Total search & MMM: Measuring the full multi-touch consumer journey

The way people research products and services has fundamentally changed. Instead of relying on a single search engine query, consumers now move fluidly between platforms, formats, and devices as they gather information and evaluate options. A shopper might scroll TikTok for trending recommendations, watch in-depth YouTube reviews, explore Reddit communities for peer opinions, and consult AI assistants like ChatGPT or Gemini before making a final purchase. Every interaction – whether it results in a click or not – shapes awareness, perception, and intent.

In today’s fragmented digital landscape, the last click tells only part of the story. To understand how marketing drives results and where every pound counts, brands need to map the full journey, capturing every interaction across platforms before a conversion happens.

Understanding multi-touchpoint search behaviour

Modern consumers no longer follow a simple, linear path to purchase. Instead, they move across multiple platforms, engage deeply with content, and interact repeatedly with brands. Key behaviours include:

• Researching across four or more digital platforms to compare information and options
• Interacting with brands 11 or more times before making a decision
• Spending over seven hours engaging with content, including videos, articles, reviews, and AI-driven experiences.
• Each touchpoint – whether it’s scrolling social media, watching videos, or querying AI tools – adds context, builds trust, and shapes the eventual purchase decision.

Ignoring these touchpoints can lead to misallocated budgets, undervalued brand-building channels, and incomplete ROI reporting.

The discovery touchpoint - TikTok & Instagram

At the discovery stage, consumers encounter a brand for the first time, often through visual and social search. Platforms like TikTok and Instagram have transformed from purely social spaces into key research channels where users actively seek inspiration, product ideas, and recommendations. Short-form videos, trending posts, and influencer content all play a role in capturing attention, sparking curiosity, and introducing brands in a natural, context-driven way.

Key stats:

Nearly 60% of Google searches in the UK and EU now result in zero clicks, yet these “zero-click” impressions still shape awareness and influence later decisions. Users might watch a tutorial on Instagram, scroll through TikTok trends, or save a post for later – these interactions create subtle but measurable brand impact that builds over time.

Best practice:

Brands should focus on visually compelling content that aligns with the intent of early-stage consumers. Messaging, aesthetics, and relevance matter just as much as reach. Early impressions set the tone for all future interactions, meaning discovery-stage content must educate, inspire, and resonate to drive engagement down the line.

The consideration touchpoint - YouTube & Reddit

Once consumers move past discovery, they dive deeper into research. They may spend hours watching tutorials, reading reviews, and exploring forums, seeking content that helps them compare options and build confidence in their choices. Platforms like YouTube provide in-depth video explanations, product demos, and expert reviews, while communities on Reddit allow peer-to-peer advice, nuanced discussion, and real-world experiences. These mid-funnel interactions are crucial for building trust and understanding before a purchase decision.

Key stats:

For informational queries, top search results experience a 34.5% drop in clicks when Google’s AI Overviews appear. This shows that many users now get the answers they need directly from AI summaries, without visiting websites, highlighting the importance of producing content that is authoritative, structured, and AI-ready.

Best practice:

Brands should focus on creating problem-solving, trustworthy content that answers consumer questions clearly and comprehensively. This type of content not only strengthens credibility but also positions the brand to be surfaced in AI-driven summaries and referenced across communities. Mid-funnel content shapes perceptions and primes consumers for the final stages of the journey, ensuring they are more informed and confident when considering a purchase.

The validation touchpoint - ChatGPT & Gemini

As consumers approach a purchase decision, they increasingly turn to AI assistants and large language models like ChatGPT or Google’s Gemini for quick, concise answers. These tools allow users to validate options, compare features, and confirm details without needing to navigate multiple websites. AI-driven summaries provide curated information, often aggregating insights from reviews, articles, and community discussions, making them a powerful touchpoint in the decision-making process.

Key stats:

In the health and wellness sector, over 230 million questions are asked on ChatGPT weekly, while Google’s AI Overviews now cover 89% of healthcare-related queries. These figures illustrate that users are relying on AI not just for convenience, but as a trusted source of verification before they commit to a purchase.

Best practice:

Brands should ensure their content is structured, accurate, and optimised for AI consumption. Authoritative, clearly written answers increase the likelihood of being surfaced in AI-driven summaries, influencing consumer perception at the point of validation. This stage is about building confidence. Brands that appear here earn trust and reinforce the research consumers have already conducted across discovery and consideration channels.

The transactional touchpoint - Google & Amazon

When a consumer is ready to buy, they turn to transactional platforms like Google and Amazon. These are the moments where intent is strongest and conversions happen, but the final click represents the result of a long series of prior interactions.

Key stat:

Even at this stage, user behaviour is highly sensitive to experience. Studies show that ecommerce conversion rates are highest when pages load in 1-2 seconds, dropping sharply from approximately 3.05% at 1 second to just 0.67% at 4 seconds. This underlines the importance of optimising speed and usability at the point of transaction.

Best practice:

To maximise conversions, brands should focus on fast, seamless experiences, intuitive navigation, clear product information, prominent reviews, consistent messaging from previous touchpoints, and regular testing of the checkout flow to remove friction and prevent drop-offs. Leveraging analytics and conversion rate optimisation (CRO) can help brands identify friction points and improve performance across every stage of the checkout experience.

Why traditional attribution falls short

Last-click attribution assumes the final interaction before a purchase deserves full credit, but today, this approach misses the bigger picture. Early-stage touchpoints – whether a TikTok video, YouTube review, or AI assistant answer – play a critical role in shaping awareness, trust, and intent, yet remain invisible in traditional reporting.

By capturing value across all interactions, multi-touch measurement methods like Marketing Mix Modelling (MMM) provide a more accurate view of which channels drive results. This enables smarter budget allocation, optimised campaigns, and a clearer understanding of the full consumer journey.

Marketing mix modelling (MMM): Measuring multi-touch Impact

Marketing Mix Modelling (MMM) is a statistical approach that quantifies the incremental contribution of each marketing channel, bringing together both online and offline data to provide a complete picture of performance. Rather than focusing solely on the last click, MMM captures the cumulative effect of every interaction, from discovery on TikTok or Instagram, through consideration on YouTube and Reddit, to validation via AI assistants like ChatGPT or Gemini.

MMM works by aggregating historical performance data across multiple channels and applying regression analysis to determine each channel’s impact on revenue, conversions, or other KPIs. It then allows marketers to simulate different budget allocations, testing “what-if” scenarios to optimise overall ROI.

Key components include:

• Data aggregation: Combine historical performance from paid search, social, display, and AI-driven touchpoints.
• Statistical modelling: Use regression and advanced analytics to quantify each channel’s contribution to conversions or revenue.
• Scenario planning: Simulate budget reallocations to identify the mix that maximises ROI.
• Authoritative insight: Unlike last-click attribution, MMM shows the full impact of discovery, engagement, and validation touchpoints.

This approach empowers marketers to answer questions such as:

• How much do early-stage channels like TikTok or Instagram drive awareness and interest?
• How does mid-funnel engagement on YouTube or Reddit influence downstream conversions?
• What is the incremental effect of AI-powered validation on final purchase decisions.

By capturing the full spectrum of the consumer journey, MMM gives brands the insights needed to make informed, data-driven decisions and allocate budgets where they will have the greatest impact.

Case example: How MMM reveals hidden channel value

Marketing Mix Modelling can uncover the true influence of every touchpoint in a consumer’s journey – insights that traditional last-click attribution would miss. Imagine a supplement brand as an example:

• Discovery content on TikTok sparks interest in new products: Short-form videos, trending posts, and influencer recommendations create initial awareness and curiosity.
• In-depth YouTube tutorials build trust and answer FAQs: Mid-funnel video content educates consumers, addresses objections, and strengthens confidence in the brand.
• ChatGPT validation ensures consumers feel confident: AI-driven search and summaries provide verification, allowing users to cross-check claims and make informed decisions.

Paid search drives the final click: While last-click metrics might suggest that paid search is the dominant driver, the reality is far more nuanced.
By modelling the full consumer journey, MMM can reveal the often-hidden influence of early-stage and AI-driven touchpoints. For instance, an analysis might show that interactions on social discovery platforms and AI validation tools account for roughly three-quarters of the total contribution to a purchase, while the final paid search click accounts for only a quarter.

This highlights how traditional last-click metrics can undervalue awareness and validation channels, enabling marketers to optimise budget allocation and measure ROI across the entire multi-touch journey.

Key takeaways for marketers

• Total Search covers every touchpoint. AI, social, video, and direct search all influence purchases.
• Multi-touch attribution is critical. Consumers interact 11+ times across platforms before converting.
• MMM reveals hidden value. It quantifies channel contributions, informing smarter budget decisions.
• Invest in early- and mid-funnel channels. Discovery and validation build trust that supports conversions.
• Content must be authoritative, structured, and AI-ready. LLMs and zero-click searches are now integral touchpoints.
• Stay agile. Consumer behaviour, platform algorithms, and AI capabilities evolve rapidly – continuous optimisation is essential.

By combining Total Search thinking with Marketing Mix Modelling, brands can finally see the full consumer journey, accurately measure every touchpoint, and make data-driven decisions to optimise multi-channel marketing success.