By now, you may be familiar with Persado’s Motivation AI–a class of generative AI that generates personalized communications at scale to motivate and engage every individual to act.
Dynamic Motivation expands on Persado’s personalization capabilities, moving beyond language alone to dynamically identify the best topic while tailoring messaging to the individual, live. In short, Dynamic Motivation automates what to serve and how to say it in real-time. Dynamic Motivation currently operates in both Email and Web channels.
Dynamic Motivation in Action
Dynamic Motivation leverages the Persado Motivation Knowledge Base, first-party data (user attributes), and customers’ decisioning input (rule-based logic) to deliver the winning combination of what to serve and how to say it. Dynamic Motivation easily and dynamically orchestrates decisioning, personalization, and delivery of motivating content for the individual across channels and topics.
For example, let’s take a look at how our Dynamic Motivation would curate content for two different individuals in real time.
You can see the difference in language, emotions, and how all these elements work together to best motivate customers to act.
How does it work?
Standard Persado Content Generation vs. Dynamic Motivation
Standard Persado content generation (e.g., Full Experiments, Predictive Content, etc.) requires you to upload a control, review multiple Variants, and configure and QA each of these Variants, and results in a single winner for each campaign. This process is repeated for each additional campaign.
With Dynamic Motivation, you can collaborate with Persado in a one-time setup phase to create a Dynamic Content Library, complete with pre-identified topics and accompanying rules/parameters for who and when to serve each topic. From there, Persado AI uses case decisioning and language personalization - just a handful of Variants (usually 6 to 8) can be delivered to tens of campaigns.
The 2 primary use cases of Dynamic Motivation are Shopping Cart and Topics.
Shopping Cart
Persado’s Dynamic Motivation for the online shopping cart uses Generative AI and our unique Motivation AI knowledge base to deliver the words that most motivate shoppers to complete their purchase. Tell Persado what customer attributes you have in your data, what the campaign goals are, and what words and phrases you currently use. Then add the Persado snippet to the checkout pages where dynamic content will appear and the Motivation AI Platform does the rest. The language and elements each user sees changes based on what is most likely to motivate them to act based on Persado’s Contextual Adaptive Algorithm, reducing the probability of cart abandonment.
Topics
You can think of Topics as two levels of personalization, one on top of another. Topics determine what subject to show a customer based on various attributes (e.g., gender, geolocation, reward status, etc.) and decisioning logic (e.g., show one Topic to women, show another to those located in New York, etc.); then, Dynamic Motivation determines which Variant of that subject message to show an individual customer. Topics are useful in making sure your customers are seeing the right type of content based on their individual data.
Once you’ve built your campaign’s Dynamic Content Library, you can utilize the Topics you wish to deploy.
Measuring Impact with Dynamic Motivation
In every Dynamic Motivation campaign, a holdout group percentage can be set. This means the specified percentage of the audience will not be served any Persado content and will see the email or web page exactly as it appears without our input.
Results will compare the average response rate of users in the Persado group against the holdout group.
Reporting
Once Persado has collected enough performance data, you’ll be able to see:
A financial summary that shows campaign return on ad spend (ROAS)
Projected metrics to evaluate the impact of the campaign over time at different audience splits
Insights on which emotional content tags are being served the most to your audience
Interactive charts that show response rate and impressions over time to enable understanding of impact and how content is being served based on decisioning by our adaptive algorithms.
KPIs
Once a topic has been selected for a user, the Adaptive Algorithm or Contextual Adaptive Algorithm chooses a Variant, based on clicks, as the standard for maximizing performance in real time.
For evaluating overall performance, we expect to leverage both CTR and Conversion Rate comparisons against the holdout group.
So, What Does This Mean for You?
Dynamic Motivation has many benefits, including:
Upgrade from Static to Dynamic Content: By upgrading from static to dynamic content, you can adapt and personalize to specific topics and individuals in real time, leveraging Persado’s Adaptive Algorithm that kicks in when an email is opened or when a user visits a website.
Reduce Manual Effort with Automated Decisioning: Dynamic Motivation allows you to automate the decisioning aspect of content delivery, enabling an unprecedented level of “set and forget” marketing. With just a one-time setup phase, Dynamic Motivation automatically chooses the best topic based on predetermined rules and attributes, freeing up your marketing resources.
Scale Motivation AI Personalized Content: You can dynamically serve personalized content across channels and topics. The ease with which Dynamic Motivation is implemented and executed makes it simple to scale large volumes of individualized messaging through a single campaign.
Distinguish Yourself from Competitors (Go Beyond Simple Offers/Recommendations): Motivation AI and machine-learning models are trained on enterprise communications, so you can distinguish your communications from competitors’ who are limited to personalizing product recommendations and cannot speak to an individual’s motivations–and that’s what makes the difference between a user converting or not.
Maximize the Efficiency of Your Tech Stack While Activating First-party Data: Personalize to the individual by activating first-party data attributes (e.g., behavioral, loyalty, transaction, profile data, language response patterns).