Content research from People also ask

1. 01Search the seed topics

   Search each topic with the country and language you write for. People also ask and related searches are on the first page, so one page per query is enough.

   GET /v1/search?engine=google_search&q=albert+einstein&country=us&page=1 · query

   {
     "q": "albert einstein",
     "language": "en",
     "country": "us",
     "page": 1
   }

2. 02Keep the questions

   people_also_ask lists the questions Google showed. These are phrased the way people ask, which makes them good headings and FAQ entries.

   GET /v1/search?engine=google_search&q=albert+einstein&country=us&page=1 · people_also_ask

   [
     "What is Einstein famous for?",
     "Did Einstein believe in God?"
   ]

3. 03Follow related searches one level

   related_searches are the queries people type next. Search the first few of them to widen the map without it growing out of hand.

   GET /v1/search?engine=google_search&q=albert+einstein&country=us&page=1 · related_searches

   [
     "Albert Einstein quotes",
     "Albert Einstein inventions"
   ]

# Map what searchers ask around a topic: People also ask and related
# searches for seed queries, expanded one level. Out: questions.csv.
import csv, os, requests

API = "https://api.clair.im"
HEADERS = {"Authorization": f"Bearer {os.environ['CLAIR_API_KEY']}"}
SEEDS = ["web scraping api", "serp api", "amazon price tracker"]

def serp(q):
    r = requests.get(f"{API}/v1/search", headers=HEADERS, timeout=60, params={
        "engine": "google_search", "q": q, "country": "us", "language": "en"})
    r.raise_for_status()
    return r.json()

rows, done = [], set()
for seed in SEEDS:
    body = serp(seed)
    done.add(seed)
    rows += [(seed, "question", q) for q in body["people_also_ask"]]
    rows += [(seed, "related", q) for q in body["related_searches"]]
    # One level deeper: related searches are queries people type next.
    for q in body["related_searches"][:5]:
        if q in done:
            continue
        done.add(q)
        rows += [(q, "question", x) for x in serp(q)["people_also_ask"]]

with open("questions.csv", "w", newline="") as f:
    csv.writer(f).writerows([("from_query", "kind", "text"), *dict.fromkeys(rows)])

Set CLAIR_API_KEY to a key subscribed to the Google Search API. Each call is one request against that API's monthly quota.

• People also ask returns the questions shown when the page loads. Google adds more as a visitor opens them; those are not returned.
• Answers to the questions are not included. Search the question itself to see which pages answer it.
• Not every query shows these blocks. Brand and navigational queries often have neither.