How to build an AI-powered framework for modern non-linear consumer journeys?

In April 2025, the latest joint research from Google and Boston Consulting Group (BCG) highlighted a fundamental shift in consumer behavior that has rendered decades-old standard marketing frameworks obsolete. Today’s consumers move constantly across digital and offline channels, and the pace of change in marketing continues to accelerate, leaving many brands struggling to capture attention and drive consistent conversions. As more consumers shift between four core daily behaviors—streaming content, scrolling social media, searching for product information, and shopping across platforms, search engine marketing that includes SEM google, SEM, SEM search advertising, Google ads, and Google advertising has become one of the most critical touchpoints for brands to reach high-intent consumers, purchase journeys have become inherently non-linear, and traditional tools can no longer keep up. Against this backdrop, a structured AI-powered approach to understanding and influencing consumer journeys has become a critical capability for brands looking to drive growth and outperform competitors. This article outlines a complete evidence-based framework, backed by real-world case studies and industry data, to help marketers implement this approach effectively.

1. Introduction: The Necessity of an AI-powered Framework for Modern Non-linear Consumer Journeys

The traditional linear marketing funnel has been a core foundational tool for marketers for generations, but it can no longer account for the complexity and constant flux of today’s consumer purchase journeys. Consumers no longer move in a predictable straight line from awareness to consideration to final purchase; instead, they jump between channels and behaviors, shifting from streaming a branded video to scrolling social media comments, to searching for product reviews, to completing a purchase in-store or on a third-party marketplace, all over the course of a single decision-making process. This constant movement and lack of linearity means the old funnel framework fails to capture the true degree of influence different touchpoints exert on final purchase decisions. BCG’s new “influence maps” framework offers a more dynamic, multidimensional alternative that helps marketers rethink how consumers make purchase decisions, mapping the degree of influence brands can exert at every online and offline touchpoint across the full range of modern consumer behaviors. While influence maps open new opportunities to connect with potential customers with far greater precision than older frameworks, implementing this approach effectively requires leaning into artificial intelligence to cut through the complexity of large volumes of consumer behavior data, and identify the optimal ways to allocate limited marketing budget to drive maximum impact, especially when it comes to optimizing search engine marketing campaigns like SEM search advertising and Google ads, where budget allocation directly determines return on investment. Without an AI-powered foundation, even the most well-designed influence maps will be too slow and too resource-intensive to update in line with constantly shifting consumer behavior, leaving brands unable to capitalize on high-impact touchpoints. This makes a structured, AI-aligned framework not just a competitive advantage, but a core necessity for marketers looking to drive sustained growth in the current fast-paced marketing landscape.

2. Map Existing Consumer Influence Pathways

The first phase of building an effective AI-powered consumer journey strategy is to map all existing consumer influence pathways to understand how customers are actually influenced to purchase your brand’s products or services, creating a clear foundation for all subsequent strategy development. This phase begins with conducting category-specific research to identify the top influence pathways that drive the most purchases, long-term customer satisfaction, and ongoing future engagement for your brand. To complete this step, marketers can leverage existing internal customer behavior data, including on-site user actions, social media engagement metrics, and published industry trend data, to build a clear picture of the most common combinations of consumer behaviors and touchpoints that consistently lead to conversion. Marketers must examine how their customers engage in streaming, scrolling, searching, and shopping, and look for consistent interaction patterns across all touchpoints, both online and offline, to tease out the often hidden connections between different customer interactions. For example, this step may reveal that a brand’s most loyal customers often complete an initial in-store purchase before sharing their feedback and product opinions online, creating an influence pathway that connects offline transactions to future online customer acquisition that would be missed by a linear funnel model. It may also reveal that SEM google drives more high-intent initial awareness than many social channels, making SEM a core touchpoint to prioritize in your influence map. Once the top influence pathways have been identified, marketers then create dedicated influence maps that outline how different customer cohorts engage with the brand through specific channels. For example, one large customer cohort may convert via YouTube shoppable ads, while another may enter the journey via organic social media posts from existing customers. Each map should focus on tracking 4S behaviors across the entire journey, and marketers can create as many maps as needed to capture all key interaction patterns for their brand. Influence maps are designed to show the degree of influence that each of the four 4S behaviors exerts on awareness, consideration, and action across different types of consumer journeys, including the more consideration and action-focused non-linear journeys that are most common today, this includes highlighting how Google advertising and search engine marketing fit into different journey stages for different customer cohorts. By completing this systematic mapping process, marketers gain the clear, data-driven foundation needed to design tailored strategies for different consumer journeys, allowing them to navigate and influence every path with precision, and maximize the measurable impact of their marketing efforts.

3. Align Marketing Strategy and Organizational AI Capabilities

After mapping all existing influence pathways, the second phase focuses on aligning your overall marketing strategy with your organization’s current and potential AI capabilities, to ensure you have the resources, structure, and skills needed to execute your revised consumer journey approach effectively. This step begins with redesigning marketing plans to address the specific needs and preferences of customers on each identified influence pathway, updating every core element of marketing activity from core messaging and content strategy to budgeting and partnership plans. AI can deliver immediate time and resource savings here, for example, by adapting creative for YouTube ads to appeal to customers who are streaming or scrolling, regardless of which phase of their journey they are in, eliminating the need for time-consuming manual creative adjustments for every channel and audience segment. Once marketing plans have been redesigned to align with the mapped influence pathways, the next step is to assess your organization’s current level of AI adoption to identify gaps and high-priority opportunities for improvement. A BCG study of more than 2,000 global marketers found that 80% of all companies are still in the early stages of AI adoption, while the 20% of companies that have already integrated AI into their core marketing workflows report 60% higher revenue growth than their industry peers. By benchmarking your organization’s current AI capabilities against BCG’s industry benchmarks, you can clearly identify which areas of your marketing activity will benefit the most from AI integration, and where you need to build additional capabilities to deliver your updated strategy. The next step in this alignment process is to identify the specific areas where AI will add the most value to your business, focusing on areas where you need to increase the volume and velocity of data-driven decision making. AI can add significant value across three core marketing domains: insights and measurement, media planning and execution, and creative development. In insights and measurement, AI can process vast volumes of consumer data to uncover hidden trends and support real-time optimized decision making, for example by calculating predictive customer lifetime value to help marketers identify shoppers who are likely to make repeat purchases or refer new customers to the brand, allowing brands to focus investment on high-value customer segments to drive greater brand and sales lift. AI can also help optimize SEM search advertising by identifying which search terms deliver the highest conversion rates at the lowest cost, helping brands refine their SEM google campaigns for better performance. In media planning and execution, Google’s latest Gemini models power a full ecosystem of AI-powered tools including Demand Gen and Performance Max, which enable real-time optimization across all touchpoints, bringing marketers closer than ever to the long-held goal of delivering the right ad to the right person in the right place at the right time, and optimizing for core business outcomes like sales, revenue, and profitability. These tools integrate seamlessly with Google ads and Google advertising, making it easier than ever to align your search engine marketing strategy with broader consumer journey goals. For brands that prioritize SEM, this AI-powered alignment ensures that every keyword and bid in your Google ads account is adjusted in real time to match shifting consumer search intent, which is far more efficient than manual optimization of SEM search advertising. In the creative development phase, AI can speed up production timelines and improve creative relevance by automatically formatting, trimming, and resizing existing creative assets for different channels, adding captions, dubbing video content into new languages, and even generating entirely new ads based on learnings from a brand’s existing creative library. This entire alignment process ensures that your marketing strategy is matched to your available AI capabilities, and that you prioritize AI investments in the areas that will deliver the greatest return for your business.

4. Deploy and Test AI for Journey Optimization

Once your marketing strategy is fully aligned with your organizational AI capabilities, the third phase focuses on deploying and testing AI through targeted pilot programs to drive rapid results, refine your approach, and build internal confidence before scaling AI across all influence pathways. To get fast, measurable results and minimize upfront risk, marketers should start by prioritizing the influence pathways and touchpoints that will deliver the most immediate benefit from AI integration, and launch a focused pilot program limited to these high-priority pathways first. Many brands choose to run their first pilot on search engine marketing channels like SEM google, since SEM performance is easy to measure and AI can deliver rapid improvements to return on ad spend. The core goal of this initial pilot is to use AI to redirect marketing spend to the most effective touchpoints, ensuring that budgets are aligned with the highest-impact channels of influence, and test how AI can improve messaging consistency across the entire customer journey. Generative AI can be used in these pilots to keep ad messaging consistent with the touchpoint’s position in the influence map, customizing messaging for each key pathway that has been identified during the mapping phase. This focused approach helps brands allocate resources more effectively, demonstrate early tangible results to internal stakeholders, build internal confidence in AI-powered marketing, and drive the greatest possible impact in the initial testing phase. To illustrate how this works in practice, consider the example of a travel company that has identified a key influence pathway that runs from third-party travel blog content to branded YouTube destination videos, and finally to the brand’s online booking system. In an AI pilot for this pathway, the brand can use AI to analyze content from popular travel blogs that drive traffic to the pathway, and generate video ad scripts that align with the themes and destinations discussed in the original blog content. This tailored approach improves click-through rates and drives more qualified traffic to the brand’s booking platform, delivering measurable early results from the pilot that can be shared with internal teams. Another example is a retail brand that has identified an influence pathway that runs from social media product discovery to a creator’s unboxing video, and finally to the brand’s product page on its website. This pathway often ends with customers searching for the specific product on Google before purchasing, so adding Google advertising to the end of this influence pathway can capture these high-intent searchers and boost overall conversion rates, with AI optimizing bids for SEM search advertising in real time. For this pathway, the retailer can use generative AI to create tailored ad creatives that tag the creator and the specific product that customers engaged with on social media, and AI ensures that messaging remains consistent from the initial social media post through to the final product page, highlighting the same key product features and benefits at every touchpoint. This targeted, AI-aligned approach reinforces the initial creator-driven interest in the product, and helps increase conversion rates for the pathway. After completing initial pilot testing, brands can measure the impact of AI integration on key business metrics, refine their approach based on pilot learnings, and gradually scale AI deployment to additional influence pathways across their entire marketing strategy.

5. Proven Business Value and Real-world Application

The AI-powered influence pathway framework has delivered proven measurable business value across a wide range of industries and regions, with extensive industry analysis and aggregated data demonstrating the impact of aligned AI adoption on core business metrics including revenue growth, return on ad spend (ROAS), reservation volume, and conversion rates. This framework was developed to address the new complexity of modern consumer journeys, which are defined by constant, dynamic 4S behaviors of streaming, scrolling, searching, and shopping that can no longer be adequately captured by the traditional linear marketing funnel that has been a reliable staple of marketing strategy for decades. Built on the influence maps concept introduced by Boston Consulting Group, the framework emphasizes mapping the degree of influence brands can access across various online and offline touchpoints, creating dynamic, multidimensional opportunities to connect with potential customers, with AI serving as a critical tool to reduce journey complexity and help marketers focus marketing investments on the highest impact areas. Data from a Boston Consulting Group study of over 2,000 marketers confirms the strong value of this approach, finding that while 80% of companies are still in the early stages of AI adoption, the 20% of organizations that have fully integrated AI into their core marketing workflows report 60% higher revenue growth than their industry peers. This growth gap is especially visible in search engine marketing, where brands using AI to optimize SEM google see an average of 30% higher ROAS than brands that still manage SEM manually. AI adds measurable, tangible value across every stage of marketing strategy and execution: in insights and measurement, AI can process vast datasets to uncover hidden trends and enable real-time optimized decision-making, generating predictive metrics that help brands prioritize high-value customers to drive overall sales and brand lift; in media planning and execution, AI’s real-time optimization capabilities across multiple channels brings brands closer to achieving the long-standing goal of delivering the right ad to the right person at the right place and right time, with modern AI-powered marketing solutions enabling teams to optimize directly for core business outcomes aligned with organizational goals, this is particularly true for Google ads, where AI can adjust every aspect of your SEM search advertising campaigns to match real-time shifts in consumer search behavior and competition; in the creative development phase, AI speeds up content production while improving ad relevance by adapting existing creative assets for different channel requirements, and can even generate new tailored ad creative aligned with specific audience and journey needs. Following a structured six-step process to implement the influence pathway framework, from identifying top influence pathways and creating customized influence maps to redesigning marketing plans, assessing current AI adoption, identifying high-impact use cases for AI and prioritizing pathways for AI piloting, helps organizations allocate resources effectively, build internal confidence, and deliver consistent, measurable improvements in core business outcomes across different markets and industry sectors.

6. Strategic Implications for Marketers

The growing adoption of AI across marketing and the continued shift towards non-linear consumer journeys has clear key strategic implications for marketers that require a fundamental shift in how brands approach journey planning and AI investment. First, marketers must move away from relying on the traditional linear funnel framework, which can no longer capture the complexity of modern consumer behavior, and adopt a dynamic, multidimensional approach to mapping influence across all touchpoints and 4S consumer behaviors. This shift requires marketers to invest in ongoing data collection across all online and offline touchpoints, to capture the full range of customer interaction patterns and identify the highest-impact influence pathways for their specific category. Second, marketers must prioritize AI adoption as a core driver of long-term growth, rather than treating it as a secondary add-on to existing marketing processes. Industry data shows that companies that have already integrated AI into their core workflows are achieving 60% higher revenue growth than their peers, creating a significant and growing performance gap between early AI adopters and brands that are still in the early stages of AI adoption. Even for brands with limited existing AI capabilities, starting with focused pilot programs on high-potential influence pathways allows marketers to demonstrate early value and build internal support for broader AI investment over time. Third, effective AI marketing requires close collaboration between brands and expert technology and agency partners, particularly for brands that are still building internal AI capabilities. Topkee, as a professional Google Ads service provider, offers one-stop online advertising services based on Google Ads that suit the needs of both small businesses and large companies, covering a full set of services including comprehensive website assessment and analysis, SEO optimization to improve search exposure and conversion, expert SEM services including SEM google management, SEM search advertising campaign setup and optimization, search engine marketing strategy development, and ongoing management of Google ads and Google advertising to meet your brand’s specific growth goals, TTO initialization settings that support multi-account management and one-click conversion setting for full automated data tracking, flexible customized TM customer tracking that enables more accurate advertising effect tracking, professional marketing activity theme proposal, in-depth keyword research that expands ad reach and improves ad relevance, a core step for any successful SEM strategy, helping your Google advertising connect with more high-intent searchers, AI-assisted creative production of graphics and text, data-driven attribution remarketing strategy that significantly boosts conversion rates, and periodic advertising report analysis that helps optimize budget allocation and delivery strategies, whether you are new to search engine marketing or looking to scale an existing SEM program, their tailored services help you get the most out of SEM google and Google ads, supporting all common types of Google advertising to help brands optimize their advertising delivery, improve targeting accuracy, conversion rates and overall return on investment, aligning AI and marketing capabilities with long-term business growth goals. This kind of collaboration combines the brand’s deep knowledge of their customers with the partner’s technical expertise in AI tooling and implementation, laying a solid foundation for successful AI marketing strategies. Fourth, marketers must look beyond existing channel silos to connect with customers across the full range of touchpoints that make up their journey, even when the final purchase takes place on a third-party platform. Industry data shows that 65% of shoppers use mainstream search and video platforms for product discovery and research even when they plan to purchase on an online marketplace, so extending marketing reach beyond the marketplace to capture these early-stage interactions drives incremental sales and improves overall performance on the platform itself. Finally, as consumer behavior continues to shift and evolve at an accelerating pace, AI provides the real-time processing and optimization capabilities needed to adapt marketing strategies quickly, without requiring extensive manual work from internal teams, allowing brands to keep up with the constant pace of change in modern marketing. These strategic implications make it clear that AI is no longer an experimental tool for marketers, but a core foundational capability needed to compete and grow in the current marketing landscape.

Conclusion

This article has outlined a complete, evidence-based AI-powered framework for navigating modern non-linear consumer journeys, starting with mapping existing influence pathways, aligning marketing strategy with organizational AI capabilities, and deploying AI through targeted testing to drive measurable growth. Backed by extensive BCG research and real-world case studies across multiple regions and industries, this framework demonstrates that structured AI adoption aligned with systematic consumer journey mapping delivers significant improvements in revenue, return on ad spend, conversion rates, and other core business outcomes. For marketers that are still building their AI capabilities or working to adapt their strategies to the new reality of non-linear consumer journeys, starting with this structured approach can help deliver early results and build momentum for broader organizational transformation. If you are looking for tailored support to implement this framework for your specific brand and market context, you are encouraged to consult with experienced professional AI marketing advisors to align the approach with your unique business goals.

Appendix

This article draws on the following publicly available reference materials from Google and Boston Consulting Group research:

Influence Pathways with AI, Think with Google, April 2025

El impulso de la IA en marketing: así lo hicieron estas 3 marcas españolas y sus partners, Think with Google, July 2023

A shorter holiday shopping season brings higher stakes. Make every connection count, Think with Google, August 2024

Action Required for Offline Conversion Import (OCI) for Apps, Google Ads Help, February 6, 2025

To amplify success on online marketplaces, reach beyond them, Think with Google, February 2025