Service
Artificial Intelligence
Shape the future with human-first AI
Highlights
- AI and Generative AI (GenAI) are powerful tools that augment the capabilities of personas supporting the sales and marketing function, helping them focus on strategy, creativity, and building long-lasting, meaningful customer relationships.
- A three-phased approach to AI adoption covering the continuum of assist, augment, and transform can help make AI more effective in organizations and guide its deployment.
- A four-layer architecture can form the foundation for a wide range of efforts that leverage the power of GenAI to boost margins and revenue.
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Why AI for sales and marketing
The sales and marketing function faces numerous challenges, as customer demands evolve and new channels continue to emerge and mature.
In the current landscape, companies must be adept at providing hyper-personalized content, accommodating dynamic user journeys, automating lead generation, converting sales without the help of sales representatives, effectively using influencer marketing, taking advantage of digital video and audio, and optimizing the use of search engines. At the same time, they must continually focus on engaging customers and enhancing their experience across the end-to-end customer journey—from initial awareness of a product or service and consideration to purchase, sale, post-sales service, and customer advocacy—keeping the customer front and center in the process.
Generative AI (GenAI) can play a vital role in helping companies understand and actively address these challenges to cultivate long-term customers and achieve sustainable growth. The technology can serve as an intelligent assistant to every persona across the customer journey, enabling use cases that enhance the quality and speed of customer engagement at critical customer touchpoints. For example, digital marketing specialists can use GenAI to plan and execute more effective marketing campaigns, while content creators can leverage GenAI to create and distribute more engaging content.
In fact, GenAI is poised to transform how every sales and marketing role operates and the value each role delivers. Let’s, for instance, consider the technology’s impact on one role: the frontline sales representatives (sales reps) responsible for online and physical stores. GenAI can provide assistance and insights, automate currently manual and tedious activities, and empower reps with the information needed to more effectively engage with and convert customers.
A structured approach to sales and marketing transformation
An enterprise-wise approach to GenAI-led transformation covering three phases—assist, augment, and transform—can help with seamless adoption and make the technology more effective for organizations.
The approach starts with the assist phase, where GenAI is used to boost human capability. For example, it can execute a knowledge search across many different data sources to help customers and agents in their daily activities. The GenAI capabilities used can include the following:
- An enterprise data assist analyzes large datasets within a company to extract insights, identify trends, and support decision-making.
- A product catalog assist organizes, categorizes, and optimizes product information for e-commerce platforms, making it easier for customers to find what they need.
- A product content assist generates product descriptions, reviews, and other relevant content, saving companies time and resources.
The next phase is augment, where humans and machines collaborate to achieve better outcomes. In sales and marketing, this collaboration focuses on two key areas:
- Activity optimization, which includes identifying prospects, providing personalized outreach, optimizing content creation, and nurturing and engaging with leads to boost efficiency, productivity, revenue, and return on investment (ROI).
- Experience play, which involves creating targeted marketing campaigns, automating and optimizing sales content creation, and qualifying and prioritizing leads to drive more informed decision making and significantly enhanced processes.
For example, GenAI can be used to provide recommendations to improve search engine rankings and can serve as a customer lifetime value advisor by analyzing customer data and producing recommended actions to maximize long-term value for customers.
Finally, in the transform phase, AI leverages its inherent creative abilities to elevate human capabilities, helping reimagine value chains and processes and develop innovative solutions. For example, by analyzing customer review comments, GenAI can suggest product features that will not only help improve current customer satisfaction levels but also help with new product discovery to improve sales and revenue.
Figure 1: A phased approach to AI-enabled sales and marketing transformation
An architecture for sales and marketing AI transformation
A valuable complement to the three-phase AI implementation approach is a four-layer architecture for GenAI transformation.
As illustrated in Figure 2, this architecture provides a comprehensive framework for integrating AI into sales and marketing. The foundation lies in robust data management—built on top of core enterprise information and operations technology systems—that encompasses structured, unstructured, and external data sources, along with data lakes and warehouses. This data fuels the foundational large language models (LLMs), including those for text, images, and video, and enables advanced analytics.
Figure 2: A four-layer AI architecture for sales and marketing transformation
The architecture's strength lies in its purposive and contextual GenAI-powered task agents, which are built on the underpinning information stores from the data lakes and data marts. Human oversight and controls ensure ethical and responsible AI implementation, with guardrails and observability mechanisms in place.
These agents serve as specific assistants to each of the personas in the ecosystem—such as consumer review insights board, next-best actions sales advisor, and assistants for consumers, agents, and data analysts—thereby enabling AI-augmented work systems that help drive intelligent, informed decisions for every customer scenario.
This four-layer architecture offers a robust solution for building complex GenAI applications, providing a modular framework that enhances maintainability and efficiency and allows developers to fully leverage GenAI’s power. The architecture delivers three key benefits:
- Enables a scalable implementation that caters to a wide array of sales and marketing needs.
- Ensures efficient and targeted solutions, developed using only the information required and by leveraging purpose-built AI agents.
- Prioritizes data security, ethical considerations, and human oversight, fostering trust and transparency in AI-driven sales and marketing transformations.
With this architecture as the foundation, companies can deploy GenAI to a wide range of use cases, helping transform the sales and marketing function to deliver critical business outcomes. Use cases can fall into three broad categories: Intelligent sales assistance, intelligent marketing assistance, and sales and marketing analytics and insights.
1. Intelligent marketing assistance: This predominantly focuses on assisting, augmenting, and enhancing the quality, productivity, and speed of marketing content creators. It includes:
Product catalog assist
- Get product information from suppliers.
- Convert into standardized product literature.
Product content assist
- Generate new product manuals and sales and marketing campaigns.
- Convert product text information into videos.
SEO content advisor
- Provide a competitor SEO analytics dashboard.
- Generate new SEO keywords from the above.
2. Intelligent sales assistance: This primarily focuses on enabling the sales representative (online or in-store) with information and recommendations that will facilitate an effective sale and create value for the customer and the business. It includes:
Next best actions sales advisor
- Leverage machine learning for predictive analytics around new client acquisition and existing client churn and retention.
- Convert insights into managerial actions.
- Create supporting sales content.
Consumer and agent assist
- Execute conversational knowledge search and generate recommendations.
- Power external websites and internal knowledge base and employee portals.
Customer lifetime value advisor
- Leverage machine learning for customer lifetime value prediction.
- Create supporting sales content.
3. Sales and marketing analytics and insights: Companies can use AI to tailor analytics and insights to different perspectives. For example, AI can synthesize customer review comments and feedback for each persona in the ecosystem, interpreting reviews consistently across the value chain and providing competition analysis to help not just win customers, but also retain them for life. Use cases include:
Consumer review insights
- Synthesize user reviews from websites and retailers.
- Map product features against user likes and dislikes to inform product enhancements.
- Generate hyper-personalized cross-sell and upsell responses.
Enterprise data insights
- Convert business user queries into natural language responses.
Legal contracts advisor
- Review, modify, and compare complex legal documents.
Agent performance advisor
- Generate performance dashboards and enable hyper-personalized training requirements for sales agents.
Sales and marketing predictive analytics
- Execute traditional machine learning modelling, augmented with GenAI, to drive insights into actions.
- Support end-to-end sales and marketing, including campaigns, sales, and churn.
Case study: Sales and marketing content generation
One example of how AI can improve sales and marketing is that of a global manufacturer, which deployed AI to help streamline content generation.
Before GenAI: Employees across various departments manually managed tasks, such as generating content, rephrasing content, translating languages, correcting spelling and grammar, summarizing documents, and analyzing data.
After GenAI: The company deploys an enterprise chatbot solution leveraging Google's PaLM 2 chat-bison model to enhance employee productivity. For example, via natural language queries, employees can interact with the chatbot and receive relevant and informative responses from the foundation model. The chatbot maintains the context of ongoing conversations, ensuring coherent and meaningful interactions.
Using AI to keep pace with the market
The sales and marketing landscape is constantly evolving, making it difficult for businesses to keep pace with the changing market landscape.
It’s especially challenging given the significant influence of factors external to the enterprise—primarily, the market and all the dimensions that shape it. GenAI is a powerful tool that can help businesses navigate these complexities to achieve sustainable growth. The technology is poised to revolutionize sales and marketing by automating tasks, personalizing customer experiences, and providing data-driven insights for decision making among sales agents, marketing content generators, and service agents who can tailor content and interactions for each individual customer or prospect. This will boost engagement, sales, and long-term loyalty that drives sustainable revenue growth. Companies should act now to lead with AI.
