Salman Baig

The strategic choice is which awareness levels to serve, not how many variations to produce.

• Product-aware buyers get short, benefit-driven ads; solution-aware buyers get one- to two-minute ads that present the product as the fix; problem-aware buyers get three- to five-minute story ads; and problem-unaware buyers get full video sales letters that raise the problem, knock down alternatives, and only then present the product.
• In Baig's view, brands stall by serving only the two easiest, lowest-funnel groups, while the opportunity to scale lies further up the funnel.
• Ask for account data to assess how well this model has worked in practice.

Baig's point: the fastest route to eight or nine figures isn't a new media-buying hack. It's mapping creative output across awareness levels—stop thinking about more ads and start thinking about more markets.

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They cite a study of 578,750 Meta ads in which about 5% became winners, defined as ads Meta gave ten times the normal spend.

• The biggest advertisers landed around 8 to 9%, and even the strongest formats won only 5 to 10% of the time.
• Baig concludes that no script or hook guarantees a hit; the better bet is to choose formats with stronger historical odds and launch them repeatedly.
• The post names no source or date for the study, so ask for the citation before relying on the figures.

The formats Baig says win most often are offer-first banners, product demos, customer testimonials, and unboxing videos. The takeaway: stop betting on one perfect ad and choose formats with better odds.

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They say every script at Ecom Bench starts with the reviews and comments most brands skip, and point to how a low return rate can coexist with a review saying the sizing runs small. The returns number is fine, Baig says, but only the review tells the brand what to fix.

Baig recounts how Jeff Bezos kept his email public and forwarded a standout complaint to his team with only a question mark, prompting three questions: Is this true?

• Why is it happening?
• What are we going to do about it?
• Baig applies the same questions to how an ecommerce brand should respond to a bad review.

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At that point, the spend stops working.

• The reasoning is mechanical: the platform ranks an ad by watch time, not budget.
• If viewers skip in the first three seconds, it reads the ad as low quality and charges more to keep showing it.
• The remedy is to fix the creative before buying distribution.

Baig describes Ecombench's process in three steps: diagnose the brand to find what's broken in its current ads; write performance creatives, including the script, shot list, and edit direction, so each ad tells a story rather than just showing the product; then run a small-budget test before scaling spend.

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They cite a study of Black Friday and Cyber Monday discount trends in which 71% of shoppers say discounts are the only reason they shop that weekend; the post doesn't name the source.

• Baig distinguishes a discount from a predictable one: if customers know a $150 item always drops to $100, they stop believing it was ever worth $150.
• The key question is whether customers will still pay full price in January.
• Baig's three rules: don't repeat the identical discount every year, don't make the discount grow the longer people wait, and don't run the sale for weeks.

Baig asks brands whether their BFCM creative protects January or just wins November.

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They argue that Upwork is a reasonable place to start but a bad place to build a career: one unfair client review can reset a profile and cut off work, regardless of effort.

• Their alternative is a personal brand built on speaking in your own voice, sharing knowledge without strings, and helping people earlier in their journey.
• This material predates the DTC creative-strategy posts and speaks to freelance client acquisition, not current brand creative work.

Baig says they lost all their Upwork badges and dropped to the platform's lowest tier, "Rising Talent," after one bad review, then went two months without closing a client.

• They also call connects expensive and the platform increasingly competitive.
• In a follow-up post, Baig suggests raising your unique voice, giving freely, and providing value and support, then invites readers to join a comments shoutout chain.

This earlier material targets freelancers and agency owners; later posts focus on DTC paid-social creative for brands. The shift is in subject and audience, not a contradiction.

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It answers the newcomer’s likely question: is this just making more ads, or is there a method?

Baig argues that creative strategy is market strategy because the ad should match how aware the customer is.

• Product-aware audiences get short, benefit-driven ads; solution-aware audiences get one- to two-minute ads positioning the product as the fix; problem-aware audiences get three- to five-minute story ads; and problem-unaware audiences get full video sales letters that raise the problem, knock down alternatives and only then present the product.
• Brands stall, they say, by serving only the two easiest, lowest-funnel audiences; scale lies further up the funnel.

For brands planning a campaign

For a DTC brief, ask for creative mapped across awareness levels, not more variants of the same lower-funnel ad. Budget for longer, story-driven assets and video sales letters: they convert less efficiently per view but reach colder audiences.

Baig cites a study of 578,750 Meta ads in which about 5% became winners, defined as ads Meta gave ten times the normal spend.

• Even the biggest advertisers landed around 8 to 9%, and the strongest formats won only 5 to 10% of the time.
• The most frequent winners were offer-first banners, product demos, customer testimonials and unboxing videos.
• Their conclusion: you cannot predict a winner, but you can improve your odds by repeatedly launching formats with better odds.

For brands planning a campaign

Set expectations around volume and format mix, not a guaranteed hit. An engagement with Baig could include repeated launches across the listed formats, with the client accepting that most individual ads will not win.

Baig writes that paid ads cannot fix a story nobody trusts, and that most DTC founders scale spend before fixing their ads, at which point the spend stops working.

• The reasoning is mechanical: the platform ranks an ad by watch time, not budget.
• If viewers skip in the first three seconds, the platform reads the ad as low quality and charges more to keep showing it.
• At Ecombench, the work follows three steps: diagnose the brand to find what is broken in the current ads; develop performance creatives with scripts, shot lists and edit direction so each ad tells a story rather than only showing the product; then test on a small budget before scaling spend.
• The post ends with an invitation to book a discovery call.

For brands planning a campaign

Structure an engagement with a diagnostic phase first, and name script, shot list and edit direction as deliverables rather than leaving production scope implicit. Confirm that the discovery call link works before quoting it as a contact route.

Rather than guessing at hooks, Baig points to customer feedback as raw material for ad scripts.

Baig retells the story of Jeff Bezos reading customer emails, forwarding complaints to the team with only a question mark, and asking whether the complaint was true, why it was happening and what would be done about it.

• The ecommerce parallel: a low return rate and a single review saying the sizing runs small can both be true, but only the review tells you what to fix.
• At Ecom Bench, they say, every ad script starts with the reviews and comments most brands skip.

For brands planning a campaign

For creative concept development, provide review text, return reasons and comment threads. Expect the first concepts to draw on that material rather than category conventions.

Baig argues that predictable discounts teach customers to stop buying until the sale, citing a study on Black Friday and Cyber Monday discount trends in which 71% of shoppers say discounts are the only reason they shop that weekend.

• For example, a $150 item that always drops to $100 on BFCM stops seeming worth $150 the rest of the year.
• The real question is whether customers will still pay full price in January.
• Three rules follow: do not repeat the identical discount every year, do not make the discount grow the longer people wait, and do not run the sale for weeks.
• Baig closes by asking whether a brand's BFCM creative protects January or only wins November.

For brands planning a campaign

For Q4 work, ask for promo creative judged by its effect on full-price demand after the sale, and avoid briefs that require escalating or long-running discounts.

It also offers the clearest example of the conversational, comment-inviting style used across these posts.

This post follows an earlier one in which Baig describes losing all Upwork badges and being demoted to "Rising Talent" after one client review, then going two months without closing a client and finding connects expensive as the platform grew more competitive.

• The follow-up argues for building a personal brand: raise your unique voice, give your knowledge away freely, and provide value and support, especially to people early in their own journey.
• Baig then invites readers to a shoutout chain in the comments and asks what has worked for them.

For brands planning a campaign

This material targets freelancers and agency owners rather than DTC brands. For a content collaboration rather than a creative engagement, factor in that part of Baig's audience is people trying to win clients; that may change the angle a brand wants to sponsor.

In their framing, strategy means matching the ad to the buyer's awareness stage: short, benefit-led ads for product-aware audiences; one-to-two-minute ads for solution-aware audiences; three-to-five-minute, story-led ads for problem-aware audiences; and full video sales letters for problem-unaware audiences. Baig argues that brands stall when they serve only product-aware and solution-aware buyers, because scale sits further up the funnel.

Classify the brand's existing ad output by awareness level, then map what's missing. Baig treats the mapping as the strategy and the ads as its output.

Baig presents the awareness-stage framework as a working model based on their practice, not cited performance data. Ask for results showing how it performs against the brand's own account.

For brands planning a campaign

A brand briefing creative help from Baig should expect a stage-by-stage map of its ad output before new scripts, and be ready to produce upper-funnel, longer-form assets—not just more short product ads.

Examples: Source 1

They conclude that winners can't be predicted, only made more likely, and name the formats that won most often: offer-first banners, product demos, customer testimonials, and unboxing videos.

Pick formats with a history of winning more often and launch them repeatedly instead of betting on one perfect script or hook. That's the testing cadence Baig describes.

The 578,750-ad figure and win rates come from a study referenced in the post, but no source or date is named. Ask for the study before treating the numbers as benchmarks.

For brands planning a campaign

Brief for a repeatable format pipeline and testing cadence, not a single hero ad. Agree up front on how many concepts and iterations the engagement covers.

Examples: Source 1

They recount a story about Jeff Bezos forwarding an angry customer email with only a question mark, meaning: is this true, why is it happening, and what will we do about it? Baig applies the same three questions to an ecommerce brand: a low return rate and a single complaint that sizing runs small can both be true, but only the complaint tells the brand what to fix.

Start with a brand diagnosis, write performance creatives with the script, shot list, and edit direction, then test on a small budget before scaling spend. Baig lays out that sequence explicitly.

The Bezos anecdote functions as an illustration of the method, not as documented evidence about the brand's own customers.

For brands planning a campaign

Ask for the diagnosis step as a defined deliverable, and supply comments and reviews as raw material for scripts rather than handing over only a product brief.

Examples: Source 1 · Source 2

They say the algorithm ranks an ad by watch time rather than budget, so viewers skipping in the first three seconds raises the cost of continued delivery. Their remedy: fix the story before putting spend behind the ads.

For brands planning a campaign

Expect creative work to address storytelling first. Increase spend after the ad shows an early watch-time signal, not to compensate for weak creative.

Examples: Source 1

Shoppers already expect a deal on Black Friday and Cyber Monday; Baig cites a figure that 71% say discounts are the only reason they shop that weekend.

• They distinguish a discount from a predictable discount: a $150 item that always drops to $100 on BFCM stops being seen as a $150 item.
• Their three rules: don't offer the exact same discount every year, don't increase the discount the longer customers wait, and don't run the sale for weeks.

Make the seasonal offer a surprise, and judge the campaign by whether customers still pay full price in January—not by November revenue alone.

The post attributes the 71% figure to a discount-trends study but doesn't name the source. Ask for the study before using the figure as a benchmark.

For brands planning a campaign

For a seasonal promotion, ask for creative that varies the offer year over year, keeps the sale window short, and is evaluated against January full-price demand as well as the weekend's sales.

Examples: Source 1

One argues that Upwork is unreliable as a long-term base, citing lost badges, a demotion to the platform’s lowest tier after a single bad review, and expensive connects. The follow-up argues for building a personal brand by speaking in your own voice, sharing knowledge freely, and supporting others.

These posts predate the DTC creative-strategy posts and don't show whether the advice was applied to a client engagement. Ask for client examples of the work in practice.

For brands planning a campaign

This is context for how Baig talks about working relationships: Baig argues for direct, relationship-led contact over platform-mediated hiring, which shapes how a first conversation or collaboration is likely to be framed. It also means older posts aimed at freelancers are not the right basis for judging current DTC creative capability.

Examples: Source 1 · Source 2

One post ends with a discovery-call link.

• The posts use “we” and “at Ecombench” but do not clarify Baig's relationship with the business.
• Ask whether they own, work for or contract with Ecombench.

View example

They say the episode cost two months of client work and argue that a career should not depend on the platform. Upwork is the subject of commentary, not a sponsor or client relationship.

View example

The DTC case study follows a similar shape to Baig's posts: the brand arrives believing it has a scaling or budget problem, but the diagnosis points to the creative funnel, not the campaign settings.

Waleed focuses on marketers starting out: positioning, what to put on a LinkedIn profile, and how to land a first client.

• Their brand-side posts use first-person account walkthroughs that end with a call, audit, or comment invitation.
• Choose Waleed for client acquisition and positioning; choose Baig for an awareness-stage model laid out as a framework.

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Differentiation, the argument goes, allows spend to grow without performance collapsing. The post on whether creative strategists are overrated takes the argument further, examining how the role should be done.

Levi writes from inside a creative team and production process, focusing on developing designers and editors into strategists and sharply critiquing prompt-and-paste strategy work.

• The tone is industry commentary for people already in the field, while Baig presents a framework to brands.
• Levi also publishes on Instagram as well as LinkedIn.

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Baig describes the same account-level problem: one hook, one angle, one message, and then the whole account feels it when that ad dies.

Ujla mixes that advice with personal career reflection and writes shorter, more narrative posts.

• Baig presents the same ground as a staged model, with named awareness levels and a sequencing rule.
• Ujla's posts stay closer to first-person account experience with DTC brands; Baig's read as a method to apply.

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In the post, he walks through a hair care brand that came in asking how to scale, reviews the creatives, and finds that only about a quarter were built for buyers who do not already know the brand; the rest speak to existing customers and warm audiences.

• That is the same awareness-level problem Salman Baig describes, but framed as a measured gap in the account rather than a mapping exercise.
• The fix is creative coverage across unaware, problem-aware, solution-aware, product-aware, and ready-to-buy buyers.
• He is also the better choice when the buyer wants to see the account walkthrough before committing: the post shows the call, the questions asked, and the direction agreed at the end.

The published material stops at diagnosis and direction.

• The posts do not explain how scripts, shot lists, or edit direction get produced, or whether the brand should test on a small budget before raising spend—a step that protects the brand if new assets lose viewers early.
• The other post advises someone trying to win their first client, covering niche choice, offer clarity, and using a profile as a sales page.
• It is sound advice, but aimed at a freelancer building a practice, not a DTC brand buying creative work.
• Both conclusions rest on two long posts.
• Ask for client results, fees, deliverable counts, and the production and testing process.

Examples: Source 1 · Source 2

The post on creative diversity names the common pattern—new hooks, a new creator, a new edit—and argues that the underlying persona, pain point, promise, and awareness level remain unchanged, so the account is still fishing in the same pool.

• The four axes offered for real variation are persona and job-to-be-done, core motivation, awareness level and objection state, and primary promise.
• The claimed payoff is incremental reach rather than a new classification from the ad platform.
• This is the better choice when the buyer needs to decide what counts as a genuinely different ad before requesting more.
• The second post is also relevant when the engagement is partly a hiring question: it argues that prompting a tool for scripts has commoditised the scriptwriting layer, describes turning a senior designer into a strategist who can diagnose an account and build an ad end to end, and suggests stress-testing what a brand is actually paying for.

Both posts make an argument rather than demonstrate a build.

• There is no client account walkthrough, sample script or asset, test plan, or reported engagement numbers.
• A brand that needs production and a testing cadence gets an interpretation of what variation means, rather than a demonstration of how the ads would be made.
• The opinion about strategist pay concerns the market in general, not this creator's own terms, so it cannot be read as a rate.
• Ask for a sample build, a testing plan, and engagement terms.

Examples: Source 1 · Source 2

The post describes the pattern directly: one winning ad carries the account from $1K to $10K in spend, then CPA climbs and ROAS drops, and the brand blames the platform.

• The stated fix is to keep testing different hooks, angles, customer problems, and formats so a replacement is already in progress when the current winner tires.
• That is the same conclusion Salman Baig reaches with the format-odds numbers, so the choice comes down to who does the work.
• This creator is the better fit when the brand wants someone whose own account of the work spans years of daily DTC and Meta Ads responsibility, including campaigns, creative, scaling, and data decisions, rather than a framework presented from outside an account.

The posts give the pattern and the aim but not the method.

• There is no diagnosis sequence, awareness-level mapping, study figures, or account walkthrough showing how a testing pipeline gets built or sized.
• The other post is a career reflection about taking a pause after five years of work.
• It shows years of DTC and Meta Ads work and a clearer direction, but says nothing about how an engagement would be scoped or delivered.
• Ask whether project engagements are offered, and request the scope, fees, and deliverables.
• Two posts do not show the method depth of a creator who has published a multi-step process.

Examples: Source 1 · Source 2