Question 1

How does a second-price auction work in real-time bidding?

Accepted Answer

In a second-price (Vickrey) auction, the highest bidder wins but pays the second-highest bid plus a small increment (e.g., $0.01). Advertiser A bids $2.00, Advertiser B bids $1.50 -- A wins and pays $1.51. The key property: bidding your true valuation is the dominant strategy. If you bid above your valuation and win, you overpay (negative value). If you bid below your valuation, you may lose an impression worth more than what you would have paid. This incentive-compatibility reduces the need for sophisticated bid shading strategies and simplifies DSP optimization. In practice, many exchanges have moved to first-price auctions (winner pays their bid) due to concerns about unfair advantages for SSPs optimizing second prices. First-price requires DSPs to shade bids (bid below true valuation) to avoid overpaying.

Question 2

How do you implement frequency capping at scale?

Accepted Answer

Frequency capping limits the number of times a user sees an ad from a campaign (e.g., max 3 impressions per user per day per campaign). Implementation: Redis counter per (campaign_id, user_id, date). INCR camp:{cid}:user:{uid}:{date} and check if result

Question 3

How do you prevent click fraud in an ad server?

Accepted Answer

Click fraud: bots or malicious publishers generate fake clicks to drain advertiser budgets. Detection layers: (1) Duplicate detection: SETNX click:{imp_id} in Redis with TTL=24 hours. If key exists, reject the click (same impression cannot be clicked twice). (2) Velocity checks: more than 5 clicks from the same IP in 10 minutes u2192 flag. (3) User agent analysis: known bot user agents, headless browser fingerprints, missing or invalid JavaScript execution. (4) Time-between-events: click within 50ms of impression load (impossible for human). (5) Invalid traffic (IVT) scoring: Google IVT standards classify traffic as GIVT (general invalid, easily detected) and SIVT (sophisticated invalid, requires ML models on behavior patterns). Flag suspicious clicks for manual review; charge advertisers only for valid clicks. Refunds for confirmed fraudulent clicks are issued monthly.

Question 4

How does user targeting with behavioral segments work?

Accepted Answer

A Data Management Platform (DMP) builds user profiles from first-party data (publisher's own users) and third-party data (purchased from data brokers). Each user profile is a set of segment IDs: user A belongs to segments [sports_fan, male_25_34, tech_enthusiast, high_income]. Segment membership is stored in Redis as a bitset per segment (bit set = user is in the segment) or as a set of segment IDs per user. At bid time: load the user's segments. For each active campaign, check if the user's segments satisfy the campaign's targeting expression (e.g., sports_fan AND (male_25_34 OR male_35_44) AND geo=NYC). Targeting evaluation must be sub-millisecond. Pre-compute targeting matches: when a campaign's targeting changes, index it against segment combinations so bid-time matching is a simple lookup rather than expression evaluation.

Question 5

What is the difference between CPM, CPC, and CPA pricing models?

Accepted Answer

CPM (Cost Per Mille): advertiser pays per 1000 impressions shown, regardless of clicks or conversions. Predictable for advertisers; risk is low conversion rate. Used for brand awareness campaigns. CPC (Cost Per Click): advertiser pays only when a user clicks the ad. Publisher bears the risk of low CTR. Used for performance campaigns where clicks signal intent. CPA (Cost Per Action/Acquisition): advertiser pays only when a user completes an action (purchase, signup). Publisher and DSP bear the conversion risk. Highest advertiser ROI certainty. RTB auctions typically clear in CPM, even for CPC/CPA campaigns -- the DSP converts its target CPC or CPA to an equivalent CPM bid: expected CPM = target CPC * expected CTR * 1000. Getting CTR and conversion rate prediction right is the DSP's core competency.

System Design: Ad Server — Targeting, Real-Time Bidding, Impression Tracking, and Click Attribution

Overview

Ad Request Flow (RTB)

Targeting

Budget Pacing

Impression and Click Tracking

Attribution

Interview Tips