Category Entry Points: A Quantitative Approach to Byron Sharp's Mental Availability Theory

TL;DR: Brand growth depends more on mental availability -- being thought of in buying situations -- than on brand preference or differentiation. Large brands are large because they are linked to more Category Entry Points (CEPs) than small brands, not because individual links are stronger. Most companies measure brand awareness when they should be measuring the number and breadth of buying situations associated with their brand.

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The Wrong Question in Brand Strategy

For forty years, the central question of brand strategy has been: why do consumers prefer our brand over competitors?

It is the wrong question.

Not because preference does not exist. It does. Not because differentiation is meaningless. It is not. But because the empirical evidence, accumulated across fifty years and hundreds of categories by the Ehrenberg-Bass Institute for Marketing Science, points to a more fundamental truth about how brands actually grow.

The question that matters more is simpler and more uncomfortable: when a buying situation arises, does the consumer think of our brand at all?

This is the distinction between brand preference and mental availability. Preference asks: given a set of brands, which does the consumer favor? Mental availability asks: when the consumer faces a need, which brands come to mind? The first question assumes the consumer is already comparing brands. The second recognizes that, in most categories, most of the time, the consumer is not comparing anything. They are reaching for whatever brand is mentally accessible in the moment.

Byron Sharp's 2010 book How Brands Grow formalized this insight, drawing on decades of evidence from Andrew Ehrenberg and the research institute that bears his name. The book argued that brand growth depends primarily on two factors: mental availability (the probability that a brand comes to mind in a buying situation) and physical availability (the ease with which a brand can be found and purchased). Not positioning. Not unique selling propositions. Not elaborate brand architectures. Availability -- mental and physical.

The marketing profession received this thesis with the enthusiasm typically reserved for a doctor who tells you that your symptoms are caused by not sleeping enough. Everyone suspects it might be true. Nobody wants to reorganize their life around it.

But the evidence is substantial. And the practical implications, once you follow them to their conclusions, restructure how you think about brand measurement, creative strategy, and media planning.

This article concerns itself with the measurement side -- specifically, with Category Entry Points (CEPs), the unit of analysis for mental availability. CEPs are the specific cues, occasions, needs, and contexts that trigger a consumer to think about a category. They are measurable. They are manageable. And almost nobody is measuring them correctly.

Mental Availability: What It Actually Means

Mental availability is not awareness. It is not recall. It is not top-of-mind. These are related constructs, but they are not the same thing.

Awareness asks: have you heard of Brand X? This is a low bar. Most consumers are "aware" of dozens of brands in any given category. Awareness does not predict purchase because it does not account for the buying context. You are aware of many brands you never buy.

Recall asks: when I say "soft drinks," which brands come to mind? This is better, but still context-free. It measures the brand's associative strength with a category label. It does not tell you when or why the brand comes to mind in actual buying situations.

Mental availability, as defined by Romaniuk and Sharp, is the propensity of a brand to be thought of in buying situations. The critical distinction is the plural: buying situations, not the buying situation. A brand does not exist in one context. It exists across a network of possible purchase triggers. The more triggers linked to the brand, and the stronger those links, the higher its mental availability.

Consider coffee. A consumer might think about the coffee category in dozens of situations: waking up in the morning, meeting a friend, needing an afternoon energy boost, finishing a meal at a restaurant, studying late at night, treating themselves on a weekend, hosting guests, buying a gift. Each of these is a Category Entry Point. A brand that is mentally linked to "morning wake-up" but nothing else has narrow mental availability. A brand linked to morning, afternoon, socializing, and gifting has broad mental availability.

The Ehrenberg-Bass research consistently shows that large brands are large primarily because they are linked to more Category Entry Points than small brands. They do not have stronger links to individual CEPs. They have more links to more CEPs. This is the mental availability equivalent of the NBD-Dirichlet model's finding that big brands have more buyers, not more loyal buyers.

Notice the pattern. The average link strength barely varies across brands -- all hover between 38% and 42%. What separates the 35% share brand from the 3% share brand is not how strongly they are linked to any particular CEP. It is how many CEPs they are linked to at all. The big brand is thought of in fourteen different buying situations. The small brand is thought of in three.

This finding has a brutal implication for brand strategy. Most differentiation-based strategies focus on strengthening the brand's association with one or two specific benefits or occasions. "We own the morning routine." "We are the premium choice." This may increase the strength of specific CEP links, but it does not expand the number of links. And the evidence says that breadth matters more than depth. The hidden cost of over-optimizing for narrow positioning is that it sacrifices the breadth of mental availability that actually drives market share growth.

Physical Availability: The Other Half Nobody Argues About

Before going deeper into mental availability, it is worth acknowledging the other half of Sharp's framework. Physical availability -- the ease with which a consumer can find and purchase the brand -- explains a large share of market share variation that mental availability alone cannot.

Physical availability encompasses distribution breadth, shelf space, store placement, online findability, delivery speed, and any other friction between the intention to buy and the completed purchase. It is less theoretically controversial because the mechanism is obvious: brands that are easier to find sell more. No one disputes this.

The relationship between mental and physical availability is multiplicative, not additive. A brand must come to mind (mental availability) AND be easy to buy (physical availability) to win the sale. High mental availability with low distribution is wasted potential. High distribution with low mental availability produces shelf warmers that move only on price promotion.

This article focuses on mental availability because it is the dimension that most brands measure poorly. Physical availability metrics -- distribution, shelf share, online search rankings -- are well-understood and widely tracked. Mental availability metrics are not. The economics of attention provides a useful bridge between the two — attention is the scarce resource that determines whether mental availability converts to physical action.

Category Entry Points: The Atoms of Mental Availability

A Category Entry Point is any internal cue (motivation, need, desire) or external cue (situation, occasion, location, time) that triggers a consumer to think about a product category.

CEPs are not brand-specific. They belong to the category. "I need something quick for lunch" is a CEP in the fast food category. "My child has a birthday party this weekend" is a CEP in the gift category. "I want to relax after work" is a CEP in the alcohol, streaming, and snack categories simultaneously. Jobs-to-be-done segmentation provides a complementary lens — where CEPs identify the triggers that bring a category to mind, JTBD identifies the progress customers are trying to make once they enter the category.

The Ehrenberg-Bass Institute has developed a taxonomy of CEP types:

The number of relevant CEPs varies by category. Fast-moving consumer goods (FMCG) categories tend to have 8-15 major CEPs. Services categories can have 20 or more. B2B categories often have fewer but more complex CEPs tied to specific business problems or procurement triggers.

The distinction matters because CEPs are actionable. A creative brief built around a CEP -- "make our brand come to mind when someone is choosing what to bring to a barbecue" -- gives the creative team a specific situation to depict and a specific mental association to build. A brief built around an abstract benefit -- "communicate that our brand is refreshing" -- is vague enough to produce anything, which usually means it produces nothing memorable.

The Ehrenberg-Bass Evidence Base

The empirical case for mental availability and CEPs rests on several decades of research at the Ehrenberg-Bass Institute at the University of South Australia, with contributions from Jenni Romaniuk, Byron Sharp, John Dawes, and their collaborators.

The key findings, replicated across categories and countries:

The Double Jeopardy Law. Small brands suffer twice: they have fewer buyers, and those buyers purchase slightly less frequently. This pattern appears in virtually every consumer category studied and is consistent with the idea that brand size is driven primarily by mental and physical availability rather than by loyalty or preference differences.

The Duplication of Purchase Law. Brands share their customers with competitors in proportion to those competitors' market share. Brand A's customers are more likely to also buy Brand B if Brand B is large. This is inconsistent with segmentation-based theories (which predict that brands serving different segments should not share customers) and consistent with the mental availability theory (which predicts that brands with more CEP links attract buyers from a wider pool).

The Law of Buyer Moderation. Heavy buyers of a brand in one period tend to buy less in the next period, and light buyers tend to buy more. This regression to the mean is exactly what the NBD-Dirichlet model predicts and is inconsistent with loyalty-based explanations of brand growth.

CEP breadth predicts brand size. Across multiple studies, the number of CEPs a brand is linked to correlates more strongly with market share than the strength of any individual CEP association. Romaniuk's 2013 study across 13 categories found a correlation of r = 0.85 between CEP breadth and market share, compared to r = 0.31 between average CEP link strength and market share.

The chart makes the hierarchy visible. Aggregate measures of CEP coverage (breadth, reach, mental market share) predict market share far better than measures of individual association strength. Being linked to many buying situations matters more than being strongly linked to a few.

This does not mean that link strength is irrelevant. A brand that is weakly linked to everything is not well-positioned. But the evidence suggests that the marginal return on broadening the CEP portfolio exceeds the marginal return on deepening existing CEP links, for most brands in most categories.

Quantitative CEP Mapping: Survey Design and Network Analysis

Measuring CEPs requires a specific survey methodology developed by the Ehrenberg-Bass Institute. The approach differs from conventional brand tracking in important ways.

Step 1: CEP Identification. Before measurement comes identification. The goal is to generate a complete list of the situations, occasions, needs, and contexts in which consumers enter the category. Methods include:

• Qualitative research (focus groups, depth interviews) with category buyers
• Diary studies tracking actual purchase occasions over 2-4 weeks
• Analysis of search query data (what phrases trigger category searches)
• Social listening for consumption contexts mentioned online
• Expert workshops with sales and marketing teams

The output is a candidate list of 15-30 CEPs, which is then refined to the 8-15 most frequent and distinct entry points through preliminary quantitative screening.

Step 2: The CEP Survey Instrument. The standard approach uses a two-stage questioning format:

Stage 1 -- CEP Elicitation. For each CEP, respondents are presented with the buying situation and asked which brands come to mind. Example: "When you want something to drink while watching sports at home, which brands come to mind?" This is a free recall task -- no brand list is provided. Respondents type in or select from a dynamically generated list.

Stage 2 -- Brand Cuing. For each brand in the category, respondents are asked which buying situations they associate with it. Example: "In which of these situations would you consider [Brand X]?" This is an aided recognition task -- respondents see the full CEP list.

The two-stage design captures both unprompted mental availability (which brands spontaneously come to mind in a situation) and the broader associative network (which situations are linked to a brand when prompted).

Step 3: Network Construction. The survey data produces a bipartite network -- brands on one side, CEPs on the other, with weighted edges representing the percentage of respondents who linked each brand to each CEP. This network is the quantitative representation of mental availability in the category.

Step 4: Network Analysis Metrics. From the bipartite network, several metrics can be computed for each brand:

• Mental Penetration -- the percentage of category buyers who link the brand to at least one CEP
• CEP Breadth -- the number of CEPs with which the brand has a statistically significant association
• Network Reach -- the total number of brand-CEP links weighted by CEP importance
• Mental Market Share -- the brand's share of all brand-CEP links across the entire network

Measuring Mental Market Share

Mental Market Share (MMS) is the single most useful summary metric for mental availability. It captures both the breadth and strength of a brand's CEP associations in a single percentage.

The calculation is straightforward:

$$MMS_i = \frac{\sum_{j=1}^{J} a_{ij}}{\sum_{k=1}^{B} \sum_{j=1}^{J} a_{kj}}$$

where $a_{ij}$ is the association strength (proportion of respondents) between brand $i$ and CEP $j$, $J$ is the total number of CEPs, and $B$ is the total number of brands. If 40% of respondents associate Brand A with CEP 1, that link gets a weight of 0.40.

MMS correlates strongly with actual market share (r = 0.91 across studies) but is not identical to it. The gap between MMS and market share reveals opportunities and threats. A brand whose MMS exceeds its market share has mental availability that is not being converted -- usually a physical availability problem. A brand whose market share exceeds its MMS is vulnerable -- it is selling more than its mental presence warrants, often because of distribution advantages or price promotions that will not sustain growth.

In this illustrative example, Brand A has a mental availability surplus -- it is thought of more than it is bought, suggesting physical availability or pricing gaps. Brand B and Brand D show the reverse pattern -- they sell more than their mental presence predicts, suggesting they are over-reliant on distribution or promotion. These are the brands most vulnerable to competitors who build stronger mental availability.

Tracking MMS over time produces a leading indicator of market share change. Shifts in mental availability typically precede shifts in market share by 6-12 months, giving brands an early warning system that conventional share tracking cannot provide.

Brand-CEP Association Strength: The Linking Matrix

The brand salience score for brand $i$ can be defined as the weighted breadth of its CEP portfolio:

$$S_i = \sum_{j=1}^{J} w_j \cdot \mathbb{1}(a_{ij} > \tau)$$

where $w_j$ is the importance weight of CEP $j$, $a_{ij}$ is the association strength, $\tau$ is the significance threshold, and $\mathbb{1}(\cdot)$ is the indicator function. This captures the Ehrenberg-Bass finding that breadth of linkage matters more than depth.

The core analytical artifact of CEP measurement is the linking matrix -- a brands-by-CEPs matrix where each cell contains the percentage of category buyers who associate that brand with that CEP.

Several patterns emerge from a well-constructed linking matrix:

Market leaders link broadly. Brand A leads in 6 of 8 CEPs. It is not dominant in any single CEP -- no association exceeds 52% -- but it is present everywhere. This is the typical profile of a large brand.

Niche strength is visible but insufficient. Brand D has its strongest association with "celebrating / special occasion" (31%) -- close to Brand A's score for that CEP. But Brand D is weak or absent across most other CEPs. This single-CEP strength does not translate to a large share.

Growth opportunities are specific. Brand E's strongest link is "trying something new" (27%), where it actually outperforms Brand A (12%). This is a legitimate CEP foothold. The strategic question is whether Brand E can expand from this beachhead into adjacent CEPs without losing its position in the one CEP where it competes.

The matrix reveals competitive structure. Brand A and Brand B compete across all CEPs -- they are primary competitors. Brand C competes most directly with Brand A on "barbecue" and "hot day." Brand D competes with Brand A primarily on "celebrating." These pairwise competitive patterns are invisible in aggregate market share data but clearly visible in the linking matrix.

The CEP Portfolio Strategy Framework

The linking matrix provides the diagnostic. The CEP Portfolio Strategy framework provides the prescription.

The framework classifies a brand's relationship with each CEP into one of four categories, based on two dimensions: the brand's link strength relative to the category leader, and the CEP's importance (frequency of occurrence in the market).

The framework has direct implications for budget allocation. A brand that discovers it has no meaningful association with a high-importance CEP should treat that as the highest-priority gap -- more urgent than reinforcing an existing strong link. The linking matrix makes these gaps visible. The portfolio framework makes them actionable.

In practice, this means that brand teams should map their entire CEP portfolio at least annually, classify each CEP using the four-quadrant framework, and allocate creative and media resources accordingly. The brands that do this systematically -- and the Ehrenberg-Bass Institute reports that fewer than 15% of their corporate partners do -- consistently outperform those that allocate based on intuition or historical spending patterns.

Competitive CEP Analysis: Finding the White Space

The linking matrix also enables competitive analysis that goes far beyond market share comparison. By examining which CEPs are contested (where multiple brands have strong associations) and which are uncontested (where no brand dominates), strategists can identify structural opportunities.

Contested CEPs are high-importance entry points where the top 2-3 brands all have strong associations. "Watching sports" in the beer category is typically highly contested. Winning share in a contested CEP requires either outspending competitors in media or producing distinctively branded creative that is more memorable. Neither is easy. Neither is cheap.

Uncontested CEPs are entry points where no brand has a dominant association. These represent white space. If the CEP is high-importance, the first brand to build a strong association captures disproportionate mental market share. The cost of building a new link from zero is typically lower than the cost of displacing a competitor from an existing link.

Emerging CEPs are entry points that are growing in importance due to cultural, demographic, or behavioral shifts. Twenty years ago, "ordering food for delivery on a weekday evening" was a minor CEP in the restaurant category. Today it is one of the most important. The brands that identified this CEP early and built associations with it captured mental availability before competitors arrived.

The practical application of competitive CEP analysis involves constructing a "CEP landscape map" that plots CEP importance on the x-axis and competitive intensity (measured as the Herfindahl-Hirschman Index of brand link shares within each CEP) on the y-axis. CEPs in the high-importance, low-concentration quadrant are the strategic goldmines -- important buying situations where no brand has established dominance.

In this example, "dinner at restaurant" has the lowest HHI (0.18) and moderate importance (68) -- it is reasonably important and highly fragmented. A brand that builds a strong association with restaurant dining captures mental market share in an entry point where no competitor has a lock. "Trying something new" is less contested (HHI 0.41) but also less important (38), making it a better fit for a niche brand than a market leader.

CEPs as Creative Strategy Inputs

The greatest practical value of CEP measurement is its ability to make creative briefs specific.

Consider two creative briefs for the same beer brand:

Brief A (traditional): "Communicate that our brand is authentic, refreshing, and perfect for social occasions. Target: adults 25-44."

Brief B (CEP-informed): "Build a mental association between our brand and the specific situation of arriving home after a long workday and reaching for a cold beer while starting to cook dinner. The buying situation occurs 3-4 times per week for our target audience. Our brand is currently linked to this CEP by only 14% of category buyers, compared to 35% for the market leader. The creative must depict the specific moment and feature our distinctive brand assets prominently."

Brief B gives the creative team a real scene to depict, a specific mental association to build, a baseline to measure against, and a clear standard for success. Brief A gives them nothing that constrains or inspires execution.

The Ehrenberg-Bass Institute recommends that each piece of brand communication should be tied to one or two specific CEPs. This does not mean every ad shows the same situation. It means the portfolio of creative executions, taken together, should cover the brand's priority CEPs as identified by the portfolio framework. Some executions depict the "after work" moment. Others depict the "barbecue" moment. Others depict the "watching sports" moment. Across the portfolio, the brand builds links to multiple CEPs.

This is where Sharp's emphasis on distinctiveness connects to CEP strategy. Distinctive brand assets (DBAs) are the sensory cues that identify a brand without the brand name being present. Think of Coca-Cola's contour bottle, McDonald's golden arches, or Intel's five-note audio mnemonic. When creative execution pairs a buying situation with a distinctive asset, it builds the brand-CEP link in memory. When creative depicts a generic situation with generic branding, it builds category salience without directing that salience toward the advertised brand.

The measurement of creative effectiveness, in this framework, is not recall or liking or purchase intent. It is whether the creative execution strengthens the intended brand-CEP link in the target population. This can be measured through pre-post CEP surveys surrounding campaign exposure.

Media Planning by CEP Occasion

If CEPs are occasions, needs, and contexts, then media planning can be organized around reaching consumers when and where those occasions occur. This is not the same as traditional media planning, which optimizes for reach and frequency against a demographic target. It is media planning that optimizes for proximity to the buying situation.

Consider the beer brand that has identified "arriving home after work on a weekday" as a priority CEP. When does this CEP occur? Between 5:00 PM and 7:00 PM on weekdays. Where is the consumer? In transit (car, train, bus) or at home. What media are they consuming? Drive-time radio. Streaming audio. Social media on mobile. Television news. Outdoor advertising along commuting routes.

A CEP-informed media plan would concentrate impressions in these time slots and channels -- not because the demographic target indexes highest there (the traditional planning criterion), but because the buying situation is active there. The consumer is in the state of mind where a brand association can be most effectively formed.

Weather-triggered and event-triggered media are particularly well-suited to CEP-based planning. The technology for contextual triggering now exists across programmatic display, digital out-of-home, and social advertising. A beer brand can activate its "hot day" creative when temperatures exceed 28 degrees in a given market, reaching consumers precisely when the CEP is active.

This is a meaningful departure from the frequency-maximization approach that dominates most media planning. The CEP approach argues that when the impression lands matters as much as how many impressions land. A single impression at the moment the buying situation is active may form a stronger brand-CEP link than ten impressions delivered at random times to the same consumer.

The empirical evidence on this point is still developing, but the theoretical logic is grounded in memory science. Associative memory formation is stronger when the retrieval context matches the encoding context. An ad seen while driving home on a Wednesday evening, depicting a person arriving home and opening a beer, forms a stronger associative link with the "after work" CEP than the same ad seen on a Saturday morning during a different mental context.

Measuring CEP Growth Over Time

CEP measurement is not a one-time diagnostic. It is an ongoing measurement system that should sit alongside market share tracking, brand awareness tracking, and financial performance monitoring.

The recommended measurement cadence depends on category purchase frequency and campaign activity:

• FMCG / high-frequency categories: Quarterly measurement with monthly tracking of top-3 priority CEPs
• Durable goods / low-frequency categories: Semi-annual full measurement with quarterly priority CEP tracking
• B2B categories: Annual full measurement with semi-annual priority tracking

The longitudinal data enables two types of analysis:

CEP link trajectory analysis. For each brand-CEP pair, track the association percentage over time. Are you building the intended links? Are competitor links growing or eroding? A brand investing in "after work" creative should see its "after work" CEP link strengthening over quarters. If it does not, the creative is not working -- either because the execution is poor, the media weight is insufficient, or the distinctive brand assets are not prominent enough.

Mental Market Share trend analysis. Track MMS alongside actual market share. The relationship between the two series provides diagnostic information:

In this illustration, Brand C's MMS begins rising in Q2 2023, a full two quarters before market share starts to follow in Q1 2024. This is the leading indicator pattern. The brand invested in broadening its CEP portfolio, and the mental availability gains showed up in the survey data before they materialized in purchasing behavior.

By Q4 2024, MMS has started to decline while market share is still rising. This is the early warning pattern. Mental availability is eroding -- perhaps because the brand reduced advertising spend, or because competitors are building into the same CEPs. If uncorrected, the market share gain will reverse within 2-4 quarters.

When Differentiation Matters (and When Distinctiveness Is Enough)

The sharpest criticism of Sharp's framework is that it de-emphasizes brand differentiation. Kotler, Keller, and the positioning tradition argue that brands must be meaningfully different to win consumer preference. Sharp and the Ehrenberg-Bass school argue that perceived differentiation is weak, category norms dominate brand perceptions, and brands should focus on being distinctive (easy to identify) rather than differentiated (perceived as unique).

The truth is not a compromise. It is a conditional.

In most mature, frequently purchased categories, distinctiveness matters more than differentiation. The evidence here is strong. In FMCG categories, consumers show low involvement, weak brand preferences, and extensive repertoire buying. They do not conduct careful comparisons. They reach for brands that come to mind and are easy to find. In these categories, mental availability and distinctive assets are the primary growth drivers. Trying to build meaningful differentiation is not impossible, but the returns are modest relative to the cost.

In categories with high involvement, infrequent purchase, and functional risk, differentiation matters more. If you are buying enterprise software, choosing a surgeon, or selecting a financial advisor, you care about meaningful differences between options. The buying process involves comparison, evaluation, and deliberation. Mental availability still matters -- the considered set is still shaped by which brands come to mind -- but the selection within that set is influenced by perceived differentiation.

In categories undergoing disruption, differentiation creates new Category Entry Points. This is the dynamic that the Ehrenberg-Bass framework sometimes underweights. When a brand introduces a genuinely new attribute or benefit that creates a new reason to enter the category, it is not playing the mental availability game within existing CEPs. It is creating a new CEP. Oat milk did not win by building broader associations with existing dairy milk CEPs. It created new CEPs: "I want a plant-based option," "I'm concerned about environmental impact," "I want something that froths well in coffee." These were entry points that did not previously exist, and the brands that created them captured them.

The practical synthesis: measure and manage CEPs for your existing business. Build mental availability by broadening your CEP portfolio and reinforcing it with distinctive brand assets. But do not treat the current set of CEPs as fixed. If you can create a new entry point through genuine product or experience innovation, you can capture mental availability in a space where no competitor exists.

This is where Sharp's descriptive science meets Kotler's prescriptive strategy. Sharp describes how brands grow in established markets with stable category structures. Kotler describes how brands can change the category structure itself. Both are correct. They are talking about different conditions.

Reconciling Sharp with Kotler

The perceived conflict between Byron Sharp and Philip Kotler is, at its core, a conflict between empirical description and normative prescription.

Sharp says: here is what the data shows about how brands actually behave in markets. Kotler says: here is what managers should do to build competitive advantage. Sharp observes that most consumers do not see meaningful differences between brands. Kotler argues that managers should create meaningful differences between brands. Sharp is describing a population of brands, most of which are undifferentiated. Kotler is prescribing a strategy for brands that want to be exceptions.

The reconciliation framework:

1. Mental availability is the foundation. No brand can succeed without being thought of in buying situations. CEP breadth, distinctive assets, and consistent brand-building advertising are non-negotiable, regardless of category or competitive position.

2. Physical availability is the enabler. Distribution, findability, and purchase ease convert mental availability into sales. Investment in both dimensions simultaneously produces multiplicative returns.

3. Differentiation is the accelerator, not the engine. In categories where meaningful differences can be created and perceived, differentiation increases conversion within the considered set. It does not replace mental availability. It augments it.

4. Category creation is the exception that proves both rules. When a brand creates a genuinely new category or CEP, it benefits from both Kotlerian differentiation (it offers something no competitor does) and Sharpian mental availability (it "owns" a new entry point by default). The greatest brand-building successes -- from Red Bull to Tesla to Airbnb -- combined both.

5. The measurement agenda is the same regardless of your theoretical allegiance. Whether you believe differentiation is the primary driver or mental availability is the primary driver, you should be measuring CEP associations, tracking mental market share, evaluating distinctive asset strength, and monitoring physical availability. The data will tell you which mechanisms are operating in your specific category and competitive context.

The marketing profession has a habit of treating intellectual disagreements as binary: you are either a Sharpian or a Kotlerian, a brand-builder or a performance marketer, a differentiation believer or a distinctiveness advocate. This is not how reality works. The empirical evidence from the Ehrenberg-Bass Institute is strong. The logical case for differentiation in high-involvement categories is also strong. The question is not which framework is "right." The question is which mechanisms dominate in your specific category, and CEP measurement gives you the data to answer it.

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Further Reading

• Byron Sharp on Wikipedia — Author of How Brands Grow
• Ehrenberg-Bass Institute — Marketing science research
• How Brands Grow (Book) — The foundational text

References

1. Sharp, B. (2010). How Brands Grow: What Marketers Don't Know. Oxford University Press. The foundational text for the evidence-based marketing movement.

2. Romaniuk, J. & Sharp, B. (2022). How Brands Grow Part 2: Emerging Markets, Services, Durables, New and Luxury Brands. Oxford University Press. Extension of the framework to categories beyond FMCG.

3. Romaniuk, J. (2013). "Modeling mental market share." Journal of Business Research, 66(2), 188-195. The empirical paper establishing the relationship between CEP breadth and market share.

4. Romaniuk, J. & Sharp, B. (2004). "Conceptualizing and measuring brand salience." Marketing Theory, 4(4), 327-342. The theoretical foundation for mental availability measurement.

5. Ehrenberg, A.S.C. (1988). Repeat-Buying: Facts, Theory and Applications. 2nd Edition. Charles Griffin. The original empirical foundation for double jeopardy, duplication of purchase, and buyer moderation laws.

6. Dawes, J. (2008). "Regularities in buyer behaviour and brand performance: The case of Australian beer." Journal of Brand Management, 15(3), 198-208. Replication of double jeopardy patterns in a specific category context.

7. Kotler, P. & Keller, K.L. (2016). Marketing Management. 15th Edition. Pearson. The canonical text for the segmentation-targeting-positioning paradigm.

8. Ries, A. & Trout, J. (1981). Positioning: The Battle for Your Mind. McGraw-Hill. The origin of the positioning concept that Sharp's work challenges.

9. Romaniuk, J., Sharp, B., & Ehrenberg, A. (2007). "Evidence concerning the importance of perceived brand differentiation." Australasian Marketing Journal, 15(2), 42-54. The empirical case that perceived differentiation is weaker than commonly assumed.

10. Stocchi, L., Driesener, C., & Jenkinson, E. (2015). "Brand image and brand loyalty: Do they show the same deviations from a common underlying pattern?" Journal of Consumer Behaviour, 14(5), 317-330. Evidence that image perceptions follow market share patterns consistent with the Dirichlet model.

11. Nelson-Field, K. (2020). The Attention Economy and How Media Works. Palgrave Macmillan. Connecting attention measurement to mental availability formation.

12. Binet, L. & Field, P. (2013). The Long and the Short of It: Balancing Short and Long-Term Marketing Strategies. IPA. Empirical evidence that brand-building (mental availability) and sales activation serve different but complementary functions.