> ## Documentation Index > Fetch the complete documentation index at: https://docs.mavera.io/llms.txt > Use this file to discover all available pages before exploring further. # Product Affinity → Focus Group > Pull Klaviyo catalog and purchase data, then run a Mavera Focus Group with Likert and NPS questions to validate cross-sell hypotheses before building flows ### Scenario Your Klaviyo account tracks what customers buy. You want to test cross-sell hypotheses — if someone bought Product A, would they buy Product B? You pull purchase data and catalog information, then run a Mavera Focus Group with product-context questions using Likert scale and NPS format. The result is validated cross-sell opportunities before you build the flow. ### Architecture ```mermaid theme={"dark"} flowchart LR A["Klaviyo catalog + purchase events"] --> B["Identify product pair affinity"] --> C["POST /api/v1/personas"] --> D["POST /api/v1/focus-groups"] --> E["Cross-sell validation"] ``` ### Code ```python Python theme={"dark"} import os, requests, time from collections import defaultdict KL_KEY = os.environ["KLAVIYO_API_KEY"] MV = os.environ["MAVERA_API_KEY"] MB = "https://app.mavera.io/api/v1" MH = {"Authorization": f"Bearer {MV}", "Content-Type": "application/json"} KH = { "Authorization": f"Klaviyo-API-Key {KL_KEY}", "Content-Type": "application/json", "revision": "2024-10-15", } r = requests.get("https://a.klaviyo.com/api/catalog-items", headers=KH, params={ "fields[catalog-item]": "title,description,url,price", "page[size]": 50, }) products = [] if r.status_code == 200: products = r.json().get("data", []) if not products: products = [ {"id": "prod_001", "attributes": {"title": "Running Shoes Pro", "price": 129, "description": "High-performance running shoes for daily training"}}, {"id": "prod_002", "attributes": {"title": "Performance Socks 3-Pack", "price": 24, "description": "Moisture-wicking athletic socks"}}, {"id": "prod_003", "attributes": {"title": "GPS Running Watch", "price": 299, "description": "Multi-sport GPS watch with heart rate monitoring"}}, {"id": "prod_004", "attributes": {"title": "Hydration Belt", "price": 35, "description": "Hands-free running hydration system"}}, {"id": "prod_005", "attributes": {"title": "Recovery Foam Roller", "price": 45, "description": "Deep-tissue massage foam roller"}}, {"id": "prod_006", "attributes": {"title": "Training Plan (Digital)", "price": 19, "description": "12-week progressive running program"}}, ] PRODUCT_PAIRS = [ {"bought": "Running Shoes Pro", "suggest": "Performance Socks 3-Pack", "logic": "Complementary — socks protect the shoe investment"}, {"bought": "GPS Running Watch", "suggest": "Training Plan (Digital)", "logic": "Watch + plan = structured training"}, {"bought": "Running Shoes Pro", "suggest": "Recovery Foam Roller", "logic": "Runners who invest in shoes care about recovery"}, {"bought": "Hydration Belt", "suggest": "GPS Running Watch", "logic": "Hydration belt = long runs = watch needed"}, ] personas = [] for name, desc in [ ("Casual Runner", "Runs 2-3x per week for fitness. Buys basics, price-conscious. Doesn't consider themselves 'a runner' — it's just exercise."), ("Dedicated Runner", "Runs 4-5x per week, tracks every metric. Invests in gear. Training for a half marathon. Reads running blogs."), ("New Runner", "Started running 2 months ago. Bought first pair of real running shoes. Overwhelmed by options. Wants guidance."), ]: p = requests.post(f"{MB}/personas", headers=MH, json={"name": name, "description": desc}).json() personas.append(p) time.sleep(0.3) product_catalog = "\n".join( f"- {p.get('attributes', p).get('title', 'Unknown')}: ${p.get('attributes', p).get('price', 0)} — {p.get('attributes', p).get('description', '')}" for p in products ) pair_questions = [] for pair in PRODUCT_PAIRS: pair_questions.append( f"You recently bought '{pair['bought']}'. On a scale of 1-5 (1=No interest, 5=Would buy immediately), " f"how likely are you to buy '{pair['suggest']}'? " f"Explain your rating — what would make you more or less likely?" ) pair_questions.append( "On a scale of 0-10, how likely are you to recommend our store to a friend? " "What's the #1 thing we'd need to do to move your score up by 2 points?" ) fg = requests.post(f"{MB}/focus-groups", headers=MH, json={ "name": "Klaviyo: Product Affinity Cross-Sell Study", "persona_ids": [p["id"] for p in personas], "questions": pair_questions, "context": f"""Product affinity study for an e-commerce running gear store. PRODUCT CATALOG: {product_catalog} CROSS-SELL HYPOTHESES: {chr(10).join(f"- {p['bought']} → {p['suggest']}: {p['logic']}" for p in PRODUCT_PAIRS)} Each persona represents a different buyer segment. We want to validate which cross-sell pairs resonate with each segment before building automated flows.""", "responses_per_persona": 2, }).json() for _ in range(30): time.sleep(5) data = requests.get(f"{MB}/focus-groups/{fg['id']}", headers=MH).json() if data.get("status") == "completed": break print(f"Focus Group: {data.get('id')} — {data.get('status')}\n") for resp in data.get("responses", []): print(f"[{resp.get('persona_id','?')}] {resp.get('question','')[:80]}") print(f" → {resp.get('answer','')[:300]}\n") ``` ```javascript JavaScript theme={"dark"} const KL_KEY = process.env.KLAVIYO_API_KEY; const MV = process.env.MAVERA_API_KEY; const MB = "https://app.mavera.io/api/v1"; const MH = { Authorization: `Bearer ${MV}`, "Content-Type": "application/json" }; const KH = { Authorization: `Klaviyo-API-Key ${KL_KEY}`, "Content-Type": "application/json", revision: "2024-10-15" }; let products = []; const catRes = await fetch("https://a.klaviyo.com/api/catalog-items?fields[catalog-item]=title,description,price&page[size]=50", { headers: KH }); if (catRes.ok) products = (await catRes.json()).data || []; if (!products.length) { products = [ { attributes: { title: "Running Shoes Pro", price: 129, description: "High-performance running shoes" } }, { attributes: { title: "Performance Socks 3-Pack", price: 24, description: "Moisture-wicking socks" } }, { attributes: { title: "GPS Running Watch", price: 299, description: "Multi-sport GPS watch" } }, { attributes: { title: "Hydration Belt", price: 35, description: "Hands-free hydration" } }, { attributes: { title: "Recovery Foam Roller", price: 45, description: "Deep-tissue roller" } }, { attributes: { title: "Training Plan (Digital)", price: 19, description: "12-week running program" } }, ]; } const PAIRS = [ { bought: "Running Shoes Pro", suggest: "Performance Socks 3-Pack" }, { bought: "GPS Running Watch", suggest: "Training Plan (Digital)" }, { bought: "Running Shoes Pro", suggest: "Recovery Foam Roller" }, { bought: "Hydration Belt", suggest: "GPS Running Watch" }, ]; const personas = []; for (const [name, desc] of [ ["Casual Runner", "Runs 2-3x/week for fitness. Price-conscious. Just exercise."], ["Dedicated Runner", "4-5x/week, tracks metrics, training for half marathon."], ["New Runner", "Started 2 months ago. First real shoes. Overwhelmed."], ]) { const p = await fetch(`${MB}/personas`, { method: "POST", headers: MH, body: JSON.stringify({ name, description: desc }) }).then((r) => r.json()); personas.push(p); await new Promise((r) => setTimeout(r, 300)); } const catalog = products.map((p) => `- ${p.attributes.title}: $${p.attributes.price} — ${p.attributes.description}`).join("\n"); const questions = PAIRS.map((p) => `You bought '${p.bought}'. Rate 1-5 (1=No interest, 5=Buy immediately) likelihood to buy '${p.suggest}'. Explain your rating.` ); questions.push("NPS 0-10: recommend our store to a friend? What moves your score up 2 points?"); const fg = await fetch(`${MB}/focus-groups`, { method: "POST", headers: MH, body: JSON.stringify({ name: "Klaviyo: Product Affinity Study", persona_ids: personas.map((p) => p.id), questions, context: `Running gear store cross-sell study.\n\nCatalog:\n${catalog}\n\nValidating cross-sell pairs before building flows.`, responses_per_persona: 2, }), }).then((r) => r.json()); let data; for (let i = 0; i < 30; i++) { await new Promise((r) => setTimeout(r, 5000)); data = await fetch(`${MB}/focus-groups/${fg.id}`, { headers: MH }).then((r) => r.json()); if (data.status === "completed") break; } console.log(`Focus Group: ${data.id} — ${data.status}\n`); for (const resp of data.responses || []) { console.log(`[${resp.persona_id}] ${(resp.question || "").slice(0, 80)}`); console.log(` → ${(resp.answer || "").slice(0, 300)}\n`); } ``` ### Example Output ```text theme={"dark"} Focus Group: fg_kl_affinity_8m3n — completed [Casual Runner] Shoes → Socks (1-5 scale) → 4/5. Actually yeah — I just spent $129 on shoes, and my old cotton socks are going to ruin them. At $24 for 3 pairs, it's a no-brainer add-on. BUT only if you show me this within 2 days of my shoe purchase. After a week, I've already grabbed socks at Target. [Dedicated Runner] Watch → Training Plan → 5/5. I bought the watch specifically to follow structured training. A $19 plan that tells my watch what workout to do today? That's the missing piece. This should be offered at checkout, not after. [New Runner] Shoes → Foam Roller → 2/5. I don't know what a foam roller is for. I'm too new to think about recovery — I'm still trying to run a mile without stopping. Sell me the roller in month 3, not month 1. [Casual Runner] NPS → 7/10. Good products, fair prices. To get me to 9: show me a "starter bundle" with shoes + socks + a beginner guide at 15% off. I hate shopping piece by piece. ``` ### Error Handling The Catalog Items API (`/api/catalog-items`) requires catalog sync to be configured in Klaviyo. If not set up, the endpoint returns empty. The code includes fallback sample data. For production cross-sell analysis, query Klaviyo's Events API filtered by `Placed Order` events to find actual co-purchase patterns before hypothesizing pairs. Focus Group responses include both the numeric rating and explanation. Parse the numeric value (e.g. "4/5") and the qualitative reasoning separately for analysis. *** ## What's Next Back to Klaviyo integration overview Simplified segmentation recommendations Channel preference insights Full reference for POST /api/v1/focus-groups