Branding Strategy
Marketing and Branding for SOAS, University of London
This campaign focused on redefining simplicity in beauty photography — blending natural tones, smooth textures, and soft light to communicate a sense of warmth and refinement.
Year
2026
Location
London, United Kingdom
Client
SOAS School of Finance & Management
Role
Graduate Marketing Intern
Deliverables
AI-SEARCH GAP ANALYSIS
Duration
2 months
Approach
How It Came Together
SOAS's School of Finance & Management faced a structural visibility gap in an emerging and increasingly critical discovery channel: generative AI assistants. As prospective students shift research behaviour from traditional search toward tools like ChatGPT and Gemini, institutions with unoptimised digital content risk being systematically excluded from the consideration set — regardless of programme quality. Partnering with a co-lead, I led a comprehensive diagnostic phase: benchmarking SFM's two flagship web properties against a nine-institution competitive set (LSE, Imperial, King's, Bayes and peers), and reverse-engineering the structural and content signals that determine whether generative engines surface and cite an institution accurately. The diagnostic identified four systemic gaps — absent FAQ architecture, no subject-specific ranking evidence, unsubstantiated employer claims, and zero social proof — each representing a quantifiable erosion of competitive positioning relative to better-optimised peers.
Findings from the diagnostic phase were triangulated against primary research — a targeted student survey validating that location, curriculum specificity and ranking credibility are the dominant decision drivers — to ensure the intervention addressed actual user intent, not assumed intent. This informed a two-workstream implementation plan: a content strategy workstream (FAQ architecture, differentiated positioning narrative, research-theme repositioning) and a technical enablement workstream handed to web engineering, spanning schema markup implementation, crawler-access verification across major AI platforms, sitemap integrity and page-load architecture — the infrastructure layer without which no amount of content optimisation would be discoverable. Critically, nine data-dependent claims (employer-specific job titles, a marketing-subject ranking, faculty credentials) were explicitly withheld from the final deliverable pending verification from the programme office, preserving the integrity of the recommendation over the appearance of completeness.
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