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When we started Staircase AI, everyone was skeptical about AI. We would often hear concerns from revenue intelligence and CS leaders saying things such as:
“It will raise a lot of false alarms” “It can’t match human thinking”“It’s going to take a lot of time”“It’s not worth the effort”“how do I know I can trust it?”
Just to name a few.
Fast forward 18 months and the entire world, not just business professionals, are in a hurried frenzy trying to understand, use, and deploy AI wherever possible. This has been accelerated by the “consumer” experience using ChatGPT.
It isn’t 100% accurate “yet” but what we are witnessing at the moment is truly astonishing. Millions of people will attest to that, more specifically over 100 million users, who are actively using ChatGPT daily. The crazy thing is that we haven’t even begun to scratch the surface.
As the data accumulates, AI will only become smarter, and more accurate. The use of AI in the business and enterprise world has been a significant driver and catalyst. In this post, I want to explore the deeper insights behind the scenes of AI and generative AI and how it is fueling customer-led growth.
Generative AI opens the door to new possibilities in terms of innovation and product differentiation.
Customers today have high expectations for personalized and seamless experiences. By analyzing large datasets and customer preferences, businesses can generate more personalized recommendations.
“Consumers don’t just want personalization, they demand it.”
Rather than interrupting the customer journey, these custom-tailored messages can be delivered at the right place and at the right time.
McKinsey pointed out that businesses with a firm grasp on personalization tactics had the fastest revenue growth, boosting revenue by as much as 40%. These same companies were also able to build better customer relationships, increase retention rates, increase the likelihood of purchase, and create a deeper sense of brand loyalty.
AI: The most popular form of AI is supervised learning which entails training machine learning models to recognize patterns and make predictions based on input data. The models are trained on labeled data, and once the training is complete, they are deployed to make predictions on new, unseen data. AI focuses on finding the most accurate solution for a specific task or problem.
Generative AI: Generative AI involves both training and generation phases. In the training phase, generative AI models learn the underlying patterns and structures of the data. In the generation phase, the models use the learned knowledge to generate new data or outputs based on given constraints or goals.
Generative AI is a differentiator and game changer in the B2B space, but its successful implementation relies on smart, accurate, and secure utilization. The ability to generate new ideas, content, and insights can give businesses the competitive edge but must be deployed carefully.
While the directive is clear, the actual implementation and deployment are often more complex. A general model trained on the entire internet may not be the best fit for an enterprise with unique data sets.
Businesses encounter a two-fold challenge when implementing AI: security concerns and the need to rethink their organizational structure.
During a recent survey we conducted on The Reality Behind CS Playbooks, we discovered that 62% of CS leaders found their playbooks to be either partially or totally inaccurate when constantly used.
CS teams don’t need to reinvent the wheel, they simply need a better solution, and that solution is AI.
AI can effectively eliminate friction points and empower both CS and sales teams into identifying untapped growth opportunities and upsell strategies, resulting in more expansion deals.
LLMs and other AI/ML models can be trained using proprietary data to gain valuable insights and make more informed decisions.
By harnessing the power of unique data sets and proprietary company data, you can greatly enhance your GTM strategies. These insights can help improve customer engagement, predict churn, and drive competitive advantage in the market.
The bottom line is that when used carefully and securely, the benefits of AI outweigh the risks. With the surge in competition, no business can afford to ignore this breakthrough in technology if they want to continue to grow.
Different teams such as sales, product, support, CS, and marketing, can all benefit from Generative AI to automate and enhance various aspects of their workflows. Below are just some of the ways that each team can leverage Generative AI to gain more actionable insights and accelerate the customer journey.
And those are just a few of the possibilities.
What happens when we combine the superpowers of AI and Generative AI?
Businesses bear the responsibility of maintaining customer privacy and security. The handling of sensitive data must be done in a thoughtful and careful manner.
Responses to customers need to be validated and verified, addressing the hallucination and inaccuracy issue of Generative AI. Challenges such as bias, ensuring fairness, and maintaining transparency must also be taken into consideration as we move forward.
AI can be used to improve productivity and efficiency. As an AI advocate, I consistently discuss the capabilities of AI whenever I get the chance. Recently, I participated in an expert panel discussion on the role of Generative AI in post-sales (you can check it out here). While AI brings tremendous potential, it is essential to exercise caution when contemplating the replacement of certain human tasks.
While LLMs excel in processing vast amounts of data and in identifying patterns with remarkable accuracy, at present they seem to lack the comprehensive cognitive abilities of human General Intelligence. This remains an unparalleled aspect of human cognition that complements the capabilities of AI, even as technology continues to evolve.
In conclusion, combining the powers of AI with Generative AI can turn every team member into a revenue generator. Businesses that leverage both forms of AI will ultimately make more data-driven decisions and tap into new and exciting revenue opportunities.
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