Chris Suglia

Suglia says it breaks down for brands selling many products with different value propositions, because mixing them confuses the algorithm. Group campaigns by user journey or product type, and have scaling brands prioritize the one or two products best suited to acquiring new customers rather than advertising 20-plus SKUs equally.

In part 3 of a five-part series on Meta performance, Suglia gives examples by vertical: high-end fashion sells on aesthetics, so one full-funnel campaign with ad sets by product type works; standard DTC fashion brands such as TrueClassic and Mugsy get one campaign per product type because search behaviour differs by product; skincare and CPG get a campaign per umbrella category, such as treatment or anti-aging, moisturizer, and resurfacing, tested first on the top product for each pain point.

• Suglia concludes: “The brands that scale don't advertise 20+ SKUs.
• They prioritize one and are specific about who it's for and what it fixes.”

Elsewhere, Suglia ranks campaign structure below product, creative, landing pages, and offer, and calls A/B testing CBO versus ABO or lifetime versus daily budgets a misuse of time. Structure has a preferred shape, but it is a second-order lever, not the first thing to optimize.

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The work that matters is developing persona-level hooks and positioning statements for creative, testing landing pages and checkout, building offers and shipping thresholds around margins, and taking the brand beyond a feature list. Higher CPMs, changed attribution, and the declining value of the “ad set” as a lever—not audience targeting—are why paid media has become more expensive, though many brands still spend most of their time on targeting.

Rather than layering audiences, Suglia describes consolidating prospecting and retargeting into single campaigns and structuring by creative: one campaign for the seasonal collection, one for evergreen apparel, and one for dynamic catalogs and carousels.

• The catalog campaign is isolated because shoppable carousels rack up clicks and otherwise eat the whole budget.
• Within evergreen, ad sets split by product type so the algorithm does not average shirts, denim, and kids together.
• Suglia reports taking a high-end fashion brand from 7x to 14x ROAS over the summer; the team watched Shopify to confirm reported ROAS tracked incremental revenue.

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Where repeat purchase is rare, the goal is profit on the first order, which usually means raising average order value rather than chasing the lowest cost per purchase. Suglia also advises brands to choose what to advertise from existing sales data, not test everything at once.

A golf grip brand sells grips for $13–$15, replaced roughly every two years, so orders of two or three items barely make money.

• The changes: free two-day shipping over $90, a higher single-grip price to make bundle discounts look worthwhile, and a site that sends traffic to the bundle page instead of single-grip product pages.
• The team checked each change against a spreadsheet of COGS, margins, and discounts, targeting a roughly 70% margin per order.
• A companion post advises brands to pull Shopify data first and find CAC payback period, LTV by product, repeat purchase rate by product, and product acquisition quality.
• Then they should take the top three product categories, test angles for each, and iterate on the winning angle with new concepts and formats.

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Expansion makes sense once the core channel is performing, and the next channel should match the diagnosed problem: an awareness gap points to CTV, TikTok, or Pinterest; a Gen Z product to TikTok and social commerce; weak repeat purchase and low LTV to post-purchase paid media plus email and SMS, which Suglia notes few brands run.

The rule: identify a problem first, then decide what tactic will solve it. The post allows diversification when performance is already solid; the point is sequencing, not refusing to expand.

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A creator who performs well organically can still deliver a UGC ad that flops because story arc, hook, and the way value propositions are highlighted work differently in paid media—even though the best-performing ads still look organic and authentic. Explaining how a product works is a different job from making engaging content.

“The best performing ads look organic and authentic.

• But the story arch? the hook? the way you highlight value props?
• Completely different,” Suglia writes, concluding: “don't work with a creator just because of their follower count.
• Work with people who understand paid media.”

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Better landing pages, content, and attribution make paid media easier to run, save the team hours, and keep clients for two to three years, which is worth more than a one-time upsell. The post names partners across creative, agency, and measurement work and states that the team collects no referral fees.

The partner post names people and firms across creative, agency, and measurement work, and invites direct messages for honest feedback about partners a brand already uses. A separate post advertises an Account Director role based in Colorado at $85,000–$140,000, preferring candidates with experience working with DTC and ecommerce brands in the $2m–$50m revenue range.

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These are Bemand's points as reported by Suglia, not Suglia's own claims.

Suglia frames the episode as the second part of a series titled “Why (Most) Agencies Suck!” and singles out two takeaways from the conversation.

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Start here for a clear explanation of when consolidation may help—and when it can blur distinct offers.

Suglia argues that campaign consolidation should reflect the products and their value propositions, not a blanket rule to put everything in one campaign.

• They contrast high-end fashion, where aesthetics can unify a full-funnel campaign, with DTC fashion and skincare, where distinct product benefits may call for product-type or category groupings.
• They recommend prioritizing the one or two products best suited to acquiring customers.

For brands planning a campaign

For a brand with many SKUs, map products by customer journey and value proposition before consolidating. Test a focused acquisition offer around priority products rather than giving every SKU equal budget.

It offers a concrete case for teams reviewing account organization and measurement.

Suglia describes taking a high-end fashion brand from 7x to 14x ROAS during summer, attributing the change to campaign organization rather than new audiences.

• They separated seasonal, evergreen, and catalog creative into campaigns, noting that catalog ads can absorb budget; within evergreen, they grouped ad sets by product type.
• They also checked Shopify to see whether reported ROAS tracked incremental revenue.

For brands planning a campaign

If catalog ads dominate spend, consider isolating them so other creative can get budget. Evaluate seasonal and evergreen work separately, and check sales data beyond platform-reported ROAS before treating a lift as business growth.

See how Suglia connects paid media choices to pricing, bundles, and the destination page.

Using a golf-grip brand as an example, Suglia connects acquisition economics to product buying frequency and order value.

• Because customers rarely replace low-priced grips, the team aimed for profit on the first order.
• The post describes free two-day shipping above $90, raising the single-grip price to make bundles more attractive, and prioritizing the bundle page.
• They say a spreadsheet checked costs, margins, and discounts against an approximately 70% margin target.

For brands planning a campaign

Before optimizing for lower CAC, model purchase frequency, contribution margin, and realistic order size. Test bundle and shipping thresholds only after checking margins, and make sure the landing page supports the advertised offer.

It’s a practical starting point for teams with historical sales data but no acquisition shortlist.

Suglia recommends using existing Shopify sales data before launching tests.

• The post names CAC payback period, lifetime value by product, repeat purchase rate by product, and product acquisition quality, then suggests finding the top three product categories and testing angles for each.
• After finding a promising angle, they advise iterating with new concepts and formats.

For brands planning a campaign

Use product-level sales and customer data to create a shortlist for acquisition testing. Treat it as a starting hypothesis, then compare creative angles and formats rather than testing every product at once.

Start here if your team is debating a new platform without a clear problem for it to solve.

Suglia argues against adding channels as a default response to weak results. They tie channel choices to specific problems: CTV, TikTok, or Pinterest for awareness; TikTok and social commerce for a Gen Z product; and post-purchase advertising plus email or SMS for repeat-purchase challenges.

For brands planning a campaign

Name the growth problem before expanding channels. Match the test to the intended audience or funnel gap; channel count alone isn’t a performance strategy.

In part three of a five-part series on Meta performance, they argue that the popular advice to consolidate everything into one campaign and one ad set breaks down for brands with diverse product ranges.

• Campaigns should instead be grouped by user journey or product type.
• High-end fashion, standard DTC fashion (including TrueClassic and Mugsy), and skincare or CPG each get a different structure.
• For skincare, they recommend organizing campaigns by umbrella category—such as treatment or anti-aging, moisturizer, and resurfacing—and testing first on the top product for each pain point.
• A separate post describes taking a high-end fashion brand from 7x to 14x ROAS by consolidating prospecting and retargeting into single campaigns, then structuring campaigns by creative: one for the seasonal collection, one for evergreen apparel, and one for dynamic catalogs and carousels.
• Shoppable formats get their own campaign because they absorb budget.
• Within the evergreen campaign, ad sets are split by product type so the algorithm can find the right buyer for shirts, denim, or kids rather than averaging everyone together.
• The recurring claim: scaling brands prioritize one or two hero products instead of advertising 20-plus SKUs equally.

Published as a numbered series (part 3 of 5) and supported by vertical-specific worked examples, then a documented client result with the structural changes listed one by one.

For brands planning a campaign

A consultant brief should request a proposed account structure mapped to the product range: which products get dedicated campaigns, which are grouped by journey, and where catalog or carousel formats are quarantined. Expect recommendations grounded in SKU-level economics and the customer journey, not a generic consolidation template.

Examples: Source 1 · Source 2

In their view, Meta's targeting outperforms hand-built prospecting, retargeting, and lookalike layers—but only if advertisers stop competing with the platform for control.

• The more valuable work is developing persona-level hooks and positioning statements for creative, testing landing pages and checkout, building margin-backed offers and shipping thresholds, and elevating the brand beyond feature lists.
• Suglia favors a particular campaign structure but says it matters far less than product, creative, landing pages, and offer.
• They call tests such as CBO versus ABO or lifetime versus daily budgets the wrong use of time, citing changed attribution and the declining value of the ad set as a lever among the reasons paid media has become more expensive.

For brands planning a campaign

Prioritize paid-media literacy over audience-targeting experience when hiring a creator or consultant. Ask candidates what they would test first in creative, landing pages, and offer construction; treat detailed audience-structure plans as a weaker signal.

Examples: Source 1 · Source 2

One post examines a golf grip brand whose grips sell for $13 to $15, are replaced roughly every two years, and rarely make two-to-three-item orders profitable on their own.

• The response was to raise average order value: offer free two-day shipping over $90, raise single-grip prices to make bundles look like better value, and route website traffic to the bundle page instead of single-grip product pages.
• The changes were checked against a spreadsheet of COGS, margins, and discounts, with a target of roughly 70 percent margin per order.
• A companion post tells brands to pull Shopify data before publishing ads and identify CAC payback period, LTV by product, repeat purchase rate by product, and product acquisition quality, then find the top three product categories and test angles for them.

Works through a single vertical example end to end, with prices, a shipping threshold, and a margin target, then generalizes the steps.

For brands planning a campaign

A campaign or consulting brief should include product-level economics, not just ad account operations. Ask for the offer, price, and shipping structure alongside the media plan, plus evidence that first-order profitability has been modelled where repeat purchase rates are low.

Examples: Source 1 · Source 2

The post opens with a familiar pitch about trying Reddit, Snapchat, or TikTok to gain more levers, then argues that channel hopping without a diagnosis is not a strategy.

• Expansion makes sense once the core channel is performing, and should match the problem: awareness problems point to CTV, TikTok, or Pinterest; a Gen Z audience points to TikTok and social commerce; weak repeat purchase and low LTV point to post-purchase paid media plus email and SMS, which the post says few brands run.
• The rule: identify the problem first, then choose the tactic that solves it.

The post explicitly allows diversification when performance is already solid, making this a sequencing rule rather than a refusal to expand.

For brands planning a campaign

Useful for briefs from brands looking to expand beyond a single platform. Ask for the diagnosed problem and the specific channel or post-purchase tactic tied to it; be sceptical of plans to add platforms while the main channel is still underperforming.

Examples: Source 1

Creators who perform well organically can still produce a UGC ad that flops: story arc, hook, and value propositions work differently in paid media, even though the best-performing ads still look organic and authentic.

• The practical takeaway is to select creators for their understanding of paid media, not their follower count.
• Explaining a product is a different job from making engaging content.

For brands planning a campaign

Relevant when a brief includes creator or UGC sourcing. Ask for selection criteria and sample paid-media work, not audience size, and expect a test-and-iterate process around winning angles rather than a one-off asset buy.

Examples: Source 1

They argue that better landing pages, content, and attribution make paid media easier to run, shorten team hours, and keep clients for two to three years—worth more than a one-time upsell.

• The post names partners across creative, agency, and measurement work, says no referral fees are collected, and invites honest feedback by direct message.
• In a podcast episode with Bianca Bemand on why most agencies fall short, Suglia highlights direct feedback as a service commitment and says the best work comes from people who enjoy it.
• A separate post advertises an Account Director role with a stated salary range and a preference for candidates who have worked with DTC and ecommerce brands in the $2m to $50m revenue range.

For brands planning a campaign

Expect a tightly defined media-management scope that brings in named specialist partners rather than bundling everything. Briefs should specify who owns landing pages, creative, and measurement, and account for a working style that favors candid feedback over broad service menus.

Examples: Source 1 · Source 2 · Source 3

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Ask Suglia about their role at Revel and whether it is a client or employer.

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Ask Suglia about their formal role in the show.

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Draws on recurring monthly audits of around 20 brands to offer an acquisition diagnostic and Google PMAX advice. Suglia focuses more on their own decisions around building structure, designing offers and unit economics, and sequencing channels.

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Presents sample studies of dozens of brands with six-figure monthly budgets and advocates aggressive scaling once signal thresholds are met. Suglia focuses on product-line structure, catalog isolation, and offer economics.

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Writes as an operator responding to sudden sales drops, with a set troubleshooting order: tracking, store conversion, account changes, then seasonality. Suglia focuses on account-structure choices and offer design before spend.

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Their posts argue that declining new-customer revenue is DTC's biggest problem and that brands often mistake a visibility problem for a conversion problem: conversion rates sit around 2-4%, and the fix is to reach more people before they are ready to buy.

• The plan is concrete: run conversion-optimized Meta campaigns with the event set to ViewContent, aggressively exclude existing and engaged segments, move away from automated structures that chase easy conversions, and check that the extra traffic is real by watching bounce rate, time on site, and pages per session, with a target of roughly doubling click-through rate.
• They also recommend using named experts in creative, such as a dermatologist for skincare, making this a fit for a skincare brief.
• If repeat buyers are carrying revenue and the brand cannot reach new ones, this is the more specific fit.

The tradeoff is depth on the offer side.

• These posts do not cover bundle pricing, shipping thresholds, COGS and margin checks, or product-level data such as CAC payback period, lifetime value by product, and repeat purchase rate by product.
• Chris Suglia's posts address which SKUs to push and how to build a first-order-profitable offer; these two do not.
• Josh Henry-Hicks also spends part of the argument on Google PMAX and search structure, which matters only if the brand runs Google.

Examples: Source 1 · Source 2

Their posts identify creative output, not targeting, as the limit: brands scaling past $500k a month on Meta launch 40-60 new creative assets monthly; a winning ad dies after 7-14 days at scale; and scaling should be conviction-based, with budgets doubled at signal thresholds instead of raised 10-20% every few days.

• Two worked examples support the argument: an apparel brand stuck at $80k a month moved to weekly creative launches and reached $340k a month at the same ROAS, while a set of $100k-a-month-plus accounts scaled from $50k to $150k in 18 days after aggressive budget moves.
• If the agency's plan hinges on how fast the brand can produce creative and how decisively it can raise spend, this is the more detailed operating discipline.

The tradeoff is scope.

• These posts focus almost entirely on creative volume and budget-scaling cadence, not offer design, margin math, multi-SKU campaign structure, or when to open a new channel—the areas Chris Suglia's posts address.
• The advice assumes the brand can produce 40 or more assets a month.
• Ask whether the team can meet that production pace before applying it.

Examples: Source 1 · Source 2

Their posts give a fixed order of checks for a sales alarm: confirm tracking by comparing Shopify, GA4, and Meta, and treat a mismatch over 10% as a reporting problem; check the store's conversion rate against the prior 30 days; look for a specific change in the ad accounts; then pull 12 months to separate seasonality and external context from a real break.

• Their case example focuses on margin rather than ROAS: cut retargeting from 65% of spend to 25% and move the rest into Advantage+ prospecting with lifetime-value-weighted inputs from Klaviyo, add a three-step post-purchase sequence, raise a free-shipping threshold by $14 after checking average cart value, and prune the weakest SKUs from the shopping feed.
• Contribution margin moved from under 12% to 23%; their point is that the ROAS figure did not tell that story.

The tradeoff is narrower demonstrated coverage.

• These posts are case-led, not a general method for product selection, bundle pricing, or first-order profitability, which Chris Suglia's posts describe.
• The shipping-threshold change is a single offer lever, not a full offer-design framework, and the diagnostic order is most useful when the cause of a problem is genuinely unknown.
• If the brand already knows its constraint is which products to push and how to price them, ask for a product-selection and pricing framework.

Examples: Source 1 · Source 2