Generative AI

What are Generative AI apps for Sales and Marketing? Where can B2B SaaS leaders apply new GenAI tools?

Crafting B2B Narratives for Digital Business Outcomes

By David H. Deans

Welcome to the future of B2B SaaS market development. Digital business transformation beckons executive leaders to constantly seek ways to drive net-new growth and outpace the competition. That's an opportunity for Technology, Media and Telecom firms who seek to explore the application of tools that can deliver significant progress.

Generative AI (GenAI) tools will enable exponential productivity for vendor B2B Sales and Marketing roles. They can accelerate the discovery of market insights about enterprise buyer and end-user requirements for SaaS applications.

Plus, go-to-market leaders can create highly differentiated B2B SaaS solution narratives that deliver meaningful and substantive revenue growth. GenAI can also enable solution providers to engage customer C-suite decision-makers.

By crafting compelling storylines that focus on your customer's digital business outcomes, you can empower your frontline organization with powerful new skills and capabilities that will take your growth engine to new heights.

The Executive's Quest for Digital Business Outcomes

In the ever-evolving digital business marketplace, senior executives are under immense pressure to harness technology to drive performance. These desired business outcomes vary across industries and organizations, revolving around the following common components:

How to Craft Your Compelling B2B Narrative

Developing commercial narratives that resonate with executive leaders requires a thoughtful approach and a deep understanding of their needs, aspirations, and priorities. Here are proven strategies, based on empirical research, to create a compelling narrative for your B2B SaaS solution:

Seizing the Untapped Market Development Opportunity

As a B2B SaaS solution provider, an untapped growth opportunity awaits your ability to shape the way executive leaders perceive and adopt technology. The narratives you craft can influence decision-making at the highest levels and pave the way for widespread adoption of your solution.

Consider how you might embrace proven practices to seize this market opportunity:

Next Steps: Apply Generative AI Value Creation Benefits

In summary, the potential of Generative AI is boundless. Focus on digital business outcomes, and your B2B SaaS solution can become a driving force behind growth. Craft compelling narratives that resonate with leaders, and capture C-suite decision-maker attention as a trusted advisor.

By incorporating Generative AI tools into market insight and content development efforts, you can produce significantly higher quality assets faster. Embrace market demand with differentiated perspectives, and pave the way for new revenue. Create a Generative AI strategy, formulate a new GTM approach and execute your tactical action plan.

Plus, imagine the possibilities of creating customized versions of content for every industry and buyer archetype. Now, it's possible. Learn how Generative AI will Transform B2B Marketing to drive net-new SaaS revenue growth.

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Glossary of Terms

Generative AI is a type of artificial intelligence that can create new content -- such as text, code, images, and video -- using patterns it has learned by training on extensive public data with machine learning techniques.

Foundation Models are deep learning models trained on vast quantities of unstructured, unlabeled data that can be used for a wide range of tasks or adapted to specific tasks through fine-tuning.

Large Language Models make up a class of foundation models that can process massive amounts of unstructured text and learn the relationships between words or portions of words, known as tokens. This enables LLMs to generate natural-language text, performing tasks such as summarization or knowledge extraction.

Fine-Tuning is the process of adapting a pre-trained foundation model to perform better in a specific task. This entails a relatively short period of training on a labeled data set, which is much smaller than the data set the model was initially trained on. This additional training allows the model to learn and adapt to the nuances, terminology, and specific patterns found in the smaller data set.

Prompt Engineer or Prompt Design refers to the process of engineering or designing, refining, and optimizing input prompts to guide a generative AI model toward producing accurate desired outputs.

GenAI Polymath possesses a polyphonic skillset. Their role is potentially more than a skilled business or IT professional; they are an architect of the future.