"The Operational Reality of High-Growth Marketing" - A Pulse Commentary

In the run up to the Pulse eCommerce Summit on the 13th - 14th May 2026, we are launching a series of commentary pieces on topics that will be a focus point at the conference, led by members of the Vervaunt team. Here is our commentary piece on managing high growth, with input from Tom Hancock. 

Most brands have growth targets, but fewer have done the work to understand what those targets actually require - the customer acquisition costs that remain sustainable, the creative volume the algorithms now demand, the measurement infrastructure needed to know what's working, and the internal alignment between marketing ambition and financial reality.

The gap between setting a growth goal and building the system to achieve it is where most strategies fail. Not because the ambition was wrong, but because the operational foundation wasn't in place. Paid media can be a growth engine, but only when it's built on unit economics that hold, creative systems that scale, and measurement that reflects business performance rather than platform vanity metrics.

This article covers what we're seeing work for brands pursuing aggressive growth - and what tends to break when the foundations aren't solid.

Defining growth before chasing it: forecasting as ongoing strategy

The most common gap we observe in high-growth brands isn't execution - it's definition. Growth targets are often set based on what leadership wants to achieve rather than what the business can support at acceptable unit economics.

Before any media plan gets built, there's foundational work that determines whether growth targets are achievable: what does the growth goal require in terms of new customer acquisition, at what customer acquisition cost does that growth remain profitable, and what investment is needed to reach customers who don't yet know the brand exists?

What the forecasting process should establish:

• The specific revenue target and new customer volume required to hit it
• The customer acquisition cost ceiling that maintains acceptable unit economics
• The proportion of spend that needs to shift toward upper-funnel activity
• Which markets and products offer the highest growth potential relative to current performance
• The realistic timeline for when acquisition investment converts to profitable returns

Brands that skip this step often end up in a cycle of optimism, overspend, and retrenchment. Targets get set, performance doesn't materialise on the expected timeline, and the response is to pull back spend - often right when awareness investment was about to convert into demand.

Why forecasting needs to be continuous:

A forecast built in January becomes increasingly unreliable by June as markets shift and channels perform differently than expected. The brands managing growth well treat forecasting as quarterly strategy work, not an annual planning exercise. They build an initial view, run activity against it, and reforecast based on what actually happens. If Meta awareness is driving stronger incrementality than YouTube, the next quarter's plan reflects that. If a particular market is outperforming its baseline significantly, budget shifts to capitalise.

This requires infrastructure - regular reporting rhythms, clear metrics, and internal alignment on what triggers a reforecast - but it's the difference between a plan that adapts to reality and one that gets abandoned when the first assumptions prove wrong.

Product-level strategy: identifying what actually drives acquisition

Not all products contribute equally to growth. Some drive first purchases and bring new customers into the brand, while others are repeat purchases or upsells that build lifetime value after acquisition. Treating the entire catalogue as interchangeable misses one of the most important strategic levers available.

How product segmentation should inform growth strategy:

The brands we work with typically segment products into acquisition drivers and lifetime value builders. Acquisition drivers might be hero products with broad appeal, entry-price items, or products that solve an obvious problem. Lifetime value builders are often consumables, accessories, or products that deepen the relationship after the first purchase.

Once that segmentation exists, media strategy can be built around it:

• Acquisition campaigns focus on hero products with proven ability to convert first-time buyers, even if margin is lower
• Bidding strategies factor in what happens after the first purchase - if a £40 product leads to £200 in lifetime value, higher acquisition costs become justifiable
• Creative strategy varies by product role - acquisition products need content that introduces and convinces, while LTV products need content that cross-sells and retains

If data shows that customers who buy Product A have a 50% repeat rate and £180 LTV, while customers who buy Product B have a 20% repeat rate and £60 LTV, acquisition strategy should weight toward Product A - even if Product B has higher immediate margins.

This requires connecting product data to customer data, which many brands haven't done despite having strong analytics in each silo. The insight that unlocks product-level growth strategy sits at that intersection.

The CAC and LTV relationship: building the case for investment

High-growth strategies require spending money to acquire customers who don't yet know the brand exists. That spend looks inefficient in the short term because it is inefficient in the short term - the return comes later, through repeat purchases and customer lifetime value.

The metric that matters isn't what you paid to acquire a customer today but what that customer will be worth over time relative to what you paid. A £60 acquisition cost looks expensive if you're expecting immediate payback, but reasonable if that customer has a 40% repeat rate and an average lifetime value of £180.

Breaking down LTV by segment:

Aggregate lifetime value figures are useful but can mask significant variation. Customers acquired through different channels, buying different products, or entering at different price points often have materially different repeat behaviour. The brands making the best investment decisions break LTV into segments - by acquisition source, by first product purchased, and by market - which allows for precision rather than applying a single CAC ceiling across all activity.

Getting finance aligned:

The brands that scale successfully almost always have alignment between marketing and finance on how acquisition investment gets evaluated. That means getting the CFO into the conversation early - not to approve a budget, but to understand the model.

When finance understands that a £50,000 acquisition investment in Q1 is forecast to return £150,000 in customer lifetime value over 18 months, the conversation shifts from "why is ROAS so low?" to "are we on track against the LTV projections?" This isn't about convincing finance to accept poor performance - it's about establishing shared metrics that reflect what growth actually requires, and holding the strategy accountable to those metrics over time.

Media planning for growth: shifting investment up the funnel

Brands in maintenance mode can concentrate spend on bottom-funnel activity - capturing existing demand through search, retargeting warm audiences, optimising for immediate conversion. Brands pursuing aggressive growth can't, because there isn't enough existing demand to hit the targets.

Growth requires creating demand, not just capturing it. That means shifting investment toward awareness and prospecting activity:

• Meta: Increased investment in awareness-optimised campaigns, not just conversion campaigns, with creative built for introduction and audience strategies that prioritise reach over remarketing
• YouTube: Investment in video content that builds brand recognition over time - underutilised by most brands for awareness, but the data consistently shows it contributes to long-term growth even when last-click attribution makes it look ineffective
• Google: Pmax campaigns configured for new customer acquisition rather than blended performance, with bidding strategies that factor in customer lifetime value

Timing awareness investment around demand cycles:

One pattern we've seen work well is concentrating brand-building activity in the first three quarters, then shifting to acquisition-focused spend in Q4 when natural demand spikes. The awareness investment creates recognition and consideration; Q4 captures it when purchase intent is highest.

This requires accepting that quarters one through three won't show the same efficiency as Q4, but the Q4 performance is built on the awareness foundation laid earlier. Brands that cut awareness spend because Q2 ROAS looks weak often find their Q4 underperforms as a result.

Creative as the growth lever: volume, diversity, and what the algorithm needs

Creative has always mattered, but what's changed is how platform algorithms use it. The algorithms have become more sophisticated at finding audiences, but they need creative variety to do it effectively - the old model of running three ads and optimising toward the winner doesn't work the same way anymore. The algorithm needs different messages, different formats, and different hooks to test against different audience segments.

What this means for growth strategies:

• Volume: More creative than most brands are used to producing - not three variations but thirty, not one concept but five or six distinct approaches running simultaneously
• Diversity: Different creative for different funnel stages - awareness content that introduces the brand, consideration content that addresses objections, conversion content that drives action, retention content that brings customers back
• Speed: Creative that worked last month may not work this month, so the brands scaling effectively have production systems that can generate and test new creative continuously

The role of influencer content:

Influencer content serves two functions in a growth strategy: it's a distribution channel reaching audiences who trust the influencer's recommendations, and often more valuable, it's a creative source. Influencers understand what resonates with their audience - the hooks that work, the format preferences, the cultural references that land - in ways brand teams often don't.

The most effective partnerships give creators latitude to present the brand in their own voice rather than scripting them into brand guidelines. This requires loosening control somewhat, but consistency optimised for brand guidelines often underperforms content optimised for audience relevance.

Measurement that reflects business reality - and avoiding 'growth theatre'

The measurement landscape has fragmented to the point where platform-reported metrics are often incomplete. Privacy changes have degraded tracking, attribution windows have shortened, and the customer journey involves more touchpoints than any single platform can see.

What 'growth theatre' looks like:

There's a pattern where internal reporting looks healthy but business performance tells a different story. Platform ROAS is strong, the Google dashboard shows good numbers, Meta reports acceptable efficiency, and the monthly report to leadership looks impressive - but when you look at top-line revenue, new customer growth, and actual profitability, the business isn't growing the way the platform metrics suggest it should be.

This is growth theatre: the metrics being reported create a false picture of performance. It happens when brands optimise for what's measurable in-platform rather than what's true for the business, resulting in over-investment in channels that capture existing demand while under-investing in channels that create it.

The most common version: Google and Meta both report strong ROAS because they're both claiming credit for the same conversions, while the customers being "acquired" are actually returning customers who would have purchased anyway. New customer growth is flat, but nobody notices because the platform dashboards look good.

How to build measurement that reflects reality:

• Marketing Efficiency Ratio (MER): Total revenue divided by total media spend - a blunt metric, but one that tells you whether overall investment is returning at an acceptable rate regardless of which platform claims credit
• New customer metrics: New customer acquisition volume and cost tracked separately from blended performance
• Incrementality testing: Geo-lift studies, holdout tests, and controlled experiments that measure what spend actually contributes
• Media mix modelling: Statistical analysis that estimates each channel's true contribution, accounting for interactions and delays that platform attribution misses

"As brands scale, complexity compounds. More channels. More markets. More tools. In practice, this is where teams start spending more time validating than advancing performance.

If the signals flowing between analytics, paid media, and retention are inconsistent, every optimisation becomes a debate rather than a decision. Progress slows not because ambition fades, but because clarity does.

The operational reality of high-growth marketing is that speed depends on trusted signals. When leadership has confidence in the performance data guiding investment, budgets move faster, testing accelerates, and creative can scale responsibly. When they do not, energy is absorbed by reconciliation rather than growth.

Sustainable expansion is built on signal clarity. The brands that scale consistently treat their data layer as a strategic asset, not an afterthought." - Jaz Field, Marketing Manager, Littledata 

Internal operating rhythm: the cadence that makes growth work

Growth strategy exists on paper until there's an operating rhythm that turns it into action. The brands executing growth effectively have clear cadences for reviewing performance, making decisions, and adjusting plans.

Weekly trade meetings review the previous week's performance: what happened across channels, how revenue tracked against forecast, and whether there are anomalies requiring action. This isn't a strategy meeting - it's an operational check-in to catch issues quickly and make tactical adjustments. The outcome should feed to whoever manages paid activity so adjustments happen within days rather than weeks.

Monthly performance reviews take a deeper look at how the month tracked against the plan - whether new customer numbers are on target, CAC is within range, and whether patterns are emerging in channel, product, or market performance. This is where the ecommerce and marketing leads assess whether the strategy is working as expected and begin diagnosis if something is off.

Quarterly business reviews bring the broader team together, including finance, merchandise, and senior leadership. Performance gets reported against business goals rather than just marketing metrics, and the next quarter's plan gets set. This is where reforecasting happens based on what the previous quarter revealed. Finance needs to stay aligned on how investment is evaluated; merchandise needs to flag what's coming so paid strategy can adapt.

Without a clear rhythm, decisions happen reactively or not at all. The brands struggling with growth often have inconsistent cadences - reviewing performance when someone remembers to, making decisions in ad hoc conversations, never finding time for the strategic review that would surface the real issues.

The signals that indicate whether growth economics are working

High-growth strategies involve accepting short-term inefficiency for long-term returns, but the model only works if the long-term returns actually materialise. Understanding when a growth strategy is on track versus when it's failing is critical, and the signals aren't always obvious in the early months.

The repeat rate test:

The entire economic model depends on customers coming back. You spend to acquire them, accepting a higher upfront cost because you expect repeat purchases to deliver lifetime value. If customers aren't repeating at the rate you forecast, the model doesn't hold.

Second-purchase rates deserve close attention, especially in cohorts acquired through upper-funnel activity. If those customers are churning faster than expected, something in the experience isn't working - and continuing to invest in acquisition won't fix it.

Where the issue usually sits:

When repeat rates underperform, the problem is rarely the acquisition activity itself - the customers came in and bought once, then didn't come back. That's typically a signal that something downstream isn't working:

• Loyalty and retention: Is there a program or communication strategy that gives customers a reason to return, or does the relationship end at first purchase?
• Post-purchase experience: Was delivery fast enough, was the product what they expected, and were returns easy if something went wrong?
• Ongoing engagement: Is the brand staying present with customers between purchases, or disappearing until retargeting?

Acquisition and retention are connected systems. Scaling acquisition without investing in retention leads to spending more to acquire customers who don't stay.

"It's never been more expensive to attract new customers, so when you do, you've got to make sure the experience is perfect. I'm talking about keeping delivery promises, accurate stock availability and consistent service; the stakes are high. Operations need to be reliable so you can grow profitably." - Ollie Slade, Partner Manager, Brightpearl by Sage 

AI as accelerator: compressing cycles without replacing judgment

AI has changed the efficiency of growth operations over the last 18 months. It hasn't changed the fundamentals of what growth requires, but it has compressed timelines and reduced manual work.

Where AI is creating leverage:

• Creative production: Generating variations, adapting formats, and testing hooks at volume - though human oversight on quality and brand consistency remains essential
• Data analysis: Querying performance data conversationally to understand which products are driving new customers in which markets and where incrementality is strongest
• Competitive research: Understanding which brands are active in a market, what messaging they're using, and which subcategories are growing

The risk is treating outputs as truth without validation. AI is effective at pattern recognition and synthesis but less reliable for judgment calls that require context it doesn't have.

AI also puts more brands on a level playing field for operational work, which means differentiation shifts to the things AI can't replicate: brand distinctiveness, creative quality, strategic judgment, and customer experience. The brands using AI well are using it to execute faster while investing the saved time in work that actually differentiates.

What to reassess before scaling paid investment

If aggressive growth is part of your plan over the next 12 to 36 months, these are the areas worth addressing before committing capital:

On strategy and forecasting:

• Define what your growth target requires in new customer volume and acquisition cost - is it realistic given current economics?
• Model customer lifetime value by acquisition source, product, and market
• Establish a quarterly reforecasting rhythm with clear triggers for adjusting the plan
  

On product strategy:

• Identify which products drive acquisition versus which build lifetime value, and weight media strategy accordingly
• Connect product performance data to customer data to understand how first-product choice correlates with repeat behaviour

On financial alignment:

• Get finance involved early so the CFO understands the acquisition model and metrics being used to evaluate it
• Separate acquisition investment from efficiency metrics in reporting
• Set clear expectations that early-stage growth investment will look inefficient before it pays back

On media and creative:

• Audit your funnel mix - is the proportion of awareness versus conversion spend appropriate for a growth strategy?
• Assess whether creative volume and diversity are sufficient for algorithm requirements
• Evaluate whether influencer content is being used as both a distribution and creative source

On measurement:

• Review whether channel performance is being evaluated on platform ROAS or business-level metrics
• Assess whether you're at risk of growth theatre - are the metrics reported to leadership accurate?
• Implement incrementality testing through geo-lifts, holdouts, or other controlled experiments
  

On operating rhythm:

• Establish weekly, monthly, and quarterly review cadences with the right people in each meeting
• Create feedback loops so insights from reviews reach the people managing campaigns quickly enough to act

On retention:

• Audit repeat rate by cohort and acquisition source
• Assess whether friction in delivery, returns, or product experience is driving churn
• Evaluate what happens between first and second purchase - is there a system that maintains the relationship?

Many of the themes explored here - from connecting roadmaps to business goals - will be examined in far greater depth at the Pulse eCommerce Summit on the 13th and 14th May 2026. Across two days, senior eCommerce leaders, operators and specialists will share how they structure roadmaps in practice, where plans most often break down, and the frameworks they use to prioritise, adapt and deliver meaningful commercial impact. If building a roadmap that genuinely drives progress is a priority for 2026 and beyond, register now to secure your place.