When good marketing advice is wrong for your business
Even if a marketing recommendation has worked for others, it might not be the right next decision for your business.
Whether the advice fits depends on whether your business has the same buyer behaviour, maturity, and conditions as where it succeeded before.
Estimated reading time: 6 minutes
Why the recommendation deserves serious consideration
Looking at outside examples can help reduce uncertainty.
A case study shows that a certain approach worked in practice.
An experienced specialist brings knowledge your team might not have.
A peer can share evidence from a similar business situation.
A playbook from a previous company is based on real experience.
Acting on that evidence can be a responsible way to make decisions.
You might review the evidence, trust an expert, and make a well-reasoned decision, but still find the results don’t carry over as expected. This raises questions beyond just execution—it also makes you wonder what the outcome really means.
Just because it worked somewhere else…
Problems start when we assume that just because something worked elsewhere, it will work for us too. Success in another business only shows the advice can work if the right conditions are there. It doesn’t mean your business has the same buyers, maturity, capabilities, constraints or commercial structure.
It’s one thing to assess the recommendation itself. Maybe it’s a product-led growth strategy, a paid acquisition plan, or a process someone saw working at a previous company. These actions can be documented, presented, budgeted, assigned, and measured.
But it’s harder to see the conditions that made it work somewhere else. These details might be missing from the case study, assumed by the person giving the advice, or unique to the company where it succeeded. Case studies and proven playbooks are worth a look, but your business still needs to understand the conditions that led to those results before moving forward.
Why a recommendation can work elsewhere and fail here
Every recommendation assumes something about how buyers will respond and what the business can support.
An approach that depends on buyers moving through the decision largely on their own assumes that buyers are willing and able to evaluate, try, approve and purchase with limited human involvement. A paid acquisition recommendation (e.g., Google Ads and industry publication sponsorship) assumes that the economics can support the cost of acquiring customers through that channel, and that the business can convert and serve the demand it generates. Advice to increase investment assumes the offer, sales process and delivery model are already working consistently.
The recommendation may have worked because the other business had the buyers, economics and operating capacity it required.
Problems emerge when the action transfers but the supporting conditions do not. A business can execute the visible recommendation while asking it to produce a response that its buyers, operating model or current stage cannot support.
Execution can improve how the recommendation is carried out. It cannot independently create every condition the recommendation requires.
The diagnosis has to consider both how well the recommendation was executed and whether the business had the conditions it required.
Before adopting what worked elsewhere
Identify the conditions the recommendation required, then compare them with what is true in your business now.
Where an important condition is absent, uncertain or untested, the business may need to adapt the recommendation, narrow the test or change the sequence before committing further.
What changes when buyers do not behave as the recommendation assumes
The buying and evaluation environment is one of the clearest places where a credible recommendation can stop transferring cleanly.
When buyers cannot purchase independently
In a November 22, 2024 episode of The Logan Bartlett Show, Databricks CEO Ali Ghodsi described the company’s early experience with product-led growth. The approach was credible and widely promoted, with strong examples to back it up.
Databricks, however, was selling an enterprise data platform used to manage sensitive organizational data. Its buyers were not individual users deciding whether to enter a credit card number and start using the product. Decisions required organizational buy-in and a more complex enterprise sales process.
Ghodsi’s account also included weaknesses in the company’s early go-to-market execution.
The example does not isolate buyer environment as the only cause, and it shouldn’t be read as proof that product-led growth is unsuitable for enterprise businesses. The example makes a narrower point. Execution may need to improve, but the recommendation may also depend on buyer behaviour that does not reflect how the sale actually happens. Better execution can strengthen the approach, but it cannot remove the security, procurement and organizational approvals that shape the buyer’s decision.
Applying the same recommendation elsewhere requires an examination of both execution quality and the behaviour the recommendation requires from buyers.
When a familiar growth approach no longer fits
Baird Hall described a related experience with Churnkey on the July 17, 2024 episode of CHURN.FM. Churnkey initially used the inbound and product-led approach he knew from previous SaaS companies, then found that buyers needed more direct involvement from a sales team before they were ready to purchase.
Previous-company experience was still valuable, but buyers in the new business needed a different path to purchase.
When lead volume does not match the buying process
The same issue appears outside SaaS. Consider a professional-services firm adopting a high-volume lead-generation model because it worked for another company in its category. The model may assume a standardized offer, rapid follow-up and a relatively short evaluation process.
If the firm’s buyers make high-trust decisions that depend on senior credibility, referrals and several conversations, the tactic may look transferable while the buying mechanism is not.
Lead generation may still be appropriate. The path from initial interest to a credible buying decision has to reflect how those buyers actually evaluate the firm. Increasing lead volume alone will not resolve that mismatch.
How stage, sequence, economics and capacity change whether a recommendation applies
Buyer behaviour is one governing condition. Business stage, decision sequence, economics and operating capacity create separate questions.
Business stage: Is the timing right?
Has the business reached the point where the recommendation can actually work? For example, there is little value in trying to grow faster before the business has shown that it can consistently attract interested buyers and turn that interest into sales. Increasing investment too early can create more uncertainty instead of better results.
Older Startup Genome research on premature scaling provides broad support for this risk, finding that startups often struggled when they expanded spending, hiring or growth efforts before the business had built a stable foundation. The research is startup-specific and should not be treated as evidence about every established business.
Its relevance here is limited to one principle: an action associated with growth can undermine performance when it is applied before the business has resolved the earlier conditions it depends on.
The recommendation may be sound while the timing remains wrong.
Decision sequence: Have the necessary decisions and capabilities been established in the right order?
A mature business can still launch demand generation before clearly defining its offer, who it is trying to reach, or how it wants to position itself. The age or size of the company does not resolve that problem. An earlier decision remains open.
The recommendation may be commercially credible and operationally feasible, yet still be applied prematurely before directional decisions are settled.
Economics: Can the recommendation produce a worthwhile return?
Economics asks whether the recommendation can produce a commercially acceptable result under the business’s current price, margin, conversion rate and customer value.
A paid advertising campaign may generate leads while remaining uneconomic. A lower-priced offer may not support the cost of the program. A longer sales cycle may make the required level of investment difficult to sustain before revenue appears.
The recommendation may produce activity while failing commercially.
Operating capacity: Can the team and systems support what it requires?
Increasing lead volume only helps when the business can identify, follow up with, qualify and serve the leads it generates. Hiring a larger marketing team only helps if the team has clear direction and priorities, enough work to focus on, and someone who can manage it well.
Even a well-established business can take on more than its people or systems are ready to support.
None of these conditions requires certainty before action. Marketing decisions are made under uncertainty all the time.
The relevant distinction is whether the recommendation is meant to test an uncertainty, or whether it depends on something that should already be decided and operational.
When to question marketing advice before committing budget
A business does not have to run a recommendation to failure before questioning whether it fits.
Sometimes the problem is already visible. An approach that expects buyers to evaluate, approve and purchase on their own may not suit a market where purchases require procurement and executive approval. Paid advertising may also cost more than the business can justify, or create more leads than the sales or delivery team can handle.
In these cases, questioning applicability is part of assessing the assumptions behind the recommendation.
The business may still choose to move forward. It might adapt the approach, test it on a smaller scale, delay the investment, or use the recommendation to learn something more specific.
What changes is the basis for the commitment. Evidence from other companies remains part of the rationale, but it is considered alongside whether the required conditions exist here.
Questioning a recommendation is useful when it improves the next decision. It becomes avoidance when every uncertainty is treated as a reason not to act, or when “our business is different” is used as a reason not to run a controlled test and see whether the recommendation could work here.
A useful check is: Are we examining the recommendation to make a better decision, or to avoid becoming accountable for one?
Complete certainty is unnecessary. The business needs enough clarity to understand:
- what conditions the recommendation depends on,
- which of those conditions are present,
- which remain uncertain,
- and what a useful test capable of producing interpretable evidence should show.
The test should have an agreed scope, enough support to be meaningful, and a clear decision standard on what results would justify continuing, changing or ending the approach.
Once those conditions are explicit, further analysis should not become a substitute for action.
A disappointing result may not prove the recommendation was wrong
The diagnosis becomes harder once the business has begun acting on the recommendation.
An early result may be weak, inconsistent or difficult to interpret, and several explanations may remain possible.
The execution may have been weak. The test may not have had enough time, budget or reach. Measurement may not clearly show the difference between attention and a meaningful response. The product may not yet be getting steady customer interest or sales, making it hard to tell whether the marketing failed or the offer itself was not ready. Weak internal support or the provider’s capability may also have affected the outcome.
Leadership conditions also affect what the result can show.
Priorities may have changed before the work had time to produce evidence. Important sales, financial or operational information may not have been available to the people making or executing the recommendation. The business may have under-resourced follow-up, overridden the agreed sequence of work, reopened settled decisions or ended the test before the result became interpretable.
These conditions affect how much the result can actually tell you. It is difficult to decide whether the recommendation was a poor fit without also asking whether the business provided the information, stability and support the approach required.
At the same time, a recommendation should not be protected from evidence simply because leadership approved it. The business still has to determine whether it gave the decision enough support to produce a useful result and learn what it needed to learn.
A poor fit becomes a credible diagnosis only when it can be linked to a condition that:
- exists independently of the disappointing result,
- materially affects how the recommendation is supposed to work,
- and could reasonably have been identified before or during adoption.
The same reasoning error can appear at both ends of the decision. A business may treat “this worked elsewhere” as proof that it will work here, then treat a disappointing result as proof that the recommendation was wrong. Both conclusions overlook what conditions were actually present.
This standard matters because explanations are easy to invent after a disappointing outcome.
“Our market is different” has little diagnostic value without a specific and relevant difference.
“Our buyers do not behave that way” becomes useful when the business can show how buyers actually evaluate, approve and purchase, and how that behaviour conflicts with what the recommendation requires.
“We were not ready” is too vague.
“The recommendation assumed a repeatable sales process, and we were still changing the offer, buyer definition and qualification criteria” identifies a condition that can be examined.
The diagnosis should improve the quality of the next decision.
What a weak diagnosis costs
When a recommendation disappoints, the business still has to decide what to do next.
It may invest more, change how the work is carried out, give it more time, abandon the channel, apply the approach to a different audience, or move on and try something else.
If the diagnosis is weak, the next decision is built on the same uncertainty.
A mismatch in how buyers make decisions may be interpreted as proof that a channel does not work. An underdeveloped sales process may be interpreted as evidence that the leads were poor. An evolving or unproven offer may be treated as a media-buying problem. Weak execution may be excused as bad timing. Leadership changes may be attributed entirely to the provider.
Each interpretation points toward a different action.
The risk extends beyond the original spend. Distorted learning changes what the business believes about its market, its team or the recommendation itself. That belief then shapes the next decision.
One misdiagnosed result can compound into a recurring pattern instead of becoming useful learning.
How to know if marketing advice applies to your business
A credible recommendation deserves more than automatic acceptance or automatic skepticism.
The central question is:
What did this recommendation require where it worked, and is that true here?
That means understanding:
- what maturity or prior capability the other business had in place,
- how its buyers evaluated, approved and purchased,
- what sequence of earlier decisions and steps had already been completed,
- what economics made the recommendation financially viable,
- what team and systems capacity it relied on,
- and what specific question the recommendation was intended to answer.
These questions allow external advice to be used responsibly.
Case studies, proven playbooks and knowledgeable advisors can still shorten the learning process and reveal opportunities the business may not see on its own.
However, good advice can still be the wrong next move if it comes too early, costs more than the business can support, depends on earlier decisions that are still unsettled, or assumes a buying process that does not exist here.
Once enough of the required conditions are in place, the business has another responsibility: support the decision properly, hold it long enough to produce useful evidence, and respond honestly to what the result shows.
When the conditions are understood, the next recommendation can be based on a clearer rationale, a defined test and evidence the business knows how to interpret.
A single recommendation can be evaluated against the conditions it requires. But what happens when several reasonable recommendations are adopted at once and fail to reinforce one another? We’ll examine that in the next essay.
Continue exploring
→ What happens when reasonable recommendations fail to reinforce one another (coming next)
→ The Spin → Explore the essay series and the diagnostic questions that lead from recurring marketing problems to better decisions.
→ How We Work → See how the Growth Roadmap evaluates fit, readiness and sequencing before ongoing marketing work is committed.
Questions explored in this essay
The recommendation may depend on conditions the other company already had, including business maturity, prerequisite capabilities, operating capacity, viable economics or a buyer process that allowed the approach to work. A case study proves that the approach can succeed somewhere. Your next decision still has to account for whether its mechanism matches how your business and buyers actually operate. The recommendation and its supporting evidence may both be credible even when those conditions differ.
A weak result alone cannot distinguish between poor execution and an inapplicable recommendation. The work may have lacked enough time, budget, reach or measurement precision. Product traction, internal commitment, provider capability or leadership behaviour may also have affected what the result could show. Applicability becomes a credible explanation when an observable condition conflicts with how the recommendation is supposed to work, materially affects its mechanism and could have been identified before or during adoption. Execution, applicability and leadership conditions can coexist. Finding one problem does not automatically rule out the others.
Yes. A business does not have to run a recommendation to failure when a material contradiction is already visible. A model where buyers can evaluate and purchase without speaking to sales may conflict with a procurement-driven market. Paid acquisition may rely on economics the current price and conversion rate cannot support. A demand program may exceed the business’s ability to follow up with and serve the resulting leads. The business may still proceed by adapting the approach, narrowing the test or clarifying what the test is intended to learn. The purpose of the analysis is to improve the decision, not to create an indefinite reason to avoid one.
No. Case studies and best practices provide useful evidence that an approach can work under identifiable conditions. Their limitation is visibility. The maturity, buyer process, capabilities and commercial structure surrounding the result may not be fully shown, or may not exist in the receiving business. A credible source, experienced operator or proven playbook can still shorten the learning process. The business has to determine what the recommendation required where it worked and whether those requirements are present here.
Ask what the recommendation required where it worked and compare those requirements with what is true in your business. Examine the source business’s maturity, buyer process, prerequisite decisions, economics and operating capacity. Then distinguish what the recommendation is meant to test from what needed to be true before the test began. Complete certainty is unnecessary. The business needs enough clarity to define a bounded test, support it properly and agree in advance on the evidence that would justify continuing, adapting or ending it. It also needs to be prepared to hold the decision long enough to learn from the result.
Yes. A move designed to scale demand assumes that demand is repeatable. Increasing lead volume assumes that sales and delivery can support it. Hiring a larger team assumes that enough direction, meaningful work and management capacity already exist. The relevant question is whether the recommendation is testing an uncertainty or depending on a condition that should already be established. The advice may become useful later, or through a narrower test now, even when it is the wrong next commitment.
Sources
Ali Ghodsi, “EP 124: Databricks CEO Ali Ghodsi Breaks Down the AI Hype-Cycle,” The Logan Bartlett Show, November 22, 2024.
Baird Hall, “Reactivation Tactics: Transforming Cancellations into Customer Retention Opportunities,” CHURN.FM, episode 254, July 17, 2024.
JF Gauthier, “Premature Scaling: A Deep Dive,” Startup Genome, September 2, 2011.
