Keywords to Customer Signals: The Next Evolution of Search Marketing
In this installment of our Ei series, Mikki Sharp explores how artificial intelligence is reshaping search marketing and why success now depends on far more than keywords alone. As AI-powered platforms increasingly rely on customer signals to predict intent and optimize performance, marketers must rethink how they measure, enrich and activate their data to stay competitive.
Mikki Sharp
Associate Director, SEM
A member of the Activation team, Mikki specializes in digital marketing strategy and campaign execution. Her background in journalism and marketing helps bridge data-driven strategy with compelling customer experiences.
For more than two decades, search marketing had revolved around one central concept: keywords.
We researched them. We organized them into tightly themed ad groups. We monitored search terms, adjusted bids, refined match types and measured success based on how well we connected a user's query with the right ad.
Keywords built modern search engine marketing (SEM).
Today, they're no longer the center of it.
The next evolution of search marketing isn't replacing keywords. It's about surrounding them with richer customer signals that help AI understand who is most likely to convert, not simply what they searched for.
Search Has Expanded Beyond the Search Box
Consumers are still searching.
They simply don't begin and end their journey on a search engine anymore.
Someone researching a product today might:
- Watch product reviews on YouTube.
- Ask ChatGPT to compare options.
- Browse Reddit discussions.
- Visit multiple retailer websites.
- Search Google several times throughout the buying process.
- Return days later after seeing a display or social ad.
Every interaction creates a signal.
By the time someone performs a Google search, AI has a much richer understanding of context than a keyword alone could provide.
The search itself has become just one signal among many.
Keywords Are Becoming Inputs, Not Strategies
Keywords still matter.
They continue to define intent, influence ad relevance and determine eligibility within traditional Search campaigns.
But increasingly, they're functioning as one input into much larger machine learning systems.
Products such as Performance Max, AI Max, broad match paired with Smart Bidding, Demand Gen and even conversational search experiences rely far less on manual keyword optimization and more on refining search signals.
Instead, these systems ask a different question:
"Based on everything that we know about this user, are they likely to convert?"
That answer comes from signals.
Customer Signals Are Becoming the Competitive Advantage
Machine learning is only as effective as the information that it receives.
The advertisers that provide the strongest customer signals give Google's AI, and increasingly ChatGPT and other AI-driven platforms, the best opportunity to identify high-value users.
These signals include:
- First-party customer data
- High-quality conversion tracking
- CRM integrations
- Customer Match audiences
- Engagement behavior
- Purchase history
- Offline conversions
- Website interactions
- Demographic and geographic patterns
- Creative engagement signals
Rather than optimizing around hundreds of keywords, marketers are increasingly optimizing the quality of the data flowing into these systems.
Garbage-in still means garbage-out.
Why Conversion Quality Matters More Than Conversion Quantity
This shift also changes how we think about measurement.
For years, advertisers optimized toward as many conversions as possible.
Today, AI doesn't just need conversion volume; it needs conversion value.
It needs meaningful conversion signals.
If every form submission, newsletter sign-up and low-value lead is treated equally, machine learning has little ability to distinguish valuable customers from poor ones.
The more accurately that businesses define success through primary conversions, enhanced conversions, offline imports and conversion values, the smarter that automation becomes. This works through conversion weighting.
The quality of the signal becomes more important than the quantity.
Search Is Becoming Intent Prediction
Perhaps the biggest change is philosophical.
Traditional SEM reacted to searches.
Modern SEM predicts them.
AI is increasingly identifying likely buyers before they perform the exact keyword that we once optimized around.
Audience signals, behavioral patterns, contextual understanding, historical performance and predictive modeling all help determine which ad is served.
Keywords still tell platforms what someone is asking.
Signals help determine whether they're the right customer.
Those are very different questions.
What This Means for Search Marketers
The role of the search marketer isn't disappearing.
It's evolving.
Tomorrow's SEM specialists will spend less time adjusting bids or restructuring keyword match types and more time helping improve data quality, integrating first-party customer information, validating conversion tracking, building audience strategies and helping AI make better decisions.
Success won't come from managing thousands of keywords.
It will come from understanding thousands of signals.
The Future Isn't ‘Keywordless’
Despite headlines claiming the death of keywords, they're not going away.
They're simply becoming one piece of a much larger decision-making system.
Search marketing is no longer just about matching a query.
It's about understanding a customer.
The marketers who embrace this shift, investing in cleaner data, stronger measurement, richer audience signals and meaningful customer insights will build systems that outperform those relying on keywords alone.
The future of SEM isn't keyword-driven.
It's signal-driven.
