Growth: Obey the forces you wish to command!
Sometimes businesses pour millions into loyalty programs, lifetime value optimization, and retention campaigns while ignoring the fundamental laws that actually drive sustainable expansion.
Research from the Ehrenberg Bass Institute (love you, Byron), spanning thousands of brands across decades, reveals how growth really happens: brands succeed by reaching new customers consistently, not by deepening relationships with existing ones.
This happens through four key drivers that directly impact acquisition costs, conversion rates, and revenue predictability:
Mental Availability: Your brand comes to mind when people need your category
Physical Availability: People can easily find and buy your product
Category Entry Points: The specific moments, needs, or contexts that trigger purchases
Distinctive Brand Assets: The colors, sounds, or shapes that make you instantly recognizable
These aren't marketing theories. Companies that master these fundamentals grow 15-20% faster than those using traditional methods.
Why Growth Efforts Can Fail
Companies ignore these fundamentals because they feel counterintuitive. Instead, they fall into four common traps:
Focus on Loyalty Over Reach
They pour resources into keeping existing customers happy while neglecting the broader market that drives actual growth.
Byron Sharp's research across thousands of brands shows that loyalty is a result of scale, not a driver of growth. The Double Jeopardy Law proves smaller brands suffer both fewer customers and lower loyalty from those customers.
Rely on Outdated Data
Most growth decisions come from lagging data - eg. CRM systems and financial reports that show what happened, not what's happening or what will happen next. Traditional datasets miss >50% of the signals that predict future demand.
Think in Silos
Marketing, sales, and product teams operate separately, missing how customers (and data/interactions) flows across touchpoints. Not all companies effectively integrate customer data across all channels.
Use Surface-Level Metrics
Growth team can get lost in the details of experimentation, and confuse channel tactics with strategy.
They track channel performance and return on ad spend but miss the deeper patterns that predict sustainable growth.
Advertising has short term as well as long term effect on d emand, and price sensitivity.
Brands that stopped advertising saw sales fall 16% after one year and 25% after two years.
What Good Measurement Looks Like: Mercury's Forecasting Model
Dan Kang, Mercury's CFO, built a forecasting model that could be used and adapted to connects brand performance to business outcomes. His framework is very elegant, as it tracks the metrics that actually matter:
New customer flow (aligned with mental & physical availability)
Retention cohorts (driven by mental and physical availability and product performance)
Average revenue per customer (reflecting value capture)
Expense levers (including brand investment)
Cash runway (showing financial sustainability)
This approach offers the opportunity to translate the four growth drivers into operational metrics: acquisition costs, conversion rates, and revenue forecasts. Mercury's model helps them predict customer acquisition 3 months ahead, allowing precise budget allocation that competitors using traditional methods can't match.
The insight? Financial performance flows from brand performance, not the other way around.
Novel Methods to Execute Growth Better
The gap between understanding growth laws and executing them requires new approaches that go beyond traditional methods and data/mind sets.
Intelligence Beyond Traditional Approaches and Datasets
How it works: Search and social data reveal demand patterns that traditional sizing methods miss. Customer intent signals predict market opportunities 6 months before they appear in traditional analytics. Companies can size markets from the bottom up using actual search behavior rather than top-down estimates.
Example: Peloton's Search Data Blind Spot
Peloton could have seen demand shifts in 2021 by tracking search patterns. Data shows search volume for "home gym equipment" peaked during COVID but began declining months before their production halt. Their share of search dropped from 27.3% to 19.33% between June 2024 and April 2025, a 73% decline in search volume that preceded sales challenges.
Dynamic Competitive Analysis Using Wardley Mapping
Wardley Mapping can be used to understand competitive market dynamics by visually representing the evolution of the value chain, identifying where a company’s activities and offerings sit within the landscape, and spotting opportunities or vulnerabilities based on technological and market shifts; the most valuable drivers of value in a company are typically those that enhance differentiation, reduce dependency on legacy systems, and enable agility—such as innovation potential, operational efficiency, and the ability to adapt to changing customer needs—while mapping helps to pinpoint where investments or strategic focuses will generate the greatest impact on sustained competitive advantage.
Wardley Mapping reveals how competitive landscapes evolve over time, technological shifts, changing customer needs, and competitive vulnerabilities that traditional Porter analysis misses. (see a detailed example with Zalando here)
Customer Understanding That Goes Deeper
Thorough Customer Discovery can be tackled with text analysis from search and social, recommendation or CSAT platforms in order to surface what customers actually value versus what they say they value in focus groups ;-)
Most organisations rely on focus groups and surveys to shape products and campaigns, yet those methods capture what people say rather than what they do. queries, social conversations, CX verbatims and recommendation‐system logs record unprompted behaviour at scale.
When analysed with modern natural-language-processing (NLP) techniques, these text streams reveal the benefits customers actually pursue, the friction they experience, and the language they use to describe both. This can further be used to monitor product or service performance over time.
NB: This approach is deeply embedded in Innovation/Canvas and human-centric approaches, but not enough seen in BAU.
Integrated Data Systems That Actually Work
Most firms track dozens of metrics yet still struggle to answer a basic question: “Who is this customer and what do really want?” The core problem is data fragmentation.
Zero-party data (declared by customers) lives in preference centres and survey tools, while behavioural data (observed actions) sits inside product analytics, CRM logs, or a data warehouse.
When the two streams remain separate, insight quality drops, personalisation falters, and growth stalls. Linking them inside a single platform—HubSpot or any modern customer data environment—produces richer profiles, sharper segmentation, and faster, evidence-based decisions.Most companies collect customer data in fragments across different systems.
Connecting zero-party data (what customers willingly share) with behavioral data creates complete pictures of the customer and richer profiles.
Synthetic data fills hard research gaps
Tools like Evidenza create statistically valid, privacy-safe customer records that mimic real behaviour. Firms in healthcare, finance, and niche B2B markets—where sample sizes are tiny or data sharing is restricted—use these synthetic cohorts to test pricing, stress-test demand forecasts, and train machine-learning models without breaching confidentiality rules. Because the output contains no personal identifiers, it skirts GDPR risk, scales instantly, and removes the bias that comes from surveying the same respondents over and over.
Why This Matters Right Now
Markets move faster than ever. Customer behavior shifts quickly. Competition intensifies across every category.
The data is clear: Companies using these approaches outperform traditional methods substantially. Mars revenue grew from $25 billion to $50 billion after adopting Ehrenberg Bass principles, with Snickers experiencing sustained double-digit growth and 30% lift in advertising effectiveness.
Coca-Cola, Procter & Gamble, and Unilever have adopted these principles to optimize their marketing strategies. Over 100,000 startups choose modern forecasting methods like Mercury's approach for financial operations.
The question is whether you'll apply them before your competitors do.
Ready to build growth engines that actually work? The science is clear. The methods are available. Your move.
References | go further
Why Mental Availability is More Powerful Than Awareness : link
Mental availability correlates with strong business results : link
How Mental And Physical Availability Drives Brand Growth: link
Modern marketing dilemmas: What role does brand play in the consumer decision journey? link
Mercury Forecast Model | Google Templates: link
