Strategy
Part of What Makes Marketing Case Studies Credible
How to Audit Marketing Case Study Libraries
A working method to audit marketing case study libraries from Google Ads and LinkedIn Success Hub: filters, claims, missing evidence, and what you may reuse.
What to take away
- Google Ads resources wins on filter depth among the marketing case study libraries. It narrows by product, campaign type, content type, industry, marketing level and goal.
- LinkedIn Success Hub wins on B2B context, naming the audience, the campaign format and the funnel stage.
- Neither library is independent. Both are vendor-published collections with no outside verification.
- Ten named stories appear below, each with the metric worth checking and the context a reader needs before trusting it.
- Reuse the audit questions and the structure. Do not reuse the numbers.
The verdict on both libraries
Google Ads resources is the deeper library for filters. A reader can narrow by product, campaign type, content type, industry, marketing level and goal. That matters when you need a story close to your own setup.
LinkedIn Success Hub filters by region, industry, product and company size. Its stories carry more context about who was targeted and where they sat in the buying process.
Filters
- Google Ads resources
- Product, campaign type, content type, industry, marketing level, goal
- LinkedIn Success Hub
- Region, industry, product, company size
Story context
- Google Ads resources
- Market, product, reported outcome
- LinkedIn Success Hub
- Audience, campaign format, funnel stage
Evidence quality
- Google Ads resources
- Platform metrics only, no independent verification
- LinkedIn Success Hub
- Platform metrics plus customer quotes, no independent verification
The short verdict: Google Ads for search, YouTube and Performance Max comparisons. LinkedIn for demand generation and lead quality.
Both pages state that results vary by advertiser. Treat one story as a lead for testing, which is the bar marketing case studies have to clear before they shape a decision.
Google Ads stories: L'Oreal, Puma, HelloFresh, Toyota, Nestle
The Google Ads resource library mixes success stories with product pages. Each story names the advertiser, the product used and a reported outcome. Check the market, the eligibility rules and the measurement source before you copy a plan.
Google Ads Story Audit
- Publication date
- Customer and publisher roles
- Measure and comparator
- Source statement
- Attribution language
- Simultaneous changes
- Advertiser-variation note
Google Ads stories
| Story | Placement | Metric to check |
|---|---|---|
| L'Oreal | YouTube and Search, beauty shoppers | Brand lift, and the source of the sales figure |
| Puma | Performance Max, ecommerce | Conversion value against the stated baseline |
| HelloFresh | Search and YouTube, subscriber acquisition | Cost per subscription, attribution window |
| Toyota | Local inventory ads, dealerships | Store visits, plus market and eligibility rules |
| Nestle | YouTube, consumer reach | Reach separated from sales impact |
Two of the five rest on platform measurement alone. Puma compares conversion value with a baseline, so the baseline definition decides whether the result transfers. Nestle reports reach, and reach is not a business outcome.
Compare a vendor write-up with the constructed marketing case study examples built to teach a method. The vendor page supplies a claim. The teaching example supplies a process you can copy.
LinkedIn Success Hub stories: Adobe, Cisco, SAP, Philips, Vodafone
Success Hub stories are written for B2B buyers. The card leads with an outcome summary, so open the full story before you trust it. Each one usually names the audience, the campaign format and a funnel metric.
LinkedIn Success Hub stories
| Story | Placement | Metric to check |
|---|---|---|
| Adobe | B2B demand generation, digital experience products | Qualified leads or pipeline contribution |
| Cisco | Sponsored Content and Lead Gen Forms, IT decision-makers | Lead quality, cost per lead |
| SAP | Targeting, business and technology leaders | Reported outcome against the stated goal |
| Philips | Healthcare professional audiences | Product and region of the study |
| Vodafone | B2B brand and demand | Engagement separated from pipeline |
Reach and engagement appear more often than pipeline here. That is the main evidence gap. Ask which metric moved, over what period, and who measured it.
LinkedIn B2B Story Architecture
Audience
- Reach or engagement
- Vendor-reported
- Business outcomes
- Customer-specific
Targeting
- Reach or engagement
- Platform-specific
- Business outcomes
- Independent proof rare
Funnel stage
- Reach or engagement
- Top-funnel
- Business outcomes
- Bottom-funnel
Reported metrics
- Reach or engagement
- Often impressions
- Business outcomes
- Revenue or leads
Example: one finished audit row
Run every story through the same table. The fields follow the marketing case study checklist, which sets out what a usable record needs. Five steps do the work.
One finished audit row
- Record publisher, customer, publication date, market and audience.
- Record the problem, the intervention, the baseline and the metric formula.
- Record the comparator, the attribution method and any disclosure.
- Record the missing evidencecontrol group, spend, sample size, confidence interval.
- Record the reusable lesson and the first-party test that would confirm it.
Example row, L'Oreal. Publisher: Google Ads resources. Market: not stated on the card. Metric: brand lift. Formula: not published. Comparator: none stated. Attribution: platform-reported. Missing: control group, spend, confidence interval. Reuse: test YouTube and Search together, then measure brand lift in your own account.
Typical range for these write-ups: one to three headline metrics, no confidence interval and no control group.
What you may reuse, and what you may not
US rules set the floor. The FTC requires a reasonable basis for objective advertising claims before they run, as set out in the Policy Statement Regarding Advertising Substantiation. A vendor figure therefore needs a source you can name.
Endorsement rules add a second layer. The FTC's Guides Concerning the Use of Endorsements and Testimonials in Advertising (16 CFR Part 255) cover selective solicitation, incentives and hidden relationships. Apply that test when a library names providers.
Sponsored placements must be identifiable. The FTC's Native Advertising: A Guide for Businesses explains when paid content has to be labelled as advertising.
Reuse questions, structure and layouts. Do not copy numbers, logos, screenshots or quotes without rights. If you need a blank structure, start with the case study template libraries collection.
Common questions
Is one library ranked above the other?
No. This is an unpaid, nonranking comparison. Google Ads is deeper on filters and LinkedIn is deeper on B2B context, and neither is independent.
Can a reported figure become a benchmark?
Only with a compatible population, metric, formula, period and spend. Without shared definitions, the number describes one advertiser.
What can I reuse from a vendor story?
The questions, the structure and the layout ideas. Not the numbers, quotes, logos or screenshots.
Do I need the publication date?
Yes. Vendor pages get edited and figures get refreshed, so an undated number cannot be checked.
