THE TOP 10 FIXES TO BECOME
AEO & GEO READY
These are not aspirational principles. They are the specific, actionable improvements that move the needle most directly on AI visibility - drawn from the consistent patterns we see across the brands making the most progress.
1.
Define a single source of product truth
Every product fact, i.e. dimensions, materials, claims, certifications, should have one definitive, governed home that all other systems and channels draw from.
Without this, consistency is impossible to achieve or maintain.
2.
Standardise your global attribute model and content taxonomy
The vocabulary you use to classify, describe, and categorise your products must be consistent across every system. Not approximately consistent - exactly consistent.
Different terms for the same attribute across PIM, CMS, and retailer feeds are invisible to humans but disqualifying to engines.
3.
Fix content inconsistencies across systems and channels
Audit the key claims and attributes for your most important products across every source an engine might consult. Where they differ, resolve them. Start with your top 20 SKUs.
4.
Move from campaign copy to answer-first content
Reframe content creation around consumer questions rather than brand messages.
What are the three things someone buying this product most wants to know? Is that information explicitly, directly, and completely present in your product content?
5.
Implement structured content formats where engines trust them
Schema markup (JSON-LD), structured FAQs, and attribute-formatted product descriptions in the places where engines look (your own brand site, your retail feeds, your CMS) make your content machine-readable rather than just human-readable.
6.
Integrate PIM and PXM with analytics and performance data
Close the loop between what your product data says and how it performs. Visibility signals from AI channels should feed back into data quality priorities, not sit in a separate dashboard.
7.
Establish clear end-to-end ownership of each content component
Map every piece of content and data to an owner. Identify the gaps. Resolve them with explicit role definitions, not assumptions about who is responsible.
8.
Reduce approval bottlenecks through automation or process efficiency
Content that sits in approval queues cannot be kept current. Where manual approval is unavoidable, streamline it. Where it can be automated safely, automate it.
9.
Create a closed-loop optimisation process
AI visibility data should flow back to content and data owners as actionable signals - not periodic reports. Build the process that turns a drop in recommendation frequency into a specific content update within a defined timeframe.
10.
Align teams around shared KPIs rather than siloed metrics
If ecommerce, marketing, data, and technology are each measuring different things and optimising toward different goals, the programme will not produce coordinated results. Shared metrics, reviewed together, are the mechanism for genuine alignment.
