There’s no doubt that organizations across industries are all in on artificial intelligence. The global AI market grew to 184 billion last year—two years after according to McKinsey, organizations that led in AI implementation generated an estimated 20% of their revenue from the technology. How can companies use AI to drive revenue?
With a technology as flashy as this, it’s easy to get lost in the buzzwords. In reality, AI is not an automatic guarantor of success. Like every other technology, it relies on strategic implementation for success. But with those parameters in place, it can potentially have a massive impact on your organization.
It’s not just about improving efficiency and cutting wasteful spending, although that is certainly part of the equation. Instead, and as the above McKinsey study shows, it’s also about actively driving revenue in ways that were impossible without artificial intelligence and machine learning. Consider these seven ways in which AI can positively impact your bottom line.
1. Use AI to Drive Revenue By Identifying Your Target Audience
Most organizations build their products around perceived audience needs. But how do you know which segments of the broader market have those specific needs? The answer is through artificial intelligence and specifically predictive analytics. These tools help to better identify the characteristics and preferences of different audience groups. As a result, you can more specifically target your marketing efforts.
For example, predictive analytics helps determine when members of your audience will feel the need for a product like yours. Their physical location may give hints as to what type of products they tend to look for. And their income may provide information on the brands they tend to frequent. Combine that with the characteristics of users browsing your website. Adapt your target pages depending on what pages they frequent. Ultimately, you can build a better profile of exactly which customers are most likely to buy your products—and when.
Often, this data is available for manual analysis. However, the sheer wealth of information makes that manual analysis impossible. AI can analyze it all in seconds, providing real-time information on both surface-level and deeper-lying characteristics to identify and target your ideal customers.
2. Forecast Demand Across Different Audience Segments
In addition to identifying your ideal audience segments, AI plays a core role in forecasting the exact demand among those segments. By analyzing patterns in sales data and broader demand in your category, the right model can estimate exactly how profitable certain segments of potential customers will be—further enhancing your decision-making.
Consider the example of this predictive analytics solution. It leveraged AI to help a building materials company improve its revenue by moving inventory after forecasting increased dangers through hurricanes. The company was ready before the dangers became acute. As a result, it was able to proactively adjust its supply chain and stay ahead of its competition.
Plenty of other examples show the potential power of AI to enhance demand forecasting—even in scenarios where no historic sales data is available. Add the ability to break down those forecasts by individual segments, and you get the potential of a powerful predictor that can determine and improve your entire sales strategy.
3. Optimize Your Pricing Through Dynamic Machine Learning
No matter your industry, getting your pricing right makes a massive difference in sales and revenue success. Price your products too low, and your profit margin won’t be sustainable. Too high, and the demand reduction can lead to potentially significant lost revenue.
But how do you get that pricing just right? Most organizations don’t have the luxury of testing different price points to get empirical evidence on the ideal price. But as AI has become more common in business applications, businesses are beginning to use AI to accomplish just that.
Through AI modeling, these organizations can calculate exactly which products should be sold at which price points—and how increases or decreases can affect demand and revenue. Meanwhile, machine learning enables organizations to compare the actual impacts of price adjustments in real-time, improving their models to offer more accurate predictions over time.
For products in which dynamic pricing is possible, this concept can go even further. Here, AI models can adjust prices based on competitive data, seasonal demand, and even audience zip codes, ensuring that it remains optimized as variables change to avoid over- or underpricing individual products.
4. Enhance the Customer Experience Across the Buyer Journey
Of course, price is not the only variable in customer demand. Research has long established that customer experience matters at least as much. In fact, one study by PwC found that for 73% of consumers, that experience matters more than price when making a purchasing decision.
Fortunately, this is another area where AI can have a significant revenue impact. AI-enabled digital assistants, for example, can learn the common pain points and questions of both prospective and current customers, building a database that can then be leveraged in the form of chatbots.
Through websites, SMS texting, and other channels, audiences can ask their questions and receive instant, accurate answers at any point in their journey. With each interaction, the digital assistant can enhance its database, ensuring that all audiences receive accurate and customized communications that address their needs and build goodwill toward an eventual purchase.
5. Hyper-Personalize Content and Ads Based on Individual Preferences
In addition to being available for these questions, AI models are also able to leverage the vast amounts of data available for audience segments to create better, more tailored marketing experiences for individual users. Information like browsing and purchase history, demographics, and even device type can be leveraged for better, more personalized content at scale.
This process is nearly impossible to accomplish manually. With AI, it becomes a reality, not just because of machine learning analyzing these individualized characteristics but also because of the follow-ups that become possible.
Email campaigns, website content, and other channels can all be tailored specifically and in real-time to audience needs and preferences. The timing of these messages can be automated as well to ensure that audiences receive the right message, at the right time. In a world where personalization is becoming increasingly necessary to woo potential customers this type of mass customization is invaluable.
6. Create New Products That Predict and Account for Demand
At its best, AI can go even deeper than building better marketing messaging and tactics. Through this technology, organizations can create entirely new products that better accommodate customer needs compared to existing options.
In 2023, the first drug created entirely by AI made headlines across the world. Designed as a treatment for idiopathic pulmonary fibrosis, a Hong Kong-based startup leveraged machine learning algorithms to learn how the disease could be treated. On the other end of the spectrum, AI has been leveraged to design new and more personalized golf clubs, in-car technology for BMW vehicles, and more.
The key in this process is not only the development of new products but the connection of these products to vast swaths of data and information that can customize preferences and demand. Put differently, the same technology that can unearth the need for a product can also take that need and put a solution into action, bringing the process of helping your customers succeed full circle.
7. Analyze Data for Deeper Insights and More Improvements
Finally, the data analysis capabilities of AI can also be leveraged to turn inward. In fact, the technology’s ability to analyze every part of your organization can lead to core insights into where your company is improving, where improvements are necessary, and how you can begin to approach these improvements.
For example, organizations across industries are leveraging AI to find and reduce operational bottlenecks. At the supply chain level, they’re able to identify where processes are not as efficient as they could be, and what steps might be possible to build that efficiency. The same is true on the production, promotion, and financial operations side.
The best part: no amount of data is too much to handle with this type of modeling. In fact, AI systems can review and analyze your entire organization, enabling faster and more data-based decision-making at every level. This 360-degree insight into your business at every level, from executives to ground-level employees, can build a significant competitive advantage and ultimately boost revenue.
Leverage the Power of AI With Dynamic Digital Assistants
As the potential use cases of artificial intelligence continue to broaden, one thing remains clear: this is a powerful technology that, applied the right way, can impact every part of your business. Especially in industries where revenue sustainability and growth are key, it can become a major driver in helping to make that happen—and helping your business thrive.
AI-enabled digital assistants are the perfect example of this type of revenue generation. 24/7 availability unlocks new audiences and builds convenience. Meanwhile, custom-tailored messaging improves the customer experience, increasing both initial conversions and long-term customer loyalty. Each has a major impact on revenue, showing just how beneficial digital assistants can be for your entire business.
