Commercializing generative AI: How can you extract business value from ChatGPT and Co?

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generative AI

GenAI is storming the world, but most firms don’t realize the capability of the technology. How can marketing and sales departments differentiate between the hype and reality? In this article, our Simon-Kucher Elevate experts explain the potential use cases and commercialization strategies with GenAI.

As we navigate through the first wave of GenAI, we realize that the technology quickly reaches maturity: It won't be surprising if "GPTing", much like "Googling", soon becomes a common term representing the use of AI models such as GPT-4 for content generation or customer support.

And every week and month there are new technological advances in GenAI: Today's models can already create unique, human-like content and interactions providing a powerful edge for businesses in competitive markets.

GenAI will revolutionize marketing and sales by personalizing customer experiences, optimizing campaign strategies, and unlocking new revenue streams. For positioning your business at the vanguard of this dynamic shift, it’s time to quickly move and build a commercial strategy for GenAI.

More than just ChatGPT: What is GenAI?

GenAI refers to AI models that can produce novel and convincing content, such as text, images, or sound, based on their extensive training data. Firms build these AI upon foundation models that have been trained on massive amounts of data.

The recent change in capability is the development of Large Language Models (LLMs) that can understand human language: Through normal written instructions (“prompting”) instead of code enabling the models to perform an array of tasks.

Consider GPT-4, a textual foundation model, which has been trained on a vast corpus of text. It can be fine-tuned to perform a multitude of tasks, including question-answering, text summarization, copywriting, or product recommendation. In the visual domain, a model like VQ-VAE-3 can generate new images, enhance existing ones, or even create variations of renowned art pieces.

Through these capabilities, GenAI paints a picture of endless possibilities for businesses across all sectors. For example, Adobe also added a built-in image generation functionality to help artists accelerate their productivity significantly.

Are the commercial applications of GenAI mature for your business cases?

GenAI presents an unprecedented opportunity to commercialize business with a powerful impact on marketing and sales. Most of the following applications have already started being used by companies, and there are many more to come:

  1. Optimized marketing communication

By commercializing GenAI, firms can revolutionize their marketing strategies. GenAI generates interesting marketing content tailored to individual customer profiles.

The technology can quickly automate the production of persuasive emails, engaging advertisements, or captivating social media posts, effectively scaling up the marketing output.

This significantly reduces the time and resources traditionally invested in content creation. Companies should not wait to implement this change. Already today, GenAI can boost conversion rates, drive up revenues, and provide a significant competitive edge in the marketplace.

  1. Data-driven sales enhancement

Generative AI can be a powerful tool in a sales team's arsenal, providing insights derived from vast amounts of customer data. Firms can commercialize this technology to derive complex insights from customer interactions, personal preferences, and purchasing history. This helps sales teams tailor their pitches to potential clients effectively.

GenAI can help build models to forecast future sales trends enabling proactive adjustment of sales strategies. These capabilities can significantly enhance sales effectiveness, leading to higher conversion rates and better customer retention.

  1. Improved customer relationship management

The commercialization of GenAI brings a paradigm shift in customer relationship management. GenAI powers intelligent chatbots and virtual assistants that provide 24/7 customer service. The tech can deliver hyper-personalized customer interactions, resolving issues promptly and accurately, and enhancing customer satisfaction.

GenAI can also help identify critical touchpoints in the customer journeys, helping firms to engage customers at the right time with the right message. This strategic utilization of generative AI can improve brand loyalty, reduces customer churn, and drives long-term commercial success.

Preparing the commercial launch of GenAI

Building a successful strategy with generative AI begins with firms actively identifying where this technology creates the most significant impact within their organization. They need to analyse their processes – from marketing and sales to customer relationship management – to pinpoint where AI-driven enhancements could be most beneficial.

Understanding the specific challenges that GenAI can address is crucial, whether that's content generation, data analysis, or customer engagement. Once these areas have been identified, businesses should establish clear, measurable objectives related to improving conversion rates, reducing churn, or optimizing marketing efforts.

Data is key: What strategy can help with commercializing GenAI?

To commercialize GenAI firms need to make use of a wide range of data such as customer demographic data, behavioural data, transactional data, and any interactions the customers have had with the company across multiple channels. Having data in an ordered accessible format would be key to unlocking the commercial benefits. The technology is moving at a breakneck speed, having high quality, easily accessible data is the key in realising the benefits. 

Data on customer responses to previous marketing and sales campaigns is also crucial, as this information can help train the AI to generate personalized content and predict customer behaviours accurately.

The big change here is that a limited amount of data is needed nowadays: While previous machine learning models required gigantic data sets to forecast results, the current generative AI models only requires targeted data instructions, which opens a lot of possibilities for firms.

They directly benefit from data that is outlined in market trends, and industry benchmarks. This data set can not only feed the generative AI with the information to perform optimally but also refine and validate the models, ensuring they align with the business's strategic objectives and drive meaningful results.

What should firms be mindful of when commercializing Generative AI?

While the upside of generative AI is very high, companies need to consider how they can commercialize this technology effectively. Many will need to adapt their commercial models with their customers. For example, professional service firms who charge by day/ hour, will need to determine how to bill their clients if they are more efficiently. And companies who have a ‘per user’ model may have less people using their software through better automation. How will this affect their model and pricing strategy in the long run?

There are also potential risks such as data privacy and ethical concerns. It's crucial to ensure that the personalization offered by GenAI doesn't infringe upon customer privacy rights or norms. Companies must always obtain proper consents for data use, uphold transparency in their AI applications, and adhere to regional and international data protection regulations.

The risk of over-reliance on AI should also not be overlooked. While GenAI can provide valuable insights, human oversight and decision-making remain vital to interpret those insights contextually and ethically.

It's essential to consider the quality and diversity of training data used. Biased or unrepresentative data could lead to skewed outputs and potential missteps in marketing and sales strategies. Therefore, risk mitigation and ethical considerations must form a core part of the commercialization strategy for generative AI.

Implementing GenAI with experts on your side

Implementing generative AI necessitates active collaboration between the AI specialists introducing the tech and the rest of the organization. Ensure that everyone understands the capabilities and potential of this technology – this encourages company-wide acceptance and smoother integration.

After this initial step, the AI specialists develop, test, and refine AI models in alignment with the identified objectives. During the implementation phase, constant monitoring is crucial to gauge the effectiveness of GenAI in achieving the set goals. Any business should use these insights to refine the models and strategies.

Want to know more? Contact us.

Our experts from Simon-Kucher Elevate can support you to utilize GenAI. We know how to commercialize your business models and improve your sales and marketing potential:  

Businesses should from now on proactively look for opportunities to create new services or products based on their unique AI capabilities, thus creating new revenue streams, and achieving sustainable competitive advantage.

You are not alone with this. It’s time to join the tech revolution.

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