This article is Part 3 of our three-part series on the Best AI Training Courses for Digital Media Publishers. It focuses on Sales and Chief Revenue Officers. Part 1 covers training courses for Content Creators, and Part 2 covers training courses for Ad Ops Professionals.

Publishers have faced several challenges in recent years, from shifting social media algorithms to consumer burnout due to an overload of online content to constant updates by Google. Despite improvements in analytics and insights, “more of the same, but faster” no longer works. 

To address these challenges, publishers are increasingly turning to Artificial Intelligence.

BuzzFeed, for example, operates over six AI copilots that automate RFP writing, recommend sellable products, and answer Q&A to aid sales teams. Forbes and the Financial Times have recently introduced AI chatbots for on-site search.

91% of publishers believe AI will impact their business over the next few years. 

According to a McKinsey report, players who invest in AI are witnessing a revenue uplift of 3-15% and a sales ROI uplift of 10-20%. In 2023, the use of generative AI in business processes grew by 400%, and RevOps was the largest adaptor with 48% use cases. 

In sales and RevOps, AI can significantly enhance efficiency and reduce manual workloads.

AI has a wide range of use cases, from automating RFPs to providing ad product recommendations to helping sales teams develop ideas and strategies through creative brainstorming.

To successfully implement AI in sales and RevOps, publishers must assess their current processes and identify areas where AI integration can be most beneficial. This means:

  • Finding AI platforms that integrate seamlessly into existing systems
  • Making predictive recommendations with AI
  • Automating workflows
  • Using AI to uncover new revenue opportunities
  • Leveraging AI-driven insights for learning and decision-making
  • Augmenting creativity with AI

A truly transformative approach to AI will require publisher teams to develop a foundational understanding of AI and select the right tools to meet their needs. Proper training is thus crucial. 

We look at some good training courses and resources that could help Sales and RevOps professionals within digital media publishing to leverage AI capabilities better. 

 

What must Sales and RevOps teams look for in AI training? 

While innovation, strategic judgment, and networking of Sales and RevOps professionals will remain key to revenue growth, AI tools can supercharge processes by making them more efficient. 

A good AI training/resource must enable teams to:

  • Grasp what is happening around AI and how it matters
  • Provide hands-on exposure to tools relevant to their work needs
  • Match their skill level and their current understanding of AI
  • Cover tools and skills that enable them to perform jobs faster and more efficiently
  • Provide access to career paths by expanding on skills they already possess

As AI models evolve, their use cases expand. To maintain a competitive edge, forward-looking sales, and chief revenue officers must be aware of this evolving landscape. 

The training programs and resources listed below will provide good exposure to essential skills and knowledge required to understand and implement AI effectively.

 

1. AI for Everyone (Course)

Understanding fundamentals is the first step to implementing AI tools. DeepLearning.AI’s AI for Everyone is a good place to start.

This non-technical course is designed to help understand AI fundamentals and spot opportunities to apply them to real-world use cases. It includes examples of what today’s AI can and cannot do and how AI impacts society. It also touches on how to navigate this technological change.

The course is divided into four modules with a total duration of 6 hours and can be completed at your own pace. 

The course costs $49 and has over 40,000 reviews (4.8/5) on Coursera.

2. AI Strategy for Sales and Marketing (Book)

Katie King, CEO of AI in Business, a firm specializing in AI consultancy and training, presents a comprehensive framework for implementing AI in her book, AI Strategy for Sales and Marketing.

She demonstrates how AI can enhance customer-centricity and drive sales through a cohesive strategy that delivers value now and in the future. Chapter 2 of the book lists interesting AI tools for sales professionals:

  • Chorus: Automatically transcribes and analyzes sales calls, identifying agreed-upon next steps and collating conversation histories and insights for contacts.
  • Prospx: Uses AI to understand businesses, their marketing objectives, and ideal clients, offering a cost-effective way to target promising leads and providing tailored results as the engine learns more.
  • Aviso: Helps sales reps with deal forecasting and statistical modeling to predict the probability of opportunities in the sales pipeline.
  • Outreach: Provides an AI-powered dashboard that shows which prospects are engaged, when contact was last made, and what opportunities exist based on data insights.
  • People.ai: Analyzes activity and contact history to anticipate risk, make recommendations, and provide insights about prospects. It also tracks individual performance against targets and offers coaching to improve team performance.
  • Clari: Streamlines CRM updates, alleviates the data entry burden for sales teams, and manages sales and forecasting with predictive insights.
  • Cresta: Learns the most effective replies to customer questions from the best agents and provides real-time prompts to less effective agents.
  • Gong: Uses natural language processing to transcribe and analyze customer communications, providing higher-order insights to sales teams.
  • Rainbird: Allows companies to build visual models of their smartest employees' thought processes, using these models to automate decision-making with full explainability.

The book offers valuable insights for sales and RevOps teams to leverage AI for improved prioritization and efficiency, personalized automation, enhanced marketing capabilities, better customer experience (CX), strategic implementation, long-term benefits, and ethical considerations.

3. Generative AI for Sales and Services Professionals (Course)

This course on LinkedIn Learning is a comprehensive examination of Generative AI and its specific applications within the Sales and Services sectors.

The course is taught by Sam Mallikarjunan, the founder and former CEO of OneScreen.ai, CRO at Flock, Harvard instructor, and head of Growth at HubSpot Labs. 

It provides an understanding of the foundational principles of Generative AI, its algorithms, and its potential in automating tasks, generating data-driven insights, and creating dynamic content. 

The course also includes case studies that show the transformative impact of Generative AI in customer interactions, sales methodologies, and service optimization while examining the ethical considerations and practical challenges of implementing AI. 

The course fee is $30 and comes with a sharable certificate on LinkedIn.

4. AI for Marketing and Sales (Course)

This concise 14-hour course by BizHack Academy weaves together insightful strategy sessions, cutting-edge case studies, and hands-on AI tool demos to make AI accessible and actionable for marketing and sales professionals. 

The course is designed and led by a Pulitzer Prize-winning former NPR correspondent and features top AI experts and guests from Microsoft, Apple, and Disney.

Major topics covered: 

  • The Human Element of AI: Partner with AI to gain a competitive advantage and grow your business.
  • AI for Text Translation and Email: Master prompt engineering with a deep dive into ChatGPT and Jasper.
  • AI for Images, Social Media, and Ads: Learn the spellbook to create winning AI-powered images.
  • Inside Microsoft's Vision for AI: A "black belt" Microsoft engineer shares the latest productivity tools built on GPT-4.
  • AI for Video, Audio, and Podcasts: Create high-quality video and audio at a fraction of the cost.
  • AI for Content Strategy and SEO: Build a world-class content engine to improve online presence.
  • AI for Analytics, Forecasting, and Prediction: Use AI to analyze competitors, predict trends, and create winning strategies.

The course fee is $497.

5. Succeeding with AI for Sales (Expert insights)

In this article by Cloudtalk, eight experts share strategies for maximizing the benefits of AI for sales. Key takeaway:

Expert

Future of AI in Sales

Challenges

Recommendations

Blue Bowen, Research Principal at G2

AI will increasingly automate sales tasks, allowing reps to focus on high-value activities without replacing them.

Issues include data collection, storage, and measuring AI effectiveness.

Start by optimizing low-value tasks, addressing data privacy concerns, and selecting AI tools that integrate well with existing systems.

Bill Vesce, Director of Sales at Beautiful.ai

Expect email writing, calling, forecasting, outreach, and sales coaching automation.

Balancing AI for tedious tasks with human interaction where customers expect it.

Use AI for time-consuming tasks while maintaining the human touch in customer interactions.

Oleg, CEO & Founder at Reply

AI will act as a co-pilot in sales, enhancing efficiency and personalization.

Data privacy and associated costs.

Focus on a few tools and use cases, and start with one task to streamline with AI.

Lenka Brozmanova, Chief Marketing Officer at Nicereply

AI will streamline processes, save time, and create personalized experiences.

Ensuring high-quality data input and maintaining human oversight.

Choose AI solutions carefully, ensure quality control, and maintain a human touch in B2B sales.

Gaurav Sharma, CEO & Founder at Attrock

AI will enhance data collection, customize services, and automate prospecting.

AI hallucinations, inconsistent data, and training employees.

Gradually implement AI, win employee support, analyze tools well, and provide ongoing training.

Will Eychaner, Business Development Representative at Dataddo

Sales professionals using AI will have an advantage due to time savings on manual tasks.

Identifying effective tools and ensuring data quality and integration.

Ensure reliable data, secure integrations, and approach AI adoption with transparency and resources.

Irina Weber, Content Strategist at LawRank

AI will provide deep customer insights, automate low-level tasks, and enhance forecasting.

Training sales teams to use AI effectively and getting buy-in for new tools.

Assess current training tools, educate on AI sales tools, identify knowledge gaps, and conduct team meetings to review metrics.

David Pawlan, Co-Founder at Aloa

AI will enhance personalization in sales and streamline the cold outreach process.

Ensuring AI-generated content feels personalized and not like mass outreach.

Use AI to supplement and enhance the sales process, paying attention to details and not replacing the sales team.

6. Building AI-powered chatbots without programming (Course)

IBM’s Watsonx Assistant provides a user-friendly platform that equips non-technical, line-of-business users with everything they need to build personalized AI chatbots without writing code.

Marketing and sales professionals can use the platform to create powerful AI-powered chatbots to improve customer experiences, boost lead generation, and drive sales with fast, personalized customer support.

Key use cases include enhanced customer segmentation and targeting, customer lifetime value prediction, data-driven content planning, automated content generation, personalized content curation, A/B testing optimization, social media listening and insights, and SEO optimization.

This IBM course covers creating chatbots with IBM Watson tools and is a good place to start. It teaches how to leverage IBM Watson's Natural Language Processing capabilities to plan, implement, test, and deploy chatbots. 

Training modules cover an introduction to chatbots, working with intents, entities, dialogues, deployment, context variables & slots, and digressions (such as handling unexpected questions).

The course is spread over 12 hours (approximately) and can be completed at your own pace. It is free to audit under a 7-day free trial and requires a Coursera subscription for extended access.

7. No Code AI and Machine Learning: Building Data Science Solutions (Course)

This 12-week MIT course suits senior sales and RevOps leaders looking to learn how AI and ML solutions can be built to make data-driven business decisions. It helps understand the theory and practical applications of supervised and unsupervised learning, neural networks, recommendation engines, computer vision, and other AI concepts. 

 

Learning outcomes include:

  • Gaining a holistic understanding of the AI landscape for various business use cases.
  • A conceptual understanding of the most widely used algorithms.
  • Hands-on experience in building AI solutions using no-code tools.
  • Practical insights into various nuances involved in implementing AI solutions 
  • Critical thinking and problem-solving skills required to tackle business problems with AI

The course fee is $2,850. Registrations for the year are open until Aug 24, 2024.

8. Other helpful resources for Sales and Chief Revenue Officers

Artificial Intelligence Books for Leaders

Toby Sinclair's blog post offers a great path to learn about AI's evolving role through groundbreaking books written by pioneers and thought leaders in the field.

Its is a great way for leaders to understand, integrate, and leverage AI for digital transformations. 

How Will AI Impact RevOps (Webinar)

Myko’s Webinar on how AI will impact RevOps provides a well-rounded perspective.

 

Key takeaways:

RevOps and AI Integration

  • RevOps is critical in evaluating, implementing, and leading AI initiatives within organizations.
  • AI tools help derive valuable insights from company data, making RevOps essential in effectively managing and utilizing these insights.
  • For effective collaboration with AI tools, having great vendors as partners is key

System and Data Management

  • Ensuring clean and well-documented systems and data is essential 
  • Adopt new AI tools cautiously to ensure they are beneficial in the long term and not just short term.
  • The effectiveness of AI tools depends heavily on the quality and cleanliness of the data being used.

Strategic Approach

  • Companies should develop a clear data and CRM strategy, focusing on desired outcomes and backing them up with necessary data and metrics.
  • Start with basic data requirements and gradually expand as the system and strategy mature.
  • Begin with low-risk, easy-to-implement AI tools to ensure smooth integration and long-term success.

In summary, RevOps has a pivotal role in harnessing AI's potential to enhance business operations and make data-driven decisions more accessible and effective.

AI for Sales 101(Guide)

This comprehensive guide by SalesMind AI covers AI's benefits, challenges, and applications in sales, including lead generation, sales forecasting, and CRM integration.

It draws an interesting comparison between traditional vs. AI-driven sales approaches:

Feature

Traditional Sales

AI-Driven Sales

Decision-Making

Based on human intuition and experience

Data-centered, using predictive algorithms

Interaction Style

Personal, face-to-face engagement

Automated, often lacks a personal touch

Key Strength

Emotional intelligence and relationship-building

Speed and volume of data processing

Data Handling

Manual, reliant on individual interpretation

Automated, capable of handling large datasets

Response Time

Slower, due to reliance on human processing

Rapid, thanks to automation

Customer Engagement

Deep, built on trust and personal connection

Efficient, but may lack depth

Adaptability

Depends on individual skill and experience

High, powered by real-time data analysis

Overall Approach

Relationship-focused, intuition-driven

Efficiency-focused, data-driven

While providing strategies for using AI in sales, the guide discusses key applications of AI, including lead generation and qualification, personalized customer interactions, predictive analytics for sales forecasting, automation of routine sales tasks, and using AI for sales insights.

Using AI in Sales (Guide)

6sense has compiled an informative guide that looks deeper into the opportunities to implement AI in sales. It discusses 7 use cases for AI in B2B Sales while providing guidelines for integrating AI into existing processes, common mistakes to avoid, and AI tools for B2B sellers.

Key takeaways for integrating AI into sales:

  • Set clear goals for your AI implementation
  • Determine the data you need to generate insights
  • Prioritize the AI use cases that are most relevant for you
  • Understand the potential of AI in sales
  • Account for the time and cost of implementing AI

Common mistakes to avoid: 

  • Failure to establish clear goals
  • Inadequate data for AI implementation
  • Lack of appropriate team or technology
  • Attempting to address too many use cases simultaneously

Summary

AI presents transformative opportunities for Sales and RevOps teams in digital media publishing. Now is the time to invest in targeted AI training and leverage these advanced tools to enhance efficiency, uncover new revenue streams, and stay competitive. Now is the time to use what is already there, collaborate, ask questions, and get things moving.