AI is all around us, and the marketing landscape is not the exception. According to recent studies, 75% of marketing professionals have either implemented or are seriously testing AI in their workflows. On the one hand, marketers want to implement AI and first-party data, but on the other, they still face challenges in using data sources and achieving true cross-channel personalisation. Data leakage, lack of necessary data, a lack of strategy or use cases, and inaccurate outputs are the main concerns of marketers about AI.
What other marketing trends will be crucial for startups in 2025? And what no longer works for startup marketing?
Trend 1: Unified data solutions
Creating a one-stop shop marketing solution is essential not only for large enterprises but also for startups. AI has transformed the structure and functionality of the entire MarTech stack. And the most significant challenge for businesses is the fragmented IT ecosystem they have. The traditional stack was based on customer relationship management (CRM), automation, analytics, and content management. However, it has evolved into a dynamic ecosystem driven by real-time AI-based decisions, predictive models, and automated customer interactions.
I worked on developing a unified data platform that enhances content, sentiment detection, and personalised user interactions, and ensures compliance with ethical AI practices. Our marketing solution included three critical components:
- MarketMuse for AI-driven content optimisation,
- The customised lead qualification and predictive lead scoring system under Salesforce Einstein to ensure business viability,
- Brandwatch machine learning capabilities for sentiment tracking.
First of all, we conducted a comprehensive data audit and traced the entire data flow between different systems, including content management systems (CMS), HubSpot marketing automation, and Salesforce CRM. This audit is crucial for achieving clean, unified data, which is the core for any AI-driven marketing transformation. We applied predictive analytics for revenue attribution, using multi-touch attribution models for precise budget allocation and better pipeline visibility. Salesforce Data Cloud helped to consolidate customer profiles from multiple sources and straighten predictive analytics. Einstein Predictive Lead Scoring was useful to rank leads based on engagement, demographics, and purchase history.
The last step involved processing social data to capture client sentiment and filter out irrelevant noise. Brandwatch used customised classification models to classify industry-specific phrases.
Trend 2: Adapting content to the new reality
According to the “Future of Marketing” report by Gartner, more than one-third of web content will be created specifically for AI and search engine consumption by 2026. It’s important to mention that content is becoming more average overall, with a modest user-generated look. At the same time, Generative AI gives brands as much text and imagery they want, making creative versioning easy and cheap.
In 2024, there was a slight increase (around 1%) in mobile-driven paid search for brands, with traffic from organic search remaining relatively flat in the first three quarters of 2024 compared to 2023. However, Gartner points out 45% of CMOs increased their paid search budgets, and 40% allocated more to SEO investment.
Search marketing remains a crucial element of every digital strategy and relies on a deep understanding of the changing channel landscape, customer focus, and solid foundational practices. New marketing strategies should be aligned with search algorithms, and companies should invest in hiring professionals skilled in SEO and generative AI fundamentals.
We saw this firsthand when implementing AI-driven content recommendations via MarketMuse. Its integration into our CMS allowed us to enrich metadata and optimise live content using topic modelling and real-time semantic analysis. The improvements in search performance were significant—our content strategy evolved to focus on AI comprehension just as much as human readability.
Marketing leaders can enhance search performance through the following steps: by reviewing and refreshing keyword strategies, balancing paid and organic search, establishing success metrics for search marketing, and determining budget allocation for search marketing.
Trend 3: RAT marketing strategies
Your brand must act fast to follow trending topics. Reactive, agile, and trending (RAT) marketing is the way companies connect with customers and engage with viral trends. Besides, small businesses have natural flexibility to adapt their content and thrive in this fast-paced environment.
During a major product launch, we successfully applied RAT marketing by monitoring real-time buzz via Brandwatch and reacting within hours to a trending topic related to sustainability. Our design team adapted campaign visuals instantly while our content team aligned messaging with customer sentiment patterns. The result? A 3x engagement boost within 48 hours, purely due to timing and relevance.
Tools like Google Trends and Trend Hunter can help monitor public interests and cultural moments. In such a manner, brands align their messaging with timely and relevant topics, whether it’s a seasonal thing trending online or a cultural phenomenon.
Trend 4: AI-powered personalisation is all over the place
Consumers continuously expect and demand tailored experiences. And one of the most significant marketing trends this year is AI-powered personalisation. Marketers can better understand and meet client expectations with the help of AI, from personalised email campaigns and targeted ads to product recommendations.
However, AI is the N1 challenge as well. Research indicates many marketers struggle to use customer data effectively: only 31% of them are fully satisfied with their capability to consolidate different customer data sources for performance analysis, audience segmentation, and campaign development. Almost every organisation, except the most advanced ones, such as Amazon and Netflix, has issues achieving a truly personalised experience.
Genuine personalisation requires comprehensive customer data, unified from several sources into one customer profile. Additionally, personalisation works well for customer retention, instead of solely for acquisition or upselling. Retaining existing customers is often more cost-effective than acquiring new ones, making it essential to invest in collecting, organising, analysing, and using available customer data. Effective retention strategies include how-to guides, loyalty program information, personalised newsletters, emails, and content-rich applications.
Trend 5: Best customers are buying more
Despite the fact that consumers purchase fewer items and spend more to do so across different categories, the rich are getting richer and retailers are getting more value from fewer customers.
It means more “VIP experiences” and super-loyalty programs that work not just for luxury hotels and airlines, but even in the online gambling industry
In our case, we built predictive models around high-value users, then segmented audiences into "VIP clusters" based on lifetime value and referral activity. Our loyalty strategy wasn’t based solely on discounts — it included early product access, customized support, and invitation-only virtual events. The response rate and customer retention significantly outperformed our non-segmented email campaigns.
Trend 6: Location-based marketing to improve local engagement
According to statistics, almost 74% of smartphone owners use location-based services. With location-based marketing, businesses can connect with local customers more effectively and take advantage of location data to deliver targeted content, advertisements, and promotions based on a customer’s physical location.
Tools for location-based marketing include local landing pages with tailored content, contact information, and region-specific offers. These instruments enhance both SEO and user experience. With the help of geo-targeted advertising, businesses can reach potential clients in specific areas through platforms like Google Ads and Facebook Ads. For instance, a retailer can use geo-targeting to promote a sale to customers in a specific location.
Location data helps businesses understand customer behaviours and preferences; with this analysis, they have the opportunity to refine promotion strategies and create more effective advertising campaigns. Above all, unified data solutions and AI-powered personalisation are the main future-proof trends for every brand.