2023 was abuzz with news of Generative AI (GenAI), but 2024 is set to be the year this groundbreaking technology transcends the realm of buzzwords to become a driving force of business. GenAI is no longer just a shiny new toy for revenue teams. It is a paradigm shift that will transform the way we operate – and hold incredible potential for revenue leaders who are ready to take the plunge.
Generative AI in sales will impact every aspect of the customer journey. With the ability to mine customer signals, craft personalized content, predict outcomes, and optimize interactions, this technology has the potential to unlock new levels of revenue — if utilized properly. In fact, McKinsey reports that AI-powered companies see revenue uplifts of 3-15% and sales ROI increases of 10-20%.
According to the State of Revenue Enablement Report, high-performing organizations are already starting to experiment with GenAI. In fact, 59% of revenue teams currently use or experiment with GenAI to accomplish tasks, and high-performing organizations are 44% more likely than lower performing ones to use or experiment with GenAI.
However, a healthy dose of caution is also warranted. Successfully harnessing the power of GenAI requires careful planning and execution. So, for businesses who aren’t quite sure where to begin amidst all this excitement, we’ve laid out 4 simple questions that will help you make the most of GenAI.
What is your organization’s tech tolerance and digital fluency?
Change management is important for the adoption of any new technology, especially AI. Some employees may still be skeptical of AI while others have fully integrated it as part of their daily regimen. To ensure the comfort of everyone on your team, you must take steps to assess their tolerance for new technology and use those conclusions to guide your pilot programs.
How does your team typically react to new technologies? Are they early adopters who jump at the chance to find potential use cases for the latest tools? Or are they more careful and risk averse, opting to wait until technology has been proven enterprise-ready? Try to match your team’s temperament and avoid overwhelming them with a tech roll-out they may not yet be prepared to handle. Failing to equip employees with tools that make new technology easy to use will lead to a disastrous user adoption rate and, subsequently, a lost investment.
You can also set the stage for a smooth integration process by understanding the digital fluency of your team. Are most folks already testing ideas in ChatGPT and Bard? Are they aware of all the use cases for GenAI in their role or could they benefit from training initiatives to show them new ways to take full advantage of the technology? Use these questions to develop an implementation strategy that aligns with your team’s current aptitude, comfort and goals.
What data are you capturing?
GenAI thrives on high-quality data. For any revenue-centric applications, you need to understand what data you have available today and how trustworthy that data is? For instance, are you documenting email communications between sellers, prospects, and customers? Are you tracking content engagement like shares, views, and time spent on page? Have you started pulling insights from meeting conversations and presentations? Think about all the potential sources of information available to your team, including being a fly on the wall in meetings with customers.
The treasure trove of information locked within these interactions helps you paint a more holistic picture of your buyer and their behavior. However, GenAI can’t pull insights out of thin air. You must start capturing recent, accurate data before the AI can analyze it to draw conclusions. It’s worth noting that 58% of high-performing companies automatically collect and upload activity data, making it much easier to feed clean data into the AI.
Where does your data live?
Perhaps the biggest question organizations need to ask themselves before getting started with GenAI is: “Where does our data live?” If your data is spread out across multiple locations or tools, GenAI models will not be able to understand the full picture of your buyer interactions. As we’ve discussed, quality data is critical for quality results from GenAI applications. If your GenAI model doesn’t have a holistic view of your customers and access to all your revenue data, it will produce inaccurate, and frankly unhelpful, insights.
To overcome this issue, it’s imperative to create a single data lake that acts as a unified source of truth for your GenAI model. Curate, monitor, and maintain the cleanliness of the data funneling into the lake to ensure the AI generates results based on an accurate and comprehensive set of revenue data.
What is the potential impact of GenAI on your organization?
GenAI has thousands of use cases and potential applications to help your revenue team drive productivity, improve customer relationships and more — which can also make it very difficult to know where to start.
As with any strategic initiative, you must begin with the end in mind. Think about what your organization, your department and your team are trying to accomplish this year and align your use cases to those goals.
Narrowing in on the most useful applications of GenAI and aligning those to business initiatives will help ensure you have executive support for your GenAI implementation. Our only caution is to be wary of trying to do too much too fast. Break down your vision into bite-sized goals that enable you to maintain morale and momentum and show forward progress over time.
If you’re thinking about GenAI to rev your revenue engine, check out this on-demand webinar that explores ways to use GenAI to unlock revenue potenial.
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