2025 Marketing Prediction: Expanding Search Optimization into Multi-Modal Search Channels

By Tracy A. Wehringer, MBA, Ph.D. Student, Moonshot-Strategy.com

"In 2025, search isn't confined to a box; it's everywhere, in every form—voice, image, and text. To thrive, brands need to be as dynamic and adaptable as the people searching for them, anticipating needs across every channel. Optimization now means being found wherever and however the client/customer asks." – Tracy A. Wehringer

Abstract In the digital age, search optimization has evolved far beyond traditional search engine optimization (SEO). As we approach 2025, the lines between text, voice, and image-based search are blurring, requiring brands to adapt to a multi-modal search ecosystem. This paper delves into the predicted trends in search optimization for 2025, emphasizing the growing importance of optimizing for voice search, visual search, and platform-specific search capabilities. Marketers must recognize the broader implications of these shifts.The expansion into multi-modal search channels challenges traditional marketing practices, demanding that brands become more agile, data-driven, and comprehensive in their approach. To remain competitive, brands must prioritize personalization, invest in AI technologies, and embrace multi-channel content strategies. This paper outlines a holistic approach to future-proofing brands, incorporating artificial intelligence (AI), machine learning, and content personalization to cater to diverse search modalities. Additionally, it explores industry-specific applications, emerging technologies such as augmented reality (AR) and brain-computer interfaces (BCIs), and ethical considerations surrounding data privacy and algorithmic transparency.

Impact on Marketers and Brands The shift toward multi-modal search will fundamentally reshape how marketers strategize and execute their campaigns. In the traditional SEO model, content creation focused primarily on written keywords and ranking on search engine result pages (SERPs). However, as voice, visual, and platform-specific search capabilities rise, marketers must now tailor content for a variety of different formats and devices.

Voice search, for example, is driving the need for conversational content, while visual search is pushing brands to invest in high-quality imagery and metadata optimization. Marketers will have to develop multi-format content that can be easily adapted across various platforms, like Alexa, Siri, to SearchGPT, Perplexity, and TikTok. This presents both an opportunity and a challenge—while new avenues for clients/customers engagement open up, the complexity of managing content across different search channels increases.

Additionally, the integration of AI and machine learning into search strategies means that marketers must adopt more dynamic, data-driven approaches. According to Gartner (2024), brands that effectively integrate AI into their marketing strategies can expect a 30% boost in overall efficiency and customer engagement. However, this requires significant investment not only in technology but also in the upskilling of marketing teams to handle advanced AI tools and predictive analytics.

Moreover, personalization will play a central role in future marketing efforts. As search algorithms grow more sophisticated, marketers will need to deliver highly tailored content that meets users’ specific search intents. This is no longer a "nice-to-have" but an essential component for brand differentiation and customer retention in an increasingly competitive digital marketplace.

Failure to adapt to these changes could result in diminished visibility, lower engagement, and lost revenue. Marketers must, therefore, embrace a holistic approach to search optimization, ensuring they remain agile and future-proofed in a rapidly changing digital landscape.

The "Engine" Has Changed. It is Now Search Optimization.

The way clients/customers search for information is transforming rapidly. No longer confined to text-based searches on engines like Google, users are now relying on voice assistants, visual search tools, and integrated social media platforms for information retrieval. By 2025, more than 50% of all searches are predicted to occur through voice and image-based interactions (Gartner, 2024). This shift is driven by advancements in AI, machine learning, and natural language processing (NLP), which enable more intuitive and accessible search experiences for users across a wide range of devices and platforms (Adobe Analytics, 2023). In response, businesses need to move beyond optimizing for search engines and adopt a comprehensive, multi-modal search strategy.

The Multi-Modal Search Ecosystem In 2025, brands that optimize for search across various modalities—voice, visual, and textual—will stand out. Each of these forms presents unique challenges and opportunities.

1. Voice Search Optimization Voice search is poised to dominate by 2025, with smart speakers projected to be present in 55% of households globally. Voice queries tend to be conversational and context-specific, with a focus on long-tail keywords and natural language. Research from Johnson et al. (2023) shows that voice searches are 30% more likely to include question-based formats such as "Where can I find the best ABM consultants?" than text-based queries. Brands that want to optimize for voice search should prioritize structured data (schema markup) and optimize for Google's featured snippets, which are frequently used by voice assistants to deliver quick answers.
2. Visual Search Strategies Visual search is gaining traction, especially on platforms like Pinterest and Google Lens. According to a report by Pinterest (2024), visual search queries increased by 140% year-over-year, signaling a major shift in clients/customers behavior. E-commerce brands, in particular, have benefited from optimizing their product images for visual search, with a 35% increase in conversion rates recorded by brands that embraced image-based search (Visual Search Quarterly, 2024). To succeed, brands must focus on high-quality images, detailed alt text, and robust metadata that aligns with the intent behind visual search queries.
3. Text-Based Search in 2025 While text-based search remains relevant, it is evolving. Google's advancements in NLP, particularly through its BERT and MUM algorithms, mean that search engines can now process and understand user intent with near-human accuracy (Google AI Blog, 2024). Brands optimizing for text search need to prioritize content quality, Expertise, Authoritativeness, and Trustworthiness (E-A-T), and aim to capture granular user intent through well-structured content that aligns with users' specific needs.
4. Platform-Specific Search Optimization As social media platforms become powerful search engines in their own right, brands must adopt platform-specific optimization strategies. TikTok and Instagram, for instance, are seeing a surge in search queries, especially among younger demographics. Nearly 40% of users aged 18-24 prefer to search for lifestyle content on TikTok rather than traditional search engines like Google (Statista, 2024). As such, optimizing for in-app search functions on these platforms through hashtags, keywords, and engaging content is critical.

Industry-Specific Applications The impact of multi-modal search optimization will differ across industries. Each sector must focus on the channels and search formats that resonate most with their target audience.

• E-Commerce: E-commerce brands stand to gain significantly from visual and voice search optimization. With the rising popularity of “search by image” functionality on platforms like Amazon and Google Shopping, companies need to ensure that their product images are optimized for visual recognition algorithms. Additionally, voice search for product discovery is projected to grow, with 60% of smart speaker owners expected to use voice to make purchases by 2025 (eMarketer, 2024).
• Healthcare: In the healthcare industry, voice search optimization is critical, as patients often use voice assistants to search for healthcare services or conditions. Incorporating question-based keywords such as "Where can I find the nearest urgent care?" or "What are the symptoms of diabetes?" into healthcare websites will enhance discoverability.
• Education: In the education sector, multi-modal search will enhance student and faculty engagement. Universities and online learning platforms can leverage voice search for common queries, such as enrollment information or course descriptions, while visual search can aid in browsing through digital course materials or campus resources.

Technology Trends: Augmented Reality and Brain-Computer Interfaces Beyond the current trends in voice, visual, and text search, the integration of augmented reality (AR) and brain-computer interfaces (BCIs) is likely to further disrupt how people search for and interact with information.

• Augmented Reality (AR): AR is expected to play a significant role in search, particularly for retail and real estate sectors. AR overlays digital information onto the physical world, allowing clients/customers to "search" for products or property listings simply by pointing their smartphones at an object. By 2025, AR-enabled searches could account for 15% of retail search activity (MarketsandMarkets, 2025).
• Brain-Computer Interfaces (BCIs): BCIs, though still in the early stages, have the potential to revolutionize how users interact with search technologies. BCIs could enable users to search for information by simply thinking about it, reducing reliance on manual input or voice commands. While the widespread adoption of BCIs is further off, companies that begin experimenting with this technology could be early movers in the next generation of search.

Ethical Considerations and Data Privacy As search becomes more personalized and complex, the ethical considerations surrounding data privacy, algorithmic transparency, and bias must be addressed. According to Pew Research Center (2024), 78% of customers are concerned about data privacy, especially as AI and machine learning power more personalized search results. Brands must ensure compliance with regulations like GDPR and CCPA while being transparent about how data is collected and used.

Furthermore, as AI-driven search becomes more prevalent, algorithmic transparency is crucial to avoid biased search results. This includes ensuring that AI models are trained on diverse datasets to minimize skewed outcomes and discrimination in search results. Additionally, companies must prioritize user consent, ensuring that personalized search experiences do not compromise individual privacy.

Future-Proofing Your Brand for 2025 and Beyond (continued)

1. AI and Machine Learning Integration AI-driven tools will play a pivotal role in search optimization. By leveraging machine learning, brands can predict search trends, personalize content, and optimize for multiple search formats simultaneously. According to MIT Technology Review (2024), brands using AI for multi-modal search saw a 50% reduction in time-to-market for new content strategies. AI will also help brands tailor content more effectively for individual user behaviors and preferences, making it easier to rank across various search modalities.
2. OpenAI's SearchGPT represents a significant development in AI-driven search. Launched in 2024, SearchGPT aims to revolutionize the search engine landscape by offering conversational, real-time answers rather than a simple list of links. By utilizing AI models to understand and retain context, SearchGPT allows users to engage in dynamic, follow-up conversations to refine their queries and receive more personalized responses. This differs from traditional keyword-based engines like Google, which require users to sift through multiple links. Brands will need to optimize their content for natural language processing and conversational queries to stay relevant as tools like SearchGPT become mainstream.
3. Multi-Format Content Creation Creating content that can be repurposed across voice, visual, and text-based searches is essential. Multi-format content strategies allow brands to deliver a seamless experience across all search modalities. A study from the Content Marketing Institute (2024) revealed that brands employing a multi-format content strategy saw a 65% increase in overall search visibility. To optimize for future searches, brands should focus on creating a variety of content types, including text, images, videos, and even augmented reality (AR) elements. For example, YouTube video content optimized with rich metadata and transcriptions is more likely to rank for both voice and text search queries, increasing its discoverability.
4. Agility and Adaptation The ability to rapidly adapt to changes in search algorithms and user behavior is critical for staying ahead in the evolving landscape of multi-modal search. Agile marketing frameworks allow brands to monitor search trends in real time and make necessary adjustments to their optimization strategies. A study by Kumar and Reinartz (2023) found that brands that adopt agile search optimization strategies outperform competitors in digital market share by 2.5 times. This agility requires a combination of continuous monitoring, rapid testing, and flexible content creation processes to remain competitive as search engines continue to evolve.
5. Data-Driven Personalization Personalization is set to become even more critical as search engines increasingly prioritize user intent and context. By leveraging AI and machine learning, brands can deliver personalized search results based on user behavior, preferences, and demographics. According to Accenture (2025), 91% of clients/customers are more likely to engage with brands that offer personalized recommendations and content. In 2025, successful brands will focus on creating personalized experiences across search modalities, ensuring that content meets the specific needs of each user while respecting privacy and data regulations.
6. Invest in Ethical and Transparent Data Practices As data privacy concerns continue to grow, brands must ensure that their data collection and usage practices comply with regulations like GDPR and CCPA. Ethical use of data, including clear communication about how user data is used in search personalization, will be key to building and maintaining clients/customers trust. Transparency in data practices is not only a regulatory requirement but also a differentiator in an increasingly privacy-conscious market. Brands that lead with transparency and ethical data use will be more likely to foster long-term loyalty and trust.

Challenges and Opportunities in Multi-Modal Search

The rise of multi-modal search presents both challenges and opportunities for brands and marketers. One significant challenge lies in the increasing complexity of managing search optimization across multiple platforms and formats. With the fragmentation of search behavior, marketers must develop a cohesive strategy that addresses the unique requirements of each search modality.

However, multi-modal search also offers new opportunities for brands to engage with clients/customers in more personalized, dynamic ways. As search becomes more contextual and intent-driven, brands that can deliver relevant and timely content will stand out in an increasingly competitive marketplace. Moreover, innovations in AR and AI offer new ways to create immersive search experiences that can deepen customer engagement and drive conversions.

Final Thoughts

As we approach 2025, search optimization is expanding beyond the confines of traditional SEO. Voice, visual, and platform-specific searches are converging to create a multi-modal search ecosystem that demands a unified and adaptive approach. To remain visible and relevant, brands must embrace a holistic strategy that incorporates AI, machine learning, and personalization to meet the evolving needs of clients/customers across diverse search modalities. By investing in multi-format content, ethical data practices, and agile marketing frameworks, brands can future-proof their search optimization strategies and thrive in the dynamic digital landscape of 2025 and beyond.

References

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