Milena Traikovich is a seasoned demand generation strategist who understands that the modern consumer no longer wants to be talked at; they want to be heard. With her extensive background in performance optimization and lead generation, she has witnessed firsthand how traditional, linear funnels are being replaced by dynamic, real-time interactions. As brands move into messaging spaces to capture attention, Milena helps them navigate the complexities of AI-driven engagement to ensure every conversation adds value. Today, we discuss how the rise of conversational ads on platforms like Snapchat is fundamentally changing the digital marketing landscape by turning passive viewers into active participants.
Conversational ads are yielding 22% higher conversions and significantly lower acquisition costs than traditional formats. How do these automated interactions reduce the path to purchase, and what specific steps should marketers take to ensure their AI agents effectively handle complex customer inquiries during the initial rollout?
The efficiency gain happens because we are finally removing the friction of the “click-and-wait” experience that usually plagues mobile advertising. When a user can get a specific product recommendation or a technical answer instantly, the cognitive load drops and the purchase intent stays high, which is why we see a 20% lower cost per action compared to standard formats. To manage a successful rollout, marketers must map out every possible friction point in the customer journey and feed those specific scenarios into their AI models to avoid generic responses. It is crucial to start with a narrow, high-value scope—focusing on the top ten most frequent inquiries—before expanding the agent’s capabilities to more nuanced or emotional consultations. This data-driven approach ensures the agent provides genuine utility, acting as a bridge to the sale rather than a barrier that the customer has to navigate.
Integrating AI agents directly into chat feeds allows brands to engage with hundreds of millions of active users. How can a company transition its creative strategy from passive storytelling to active dialogue, and what metrics best capture the success of a conversation that doesn’t immediately end in a sale?
Transitioning to conversational commerce requires a complete mindset shift where the “creative” is no longer a static image or a video, but a branching logic tree of potential outcomes and personalities. Instead of focusing on a single punchline or a catchy headline, creative teams need to build a library of responsive dialogues that reflect the brand’s voice in a natural, back-and-forth setting. We measure success here through engagement depth and sentiment analysis rather than just the final conversion pixel. Even if a sale does not occur immediately, a user spending several minutes exploring credit health or product features with an AI agent represents a massive lift in brand affinity and future intent. We should be tracking “meaningful interaction rates” to understand how effectively we are moving users from curious observers to highly informed prospects who are likely to return.
Messaging platforms are seeing nearly a trillion interactions per quarter, suggesting that chat is becoming a primary conversion surface. What technical or branding hurdles do companies face when deploying their own AI agents into these private spaces, and how can they prevent “bot fatigue” among savvy younger audiences?
The scale of this shift is staggering, with platforms recording 950 billion chats in a single quarter, proving that users are already living in these private interfaces. The biggest hurdle for any brand is making sure their AI doesn’t feel like an uninvited guest or a telemarketer breaking into a private conversation between friends. To prevent “bot fatigue,” the interaction must be extremely value-heavy and contextually relevant to what the user is actually doing at that exact moment. We have to leverage the fact that over 500 million people have already interacted with My AI, which tells us that the hurdle isn’t the technology itself, but the relevance of the message. If the brand’s agent acts as a helpful concierge that solves a problem in three messages or less, younger audiences will embrace it as a tool rather than dismissing it as another intrusive ad.
Some organizations use AI to turn educational content, like financial health tips, into interactive experiences. How should brands decide which parts of their customer journey to automate versus keep human-led, and what does a successful step-by-step onboarding process look like for a user interacting with a brand’s AI?
The alpha testing with partners like Experian shows us that high-complexity, high-emotion topics like financial health are actually perfect for AI because it allows users to ask “embarrassing” or basic questions without feeling judged. Brands should look to automate the repetitive, data-heavy discovery phases where speed and accuracy are paramount, while reserving human intervention for high-stakes problem resolution or the final steps of a high-ticket closing. A successful onboarding process starts with a clear, transparent greeting that defines exactly what the AI can do, which helps set user expectations from the first second. From there, the process should be supported by “quick-reply” buttons that help the user navigate the initial menu of options without having to type out long sentences. This structured guidance reduces the “blank page” syndrome where a user is interested but doesn’t know how to start the dialogue with the bot.
When a chat interface handles everything from product discovery to final payment, the traditional marketing funnel collapses into a single screen. How does this shift change the way brands allocate their budgets, and what should be the primary focus when designing a persona for a brand-specific AI agent?
We are witnessing the end of the fragmented budget where awareness, consideration, and conversion are treated as separate, isolated line items in a spreadsheet. Because the entire journey now happens within a single chat window, budget allocation is shifting toward “engagement-at-scale” and optimizing the quality of the interaction rather than just buying cheap impressions. When designing the AI persona, the primary focus must be on technical reliability and brand-consistent empathy, ensuring the tone matches the native, informal vibe of the platform. The agent should never try to deceive the user into thinking it is a human, but it should behave like a highly knowledgeable, digital-first representative of the brand. This consistency across the single-screen experience is what ultimately builds the trust necessary to drive those 22% higher conversion rates we are seeing in the early data.
What is your forecast for conversational AI in social commerce?
I believe we are rapidly heading toward a digital economy where the “buy” button is eventually secondary to the “ask” button. In the next few years, we will see these AI agents evolve to remember past conversations across different sessions, creating a truly personalized shopping concierge for every individual user on the platform. As chat interactions continue to dominate, nearing a trillion interactions per quarter, brands that fail to develop a conversational strategy will find themselves essentially invisible in the most active digital spaces. Social commerce will no longer be about scrolling through an endless feed of static products, but about having a tailored, intelligent dialogue that results in a seamless, one-click purchase. The brands that master this interactive layer early will see their customer acquisition costs continue to drop as they build deeper, more direct relationships with their audience than ever before.
