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Accelerating Conversational and Multimodal Research: The New Marketing Landscape
In recent days, the marketing sector has witnessed an intensification of the debate and investments in Conversational and Multimodal Search , driven by announcements from major AI vendors, global events, and case studies of its application in omnichannel campaigns. Advanced tools are making the exchange between voice, text, image, and video increasingly natural, expanding touchpoints and adding more data to the martech ecosystem.
Multimodal AI and omnichannel: New standards in customer experience.
ElevenLabs, a leader in conversational AI, announced advancements that enable simultaneous text and voice comprehension, making interactions more flexible and reducing friction, especially in the customer service and content consumption journey[1]. This evolution reflects the moves of Google, which presented new multimodal integrations and visual and voice search features at Google Marketing Live 2025[6], confirming the leading role of omnichannel and expanded interactivity. Recent data indicate that seamless experiences across WhatsApp, Instagram, web, and apps are already mandatory—65% of consumers abandon purchases if they have to repeat data across different channels[2].
Multimodal SEO and growth: Engagement across multiple formats and smarter attribution.
Multimodal SEO has gained prominence in the sector, requiring brands to optimize content not only for text, but also for images, videos, and audio, prioritizing responses to natural and conversational queries made via virtual assistants or visual search[8]. The market is witnessing the maturation of cross-channel campaigns that use real-time conversational triggers, chatbots trained by generative AI, and dynamic segmentation based on real-time customer interactions. Examples include global brands such as L’Oréal and Flipkart, which drive growth and intelligent attribution with conversational AI stacks and predictive behavioral data analysis[3].
Strategic impacts and next steps for marketing professionals.
Trends point to an increasing integration between structured and unstructured data, enabled by high-performance multimodal language models that already operate from sentiment understanding to automatic product recommendations or personalized visual content[4][5]. For brands seeking to be at the forefront, the challenge lies in adopting open platforms, strengthening their data layer, and migrating from repetitive marketing to AI-optimized conversational experiences—measuring not only conversion, but also satisfaction, engagement time, and cross-channel continuity.
References
- [1] elevenlabs.io/pt/blog/introducing-multimodal-conversational-ai
- [2] kmedia.co/pt/%F0%9F%94%AE-tendencias-emergentes-en-marketing-conversacional-para-2025/
- [3] marcasemercados.com.br/comercio-conversacional-veja-seis-tendencias-para-2025/
- [4] siliconflow.com/articles/pt/best-multimodal-ai-for-chat-vision
- [5] blog.madrigan.com/pt/blog/202511051307
- [6] artefact.com/br/blog/google-marketing-live-2025/
- [8] grayhat.com.br/t/guia-definitivo-de-seo-multimodal-2025/14
