articles

Find the original sources, practical reading and people behind the collective. These links open the full public pages.

29 pages · Page 1 of 1

• PPC articles & analysis

  Selected research, interviews and perspectives for paid media managers, with reading notes and links to the original publishers.

• Which campaign boundaries still matter with AI?

  Navah Hopkins considers which parts of campaign structure remain useful as advertising platforms automate more decisions. The article connects consolidation with signal quality while preserving distinctions that matter for budgets, goals and business constraints. Read it before reorganising an account simply to follow a consolidation trend. It offers a way to question each boundary: whether it helps the business control something important or fragments learning without a clear purpose, with measurement and asset quality still central to the decision.

• Does AI-assisted content make the reader’s job easier?

  Kirk Williams distinguishes using AI to clarify an expert’s ideas from using it to pass unfinished thinking to someone else. The essay is relevant to PPC reporting, client emails and strategy documents, where producing more text can create more work for the recipient. Read it before standardising an AI writing workflow. The useful test is whether the final message helps a reader understand the argument and make a decision, with a person still responsible for its accuracy.

• Who controls AI-assisted programmatic buying?

  Ronan Shields examines the gap between using AI to optimise campaigns and authorising it to buy media. His analysis of IAB Europe’s survey looks at adoption, human oversight and how teams measure success, then connects those questions to publisher controls. It offers a useful agenda for conversations with programmatic partners: who can approve spending, inspect decisions and intervene? Read the original for the survey’s small respondent groups and the distinction between operational efficiency and proven business performance.

• Improve the signals your advertising automation learns from

  Brooke Osmundson argues that increasing automation makes measurement choices more consequential. A campaign can optimise efficiently towards a conversion that does not represent a qualified lead, a profitable order or the outcome the business actually values. Read the article before making a major campaign change. It provides a reason to review CRM feedback, conversion definitions and a baseline of mature results first, so the team can distinguish more reported activity from an improvement in the quality of its acquisition.

• Design B2B campaigns for a buying group

  Michelle Wiltz considers why campaigns aimed at a single decision-maker can stall when a business purchase depends on several people. Drawing on industry discussions, she connects campaign messaging with the different concerns, risks and questions inside a buying group. Read it when leads arrive but opportunities struggle to progress. It offers a way to review whether your content helps people build agreement, rather than repeatedly asking one contact to convert without giving them the evidence their colleagues need.

• What holiday account data can tell you about BFCM planning

  Lakshmi Padmanaban examines Optmyzr’s holiday dataset of more than 4,200 Google Ads accounts, separating the periods before, during and after the main sale. The findings connect changing costs and conversion behaviour with decisions about budgets, targets and product margins. Read the original methodology before adapting the advice to your own account. Its most useful contribution is a three-period planning framework, supported by observed campaign patterns and practitioner commentary, rather than a single bid setting to copy across every retailer.

• Reading the evidence on Smart Bidding and budget limits

  Mike Ryan examines changes in CPCs and impression-share loss around Google’s August bidding change using smec campaign observations. The analysis compares campaigns with different budget constraints and considers how losses to budget and rank can change the interpretation of auction performance. It is useful for deciding which account signals to investigate before adjusting targets. Read the charts and their limitations together: conversion attribution was still incomplete at publication, so the early observations do not establish a final return-on-ad-spend outcome.

• Give brand and generic search different jobs

  Chanelle Dzwowa explains why brand and generic search can look very different while both contributing to a marketing plan. Brand campaigns tend to capture existing intent, whereas generic activity can introduce a business to people who do not yet know it. Her article challenges teams to define those jobs before comparing cost per acquisition. Read it when a budget discussion treats the cheapest campaign as the only useful one, and consider what evidence would demonstrate additional customers rather than simply more attributed conversions.

• Why early ChatGPT Ads results are hard to benchmark

  Brooke Osmundson compares early public accounts of ChatGPT advertising and explains why they do not yet provide a reliable universal benchmark. Advertisers are testing different offers, audiences and measurement setups, while reporting and targeting differ from established search campaigns. Read this before using a quoted CPC or success story in a forecast. The article is most useful for framing a test around your own lead quality and commercial outcomes, and for separating a recommended bid from an observed acquisition cost.

• Decide what a ChatGPT Ads test is meant to prove

  Brooke Osmundson sets out the questions advertisers should answer before allocating budget to ChatGPT Ads. The discussion starts with the channel’s intended role, then considers intent, measurement and the opportunity cost of moving money from existing campaigns. Read it when an exploratory budget is being proposed without a clear decision at the end of the test. It helps frame an experiment around a business question, rather than assuming conversational advertising should immediately behave like established paid search.

• What one early ChatGPT Ads test can teach you

  Mery Hayles reviews an early ChatGPT Ads test alongside Adthena’s monitoring of advertising activity. The piece is useful as a record of what practitioners were learning in July, when targeting, reporting and advertiser participation were still developing. Read it for questions to bring to your own experiment: how context affects delivery, what the reporting can establish and what still needs independent measurement. Treat the examples as a historical test snapshot rather than a current product specification or a forecast for another advertiser.

• What early ChatGPT Ads practitioners learned

  Boluwa Olojo interviews six marketers about their early experience with ChatGPT Ads. Their accounts cover lead quality, measurement, targeting and the conditions that would justify increasing investment. Read the interviews to compare the questions different businesses ask of the same emerging channel. The variety is more useful than a single headline result: it shows why a test needs its own commercial definition of success, downstream tracking and a clear distinction between an encouraging observation and evidence that can support scaling.

• Connect demand-generation budgets to buying progress

  Emanuela Mafteiu explores how demand-generation teams can explain their investment when every budget line is under pressure. Her account connects buying groups, sales coordination and measurement across the journey rather than relying on a single lead metric. Read it when planning a campaign with a long sales cycle or discussing performance with finance. The useful question is whether the team can connect media activity to meaningful buying progress and business value, while recognising that a recorded touchpoint is not proof of causation.

• Where email placements fit in paid-media planning

  Jonathan Kagan, with contributions from Brandon LaRocco and Patrick Dunfey, examines advertising placements in email environments such as Gmail and Outlook. The article connects campaign access, creative and measurement with a more useful comparison set than branded search. Read it when deciding whether inbox inventory deserves a test alongside other discovery channels. Its account examples help frame the opportunity, but the decision should still rest on customer quality and additional business outcomes, with paid placements complementing your existing email programme.

• Who should control a client’s Google Ads account?

  Anu Adegbola brings together five practitioners’ perspectives on control of a client’s Google Ads account. The discussion covers continuity, access, historical data and the complications that can arise when an agency relationship ends. Read it before agreeing an onboarding or handover process. The contributors explain why the operational arrangement should be understood from the start, including any reseller constraints, so a business can retain access to the information and capabilities it needs when its service providers change.

• What a Google Ads CTR benchmark can and cannot tell you

  Vimal Bharadwaj explores click-through-rate differences across Google Ads campaign types, account sizes and business categories using Optmyzr’s research. The breakdown helps explain why an overall average is a weak target for an individual campaign. Read it when reporting a CTR change or evaluating creative performance. A higher rate may reflect a different mix of impressions as well as better messaging, so the comparison becomes more useful when you also examine query relevance, qualified traffic and the commercial results after the click.

• How to interpret Google Ads ROAS benchmarks

  Vimal Bharadwaj breaks down Optmyzr’s Google Ads return-on-ad-spend findings by spending level and business category. The comparisons are useful for understanding how far an overall median can hide differences between accounts. Read the study alongside your own conversion-value definitions, margins and acquisition goals. A reported return can mean very different things for an online retailer and a lead-generation business, so the practical value is in choosing a relevant comparison and questioning the inputs before adopting a headline target.

• What Microsoft’s holiday research means for campaign planning

  Danielle McMeekin presents Microsoft Advertising’s research on holiday shopping, AI-assisted discovery and the timing of purchase journeys. The article connects early consideration, value-conscious shopping and brand discovery with questions advertisers face when preparing seasonal campaigns. It is useful for reviewing when to start activity and which assumptions about discovery deserve testing. Read the findings by market and evidence type: survey intentions and observed conversion journeys answer different questions, and neither should automatically replace what your own customer and account data show.

• Look beyond the cheapest lead in bidding decisions

  Laura I. Abreu examines the tension between a low cost per lead and leads that are useful to a business. Her discussion connects bidding targets with budget constraints, qualification and the information advertisers send back to the platform. Read it when changing targets seems to improve volume without improving sales. The article encourages a closer review of what the account rewards and how ad messaging qualifies interest, before making a broad bidding change or adding friction to every lead form.

• Where manual work persists in Google Ads

  Optmyzr examines change histories from 72,358 accounts to understand where manual Google Ads work remains common. The study separates the number of changes from the frequency of manual working sessions, a useful distinction when looking for tasks that repeatedly interrupt an account manager’s day. Frederick Vallaeys uses these patterns to explore automation opportunities. Read the methodology alongside the findings: this is a dataset of Optmyzr accounts, and estimates of time saved depend on assumptions rather than direct measurements of every advertiser’s working day.

• Read paid-search benchmarks against the right calendar

  Brooke Osmundson examines a quarterly advertising report through the context of prior-year comparisons, promotional timing and changing search behaviour. Her analysis is useful when a slowdown in growth is being treated as evidence that an entire channel has stopped working. Read it alongside your own trading calendar before adjusting forecasts. The article encourages a more careful distinction between market spending trends, the timing of demand and the results an individual advertiser can achieve with its next unit of budget.

• Build a pipeline measurement story finance can inspect

  Natalia Hernandez explores how marketers can connect campaign activity with the pipeline measures finance needs. Her article brings together CRM integration, consistent identifiers and a broader view of measurement than platform-reported conversions alone. Read it when marketing and finance disagree about the value of leads or opportunities. The useful starting point is a shared definition of progress and value, followed by an honest account of what each measurement method can establish, rather than presenting one attribution model as a complete explanation.

• Why questioning AI still matters in PPC

  Kirk Williams makes the case for challenging AI claims while continuing to experiment with the technology. The essay gives PPC teams a starting point for evaluating new workflows when the pressure to adopt AI runs ahead of the evidence. It encourages a closer look at the usefulness and reliability of individual applications. Read it to shape a more specific team discussion about what a tool should achieve and what evidence would justify continued use, rather than treating enthusiasm or scepticism as a verdict.

• Which search audiences does your PPC plan miss?

  Andy Squire asks advertisers to look beyond performance inside their familiar search accounts and consider people using other search services. The article encourages a broader discussion of audience coverage, rather than assuming that strong results in the largest platforms represent the whole opportunity. Read it when reviewing channel concentration or proposing a small expansion test. Its value is the question it raises about reach; any investment still needs evidence of relevant queries, qualified customers and returns that justify the additional management work.

• Smart Bidding after August 17: practitioner perspectives

  Anu Adegbola brings together Reva Minkoff and Craig Graham’s answers to PPC Live community questions about budget-constrained Smart Bidding. The discussion explores how practitioners assess efficiency targets and investigate a change in results before reacting. It is useful when reviewing configured targets against delivered CPA or ROAS, alongside conversion lag, seasonality and account history. Read the different perspectives as diagnostic prompts for your own campaigns. These are practitioner observations, and the appropriate response still depends on the campaign objective and the business behind it.

• Review the targets your Smart Bidding strategy is following

  Frederick Vallaeys examines what it means for Smart Bidding to operate closer to the targets advertisers set. He separates possible mechanisms from established observations and asks teams to review efficiency goals, budget constraints and conversion maturity before reacting to a performance change. Read it when an account no longer behaves as expected around its CPA or ROAS target. The article supports a disciplined diagnosis using dated changes and business context, rather than assuming that one platform update explains every movement.

• What reliable AI infrastructure means for PPC

  Kirk Williams argues that useful PPC automation needs testing, maintenance and safeguards beyond a successful prompt. The distinction matters when an experiment starts making repeated changes in live advertising accounts. His argument shifts attention from the initial demonstration to the testing, maintenance and oversight needed afterwards. Read it when comparing a custom workflow with a maintained product, and use it to question who will detect errors, handle edge cases and reverse an unwanted change.

• Why YouTube needs its own paid-media strategy

  Sarah Stemen argues that advertisers weaken YouTube tests when they bring search-campaign expectations to a video environment. She focuses on measurement, creative built for video, a clear offer and enough room to learn. Read the article before judging a campaign solely by immediate conversions or repurposing existing assets without a plan. It provides a framework for discussing what YouTube should contribute and how to investigate that contribution, while leaving the budget and evaluation method to the advertiser’s circumstances.