Many advertisers have traditionally focused on tactical considerations in their performance marketing campaigns: placement strategies, creative formats and bid optimizations. Marketing used to operate in pretty predictable cycles, where you plan a campaign, launch it, measure it and optimize it.
But strategic thinking should evolve to understanding how the modern shopper actually moves through the buying process and what problem they are trying to solve at each step. Consumers are increasingly expecting real-time responsiveness and relevance across channels. They’re used to hyper-personalized experiences from platforms like Netflix and TikTok, so now they expect to be treated as a “segment of one” when shopping too.
To this end, shoppers don’t always progress linearly through a purchase funnel, from awareness straight to purchase. Instead, the shopping journey today may resemble more of a spiral staircase. After becoming “aware” of a product or brand (the top of the staircase), they may research with search engines, AI chatbots and marketplaces, use browser extensions or other tools to discover deals and rewards, compare options across numerous sites and check product reviews or FAQs before they even put something in their cart. Each “loop” down the “staircase” gets the shopper closer to the bottom — the purchase.
Yet many affiliate strategies still measure performance based on last click, get in the weeds with partner reporting, tweak commissions, etc. without asking the fundamental question: Did we help this shopper solve their problem at the right time, and with the right content, based on their (inferred or explicit) intent?
Shopper Intent is Contextual, and AI is Accelerating that Shift
Shopper intent is showing up in new ways, with new tools. Shoppers no longer just use a search engine and click on static links. Instead, the modern shopper journey is also informed by conversation and context.
This is illustrated by how much shoppers are relying on AI-assisted tools. Salesforce reported that during Cyber Week 2025, AI chatbots and agents drove $67 billion in global sales, and influenced 20% of all purchases. And for the full Holiday 2025 season, Adobe Analytics observed that “consumers embraced generative AI more than ever as a shopping assistant in their purchasing decisions,” with LLM-referred traffic to retail sites increasing almost 700% vs. the prior year.
A new study by McKinsey explored how consumers are adopting Gen AI tools specifically for shopping in early 2026. The findings show the majority of shoppers (62%) used AI to compare options, such as brands, models, prices and reviews; while 55% said they relied on AI to learn more about a category or product, including what features to consider.
Recent technological developments will only reinforce this trend. Google’s Universal Commerce Protocol (UCP) introduces a new open standard for AI-assisted shopping that enables agents to interact with detailed product catalogs, answer shopper questions in context, view alternatives and ultimately make purchases directly within AI search surfaces. Google Merchant Center feeds are being expanded with dozens of new product attributes that go far beyond the existing available fields to include answers to common questions, compatible accessories, acceptable substitutes and context for usage.
These are signals designed for conversational discovery when a human shopper “speaks with” an AI chatbot or when an agent shops for them, and not just for keyword matching by a one-way interaction with a search engine.
Similarly, early guidance from Microsoft’s new “Answer Engine Optimization” playbook emphasizes that merchants need to enrich product feeds and content assets with data points that explain not just the obvious product attributes, but with more context around why a product matters and when it performs best.
Brands that invest in structured, high-quality product information that provides this context for shoppers aren’t just feeding machines with dry catalog data. Instead, this data will enable AI chatbots and agents to “resolve shopper intent accurately,” as PPC Land notes.
Reframing Affiliate Strategy Around Shopper Needs
As consumers increasingly expect a more personalized experience, marketers need to think beyond their current approaches and invest in unified customer data foundations that they can layer intelligent personalization tools into.
These tools must prioritize use cases that provide measurable customer value by delivering the right messages at the right time to the right shopper. This is how marketers can begin to think of personalization as a system, rather than just a tactic.
As part of this, affiliate partnerships that truly drive value are the ones that intersect with the shopper’s problem-solving process. That means evaluating affiliate strategy through questions like:
- Where and how are shoppers seeking reassurance about the “value for the money” of this product?
- What informational gaps cause friction resulting in shopper doubt before checkout?
- Are product and offer data structured in ways AI systems can understand and surface?
- How can offers, cashback and rewards reinforce confidence in a product at the moment of high intent to purchase?
With all the different types of publishers that can contribute to a shopper’s confidence in the product and in the value of your products, from influencers to review sites to LLMs/agents to cashback partners, affiliate can become part of the overall experience that guides a shopper through their cycle of exploration, research, comparison, validation and, finally, purchase.
The Strategic Opportunity
Merchants need to keep the importance of contextual problem-solving data in mind, and work to integrate robust product information, structured conversational attributes and seamless value propositions by working with publishers and systems that can best deliver this information at the right time in shoppers’ journey.
In this new era, understanding and investing in the journey is the highest-paying strategic investment you can make. As marketing becomes less about message amplification and more about individualized experience architecture, marketing leaders should evolve from asking, “How do we reach customers?” to, “How do we design systems that continuously earn customer trust and relevance?”
Michelle Wood oversees the merchant network side of the Wildfire Systems platform. Her team builds productive partnerships with online retailers and affiliate networks, bringing them into the Wildfire platform and improving their incremental revenue opportunities. With over 16 years of experience in digital media, affiliate marketing and influencer media sales, Wood has worked with many of the world’s most notable enterprise ecommerce companies to acquire new and loyal customers and exceed revenue targets with positive ROI. Prior to Wildfire, she held executive positions with leading performance marketing companies including ShopAtHome.com and Coupons.com.
