How will AI change the future of marketing and sales?

The combination of AI with marketing and sales is creating a revolution. So how can we explore the application of AI in marketing and sales to gain greater competitive advantages?

AI is at the forefront of disrupting marketing and sales in every industry, a result of consumer sentiment and rapid technological change.

Omnichannel marketing has become a trend because today’s customers want everything, anytime, anywhere. While they still want a mix of traditional, remote and self-service channels (including face-to-face, inside sales and e-commerce), we see continued growth in customer preference for online ordering and reordering.

Winning companies that are growing their market share by at least 10% per year tend to leverage more advanced sales techniques; have the ability to build hybrid sales teams; and customize strategies for third-party and proprietary e-commerce marketplaces. These successful companies are able to achieve excellence across the entire funnel and provide hyper-personalization (providing unique information to individual decision makers based on their needs, profile attributes, behaviors, and interactions (both past and predicted)).

Digitalization and automation are undergoing major changes. AI technology is developing rapidly. It is becoming easier and cheaper, while providing sophistication and speed beyond human capabilities. According to McKinsey research, one-fifth of sales team functions can be automated.

Venture capital investment in AI has grown 13-fold over the past decade. This has led to an explosion in “usable” data (data that can be used to develop insights and recommend specific actions) and accessible technology (such as increased computing power and open source algorithms).

There is now a vast and growing amount of data available to base model training on, and computing power has increased a million-fold since 2012, doubling every three to four months.

Based on the above underlying data and the essential breakthroughs in technology, what does generative AI mean for marketing and sales? The rise of AI, especially generative AI,

There are three areas of potential impact in marketing and sales: customer experience (CX), sales growth, and productivity improvements.

For example, in terms of customer experience, hyper-personalized content and offers can be provided based on individual customer behavior, persona, and purchase history. Growth can be accelerated by leveraging AI to improve performance at the upper end of the sales funnel and providing sales teams with the right analytics and customer insights to capture user needs.

In addition, AI can improve sales efficiency and performance by automating many tedious sales activity processes, freeing up more time for face-to-face communication with customers and prospects, reducing service costs. In all of these actions, personalization is key. AI combined with company-specific data and context enables consumer insights to be at the most granular level, allowing B2C companies to personalize through targeted marketing and sales services.

B2B companies that are winning in the market are also adopting hyper-personalization strategies in their marketing, going beyond account-based marketing and using hyper-personalization disproportionately in their outreach. There are many applications of generative AI in the customer journey that can make a difference:

Generative AI Sales Cases: In the upper half of the marketing funnel, generative AI goes beyond traditional AI-based lead identification and targeting, which uses web crawling and simple priority classification. Generative AI's advanced algorithms can use patterns in customer and market data to stratify and reach relevant users. With these capabilities, companies can efficiently analyze and identify high-quality leads, resulting in more effective, tailored lead activation campaigns.

In addition, Generative AI can optimize marketing strategies by A/B testing various elements such as page layout, ad copy, and SEO strategies, leveraging predictive analytics and data-driven recommendations to ensure maximum return on investment. These actions can continue throughout the customer journey, with Generative AI automating lead nurturing activities based on changing customer patterns. During the sales process, Generative AI goes beyond the initial sales team’s engagement and interaction capabilities to provide ongoing critical support throughout the sales process, from proposal to closing of the deal.

Generative AI can analyze customer behavior, preferences, and demographics to generate personalized content and messaging. From day one, it can assist with hyper-personalized follow-up emails and contextual chatbot support at scale. It can also act as a 24/7 virtual assistant for every team member, providing tailored recommendations, reminders, and feedback, leading to higher engagement and conversion rates.

As a deal progresses, Generative AI can provide real-time negotiation guidance and predictive insights based on a comprehensive analysis of historical deal data, customer behavior, and competitive pricing.

After a customer signs up, there are many more use cases for generative AI, including providing necessary customer training and customer retention. When a new customer joins, generative AI can provide personalized training content, highlight relevant best practices, and give a warm welcome. Chatbot functions can answer customer questions immediately and continuously optimize training materials for future customers based on this.

Generative AI can also provide sales leaders with real-time next-step recommendations, modeling ongoing churn based on usage trends and customer behavior.

Additionally, dynamic customer journey mapping can be leveraged to identify key touchpoints and drive customer engagement. This revolutionary approach is changing the landscape of marketing and sales, driving greater marketing effectiveness and higher customer engagement from the very beginning of the customer journey.

Business leaders are optimistic and seeing huge benefits from the application of generative AI in marketing and sales. McKinsey asked a group of business leaders to share their views on use cases and the role of generative AI in marketing and sales.

The results showed that leaders were generally cautiously optimistic: Respondents expected each of the use cases presented by McKinsey to have at least a modest impact. In particular, these participants were most enthusiastic about the use cases for lead generation, marketing optimization such as SEO and A/B testing, and personalized outreach in the early stages of the customer journey (see Appendix 1).

With all three of the most significant use cases focused on high-potential lead generation, we’re seeing significant early momentum in AI marketing. This is not surprising given the massive growth in the amount of potential customer data available for analysis and the historical challenges marketers have faced in personalizing marketing at scale.

Many companies have already deployed and produced generative AI use cases, but this is undoubtedly just the tip of the iceberg. McKinsey research found that 90% of business leaders expect to use generative AI solutions "frequently" in the next two years (see Appendix 2).

Overall, the most effective companies are prioritizing and deploying advanced sales technologies, building hybrid teams, and achieving hyper-personalization. They maximize sales through third-party and self-owned e-commerce platforms through data analysis and AI technology. Successful companies have the following common characteristics:

• Have a clear AI vision and strategy.
• More than 20% of digitalization budgets are invested in AI-related technologies.
• Hire teams of data scientists to run algorithms to develop quick pricing strategies and optimize marketing and sales.
• Strategists are looking ahead and distilling easy-to-use, generative AI use cases.
• These pioneers have realized the huge potential of generative AI to improve their business.

McKinsey research shows that companies that invest in AI see revenue increases of 3% to 15% and a 10% to 20% increase in return on sales investment.

While the business case for AI is compelling, AI technology is changing at an alarmingly fast pace and is not without risk. When business leaders were asked about the biggest barriers limiting their organizations’ adoption of AI technology, internal and external risks topped the list.

From intellectual property infringement to data privacy and security, there are many issues that require thoughtful mitigation strategies and governance. Human oversight and accountability will be needed, and new roles and capabilities may need to be created to fully exploit future opportunities.

In addition to immediate action, leaders can also start to think strategically about how to invest in AI in the long term to achieve business excellence. It is important to determine which use cases are essential requirements and which can help the company establish a competitive differentiation in the market, and then prioritize them based on impact and feasibility.

AI is advancing faster than anyone can imagine, and today’s winners may not be tomorrow’s winners. Small startups are great innovators, but may not be able to scale on demand or generate sales growth-focused use cases that meet your needs. Enterprises can test and iterate with different players, but need to pursue strategic partnerships based on sales-related innovation, speed of innovation rather than time to market, and the ability to scale.

AI is changing at an incredible pace, and while it’s difficult to predict the course of this revolutionary technology, it will certainly play a key role in the future of marketing and sales. Leaders in marketing and sales are turning to generative AI to maximize their operational productivity, leveraging advancements in personalized marketing and inside sales excellence to fuel their marketing growth and career success. How will you react?

Author: Zhu Jingyu

Source: WeChat official account: "Jade Digital Marketing (ID: Jade_Digital)"