By Steve Merrill, Founder of WRKNG Digital | June 15, 2026
Most Shopify agency case studies tell you nothing. They show a big revenue number, a recognizable brand category, and a percentage lift. That's it. You're supposed to be impressed and reach out.
Don't be.
A case study is sales collateral. Agencies write it to win business. So the numbers may be real, but they're curated. The context that would actually help you judge whether an agency can move your store? Absent.
That's a serious problem when you're making a $3,000 to $15,000 per month decision. So let's break it down.
What Are Most Shopify Agency Case Studies Actually Missing?
Most agency case studies are missing three things: the brand's starting state before the work began, the specific tactic that drove the result, and the attribution source that proved it. A revenue number without those three pieces is just noise dressed up as evidence.
"We drove $2.4M in new revenue for a Shopify brand in Q4" sounds impressive. But ask a few questions and it falls apart. Was their Q4 already $2M before the agency touched anything? Did ad spend go up 4x during that same period? Was the revenue from email, paid social, or organic? What product line? What did ROAS look like before versus after?
Most agencies won't answer those questions in print. Which tells you something.
A 2024 analysis by Forrester Research found that fewer than 20% of digital marketing case studies include pre-campaign baseline metrics. The rest show you the finish line without the starting block. You're meant to fill in the gaps with optimism.
What Should a Real Shopify Agency Case Study Include?
A real case study has five components: the brand's baseline state before the engagement, the specific tactic the agency ran, the measurement window, the attribution source used to track results, and an honest account of what role the brand itself played in the outcome.
Here's what each one looks like in practice.
What Was the Brand's Baseline Before the Agency Stepped In?
Before the agency started, what were the actual numbers? Monthly revenue, average order value, ROAS on paid, CAC by channel, and traffic volume. If those numbers aren't in the case study, you can't tell whether the agency moved the needle or just showed up during a strong quarter.
Q4 lifts almost every Shopify store. If an agency's best case study is from November through December, ask what happened in January. That's when the work shows.
What Specific Tactic Did the Agency Actually Deploy?
Vague is a red flag. "A full-funnel strategy" or "an omnichannel growth approach" tells you nothing. What did they do? Did they restructure the ad account? Rebuild the retention email flows? Rewrite product descriptions for AI feed ingestion? Migrate to a Shopify theme that cut page load time by 2.3 seconds?
Specificity is accountability. When an agency can't tell you what they did, they often don't know what worked either.
What Attribution Source Tracked the Outcome?
This is the question most brands forget. Shopify's native analytics, Meta Ads Manager, and Google Analytics will each report a different revenue number for the same campaign. Sometimes the difference is enormous.
A credible case study names the attribution platform. "We track this in Northbeam, last-touch" is information. "Revenue grew 87%" with no source is a claim. Those are different things.
What Are the 3 Numbers Every Shopify Agency Case Study Should Show?
The three numbers that actually matter are ROAS improvement (the change, not just the current rate), customer acquisition cost change, and lifetime value shift. Top-line revenue alone tells you almost nothing about whether the agency's work was sustainable or profitable.
I've reviewed hundreds of these across the brands we've audited. The ones that lead only with revenue are usually hiding something. Margin compression. A spike that didn't hold. Spend increases dressed up as efficiency.
ROAS improvement, not a static ROAS figure. A 3.2x ROAS sounds fine until you find out they inherited a 4.8x ROAS and "improved" it down. You want to see where ROAS started and where it ended, month by month. That trajectory tells you more than any single snapshot.
CAC change matters because acquisition cost is what separates profitable growth from expensive growth. Revenue going up while CAC doubles is a problem with a good-looking spreadsheet attached to it. Ask for CAC at the start of the engagement and at the end.
LTV shift is the number agencies almost never show, because measuring it takes 6 to 12 months. But if the agency rebuilt your retention flows or subscription program, your LTV should be moving. If they can't show LTV data from previous clients, ask why. You'll learn something from the answer.
How Do You Read an AI Commerce Case Study from a Shopify Agency?
This is the newest category and the one with the most vague claims. "We improved AI visibility by 40%" is a meaningless number without a definition, a measurement method, and a change in a downstream business metric you can trace back to it.
This matters because AI shopping is splintering fast. ChatGPT Shopping, Perplexity's commerce tab, and Google AI Overviews all pull product data from different sources. Search Engine Land's 2025 breakdown confirmed ChatGPT Shopping pulls from Bing's product index while Google AI Overviews draws from the Shopping Graph. An agency claiming "AI visibility improvement" needs to specify which platform, which data layer, and what metric moved.
The metrics that actually mean something for AI commerce performance:
Product mention rate by AI platform. How often does an AI assistant recommend your product category, and how often does your brand appear in those answers? This is measurable. Tools like Ahrefs are tracking AI mention frequency for brands. Credible AI commerce agencies should be pulling this data and showing it before-and-after.
Feed coverage score. What percentage of your product catalog has complete structured data for AI ingestion? A score below 70% means most of your catalog is effectively invisible to AI shopping assistants. Any agency claiming AI commerce results without showing feed coverage improvement didn't do the core work.
AI-referred click-through rate. Google Search Console now segments AI Overview traffic separately from standard organic. If an agency improved your AI visibility, this number should move in GSC. If the case study shows no GSC data at all, that's a gap worth pressing on.
What Are the Red Flags in a Shopify Agency Case Study?
Walk away slowly.
The biggest one: "drove $X in revenue" with zero ROAS context. Revenue is a gross number. It tells you scale, not profitability. An agency hiding the margin story is either not tracking it or choosing not to show it. Neither option is good.
No baseline is almost as bad. "We helped Brand X grow 200% in 6 months" could describe a brand going from $10K/month to $30K/month, or one going from $800K to $2.4M. You can't evaluate either without the starting point.
Every case study is brand-unnamed. Sometimes agencies legitimately can't name clients. But if the entire portfolio is "a leading DTC brand in the beauty space," ask for at least one named reference who will take a call.
The brand's contribution is absent. If a client doubled their ad spend during the engagement, that needs to be disclosed. Case studies that take full credit for results driven primarily by client budget are misleading by omission.
What Green Flags Appear in a Strong Shopify Agency Case Study?
The data is specific and slightly uncomfortable.
Good case studies show the number that didn't improve alongside the ones that did. "Email revenue increased 34% but paid social CAC also climbed 18% in the same period, here's why and what we did next" is a case study written by an agency that understands its own work. Clean wins across every channel are suspect.
They name the tools. What attribution platform? What ESP? What feed management software? Agencies willing to name their stack are accountable to it. Vague process descriptions cover inconsistent execution.
A past client contact is available. The best case studies include a direct quote from a founder or CMO and an offer to connect you with them. That's confidence. That's accountability.
How Should You Actually Use Case Studies When Evaluating Shopify Agencies?
Use them as a filter, not proof.
A strong case study shows you an agency that can measure, communicate, and take ownership. A weak one shows you they either don't know what drove their results or they chose not to share it. Both disqualify.
I built and ran a clothing brand for 15 years. I hired and fired more agencies than I can count. The ones that burned the most money had the most polished pitch decks. The ones that actually moved metrics spent 20 minutes asking about my current numbers before showing me anything. That's the tell.
An agency leading with case studies wants to impress you. An agency leading with questions wants to understand you. Those are different orientations. The second one is far more likely to get you somewhere real.
FAQ: Shopify Agency Case Studies in 2026
What should a Shopify agency case study always include?
Five things: the brand's baseline metrics before the engagement, the specific tactic deployed, the measurement window, the attribution source, and what the brand itself contributed. Without all five, you're reading marketing copy dressed up as evidence.
What numbers should I ask for when reviewing a Shopify agency case study?
Ask for ROAS at the start versus the end, CAC change month-over-month, and LTV shift over at least 6 months. Revenue alone isn't enough. Profitable growth requires all three to move in the right direction.
How do I evaluate an AI commerce case study from a Shopify agency?
Ask which AI platforms they improved visibility on, how they measured it (feed coverage score, brand mention rate, GSC AI Overview traffic), and what attribution source they used. "AI visibility improved 40%" without a measurement method is a claim, not a result.
Why do most Shopify agency case studies leave out baseline data?
Because showing the baseline makes results relative. A 200% lift from $20K/month looks very different than a 200% lift from $500K/month. Most agencies want you focused on the multiplier, not the math. Always ask for the starting numbers.
What's the most useful way to vet a Shopify agency beyond reviewing case studies?
Ask for a direct reference from a past client in your revenue range and product category. Talk to the actual account lead, not just the sales rep. A 30-minute call with a past client tells you more than 10 polished case studies.
If you're evaluating agencies to help your Shopify store appear in AI shopping results, the standards are different than traditional performance marketing. The data sources are different. The measurement is different. Most agencies haven't caught up yet.
Get the WRKNG Digital AI Commerce Readiness Assessment. We'll show you exactly where your store stands on AI visibility, feed coverage, and structured data before you spend a dollar with anyone.
