Mindspeller is an AI-powered technology that helps marketers optimize their brand’s tone of voice to ensure a customer experience that truly resonates.
Their technology is rooted in understanding how neuroscience and word semantics can influence consumers’ behavior. Mindspeller’s AI drives brand equity by tracking companies’ brand maps of implicit associations and uses that data to influence consumer behavior.
We spoke with Mindspeller’s cofounder and CEO Hannes De Wachter to learn more.
In a single sentence or statement, describe your company.
Our technology can help optimize your brand equity based on neurosemantic AI.
How does your company use artificial intelligence in its products?
We use natural language processing techniques to retrieve, group and predict word associations and their emotional effect in semantic contexts. We use artificial intelligence techniques to support the said processes (retrieve, group and predict), i.e. graph-based artificial intelligence.
What are the primary marketing use cases for your AI-powered solutions?
Mindspeller’s technology is primarily leveraged in three marketing use cases; neurobranding (brand strategy), content testing and optimization, and brand tracking on the implicit level. Ultimately, these use cases can help drive 95% of consumer behavior.
What makes your AI-powered solution smarter than traditional approaches and products?
Mindspeller manages the world's largest implicit brand association network based on spontaneous, human (not machine!) brand associations. Our network covers the entire natural language and is validated with medical-grade BCI paradigms that are starting to decode the subconscious ("System 1") mind.
Mindspeller software applications offer the value of high-end consumer neuroscience (i.e. medical-grade EEG focus group testing) at a fraction of the cost and via a user-friendly, do-it-yourself user interface.
Are there any minimum requirements for marketers to get value out of your AI-powered technology? (e.g. data, list size, etc.)
Marketers must upload their brand assets (logos, key visuals, campaign content, etc.) and select their intended associations.
Who are your ideal customers in terms of company size and industries?
We serve both SMEs who are just starting to invest in branding as well as big corporations who are considering a re-branding strategy or want to claim a unique verbal brand identity.
What do you see as the limitations of AI as it exists today?
Traditional AI that is used in martech is typically based unilaterally on black-box machine learning (e.g. co-occurrence based semantics). This strategy is not without risk, as has been proven. For example, consider how Disney pulled out of an AI-driven Google/YouTube campaign that was attracting pedophiles to their content. Also, consider AI that is completely replacing the human marketer, yet produces large quantities of meaningless content/spam, rather than meaningful content that truly resonates.
What do you see as the future potential of AI in marketing?
We believe in neuroscience to drive brand equity via “explainable” (rather than blackbox) AI. We think it is too early to consider replacing the human marketer with AI. Instead, we want to augment the intuition of the marketer with AI that is helping to decode the “System 1” biases that consumers have.
Any other thoughts on AI in marketing, or advice for marketers who are just starting with AI?
Always investigate the underlying methods of the AI being used. If the algorithms are only using machine data (i.e. large data-sets scraped from online forms) the insights derived will not be of the same predictive nature as AI applied to real human (spontaneous) association data. The latter should of course be considered only in a statistically relevant context.
Paul Roetzer is founder and CEO of Marketing AI Institute. He is the author of Marketing Artificial Intelligence (Matt Holt Books, 2022) The Marketing Performance Blueprint (Wiley, 2014) and The Marketing Agency Blueprint (Wiley, 2012); and creator of the Marketing AI Conference (MAICON).