Crafting Words that Sell: How Persado Harnesses Specialized Language Models for Marketing

Large Language Models (LLMs) have become a transformative force in the marketing industry. Their sophisticated algorithms and vast data processing capabilities can automate and optimize a wide array of marketing functions, including content creation and management, ad copywriting and customer interaction, personalization and SEO enhancement, and market insights and campaign optimization. Through these applications, LLMs not only streamline and enhance the efficiency of marketing operations but also enable more creative and tailored marketing strategies. This integration of advanced AI tools allows marketers to better engage with consumers, leading to increased loyalty and improved business outcomes.

Getting started: Choosing the right LLM for your Brand

Well-known LLMs such as those from OpenAI, Google or Anthropic are engineered to perform a broad range of tasks across diverse datasets. These models are trained on the “Wild West” of the Internet, meaning they may not always deliver relevant results for specialized content generation. This can be a limitation when brands require highly tailored content that resonates with a niche audience or adheres to a unique brand voice.

Specialized models based on open-sourced LLMs, like Llama or Mistral, however, are a compelling alternative for organizations looking to infuse their specific domain knowledge into generated content. These models can be fine-tuned on a proprietary dataset—a process that involves retraining the model on text that is closely aligned with a company’s communication style and the preferences of its target demographic. This process allows companies to mold the model’s outputs to better match the tone, style, and subtleties specific to their brand, enhancing the relevance and impact of marketing content. Moreover, using open-sourced models mitigates dependency on external providers, offering greater control over the model’s development and usage, which can be crucial for maintaining competitive advantage and compliance with data privacy regulations.

Persado, a generative AI for marketing solution trusted by some of the world’s leading brands in financial services, retail, travel, and telco, has utilized open-sourced models to create Motivation AI, a specialized class of enterprise generative AI that delivers personalized customer engagements and significant business impact.

Evolution of Motivation AI

To create the Motivation AI platform, Persado has leveraged advanced machine learning techniques, such as Supervised Fine-Tuning (SFT) and Reinforcement Learning from Human Feedback (RLHF), to enhance the relevance and impact of its campaign messages across diverse industries, channels, and languages. By training its models on a rich, proprietary dataset encompassing a wide array of campaign messages, Persado’s LLMs have been tailored to capture nuanced communication patterns that resonate across different sectors. The SFT approach allows these models to learn from specific examples that embody successful communication tactics, enhancing their ability to generate compelling content that aligns with varied marketing objectives.

Additionally, Persado employs RLHF to refine the quality of content further. This method utilizes direct feedback from campaign performances to teach the models what constitutes effective versus less effective content. By continuously learning from real-world interactions and user engagements, Persado’s models adapt and evolve to produce increasingly effective messages that are not only engaging but also directly contribute to the campaign’s success.

When crafting messages for individual clients, Persado Motivation AI incorporates the client’s brand guidelines through sophisticated prompt engineering techniques. This ensures that every piece of content generated adheres to the brand’s voice and tone while aligning with their strategic marketing goals. By integrating these guidelines into the model’s inputs, Persado guarantees the resulting messages uphold the brand’s identity and resonate with its target audience.

Measuring — and Anticipating — the Performance of LLMs in Marketing

The effectiveness of Large Language Models (LLMs) in marketing campaigns can be quantitatively assessed using a variety of key performance indicators. Metrics such as engagement rates, which track how audiences interact with content (likes, shares, comments), and conversion rates, measuring the percentage of audience members who take a desired action (such as making a purchase or signing up for a newsletter), are crucial. Additionally, the overall ROI provides a comprehensive view of the financial impact generated by campaigns using AI-created content.

Persado applies advanced AI technologies to predict the performance of LLM-generated marketing messages by leveraging data from past campaigns. With our lighter, self-service solution, Generate and Predict, marketing teams can see a predicted performance score for every message (screenshot shown below).

Using machine learning algorithms, Persado identifies trends and insights from previous campaigns, such as which phrases, emotions, or call-to-actions resonated most effectively with various audience segments. This process allows the platform to forecast the potential success of future messages and optimize them for increased engagement and conversion rates. 

Persado also illustrates the unique content insights designed to help clients track and analyze the performance of their past marketing campaigns. This sophisticated dashboard provides a comprehensive overview, highlighting the performance trends across different tags that categorize messages by emotional, descriptive, and linguistic elements, such as intros, calls-to-action (CTAs), and more.

Persado offers marketers a comprehensive content insight dashboard that tracks and analyzes the performance of their past campaigns. This helps them understand which specific linguistic components, tagged by Persado’s proprietary tagging system, drive campaign effectiveness and why.

Detailed Insights Offered by the Dashboard

• Top Performing Tags: This section lists the most effective tags such as ‘Intimacy’, ‘Fascination’, and ‘Gratification’. These tags represent emotional or thematic elements that have resonated the most with audiences, giving marketers direct insights into which emotional triggers are driving engagement and conversions.
• Language Performance: This allows users to drill down into specific elements of campaign content. Users can analyze how different components—like headlines, subheadlines, CTAs, and body text—perform under different campaign tags. This level of detail enables marketers to fine-tune every aspect of their message to optimize engagement and effectiveness.
• Campaign Overview Metrics: The dashboard provides essential metrics such as the Persado Conversion Rate and Persado Impressions, alongside totals of deployments and messages. This summary allows users to quickly gauge the overall impact and reach of their campaigns.
• Filtering and Segmentation: Users can filter and segment data based on various criteria, such as the time frame, channel type, and more. This feature enhances the ability to monitor trends over time and adapt strategies based on actionable analytics.

The integration of these insights into a single, user-friendly interface empowers marketers to leverage past campaign data effectively. By understanding which tags and message elements perform best, you can craft future communications that align more closely with proven strategies, ultimately leading to improved campaign outcomes and more effective use of marketing resources.

Maintaining Data Privacy, Consumer Trust and Authenticity with LLMs

The use of Large Language Models (LLMs) in marketing raises critical ethical challenges that businesses must navigate to maintain consumer trust and comply with stringent regulations. Transparency is a key issue, as AI’s ability to produce human-like content can obscure the distinction between human and machine-generated communications. It’s crucial for companies to disclose when content is AI-generated to ensure clarity and prevent deception. Additionally, data privacy is of paramount importance since LLMs often rely on extensive datasets, including sensitive customer information. Firms are obligated to securely manage this data and adhere to strict privacy regulations like the GDPR in the EU or the CCPA in the US to safeguard consumer data and avoid breaches.

Moreover, the authenticity of AI-generated communications presents a significant concern. While LLMs are capable of producing compelling, high-quality texts that can enhance marketing strategies, there is a risk of generating misleading content. Companies must responsibly use AI, establishing clear guidelines for what AI can generate and actively monitoring its output to prevent unethical practices. Effectively addressing these ethical issues extends beyond mere legal compliance; it involves cultivating a corporate culture that values consumer rights and fosters lasting trust. Engaging proactively with regulatory bodies, consumer groups, and industry experts helps companies stay abreast of ethical standards and adapt their practices, thereby mitigating risks and positioning themselves as leaders in ethical AI usage, which attracts consumers who prioritize transparency and integrity.

Persado addresses ethical considerations in its use of Large Language Models (LLMs) for content generation through clear strategies focused on transparency, data privacy, and authenticity.

• Transparency: Persado tackles transparency concerns with two distinct product offerings. The “Essential Motivation” product is a self-service option where content generation is directly handled by LLMs. In contrast, the “Elite Motivation” product involves a more hands-on approach. Here, Brand Content Strategists (BCS) play a crucial role in optimizing inputs to the LLM for each campaign. They also review every piece of content generated by the LLM, ensuring it meets the required standards before it is finalized. This tiered product approach allows customers to choose the level of human oversight they prefer in their content creation process.
• Data Privacy: Persado employs several techniques to safeguard sensitive information, for example, data normalization to standardize elements like specific offer numbers and currency amounts, reducing the risk of sensitive data exposure. Additionally, data anonymization is implemented to remove person identifiers (e.g., person name), brand-specific info (e.g., brand name, product name) from messages, further protecting privacy and ensuring that the content cannot be traced back to any individual or sensitive corporate information.
• Authenticity: Ensuring the authenticity and ethical integrity of communications is a cornerstone of Persado’s strategy. The AI platform is meticulously designed to generate marketing language that is not only effective but also aligns seamlessly with each client’s brand voice and ethical guidelines. Persado provides robust tools that allow clients to review and adjust AI-generated content before it goes live. This ensures that all communications are accurate, resonate with the brand’s values, and uphold ethical standards.

Through these comprehensive measures, Persado enhances the effectiveness of its marketing solutions while ensuring they meet high ethical standards, fostering trust and aligning with clients’ values.

The Bottom Line: Sales

In a world of digital noise, GenAI should deliver not just outputs, but also outcomes.

The integration of Large Language Models (LLMs) into marketing has transformed how brands create content, engage with customers, and optimize strategies. These models, varying in their capabilities and applications, require careful selection and customization to align with specific brand needs and ensure content consistency across all digital platforms. After all, not all LLMs are created equal.

Persado’s product suite, built on the Motivation AI platform, showcases a robust implementation of LLM technology, where open-source models are meticulously selected and fine-tuned on tailored datasets to ensure high personalization and brand coherence in every message. The integration of features like predicted performance and brand alignment scores empowers marketers by providing insights into how well each message aligns with the brand’s identity and its potential effectiveness in driving conversions and ROI in real-time campaigns.

The business impact is proven. Persado Motivation AI creates AI-generated content that consistently outperforms your best copy 96% of the time, driving 41% more conversions, on average. And for our financial services clients alone — including 7 of the 10 largest U.S. banks — Persado has driven more than $2.5B in incremental revenue.