Artificial intelligence (AI) and machine learning (ML) We continue to push the boundaries of marketing and sales possibilities. And now, the incremental evolution of generative AI (gen AI) continues, with the use of open source platforms permeating the sales floor and increasing investment in generative AI innovations by sales technology companies. Given the increasing complexity and speed of business in a digital-first world, these technologies are becoming essential tools.
This inevitably impacts how businesses operate and how they connect and serve their customers. In fact, you probably already have. Forward-thinking executives are considering how to adapt to this new environment. Here, we outline the marketing and sales opportunities (and risks) in this dynamic space and suggest productive paths forward.
How AI is reshaping marketing and sales
AI is poised to disrupt marketing and sales in all areas. This is the result of changing consumer sentiments associated with rapid technological change.
Omnichannel is a gamble
Engagement models are changing across industries, and today’s customers want anything, anywhere, anytime. Customers still want an equal mix of traditional, remote and self-service channels (face-to-face, inside sales, e-commerce, etc.), but their preference for online ordering and reordering continues to grow. It is considered that
Winning companies, those that are growing their market share by at least 10% each year, tend to leverage advanced sales technology. Build hybrid sales teams and capabilities. Tailor your strategy for third-party and proprietary marketplaces. Deliver ecommerce excellence across the funnel. Provides hyper-personalization (unique messages for individual decision makers based on both past and projected needs, profiles, behaviors and interactions).
Digitization and automation are making incremental changes
AI technology is evolving rapidly. Implementations are becoming easier and cheaper, but they are also becoming more complex and faster than human capabilities. Our research suggests that one-fifth of current sales team functions could potentially be automated. Additionally, the rise of generative AI is pushing new ground (see sidebar, What is Generative AI?). Additionally, venture capital investment in AI has increased 13-fold over the past decade. This has led to an explosion of “usable” data (data that can be used to formulate insights and suggest concrete actions) and accessible technologies (such as increased computational power and open-source algorithms). bottom. Today, the vast amount of data available for training underlying models continues to grow, with computational power increasing a millionfold since 2012, doubling every 3-4 months.
What does Gen AI mean for marketing and sales?
The rise of AI, especially artificial AI, has the potential to impact three areas of marketing and sales: customer experience (CX), growth, and productivity.
For example, CX can deliver hyper-personalized content and services based on individual customer behavior, personas, and purchase history. Leverage AI to dramatically improve your sales and accelerate growth by giving your sales team the right analytics and customer insights to capture demand. In addition, AI can improve sales effectiveness and performance by offloading and automating many routine sales activities, freeing up capacity to spend more time with customers and prospects. (while reducing service costs). Personalization is key in all these actions. Combining AI with company-specific data and context enables insight into the consumer at the most granular level, enabling his B2C-powered personalization through targeted marketing and sales services. His successful B2B company overuses hyper-personalization in outreach beyond account-based marketing.
Bringing Gen AI to life in customer journeys
There are many Gen AI-specific use cases that can impact you across the customer journey.
- At the top of the funnel, gen AI surpasses traditional AI-driven lead identification and targeting using web scraping and simple prioritization. The advanced algorithms of Gen AI are Leverage customer and market data patterns to segment and target relevant users. With these capabilities, businesses can efficiently analyze and identify high-quality leads for more effective and customized lead activation campaigns (sidebar, Generation AI for Sales See Use Case: Dynamic Audience Targeting and Segmentation).
Additionally, gen AI optimizes marketing strategies through A/B testing of various elements such as page layouts, ad copy, and SEO strategies, leveraging predictive analytics and data-driven recommendations to ensure maximum return on investment. To do. These actions can continue throughout the customer journey with gen AI automating lead nurturing campaigns based on evolving customer patterns.
- In the sales process, gen AI goes beyond the initial sales team engagement to provide ongoing and critical support throughout the sales process, from proposal to closing the deal.
With the ability to analyze customer behavior, preferences and demographics, gen AI can generate personalized content and messaging.From the beginning, it can help Hyper-personalized follow-up emails at scale and contextual chatbot support. It can also act as a 24/7 virtual assistant for each team member, providing customized recommendations, reminders and feedback to increase engagement and conversion rates.
As the deal progresses, Gen AI will be able to offer: Real-time negotiation guidance and predictive insights Based on comprehensive analysis of historical transaction data, customer behavior and competitive pricing.
- After customers sign the dotted line, there are many generative AI use cases, such as onboarding and retention. As new customers join, Gen AI can provide: A warm welcome with personalized training content, highlight relevant best practices. Chatbot functionality allows you to answer customer questions instantly and enhance training materials for future customers.
Gen AI can also provide sales leadership with real-time next-step recommendations and continuous churn modeling based on usage trends and customer behavior. moreover, Enable dynamic customer journey mapping Identify key touchpoints and drive customer engagement.
Commercial leaders are optimistic and profitable
We asked a group of commercial leaders to provide their perspectives on the use cases and role of generational AI in broader marketing and sales. In particular, there was general cautious optimism. Respondents expected at least moderate impact from each of our proposed use cases. In particular, these companies are most enthusiastic about lead identification, marketing optimization, and personalized outreach use cases early in the customer journey (Exhibit 1).
All three of these use cases, focused on lead generation and lead generation, are seeing great momentum in the early stages. This is not surprising given the vast amount of data about prospects available for analysis and the historical challenge of personalizing early marketing efforts at scale.
Various companies are already implementing AI use cases, but this is arguably just scratching the surface. According to our survey, 90% of commercial leaders expect to “frequently” use generational AI solutions over the next two years (Figure 2).
Overall, the most effective companies prioritize deploying advanced sales technology, building hybrid teams, and enabling hyper-personalization. We also make the most of e-commerce and third-party marketplaces through analytics and AI. Successful companies have found that:
- Have a clearly defined AI vision and strategy.
- Over 20% of digital budgets are invested in AI-related technologies.
- A team of data scientists are employed to run algorithms to inform rapid pricing strategies and optimize marketing and sales.
- Strategists look to the future and outline simple generative AI use cases.
Pioneers like these already recognize the potential of genetic AI to improve their own operations.
Risk prediction and mitigation in genetic AI
The business case for artificial intelligence is compelling, but the speed of change in AI technology is staggeringly fast and not without risk. When a commercial leader was asked about the biggest barriers limiting her organization’s adoption of AI technology, internal and external risks topped the list.
From intellectual property theft to data privacy and security, there are many issues that require thoughtful mitigation strategies and governance. The need for human oversight and accountability is clear, and new roles and capabilities may need to be created to maximize the opportunities ahead.
Beyond immediate action, leaders can start thinking strategically about how to invest in AI commercial excellence for the long term. It is important to identify which use cases are key factors and which use cases will help differentiate your market position. Then prioritize based on impact and feasibility.
The AI landscape is evolving so rapidly that today’s winners may not be tomorrow. Small start-ups are great innovators, but they may not be able to scale as needed or create sales-focused use cases that meet their needs. Test and repeat with different players, but strategically pursue partnerships based on sales-related innovation, speed and time to market of innovation, and ability to scale.
AI is changing at breakneck speed, and while it’s difficult to predict the fate of this game-changing technology, it’s sure to play an important role in the future of marketing and sales. Leaders in this space are succeeding by turning to generative AI to leverage advances in personalization and internal sales excellence to maximize their operations. How will your industry react?
