Can GenAI Drive Profitable Growth in Your Business?

The ROI of GenAI

Today, after ~1.5 years since the release of ChatGPT, the imperative for every organization to leverage generative AI (GenAI) is apparent. However, because GenAI hasn’t been around long enough for standard best practices to be established, everyone (professional or consumer) is experimenting with this new tech. Despite the growing number of use cases, the primary mechanism for ROI has always been a huge improvement in productivity and efficiency gain, no matter how you look at it.

But a central question that is at the heart of every business is whether GenAI can help your business by driving profitability. The answer is simple. They can, but not directly! They do so by freeing up people’s time and resources due to the dramatic productivity boost they provide. Hence, these people and resources can be redirected to more profit-driving activities.

This indirect impact on profitability sounds good in theory, but it’s very difficult to realize in practice. Because GenAI is only an indirect profit driver, in practice, there are way too many factors and uncontrolled variables that could limit its efficacy in driving profit. Leveraging GenAI will definitely free up workers’ time, because productivity gain is a direct impact of GenAI. Although this will enable workers to do more profit-generating activities, in practice, directing these free-up resources to generate profit is very challenging.

First, not everyone knows how to generate profit for a company. Many don’t even know which task will drive profit most significantly. Some may not even be interested in doing such tasks, because they weren’t trained to do it. Finally, most people will simply just use their free-up time to do other similar, mundane, but necessary tasks that they’ve always been doing and know how to do.

This begs the question of whether GenAI can drive profit directly.

The Answer is From 2 Different Lectures

If you’ve been following me, you might recall that I was just in Sofia, Bulgaria, giving several lectures and meeting my fellow PROS in Sofia. And the reason I had to cut short my first-ever trip to Sofia is because I must return to the US for a couple of committed engagements. Although these 2 engagements look unrelated, they are key to answering our question of interest today—Is there a way for us to use GenAI to drive profit directly?

1. A lecture in SF to a Silicon Valley visiting cohorts from Ecole des Ponts Business School (EPBS)

My 2-hour-long EPBS lecture was aimed specifically at addressing our question of interest today. But the 2-sentence conclusion is the following:

There is a way to use GenAI to drive profit directly, but you cannot do it using GenAI alone (just as you cannot use LLM alone in a fact-based Q&A due to the high potential of hallucination). You must augment it with other AI tools that are designed to work with tabular data to optimize profit (just as you must augment LLM with another tool, a search engine, to ground the LLM using RAG).

If you are here looking for the lecture slides, here you go!

2. A talk in Chicago at the Professional Pricing Society (PPS)

If you reached this point, the natural question that comes to you is what are these other AI tools designed to work with tabular data to optimize profit? The answer to this question is the subject of my PPS talk, “AI’s Answer to Uncertainty: Pricing Under Big Data.” From this title, you can probably guess what these other AI tools might be. And you are right, they are precisely AI pricing solutions.

Although everything a business does should eventually contribute to its profitability, some activities are more direct contributors than others. For example, sales is a more direct contributor to revenue than marketing, because marketing is further upstream from sales. Therefore it’s often the case that many marketing metrics may look great (e.g. 80% conversion rate), but they barely move the needle when it comes to their profit impact.

Similarly, engineering a better product should eventually contribute to a company’s profitability. However, since product engineering is even further upstream from marketing, its revenue impact has to trickle down further. So product engineering is an even more indirect profit driver than marketing.

Evidently, pricing is the most direct driver of revenue, because pricing is even further downstream from sales. Before sales can sell anything, a price must be set. Although this is no secret, many businesses still overlook the importance of pricing. If you want to dive deeper to really understand the power of pricing, I can recommend 2 important references on this topic:

1. Managing Price, Gaining Profit—Harvard Business Review, 1992 Sep, by Michael Marn and Robert Rosiello
   This is the seminal paper that demonstrated the power of pricing and its efficacy in driving profit. It’s one of the most downloaded HBR article, and it’s the article that led the global industry to recognize the profit impact of pricing.
   
2. The Price Advantage (2nd Ed), 2010 May, by Walter Baker, Michael Marn, and Craig Zawada
   This is the most authoritative and comprehensive guide to pricing excellence, drawing on the extensive experience of the McKinsey authors in helping companies improve their profitability via pricing. It’s the bible for pricing professionals.

At PROS, we are proud to have Craig Zawada onboard as our Chief Visionary Officer (3rd from the left in the above photo). And I am personally honored to be able to call him a colleague.

Now, returning to the question of interest today—Can GenAI directly drive profitable growth in your business? Now you know the answer.

GenAI can directly drive profitability if it is augmented by other AI profit optimization solutions, it can only drive profitability indirectly if used alone.

Success in AI Profit Optimization

Now, you might wonder, if there is an AI that can optimize your profit, why isn’t every single company using it? Pricing is a very important ingredient, but it’s not the only one, since the profit equation has 2 components (i.e. revenue and cost). Yet, if we just consider pricing, this is already a huge challenge. Many pricing software implementations fail to meet their goals (some sources cited as high as 92%). If we factor in the other ingredients, the implementation can get very ugly, very fast.

In contrast, companies utilizing AI pricing optimization from PROS have experienced remarkable success. They are so successful that we are seeing an impressive customer retention rate of 93%, measured through organic customer renewals. Such a disparity in outcomes on the 2 opposite ends of the spectrum cannot be dismissed as mere coincidence.

So, what sets PROS apart with regard to successful AI profit optimization? What’s their secret sauce?

I must say that PROS does have a secret ingredient for success. But I will be revealing this secret at our Outperform 2024 conference, happening in just a couple of weeks. So, if you’re curious about how our AI is able to pull off this profit-boosting magic consistently, you should join me in Orlando, FL, May 20—22. Come to Outperform with PROS, and I will show you “The Secret Sauce of AI Profit Optimization.”