Competitor Rank Tracking & Monitoring, via one SERP API

A typical competitive-intelligence (CI) suite bundles SERP data with backlinks and traffic estimates, then hides the raw signals behind a UI. cloro returns just the SERP slice, as JSON: any competitor's organic positions, ads, AI Overview citations, and People Also Ask (PAA) appearances for any query, country, and device. Whatever scoring methodology your team has, you can run it on the response yourself.

What is competitor rank tracking?

Competitor rank tracking is watching where your rivals rank in Google — not where you rank — for the keywords you both compete on, on a fixed cadence. It is the most measurable form of competitor analysis, because on the search results page a competitor's footprint is concrete: which queries they rank for and where, which ads they run and when, whether the AI Overview cites them, and whether they own the People Also Ask slots your buyers click. Broaden the same loop beyond positions — ads entering the auction, new domains in the top ten, citation changes — and you have competitor monitoring.

The tooling splits in two. Full CI suites bundle that SERP data with backlinks, traffic estimates, and a scoring methodology baked into the dashboard. A SERP data primitive returns the raw rows — organic positions, ads[], AI Overview sources, PAA — so the scoring methodology stays in your code and survives every tool change. cloro is the primitive: the SERP slice as JSON, for whatever competitor math your team already runs.

The SERP signals competitor analysis actually depends on

Where do competitors rank? Which ads are they running? Are they cited in the AI Overview for the queries that matter? Are they showing in PAA, related searches, or sponsored slots? cloro returns every SERP element that informs competitor positioning, parsed and position-tagged, in one JSON response. One call answers all four questions.

Why competitive-intel teams build on cloro, not on bundled CI suites

Competitor analysis comes in two product shapes: full CI suites (all-in-one dashboards with their methodology baked in) and SERP data primitives (cloro — raw structured response, your methodology applied in your code). Teams that need their CI methodology consistent across vendor changes pick the primitive. Here's why.

CI suites bake their methodology into your reports

Pull the same competitor through three CI suites in the same week and you get three different "strength" numbers: 67 on one (organic-weighted), 71 on another (backlink-weighted), 4,210 on a third (traffic-modeled). None of those numbers map cleanly to whatever your team actually reports. cloro returns the SERP fields directly, including rank_group, rank_absolute, and the full envelope, so you can run your own share-of-voice math against the same data each time.

Competitor ad monitoring needs the live SERP

SERP ads rotate hourly with competitor bids and budget pacing. CI suites refresh ad data weekly, so a burst of competitor spend can start and finish between snapshots. cloro returns parsed ads[] on every call: sample hourly across your top 100 commercial queries and you see exactly when a competitor enters the auction, raises bids, or pauses.

AI Overview is the competitor signal of 2026

AI Overview renders on ~40% of commercial queries. Competitors cited in the source list capture the answer-traffic that organic position 1 used to win. CI suites are still building this; cloro returns aioverview.sources[] (position, URL, citation context) per call alongside the standard SERP, so you see which rivals Google is quoting. It is also the common case rather than an edge case.

Cross-keyword competitor coverage needs the API

Tracking 50 competitors × 500 keywords is 25,000 cells of SERP data. CI suites cap this with per-competitor and per-keyword bundles. cloro is flat per-call: 500 keywords × 50 competitor-presence checks happens in one batch of 500 calls. Your detection is a warehouse query, not a per-row upcharge.

Use cases

Four competitor rank tracking and monitoring workflows CI teams ship on top of cloro SERP data.

Competitor rank tracking at scale

Track every competitor's organic position across your keyword set on a daily cadence, weight by position with your own share-of-voice math, and trend it in your BI tool.

Competitor ad-rotation tracking

Sample your top commercial queries hourly and diff ads[] between runs — see exactly when a competitor enters the auction, shifts position, or pauses.

AI Overview citation audit

Map which competitors the AI Overview cites across your keyword set — the answer-traffic signal organic position 1 used to own.

Always-on competitor monitoring

Alert the day an unfamiliar domain enters the top-10, the ad slots, or the AI Overview sources on a query you own — launch detection from the SERP itself.

Competitor rank tracking across your keyword set

One call per query × country × device, cloro parses the SERP, you filter for any competitor domain across organic, ads, AI Overview, and PAA. Roll up to your warehouse for share-of-voice math, ad-rotation tracking, or AI Overview citation auditing.

Detect a competitor's SERP presence across a keyword set

from cloro import Cloro

client = Cloro(api_key="sk_live_your_api_key_here")

# Your keyword set + the competitor you're auditing.
keywords = ["best project management software", "asana alternatives", "trello alternatives"]
competitor_domain = "monday.com"

results = []
for query in keywords:
    response = client.monitor.google(
        query=query,
        country="US",
        device="desktop",
        include={"aioverview": {"markdown": True}},
    )
    data = response["result"]

# Detect competitor across every SERP surface
    organic_pos = next((r["position"] for r in data["organicResults"]
                        if competitor_domain in r["link"]), None)
    in_ads = any(competitor_domain in a["domain"] for a in data.get("ads", []))
    aio_sources = data.get("aioverview", {}).get("sources", []) or []
    in_aio = any(competitor_domain in s["url"] for s in aio_sources)
    aio_position = next((s["position"] for s in aio_sources
                         if competitor_domain in s["url"]), None)

results.append({
        "query": query,
        "competitor": competitor_domain,
        "organic_position": organic_pos,
        "in_ads": in_ads,
        "in_aioverview": in_aio,
        "aioverview_position": aio_position,
    })

print(results)

Response example

{
  "success": true,
  "result": {
    "organicResults": [],
    "ads": [],
    "peopleAlsoAsk": [],
    "relatedSearches": [],
    "aioverview": {}
  }
}

Competitor Analysis, answered

Is cloro a full competitor-analysis suite?

No. cloro is the SERP data primitive that CI tools build on. Full suites bundle SERP, backlinks, traffic, and site-audit into one dashboard. cloro provides the SERP slice as raw JSON so your methodology stays in your code. Most enterprise CI programs use both: a suite for breadth, cloro for SERP-data depth.

What competitor signals does the SERP expose?

Five per call: organic position, sponsored-ad presence (with bid position and creative), AI Overview citation (URL + position), PAA appearance, and named-in-related-searches. Every signal in one structured JSON response, so you see whether a rival earned the placement or bought it.

Can I compute share of voice from this?

Yes. For a fixed keyword set, count where each competitor (including you) appears across organic top-10, ads, and AI Overview citations, weight by position, divide by total. The math runs against the SERP rows in your warehouse — methodology stays yours.