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Media & Consumer Technology

How Sales Compensation and AI Can Drive Growth

Author
Matt Bartels Principal

Artificial intelligence (AI) is revolutionizing commercial operations in the media and consumer technology space, enabling organizations to execute strategic growth initiatives more effectively through data-driven insights, task automation, content generation and actionable recommendations. However, AI alone cannot guarantee the success of growth strategies. Aligning sales compensation plans with growth objectives is equally crucial, as these plans motivate and reward behaviors that drive growth, such as acquiring new customers, expanding accounts, increasing product adoption and enhancing customer satisfaction.

The Current State of Sales Compensation

Sales compensation is a critical aspect of driving performance and retaining top talent. However, many media sales compensation leaders feel their current plans are not as effective as they could be. According to Alexander Group’s recent research, 79% of sales compensation leaders believe their plans could be more effective, and 91% are making changes to their plans in 2024. The primary focus of these changes includes adjusting plan measures and weights to better align sales incentives with strategic goals such as product focus and cross-selling.

Leveraging AI for Media Growth Strategies

Artificial intelligence is a major external shift that’s begun to impact compensation — 43% of compensation leaders are currently using, or plan to use AI in their sales comp plans. AI uptake is on the rise with a third of companies adopting solutions, with the belief that AI can revolutionize sales compensation design and administration.

AI enhances three core elements of the commercial model: data capture and analysis, strategy development and execution, and content and interaction generation. Depending on the growth strategy, AI employs different techniques such as machine learning (ML) and generative AI (GenAI).

  • Data capture and analysis: AI helps organizations gather, clean and interpret data from sources like customer interactions, market trends, competitor activity and social media. This enables understanding customer intent, behavior, preferences and pain points, while identifying new opportunities, segments and channels.
  • Strategy development and execution: AI aids in designing and implementing strategies based on data insights and models, optimizing segmentation, targeting, and positioning and predicting the success of new strategies.
  • Content and interaction generation: AI delivers relevant content and interactions to customers and prospects, assisting in lead generation, personalized communication, providing information and improving customer experience.
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Examples of AI-Driven Growth Initiatives

 

Growth Play

Data Capture & Analysis

Strategy Development & Execution

Content & Interaction Generation

Developing Qualified Pipeline

Capture and interpret unstructured prospect data (e.g., web analytics, social media, news articles)

Route leads based on intent and history

Generate hyper-relevant content across customer segments and persona groups

Cross-selling and Upselling for Profitable Growth

Recognize and prioritize new buying teams within accounts

Identify offerings to complement existing purchases

Hyper-personalize communication

Enhancing Service Delivery Quality & Efficiency

Track and manage to customer experience indicators

Develop high-performing service reps

Build off-the-shelf service documentation

Improving Revenue Planning & RevOps

Enable better decision-making with clean data

Improve forecasts and planning via advanced trend analysis

Use chatbots to get relevant commercial insights on-demand

Aligning Sales Compensation with Growth Objectives

Media sales compensation plans should align with growth strategies by incenting and rewarding behaviors that support growth. These plans can be fine-tuned using various levers:

  • Pay mix: Adjust the ratio of fixed to variable pay to reflect the complexity and value of sales tasks.
  • Measures: Define metrics that align with growth objectives such as revenue, margin, customer acquisition, retention, expansion and satisfaction.
  • Weights: Allocate percentages to each measure to emphasize their importance and balance different growth goals.
  • Thresholds: Set minimum performance levels required for incentive payouts, ensuring rewards for above-average results.
  • Accelerators: Increase incentive payout rates for exceeding targets to motivate high performance.

Optimizing Sales Compensation with AI

AI can help improve sales compensation management and design by providing insights, automating tasks, generating content, and recommending actions across various processes:

  • Data capture and analysis: AI collects and interprets data from sales performance, customer feedback, market trends and competitor practices to understand the impact of compensation on behaviors and outcomes.
  • Strategy development and execution: AI helps design effective incentive plans, optimizing levers such as pay mix, measures, weights, thresholds and accelerators.
  • Content and interaction generation: AI delivers relevant content and interactions to sales teams enhancing plan communication, understanding and satisfaction.

Here are some examples of how AI can integrate and support different sales compensation processes across these three elements.

 

Sales Compensation Process

Data Capture & Analysis

Strategy Development & Execution

Content & Interaction Generation

Plan Design

Analyze sales performance and compensation data to evaluate plan effectiveness and efficiency

Use ML models to simulate and compare different plan scenarios and outcomes

Use ML models to simulate and compare different plan scenarios and outcomes

Quota Setting

Analyze sales performance and market data to assess quota attainment and fairness

Use ML models to allocate and assign quotas based on historical and predictive data

Use GenAI tools to generate quota letters and reports

Payout Calculation

Analyze sales performance and compensation data to validate payout accuracy and timeliness

Use ML models to automate payout calculation and adjustment based on predefined rules and exceptions

Use GenAI tools to generate payout statements and dashboards

Plan Communication

Analyze sales performance and feedback data to measure plan understanding and satisfaction

Use ML models to segment and target salespeople based on their plan preferences and behaviors

Use GenAI tools to generate personalized plan messages and nudges

Using Sales Compensation and AI for Growth

AI is a powerful tool for executing growth strategies and driving revenue. However, its full potential is realized only when integrated with well-aligned sales compensation plans. By combining AI with world-class sales compensation, media commercial leaders can effectively motivate and reward behaviors that support growth and enhance both sales performance and overall organizational efficiency.

Need Help With Your Organization?

For more insights on how your sales compensation plans and artificial intelligence can drive growth, please visit Alexander Group’s Media page or contact us.

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