Matthew Bernardini, Ceo And Co-founder Of Zenapse – Interview Series

Matthew Bernardini is nan CEO and Co-Founder of Zenapse, wherever he leads nan company’s imagination and oversees nan improvement of its proprietary AI instauration exemplary into category-leading products. With a inheritance arsenic a merchandise marketer, information strategist, and technologist, he brings a blend of entrepreneurial experience—having achieved 4 successful exits—and firm expertise from organizations specified arsenic JPMorgan Chase, Omnicom, and Capgemini.

Throughout his career, Bernardini has maintained a beardown liking successful artificial intelligence, psychology, user behavior, crippled theory, and statistics, which proceed to pass his activity astatine Zenapse.

Zenapse is an AI-driven level that boosts customer acquisition, engagement, and retention done emotionally intelligent experiences. Powered by nan world’s first Large Emotion Model (LEM), Zenapse uses psychographic insights and goal-based optimization to thief brands link much profoundly pinch audiences. Fast to deploy and easy to use, it delivers measurable results successful hours—not weeks—while reducing costs and expanding ROI.

Zenapse is built astir nan intersection of affectional intelligence and AI. What was nan ‘aha’ infinitesimal that led to nan creation of nan Large Emotion Model (LEM)?

Zenapse has a seasoned founding squad pinch backgrounds successful nan merchandise development, advertising, marketing, and customer acquisition spaces, pinch much than 100 years of mixed acquisition astatine companies for illustration Capgemini, Omnicom, and JP Morgan Chase. Over our careers, we’ve seen a caller paradigm displacement look for marketers, wherever AI has changed really we deliberation astir and prosecute pinch consumers.

In today's fast-paced integer landscape, customers expect personalized and resonant experiences crossed each touchpoints, but accepted trading solutions deficiency nan velocity and insights needed for real-time decision-making and struggle to meet these expectations. Simultaneously, from merchandise decisions to advertizing campaigns, leaders struggle pinch nan precocious costs of hiring aggregate squad members to complete this work.

To reside this need, we’ve built nan world’s first Large Emotion Model (LEM), which helps marketers summation gross and income by bringing affectional intelligence into their consumers’ experience. By orienting their connection towards what is of worth and liking to consumers, alternatively than a azygous “brand-first” message, brands tin create much meaningful interactions that lead to higher engagement, sales, retention, and customer acquisition.

How do you specify a Large Emotion Model (LEM), and really does it disagree technically and functionally from a accepted Large Language Model (LLM)?

Our Large Emotion Model (LEM) is simply a predictive AI motor powered by a dataset built connected knowledge of much than 200 cardinal consumers pinch 6 cardinal datapoints. Through AI-driven psychographic insights (i.e., beliefs, sentiments, and emotions), companies tin understand what motivates their customers to person – whether that’s nan features aliases benefits of a product, typical promotions and incentives, imagery aliases calls to action, past allowing them to prioritize nan marque acquisition contented to a consumer’s preference.

In opposition to our LEM, which focuses connected emotion and behavior, ample connection models (LLMs) attraction connected matter and functions related to earthy connection processing (NLP) without deeper insights into what different segments of audiences judge and value.

We’ve worked intimately pinch Google, done their Google Startup and Google Cloud Marketplace programs, arsenic good arsenic Comcast Lift Labs, to guarantee that our solution is enterprise-ready and meets nan needs of nan world’s astir demanding marketers.

Why do you judge affectional intelligence is nan “missing link” successful astir trading AI platforms today?

The elemental reply is that marketers person not been capable to genuinely understand their customers because existing bequest exertion focuses connected demographics and behavior. We seamlessly merge pinch devices from companies specified arsenic Adobe, Salesforce, and Google to present bonzer results.

95% of user decisions are subconscious and driven by emotion. Yet, for decades, brands person utilized demographic (e.g., zip code, race, income) and behavioral information to pass trading campaigns. While this type of information has its uses, astir acquisition decisions are driven by emotions, which these information points neglect to capture. As a result, marketers struggle pinch constricted accuracy and effectiveness, often resorting to generalized solutions.

Now, done our LEM, brands tin pat into psychographic insights to build this afloat image and summation income and revenue. The impervious of conception for affectional intelligence’s domiciled successful trading lies successful nan numbers: we’re helping household-name brands summation conversion rates by 40-400% and engagement upwards of 80%.

What are nan astir communal misconceptions you spot astir AI’s domiciled successful knowing quality emotion?

One of nan biggest misconceptions is that AI is present to switch marketers. At Zenapse, we’re taking a different attack – we’re helping marketers create trading and advertizing pinch affectional intelligence and AI that helps them diversify their perspectives done nan expertise to link and understand their customers connected a deeper, much affectional level.

Traditional campaigns person often relied connected lumping consumers into wide categories defined by demographics, for illustration age, income, and zip code, which ignores nan nuances of what humans genuinely attraction about. With our LEM, marketers tin align campaigns astir what matters astir to each person.

Instead of guessing what mightiness resonate, our level helps marketers confidently create experiences that genuinely resonate because it’s built connected a instauration of affectional intelligence. That’s not replacing nan quality touch – it’s making it stronger.

In your view, what separates hype from existent invention successful nan AI + EQ abstraction correct now?

We’re entering a caller era of trading that’s defined by emotionally intelligent experiences, not surface-level personalization.

Consumer behaviour has changed dramatically. The mostly of consumers now for illustration personalized experiences – they expect brands to cognize what they attraction about. This presents an opportunity for brands to leverage AI successful a measurement that creates deeper connections pinch their consumers.

The quality betwixt hype and existent invention is nan value of data. Our LEM is built connected knowledge of 300 cardinal consumers and six cardinal real-time information points, which gives brands a broad knowing of who their consumers are – thing they couldn’t person done earlier now.

What types of psychographic signals and real-time information powerfulness nan LEM, and really are these modeled into nan Data Lake?

The psychographics down our LEM are based connected 4 pillars:

1. Beliefs – we group beliefs into individual categories, including really they worth things for illustration money, knowledge, family, and belonging, among others
2. Emotions – deliberation astir really you respond aft seeing an advertisement aliases promotion. Does it bring you joyousness aliases make you anxious?
3. Activities – from farming to gaming, we relationship for each different types of real-world and integer activities
4. Behaviors – nan events and actions a user performs successful a company’s experiences, specified arsenic completing a form, watching a video, aliases making a purchase.

Consumers make buying decisions pinch their hearts arsenic overmuch arsenic pinch their minds, truthful we cognize that addressing nan affectional constituent is nan cardinal to unlocking existent worth crossed nan full customer lifecycle.

LEM is described arsenic leveraging 6+ cardinal information points crossed 300M+ consumers. What safeguards and ethical considerations are successful spot to guarantee privateness and transparency?

Privacy is nan halfway of our merchandise development. Our full exertion ecosystem is SOC2 compliant, and our dataset does not seizure aliases clasp immoderate user personally identifiable accusation (PII). Our information is aggregated and anonymized. We besides support clear soul policies and governance practices to guarantee ethical usage of AI successful each measurement of development.

Can you locomotion america done nan domiciled of ZenCore, ZenInsight, and ZenVision successful powering emotionally intelligent customer experiences?

ZenCore is our proprietary user psychographic exemplary and nan motor that powers our LEM. ZenInsight is nan information instauration of emotionally intelligent experiences. ZenVision, successful existent time, translates these insights into predictions connected which messaging aliases contented will resonate pinch a fixed psychographic conception and provides actionable recommendations for marketers. Together, these devices shape a full-stack solution for trading pinch affectional intelligence.

How does Zenapse accommodate affectional predictions crossed verticals for illustration retail, telecom, and healthcare? Are location immoderate astonishing manufacture usage cases?

We’re already moving pinch companies for illustration Comcast, Sam’s Club, Aeropostale, Bread Financial, Bayada Education and Action Karate to amended conversion rates of integer marque experiences by 40-400%. While nan affectional drivers alteration by vertical, nan model remains consistent: we decipher what matters to a fixed user and thief brands align their experiences accordingly.

What’s your semipermanent imagination for LEM—do you spot it evolving beyond trading into different domains for illustration healthcare aliases education?

Right now, we’re focused connected utilizing AI to thief marketers and advertisers amended subordinate to their customers, and arsenic our information continues to get amended complete time, truthful excessively will our LEM. We person precocious extended nan level beyond websites to support CTV done our business pinch LG Ad Solutions and their invention lab.  Our extremity is to widen our level cardinal user touchpoints by 2028 – video games, automobiles and connected homes to sanction a few.

How do you spot emotionally intelligent AI reshaping nan adjacent decade of integer experiences?

The expertise to present real-time, hyper-personalized experiences crossed each integer platforms is already much powerful than ever, creating caller opportunities for partnerships. AI and affectional intelligence will proceed to beryllium adopted, and arsenic these technologies and insights go progressively sophisticated, they will beryllium nan driving unit down trading efforts crossed each integer media.

Our squad is moving difficult to enactment up of this curve. We recently announced our partnership with LG Ad Solutions’ Innovation Labs to thief CTV advertisers present emotionally intelligent experiences crossed LG’s ecosystem of 200 cardinal smart TVs, and we’re moving to bring our insights to different screens, for illustration web, mobile, AVs, music, movies, connected cars, and more

We spot nan early of integer experiences being shaped by AI and affectional intelligence. Businesses that neglect to accommodate to this displacement consequence being near down by competitors who are quicker to respond to nan changes successful user preferences and behaviors.

Thank you for nan awesome interview, readers who wish to study much should sojourn Zenapse.