoption process — and why it’s important to do so.

What Is ROI?
Short for Return on Investment, ROI is a performance measure used to evaluate the profitability of business expenditures. ROI looks at the upfront cost of an investment versus the net profit it produced to determine whether it’s profitable or not. ROI is extremely useful for measuring success over time. Executed well, ROI becomes the common denominator for assessing the contributions of various initiatives across the organization.

Why Measure The ROI Of AI Strategies/Projects?

According to a 2019 MIT SMR-BCG survey, 70% of companies reported little to no value from their AI investments. The reason most AI projects fail to meet ROI objectives is that ROI is too narrowly defined. Therefore, it’s important for organizations to establish some measurable benchmarks by which they can demonstrate the ROI of their AI investments.

Obviously, measuring ROI has benefits for marketing and the organization as a whole. But AI initiatives can appropriately be considered more of a research and development expense. That being the case, AI projects may not get the scrutiny they deserve. On the other hand, AI projects that focus too narrowly on a near-term positive payoff are not realizing the full suite of benefits the effort delivers to the organization. Because of this unique position, we propose a new way to view and assess the ROI of AI.

How to Measure ROI of AI Projects

AI is set to become the next big game-changer in the constantly evolving digital marketing landscape. Some will argue it’s already begun changing the game and we won’t argue that position. AI, in whichever form it takes (e.g. ML, Deep Learning, NLP, machine vision, etc.), provides insights and understanding that can shape a company’s future. As such traditional net revenue over cost equations for ROI doesn’t provide the full picture.

So, how do you demonstrate the ROI of your AI projects? Here are three techniques we feel provide a more complete view of how AI initiatives impact organizations.

Measurable ROI

Measurable ROI describes the calculable aspects of AI project impact. It entails both financial and qualitative outcomes. One of the most accurate ways to gauge the ROI of AI is by examining measurable benchmarks such as operating efficiency, risk reduction, and ultimately revenue growth. Evaluating investments in terms of these three metrics is the most common approach to assessing ROI.

Operating Efficiency. Many digital marketers want to implement AI to assist in automating key processes, such as data entry and customer service. Further efficiencies are gained in media optimization enabling greater returns at existing or reduced budget levels. These efficiency gains provide marketers with another way to compute the ROI of AI. Identify which processes were improved and by how much, and then determine if there are clear time or resource savings.

Risk Reduction. AI applied to deliver predictive analytics and latent effects modeling can identify issues to be avoided or leveraged which minimizes organizational risks. For example, with data privacy laws such as GDPR and CCPA, digital marketers can incur financial risks due to improper security considerations. Or enter markets that initially seemed lucrative but don’t yield needed returns. The avoidance of risks results in saved resources which can be calculated in terms of ROI.

Revenue Growth. A well-implemented intelligent solution can lead to an increase in both the number of buyers, understanding customer price sensitivity, new product and service development or new markets to enter. The financial gain that your AI initiative will generate presents marketing and sales with an opportunity to quantify the ROI of the investment(s) made.

There are many ways to calculate hard financial returns. Whether it’s cost savings from efficiencies, risk reduction, or revenue growth, the most important thing is to demonstrate that your AI project improves or protects the company’s bottom line.

Strategic ROI

Strategic ROI refers to the ability of an AI initiative to move the company towards achieving its long-term goals. For those who can harness its potential, AI has the potential to enhance customer experience, expedite digital transformation, and enhance existing capabilities. Measurement of Strategic ROI starts with aligning AI initiatives to specific long-term organizational goals and potentially developing proxies to revenue and costs to approximate economic returns.

An essential component is being able to articulate to leadership how these AI investments aid the progress of the organization. This argument needs to be communicated at the earliest stages of the project to get critical support. To demonstrate strategic ROI for AI initiatives, marketing teams exploring AI capabilities need to tie their projects to a relevant strategic anchor, such as market share, new product pipeline, customer experience or data security. When choosing a strategic value point, make sure it’s something the leadership truly cares about.

Capability ROI

Capability ROI is the value a business derives from building a solid foundation of AI to support future innovation and digital transformation. It’s all about improving the firm’s collective skills and processes as a team, putting the organization in a better position to leverage AI to gain a competitive advantage in the market.

Capability ROI can help your organization achieve AI maturity, the ability to achieve and scale impact from AI systems. When your labor force has the skills to successfully implement AI initiatives and the leadership has the conceptual grasp of the underlying technology, the organization will be in a better position to harness the full potential of AI. In short, AI isn’t going away and the more members of the organization who are AI-capable the better position it will be in to take advantage of opportunities.

Taking into consideration the massive financial investment businesses are making and the expected returns, there needs to be a way for marketers and other professionals to hold AI projects accountable. By calculating the ROI of your AI projects, you can better understand how well your AI initiatives are doing and which areas could use improvement.

Conclusion

More and more organizations are quickly implementing intelligent technology solutions to gain a better, more nuanced understanding of their target markets. But if you choose to use AI in your marketing campaigns, you need to make sure that you communicate progress in the most appropriate manner. Measuring the ROI of AI projects can help you demonstrate gains from AI solutions.

AI is revolutionizing the way marketing teams manage their campaigns, create personalized content, and improve customer experience with brands. Interested in learning more about how to deliver ROI from AI initiatives? Don’t hesitate to contact us if you have any questions about using AI and other intelligent data-intensive solutions to thrive in a rapidly changing world.