B2B营销中人工智能使用现状（英文版）_28页_638kb

Summary of "The State of Artificial Intelligence in B2B Marketing"

Core Content

This report explores the current state of Artificial Intelligence (AI) adoption in B2B marketing and sales. It is based on a survey of over 100 B2B marketing and sales professionals from organizations with annual revenues of $25 million or more, conducted by Demand Metric in partnership with Demandbase and Salesforce Pardot.

The report outlines the growing awareness and interest in AI, highlighting both the promise it holds and the challenges in its implementation. It provides actionable insights and an action plan for B2B marketers looking to leverage AI in 2019 and beyond.

Main Findings

Understanding of AI

• Marketers rate their understanding of AI as "average" or better in over 75% of cases.
• The average self-assessment is about a C+, indicating room for improvement.
• Larger companies tend to have a higher understanding of AI, as their average grade increases with annual revenue.

AI Adoption

• 84% of participants are either planning, evaluating, implementing, or using AI.
• Less than 1 in 5 (i.e., 20%) are currently using AI for marketing and sales.
• There is a clear trend toward increased awareness and interest in AI.

Perceived Value of AI

• AI is perceived as having the highest value in MarTech (Marketing Technology) applications.
• 40% of participants are either unaware of AI capabilities in their current vendor solutions or not using them.
• AI is expected to significantly improve lead quality, engagement, and buyer intent understanding.

Top AI Applications

• The most interest is in top-of-funnel applications, such as:
  • Improving the reach of digital advertising
  • Identifying the right accounts or individuals to target
• Real-time website personalization and automated sales assistants (e.g., chatbots) are the top applications of AI in marketing and sales.

AI Implementation Strategy

• More buying than building is the preferred strategy for AI adoption.
• Data scientists are becoming part of marketing teams, but are not a prerequisite for AI adoption.
• Vendor solutions are seen as a way to offset skills gaps and reduce implementation costs.

Time-to-Value of AI

• 60% of marketers expect to see value within six months.
• 75% of current AI users report a time-to-value of less than six months.
• Marketers are bullish on the short-term benefits of AI.

Revenue Impact of AI

• Over 70% of the full survey sample forecast double-digit revenue lift from AI within two years.
• 85% of current AI users expect double-digit revenue increases within two years.
• 20% or more revenue lift is anticipated by almost three times as many current AI users compared to the full sample.

Barriers to AI Adoption

• The top barriers to AI adoption are:
  • Cost/budget constraints
  • Skills and expertise
• These barriers are offset by:
  • Revenue lift from AI
  • Built-in AI capabilities in vendor solutions

Optimism Toward AI

• Over 75% of B2B marketers are either cautiously optimistic or wildly excited about AI's potential.
• Current AI users show unbridled enthusiasm, indicating that the benefits are real and impactful.

Key Insights

• AI is not yet widely implemented in B2B marketing and sales, but interest and planning are high.
• MarTech is the area where AI is seen as most valuable.
• Top-of-funnel applications are the most popular and expected to deliver significant results.
• Vendor solutions are the preferred route to AI adoption, especially due to their built-in capabilities and cost-effectiveness.
• Data scientists are increasingly involved in marketing, but not essential.
• Short-term revenue lift is a major driver of AI adoption.
• Skills and cost are the main challenges, but vendor AI capabilities help mitigate these.

Action Plan

1. Learn

   • Stay informed through industry analysis, case studies, webinars, and existing content.
   • Understand how AI is evolving and what it can do for your marketing and sales efforts.

2. Set an Objective

   • Focus on improving digital advertising reach or identifying the right accounts as top priorities.
   • Choose one of these or another clear objective for your AI initiative.

3. Lean on Your Vendors

   • Explore the AI capabilities already embedded in your MarTech and sales platforms.
   • Vendors are often eager to help you leverage their AI tools.

4. Run an Experiment

   • Start with a small-scale experiment to understand how AI works in your context.
   • Use insights from these experiments to refine and scale your AI strategy.

5. Build Momentum

   • Measure the results of your initial experiments.
   • Fine-tune and expand your AI initiatives based on performance.

Conclusion

AI is poised to revolutionize marketing and sales performance in B2B organizations. While many are still in the planning or evaluation phase, the potential for revenue growth is high, and the time-to-value is faster than anticipated. Marketers are optimistic about AI's ability to transform their programs, and the key to success lies in starting early, leveraging existing vendor capabilities, and focusing on top-of-funnel applications.