How do I analyze auction insights effectively?

What Auction Insights really tells you (and what it doesn’t)

The Auction Insights report is your “competitive visibility” dashboard inside Google Ads. It doesn’t tell you who has the best ads, the best landing page, or the lowest CPA. What it does tell you is how your visibility compares to other advertisers who entered the same auctions you did, during the time range you’re looking at. When you analyze it correctly, it becomes one of the fastest ways to answer questions like: “Are we losing out because of budget, Ad Rank, or a new competitor?” and “Where do we actually need to bid harder vs. improve quality?”

Where it’s available (and why it sometimes appears blank)

Auction Insights is available for Search, Shopping, and Performance Max campaigns, but the available metrics and “granularity” differ by campaign type. In Search, you can typically run it at keyword, ad group, or campaign level. In Shopping, it’s typically available at ad group and campaign level. In Performance Max, it’s available at campaign level, and the report breaks out Search versus Shopping impressions on the Search Network so you’re not mixing two very different auction behaviors.

If you’re not seeing any data, the most common causes are simply that the entity you selected (keyword/ad group/campaign) didn’t meet the minimum activity threshold for the selected date range, or your impression share is below 10% (in that case, Auction Insights won’t show). Also, Auction Insights focuses on Google Search Network auctions; Search Partners won’t be included in the same way and can’t be interpreted as “top vs. other” placements within Auction Insights.

The Auction Insights metrics that matter (and how to interpret them)

Impression share: your visibility slice of the auctions you were eligible for

Impression share is the percentage of impressions you received out of the total impressions you were eligible to receive. Eligibility is influenced by your targeting settings, ad approvals, and (for Search) components that feed Ad Rank (including quality signals). The key nuance in Auction Insights is that the competitor impression share you see is based on the auctions where you were also eligible—so it’s a “within your world” view, not necessarily their overall market presence.

For Shopping, impression share behaves differently because multiple Shopping ads from the same advertiser can appear in the same auction. Reporting avoids double counting by attributing the “impression opportunity” to the highest-ranked Shopping ad for that advertiser in that auction, which is why Shopping visibility metrics often feel less intuitive than Search.

Overlap rate: “How often do we show up together?”

Overlap rate tells you how often another advertiser got an impression when you also got an impression. High overlap is your signal that the advertiser is a consistent head-to-head competitor for the same intent (or the same product queries in Shopping). Low overlap with a high competitor impression share usually means they’re strong in auctions you’re not in (different geos, different query sets, different match strategy, different products, etc.).

Outranking share: your “win rate” in shared auctions

Outranking share is one of the most actionable metrics in the report. It tells you how often you ranked higher than the competitor, or you showed when they didn’t, in auctions where at least one of you showed. If you see a competitor with high overlap and your outranking share is low, you’re not just competing—you’re consistently losing. That’s when you diagnose whether the gap is budget, bids, Ad Rank/quality, or coverage (match types, query expansion, product feed depth).

Position above rate, top of page rate, and absolute top of page rate (Search only)

For Search campaigns, you get additional placement context. Position above rate tells you, when you both showed, how often the competitor appeared in a higher position than you. Top of page rate tells you how often an ad was shown above the organic results. Absolute top of page rate tells you how often an ad was the very first ad above the organic results.

In real accounts, these metrics are most useful for confirming a suspected change in competitive pressure. For example, if your impression share hasn’t moved much but a competitor’s position above rate has climbed over the last two weeks, it often indicates they’ve increased bids, improved Ad Rank, or shifted budget toward your core auctions.

A practical workflow to analyze Auction Insights effectively

Step 1: Start with a clear objective (visibility vs. efficiency)

Before you react to a competitor showing up, decide what you’re optimizing for. If you’re trying to maximize profitable conversions, your goal isn’t to “win every auction”—it’s to win the right auctions at the right price. Auction Insights is at its best when you use it to support a business decision, such as defending brand demand, protecting your best-selling categories, or identifying where you can safely reduce bids because you’re already dominant.

Step 2: Pull Auction Insights at the right level, then segment by time and device

If you run Auction Insights only at account level, you’ll blur together brand and non-brand, high-intent and research queries, and strong and weak geographies. Instead, pull it where decisions are actually made: brand campaign vs. non-brand campaign, your top ad groups, and (in Search) your highest-value keyword themes.

Then segment by time and device. Competitive behavior often differs massively on mobile versus desktop, and shifts over time are the difference between “normal noise” and “a competitor just launched a new push.” In practice, a clean approach is to compare the last 7 days vs. the previous 7 days for early detection, then validate with a 28-day view so you don’t overreact to a short-term fluctuation.

Step 3: Pair Auction Insights with impression share diagnostics (this is where most advertisers level up)

Auction Insights tells you who is in the auction and how visibility compares. It doesn’t tell you why you’re missing impressions. For that, you combine it with competitive impression share columns such as Search lost IS (budget) and Search lost IS (rank). This is the fastest way to separate “we’re constrained by budget” from “we’re losing Ad Rank” without guessing.

For Search campaigns, add top-of-page opportunity metrics when visibility is the priority. Search top impression share and Search absolute top impression share help you understand whether you’re missing out on top placements specifically, not just impressions anywhere on the page.

If you use broad match heavily, don’t skip Search exact match impression share. It helps you distinguish whether you’re under-serving even on the searches that match your keywords most precisely, versus being spread thin across broader matching where you may be less competitive or less relevant.

Important nuance with Smart Bidding: if you’re using Maximize conversions or Maximize conversion value, treat “Lost IS (budget)” carefully. Those strategies are designed to spend the budget you set, and a campaign being “limited by budget” can be inherent to how you’ve chosen to operate. In other words, don’t automatically “fix” Lost IS (budget) on those strategies unless you’re intentionally trying to buy more volume and your unit economics support it.

Step 4: Turn the patterns into actions (a decision framework you can apply weekly)

Once you have (1) Auction Insights and (2) impression share diagnostics on the same campaign/ad group set, you can translate insights into optimizations without overcorrecting.

• If overlap rate is high and outranking share is low: you’re consistently losing head-to-head. First confirm whether you’re losing due to Ad Rank (Lost IS (rank) high) or budget (Lost IS (budget) high). Then decide whether the business can support paying more (higher bids/budget) or whether the smarter move is to improve Ad Rank via tighter relevance, stronger creative, and better landing page alignment.
• If competitor impression share is rising but your Lost IS (rank) is stable: often they’re entering more auctions (coverage expansion) rather than beating you in the same auctions. Your counter-move may be better query sculpting, adding high-intent terms, or improving your Shopping feed depth—not just bidding higher.
• If your impression share is strong but top/absolute-top rates are weak (Search): you’re showing, but not prominently. This can be fine if performance is strong. If performance depends on premium placement (common for brand defense), consider a visibility-focused approach (like Target impression share) with sensible bid caps, because aggressive “absolute top at all costs” can inflate CPCs quickly.
• If Shopping overlap is high: don’t assume “bids fix everything.” Shopping eligibility and performance are heavily influenced by product data quality and coverage. Often the fastest win is improving product titles, attributes, and feed completeness so you enter more relevant auctions and rank better when you do.

Advanced tips and common mistakes (so you don’t misread the report)

Mistake: Treating competitor impression share as their “total market share”

The impression share you see for other advertisers inside your Auction Insights is constrained to the auctions that overlap with your own eligibility. That’s why you can see scenarios where you have extremely high impression share, yet a competitor still shows a meaningful impression share in the same report—because their eligible impressions and your eligible impressions don’t perfectly overlap.

Mistake: Over-optimizing to “absolute top” and assuming it always improves results

Top placement metrics are useful, but they’re not a universal goal. Higher bids can qualify you for more competitive auctions where you actually appear in worse locations than before, which can cause certain placement rates to move in unexpected ways. Treat prominence as a lever you pull for specific campaigns (brand, high-margin hero categories, short-term promos), not as a default KPI across the entire account.

Pro move: Use Auction Insights to guide controlled tests, not constant bid chasing

The biggest accounts I’ve managed don’t “react-bid” every time a competitor appears. Instead, they use Auction Insights to identify where competitive pressure is changing, then run contained tests: a budget increase on a single campaign, a bid strategy shift on a defined segment, or a creative refresh for a high-overlap theme. That keeps learning clean and prevents you from destabilizing performance across the account.

Pro move: Build repeatable reporting views for Search vs. Shopping vs. Performance Max

Auction behavior differs by campaign type, so keep your reporting separated. In reporting tools inside Google Ads, use the Auction Insights report types designed for Search and for Shopping so you’re comparing like with like. For Performance Max, always interpret Auction Insights through the Search-versus-Shopping segmentation so you don’t make Search bidding decisions based on Shopping auction dynamics (or vice versa).

A quick weekly checklist (what I’d do in 15 minutes per core campaign)

• Check Auction Insights for the last 7 days vs. prior 7 days, segmented by device.
• Identify any competitor with rising overlap rate or falling outranking share.
• Add Search lost IS (budget) and Search lost IS (rank) (and top/absolute-top impression share if prominence matters) to confirm the root cause.
• Choose one action per campaign: adjust budget, adjust bids/strategy, improve ad quality and relevance, narrow/expand targeting, or improve Shopping feed coverage—then measure the change over the next 7–14 days.

To analyze Auction Insights effectively, start by treating it as a visibility and competition dashboard (not a “who has the best ads” report) and anchor every read to a clear objective—defend brand, grow category volume, or protect efficiency—then pull the report at the decision level that matters (brand vs. non-brand, key campaigns, top ad groups/keywords) and compare short windows like last 7 days vs. prior 7 days while sanity-checking with a longer view to avoid noise. Use impression share to understand your visibility only within the auctions you were eligible for, use overlap rate to identify true head-to-head competitors, and use outranking/position-above and top/absolute-top metrics to spot shifts in pressure; then pair those patterns with impression share diagnostics like Lost IS (budget) and Lost IS (rank) to separate “need more budget” from “need better Ad Rank/quality/coverage,” especially if you’re on Smart Bidding where some budget loss may be intentional. If you want help turning these signals into a repeatable weekly workflow, Blobr connects to your Google Ads account and runs specialized AI agents that continuously monitor changes and translate insights into clear, prioritized actions—like tightening wasted coverage, expanding keywords, or improving ad copy and landing-page alignment—while keeping you in control of what runs where and how often.