AI Services for Ecommerce

AI Brand Perception Audit

Your brand has an AI reputation, and you probably don't know what it is. AI platforms like ChatGPT, Gemini, Perplexity, and Claude are already answering questions about your products, your company, and your competitors. The answers may be outdated, inaccurate, or missing entirely.

An AI Brand Perception Audit reveals exactly how generative AI models understand and represent your brand. I query the major AI platforms with the same prompts your customers use and deliver a detailed report covering:

• Accuracy assessment — Are your company facts, product information, leadership details, and service descriptions correct across AI platforms?
• Sentiment analysis — What is the overall tone when AI discusses your brand? Positive, neutral, or negative?
• Competitive positioning — When customers ask AI for recommendations in your category, who gets mentioned? Where do you rank relative to competitors?
• Visibility gaps — Which product categories, service areas, or industry topics should mention your brand but don't?
• Actionable recommendations — A prioritised list of content, schema, and digital PR actions to correct inaccuracies and improve AI representation.

This is the fastest, most tangible entry point into AI optimisation. Most businesses are shocked by what they discover.

GEO & AEO: Search Visibility for AI Engines

Generative Engine Optimisation (GEO) and Answer Engine Optimisation (AEO) are the disciplines that determine whether AI platforms cite, recommend, and trust your brand when users search for solutions in your category. This is not traditional SEO with a new name — it requires fundamentally different strategies.

Traditional SEO focuses on ranking in a list of links. GEO and AEO focus on being the answer AI gives directly to the user, often without a click to your website. I help ecommerce businesses earn that position through:

• Entity optimisation — Structuring your brand identity so knowledge graphs and AI models correctly understand who you are, what you sell, and why you're authoritative.
• Structured data and schema implementation — Deploying Organisation, Product, FAQ, and other schema markup that gives AI models verified, machine-readable information about your business.
• Conversational content strategy — Creating and restructuring content in answer-first, modular formats that AI systems prefer to cite. This includes E-E-A-T signal strengthening (Experience, Expertise, Authoritativeness, Trustworthiness).
• AI platform monitoring — Tracking your share of voice across ChatGPT, Gemini, Perplexity, Claude, and Google AI Overviews to measure progress and identify new opportunities.
• Citation and authority building — Earning mentions and references from the authoritative sources that AI models rely on when constructing answers.

Agentic Commerce Readiness

Agentic commerce is the next structural shift in ecommerce. AI agents — embedded in platforms like ChatGPT, Gemini, and shopping assistants — are beginning to research, compare, and purchase products on behalf of consumers. These agents don't browse your website the way humans do. They read structured data, query APIs, and evaluate machine-readable product attributes to make purchasing decisions.

If your product data isn't structured for machines, your products won't surface where shopping now begins. I help ecommerce businesses prepare for this shift through:

• Product data audit and enrichment — Reviewing your entire catalogue for machine-readability. This includes standardising product attributes, ensuring consistent identifiers (GTIN, SKU, MPN), and enriching descriptions with specific, factual attributes that agents use for comparison.
• Schema implementation for commerce — Deploying Product, Offer, MerchantReturnPolicy, and AggregateRating schemas that agents rely on to interpret pricing, availability, returns, and customer satisfaction.
• Policy machine-readability — Ensuring your shipping, returns, and warranty policies are structured so AI agents can parse and evaluate them during purchase decisions.
• API and feed readiness assessment — Evaluating whether your product data can be exposed via feeds and APIs that AI platforms require for agent-driven discovery.
• Agentic Commerce Protocol (ACP) preparation — Positioning your ecommerce platform for emerging standards that enable AI agents to transact directly with your store.

This service builds directly on my ecommerce and marketplace expertise. I've spent years working with product data optimisation, catalogue management, and platform integrations — agentic commerce is the natural next frontier.

AI Agent Configuration

Purpose-built AI agents are already delivering measurable ROI for ecommerce businesses — handling customer service enquiries, automating repetitive workflows, and providing personalised shopping assistance. The challenge for most mid-market companies isn't whether to use AI agents, but how to select, configure, and deploy them without wasting time and budget.

I help businesses move from experimentation to production by:

• Use case identification and prioritisation — Mapping your business processes to identify where AI agents deliver the highest ROI. Common high-impact starting points include customer service automation (order status, returns, FAQs), internal workflow automation, and product recommendation assistants.
• Platform selection — Evaluating and recommending the right AI agent platforms based on your existing technology stack, budget, and operational requirements.
• Configuration and deployment — Setting up, training, and deploying agents with your brand voice, product data, and business rules. This includes testing, refinement, and handoff protocols for when human intervention is needed.
• Integration management — Connecting agents to your CRM, helpdesk, ecommerce platform, and other systems to ensure seamless data flow.
• Performance monitoring and iteration — Establishing KPIs, monitoring agent performance, and continuously refining to improve resolution rates and customer satisfaction.

My project management background is a genuine differentiator here. AI agent deployment is a cross-functional project that touches customer service, IT, marketing, and operations. I coordinate all stakeholders and ensure the implementation stays on track.

AI Readiness & Team Adoption

The biggest barrier to AI adoption isn't technology — it's organisational readiness. Companies that assess their maturity before implementing AI have significantly higher success rates. I help businesses build the foundation for sustainable AI adoption through:

• AI readiness assessment — Evaluating your current data quality, technology infrastructure, team capabilities, and process maturity against a structured AI maturity framework. This identifies exactly where you are and what needs to change before AI investments deliver returns.
• AI adoption roadmap — A prioritised plan of AI use cases ranked by business impact, feasibility, and effort. This ensures you invest in the right AI initiatives first, not the most exciting ones.
• Team training and enablement — Practical workshops that demystify AI for your teams — from leadership to operational staff. This covers how to use AI tools effectively, how to evaluate AI outputs, and how to integrate AI into daily workflows.
• AI governance framework — Establishing policies for responsible AI use, data handling, and quality assurance that protect your business and build customer trust.
• Ongoing advisory — Regular check-ins to assess progress, adjust priorities, and introduce new AI capabilities as they become relevant to your business.

This is not a slide deck exercise. It's a practical programme that prepares your people, data, and systems to adopt AI in a way that sticks.