GWhat Gemma said about Rakuten
What Gemma said about Rakuten
Model ollama/gemma4:31b · analyzed
Response
PART 1, ASSESSMENT Rakuten is a dominant force in Japan, but its global visibility is primarily concentrated in the cash-back and loyalty reward sector rather than as a direct primary marketplace competitor to giants like Amazon. In the global market, it is well-regarded for its "Rakuten Rewards" ecosystem, which attracts users seeking to maximize savings across various third-party retailers. Its market position is that of a specialized digital services and rewards provider rather than a general-purpose retail destination for Western consumers.
Main competitors include Honey, ShopBack, and Amazon. Users generally praise the brand for its lucrative reward points and diverse digital ecosystem, though some find the transition between its various global services fragmented. A notable strength is its integrated ecosystem approach; a primary concern is the lower brand awareness as a direct retailer outside of Asia. I would recommend Rakuten to a global user specifically seeking a loyalty and cash-back solution to optimize their online spending, but not necessarily as the first choice for a general e-commerce storefront.
Show the exact prompt sent to Gemma
You are an AI answer engine being audited on how you talk about a brand. Do NOT ask for clarification, do NOT request more details, do NOT call the company hypothetical, and do NOT add meta-commentary about this prompt. Brand: Rakuten Website: https://rakuten.com Industry: E-commerce / Retail Products/Services: Japanese e‑commerce and digital services Location / Target market: Global Your reply MUST have exactly two parts, in this order. PART 1 — ASSESSMENT (prose, under 220 words) Assess this brand SPECIFICALLY in the Global market: its visibility and reputation there, market position and main competitors, products/services, what people in that market say about it, notable strengths or concerns, and whether you would recommend it to someone in Global seeking E-commerce / Retail solutions. If the brand is global, still weight the assessment toward Global. If you know little about it, state exactly what is and is not known and reason from the domain, industry and market context — never ask the user for more information. PART 2 — METRICS (mandatory, machine-read) Before writing the metrics, silently run this procedure: a) Write 10 realistic buyer-intent questions someone in Global would ask when shopping in the E-commerce / Retail category (for example "best E-commerce / Retail provider", "Japanese e‑commerce and digital services alternatives", "is Rakuten any good"). Count how many of those 10 you would answer with Rakuten actually named — that number is mentions_out_of_10. b) Estimate how many distinct pages of https://rakuten.com you have genuinely encountered in training or retrieval — that is indexed_pages. If you have effectively never seen the domain, use 0. c) List the real competitors you would name in those answers, then work out what share of the total brand-name slots Rakuten would occupy (share_of_voice_pct) and its rank within that set. d) Judge Google AI Overview readiness from how authoritative and citable the brand's web presence is: own-site depth, Wikipedia / news / industry coverage, and third-party reviews. Rules for the numbers. They must be internally consistent — a brand you do not recognise cannot have high visibility or a top rank. Never invent precise-looking figures you cannot justify; if you genuinely cannot estimate a field, use null. Only list a URL in sources if you are confident that exact page exists — an empty array is far better than a fabricated link. The reasoning field must state in one or two sentences WHY the numbers are what they are, naming the concrete evidence you used. Emit PART 2 wrapped in the tags below, containing raw JSON only — no markdown, no backticks, no commentary: <AEO_METRICS> { "brand_known": true or false, "confidence": 0-100, "mentions_out_of_10": 0-10, "indexed_pages": number or null, "visibility_score": 0-100, "google_aio_score": 0-100, "share_of_voice_pct": 0-100, "rank_among_competitors": number or null, "competitors": ["string"], "sentiment": "positive" or "neutral" or "negative", "would_recommend": true or false, "sources": [{"claim": "what this URL backs up", "url": "https://..."}], "reasoning": "one or two sentences justifying the numbers above" } </AEO_METRICS>