Loyalty programs have become a cornerstone of modern marketing strategy, with businesses across every sector investing heavily in their design, operation, and evolution. The global question that sits behind this investment is deceptively simple; do loyalty programs actually work?

After decades of academic research, two comprehensive meta-analyses, and an expanding body of large-scale industry surveys, the evidence can finally be stated with reasonable confidence; loyalty programs do work, but conditionally. Their effectiveness depends substantially on program design, industry context, competitive dynamics, and how ‘effectiveness’ is measured.

This review conducted by Loyalty & Reward Co consultants synthesises the most robust scientific evidence available, from foundational academic studies through to current market research, to provide a rigorous answer.

Methodologies Used to Study Loyalty Program Effectiveness

Understanding what the research says requires understanding how that research was conducted. The study of loyalty programs has employed increasingly sophisticated methods, and the quality of evidence varies significantly across approaches.

Experimental and Field Studies

The strongest causal evidence comes from field experiments that compare matched customer groups across program conditions. Kivetz, Urminsky and Zheng (2006) conducted a landmark field study tracking 948 real members of a coffee shop loyalty card program, observing actual purchase behaviour rather than stated intentions [1]. This design allows researchers to attribute observed behavioural change directly to the program rather than to pre-existing loyalty.

Before-and-after experimental designs provide another controlled approach. Taylor and Neslin (2005) used this method to examine a turkey reward frequency program at a US supermarket chain, comparing storewide sales across pre-program, program, and post-program periods with a matched control group [2]. This study yielded some of the most precise effect size estimates in the literature.

Longitudinal and Panel Studies

Longitudinal studies track member behaviour over extended periods. Liu (2007) monitored customers of a convenience store franchise over time after enrolment, distinguishing behavioural change by pre-program spending level [3]. Meyer-Waarden (2008) analysed three years of retail panel data, comparing member and non-member spending trajectories across multiple basket and frequency metrics [4]. These studies are essential for understanding whether early effects persist.

Leenheer et al. (2007) tracked Dutch households across seven grocery loyalty programs, enabling comparison of share-of-wallet effects across different program structures and competitive contexts [5]. Large panel studies of this kind allow researchers to identify moderating variables that determine when programs work and when they do not.

Large-Scale Firm-Level Analysis

Chaudhuri, Voorhees and Beck (2019) examined the financial performance of 322 publicly traded firms that introduced loyalty programs between 2000 and 2015, linking program introduction to changes in sales and gross profits using publicly reported financial data [6]. Kim, Steinhoff and Palmatier (2021) synthesised findings from 129 empirical loyalty program papers across 37 journals into a comprehensive conceptual model, mapping program mechanisms to customer relationship stages [7].

Meta-Analyses: The Highest Level of Evidence

The most significant methodological advance in loyalty program research is the arrival of formal meta-analyses, which aggregate findings across many studies to produce pooled effect estimates. Belli et al. (2022) published the first comprehensive meta-analysis of loyalty program effectiveness, drawing on 429 effect sizes from studies published between 1990 and 2020 [8]. Liu-Thompkins, Khoshghadam, Attar Shoushtari and Zal (2022) followed with a meta-analysis of 1,908 effect sizes drawn from 319 studies of retailer loyalty across 50 years, finding that affective (emotional) drivers of loyalty are 50% stronger than cognitive drivers and 24% stronger than social drivers [9]. These two studies represent the gold standard in the field and anchor the findings reported in this review.

Econometric and Marketing Mix Modelling

Econometric approaches use statistical modelling to isolate the contribution of loyalty programs from other marketing inputs. Marketing mix modelling applies aggregated data to identify the incremental sales attributable to the program, and has gained renewed importance as third-party tracking capabilities have declined. Game-theoretic models have been used to examine competitive dynamics, including the implications of reward expiry and program arms races between competing firms [10].

The Evidence That Loyalty Programs Work

Meta-Analytic Confirmation

The clearest statement of the evidence comes from Belli et al. (2021), whose meta-analysis of 40 years of research concluded that loyalty programs do enhance customer loyalty across a broad range of contexts [8]. This represents the strongest available evidence, drawing on a body of individual studies that no single practitioner or researcher could otherwise evaluate in aggregate. A second meta-analysis by Liu-Thompkins et al. (2022) found that affective (emotional) factors are stronger predictors of retailer loyalty than cognitive factors such as price or convenience, and that social factors are also significant [9]. Taken together, these two analyses confirm the underlying effectiveness of well-designed programs while clarifying the psychological mechanisms that drive their impact.

Share of Wallet and Purchase Behaviour

Multiple independent studies confirm that loyalty program membership produces measurable increases in share of wallet and purchase frequency, particularly among customers with the most room to grow their behaviour.

Leenheer et al. (2007) found a small, positive, and statistically significant effect of loyalty program membership on share of wallet across seven Dutch grocery programs, and described creating membership as “a crucial step” to enhancing wallet allocation [5]. Meyer-Waarden (2008) found that members exhibited significantly higher total basket values, purchase frequency, average basket sizes, share of category purchases, and shorter inter-purchase intervals than non-members across a three-year retail study [4]. Wirtz, Mattila and Oo Lwin (2007) found that more attractive credit card reward programs drove higher perceived rewards and greater share of wallet in a financial services context [11].

Liu’s (2007) longitudinal study produced one of the most practically important findings in the literature. The program studied had no measurable effect on the behaviour of heavy buyers, who were already loyal, but produced sustained behavioural improvement among light and moderate buyers, who gradually purchased more, increased their frequency, and expanded their relationship into other business areas [3]. This finding fundamentally shapes how loyalty program ROI should be optimised; incremental value flows from the members with the most potential to change, not from the already-loyal segment claiming the most rewards.

Revenue and Profit Effects

Taylor and Neslin (2005) were the first researchers to formally separate two distinct sales mechanisms in loyalty programs [2]. The first is the “points pressure” effect: during the program period, members increase spending to reach reward thresholds. In their supermarket study, this produced a 6% storewide sales lift during the eight-week program. The second is the “rewarded behaviour” effect: in the four weeks after redemption, redeemers increased weekly spending by 17.5% above baseline. The program generated an estimated return on investment of approximately 400%, though only around 20% of customers redeemed, meaning the aggregate impact depends heavily on driving redemption rates.

Chaudhuri, Voorhees and Beck (2019) found that the introduction of loyalty programs by 322 publicly traded firms increased both sales and gross profits within the first year, with sustained effects over the following years [6]. Gross profit effects lagged sales, becoming statistically significant only in the second quarter after launch. This suggests that patience and investment discipline are required, as programs do not typically deliver full financial returns immediately.

Reduced Price Sensitivity

One of the commercially significant effects of loyalty programs is their ability to reduce members’ sensitivity to competitive pricing. McCaughey and Behrens (2011) quantified this effect directly by identifying that frequent flyer program members in the Netherlands were willing to pay a price premium of up to 6% rather than switch carriers, an effect directly attributable to FFP participation [12]. Reichheld (1996) identified the broader mechanism that programs decrease members’ sensitivity to competing offers by increasing frequency, familiarity, and the psychological switching cost of moving to a competitor [13].

Competitive Advantages and Switching Costs

Loyalty programs create a multi-layered architecture of switching costs that defend members against competitive acquisition. The most direct evidence comes from the Norwegian government’s decision to ban domestic frequent flyer program earning in the 1990s, specifically because SAS EuroBonus was so effective at creating switching costs that it impeded competition. A new entrant, Colour Air, failed within 13 months of launch in 1998, partly attributed to its inability to offer a competitive FFP. The ban was eventually lifted in 2013 after sufficient competitive balance was established [14]. This is among the strongest real-world evidence for program effectiveness: a government intervened because the program worked too well.

Cairns and Galbraith (1990) identified the mechanism that elite tier status generates social identity-based switching costs, distinct from and potentially larger than the financial cost of forfeiting accumulated points. The prospect of losing status, recognition, and the psychological identity associated with tier membership creates powerful retention forces [15].

Bendapudi and Berry (1997) demonstrated that loyalty programs increase customers’ perceptions of switching costs more broadly, reducing churn across categories [16]. Melnyk and Bijmolt (2015) found, in the first empirical study of loyalty program termination effects, that non-monetary program elements (member-only events, recognition, exclusive services) both enhanced loyalty at introduction and sustained that effect at termination, outperforming monetary savings, which had no significant loyalty effect at either point [17].

Consumer Perception Evidence

Large-scale consumer surveys consistently confirm positive program attitudes. Nielsen’s 2016 global retail survey found that 72% of consumers would prefer to buy from a retailer with a loyalty program over one without (all else equal), and 67% reported shopping more frequently and spending more at retailers with programs [18].

Among recent market research, the Antavo Global Customer Loyalty Report 2026 surveyed 10,000 consumers and 3,000 loyalty professionals across 16 countries, and found that 92.7% of program owners who measure return on investment reported a positive return, with an average ROI of 5.3X, the third consecutive year of growth [19]. The EY 2025 Loyalty Market Study found that 41% of consumers cited the existence of a loyalty rewards program as the primary reason they remain loyal to a brand, ranking above product quality (33%) and customer service (8%) [20].

The Evidence That Loyalty Programs Do Not Always Work

Our review also focused on the substantial body of evidence that contradicts simple optimism. Programs do not work under all conditions, and several well-documented failure modes are established in the literature.

Competitive Neutralisation

Meyer-Waarden and Benavent (2006) analysed competitive dynamics in French grocery markets and found that when all competitors operate loyalty programs, the individual programs neutralise each other’s effects. Market share and switching behaviour are largely unchanged compared to a no-program baseline [21]. This is the loyalty program arms race, where each program is strategically necessary to match competitors but no longer strategically advantageous because the field has levelled.

The BCG Global Loyalty Survey (2024) provides contemporary market data consistent with this dynamic. Across 10,000+ consumers in nine countries, US consumer loyalty had declined 20% and engagement had declined 10% since 2022, a period of accelerating program proliferation [22]. As consumers accumulate an average of 15+ program memberships, the ability of any individual program to differentiate and drive exclusive behaviour has materially declined.

Bombaij and Dekimpe (2020) provided the most rigorous empirical test of competitive neutralisation, examining 358 grocery banners across 27 European countries. They found that basic programs with direct, immediate rewards had a positive effect on sales productivity, but this effect disappeared entirely in markets where 75% or more of competitors also operated programs [23]. Competitive loyalty program penetration was the strongest country-level moderator, outweighing program design factors.

Low Engagement and Dormancy

The gap between loyalty program membership and active engagement is persistent. Ferguson and Hlavinka’s (2007) analysis of the US loyalty market found that despite 1.3 billion loyalty memberships (approximately 12 per household), active participation rates were only 39.5%. They characterised this as dismal, noting that “fat membership rolls may look good in a press release, but active loyalty program members are the only members who count” [24].

The Antavo 2026 data reveals a more granular picture of the engagement problem: 74% of members “quietly quit” their programs within the first two months, and only 3.4% formally opt out. The silent majority simply stop engaging [19]. The Bond Brand Loyalty Report 2025, drawing on 22,000+ US consumer responses, found that while average memberships per consumer stand at 17.4, only 8.8 are active, a decline from the prior year [25].

Short-Lived Launch Effects

Lin and Bowman (2022) analysed the category-level sales impact of loyalty program introductions across multiple retail contexts [26]. They found that program launches produced immediate spikes in sales and category expenditure, but that these effects were generally short-lived, dissipating within approximately six months as the market normalised. The initial redistribution of category spend that follows a program launch does not automatically convert into sustained behavioural change.

Programs Can Backfire

Baker and Legendre (2021) documented an important and previously underexplored risk; loyalty programs can actively drive defection when members perceive that competitors are offering better endowed benefits to new joiners [27]. This “earned versus endowed” comparison triggers a fairness violation that can override accumulated loyalty, making competitive endowment strategies a potential liability for incumbents.

Nishio and Hoshino (2024) found, in a study of 210,657 MUJI loyalty program members in Japan, that birthday rewards, despite their widespread use as personalised gestures, had no positive effect on customer lifetime value [28]. Customers who received birthday incentives had a materially lower average CLV ($72) than the control group ($125), suggesting that birthday promotions disproportionately attract impulsive buyers rather than high-value customers.

The Loyalty Program Paradox

Wallström et al. (2024) identified a deeper structural tension through qualitative research with Swedish retailers, drawing on social resource theory [29]. Programs designed primarily around concrete monetary rewards (points, discounts, cashback) train customers to respond with correspondingly transactional behaviour. This identifies a paradox, whereby the reward system intended to create loyalty may undermine it by framing the entire customer relationship as an economic exchange. The customers who engage most with monetary mechanics are often the least emotionally attached to the brand.

Short-Term Versus Long-Term Effects

The evidence consistently shows that loyalty programs produce different effects across different time horizons. The Taylor and Neslin (2005) framework of “points pressure” (during program) and “rewarded behaviour” (post-redemption) provides the clearest mechanical decomposition [2]. Both effects are real but operate through different psychological pathways and apply to different customer segments. Points pressure operates through goal gradient motivation, while rewarded behaviour operates through positive conditioning and reciprocity.

Kim, Steinhoff and Palmatier (2021) proposed the most theoretically complete account of time-varying program effects, mapping the psychological mechanisms relevant to four distinct customer relationship stages; acquisition, onboarding, expansion, and retention [7]. Their synthesis of 129 studies concluded that most apparent contradictions in the loyalty program literature can be resolved by recognising that different findings apply to different relationship stages. A program element that works during onboarding (immediate, tangible rewards that reduce perceived risk) may actively harm retention (where relational and status-based mechanisms should dominate). Stage-matched program design is an important emerging frontier of loyalty programs that requires additional focus.

Industry-Specific Findings

Retail

The retail sector has generated the most extensive loyalty program research. The broad finding from Bombaij and Dekimpe (2020) across 358 grocery banners in 27 countries is that basic programs with direct, immediate rewards have a positive and significant effect on sales productivity, but complex progressive reward structures and multivendor designs neutralise this effect [23]. Simplicity and directness are empirically validated design principles for grocery loyalty.

Melnyk and Bijmolt (2015) found that the severity of customer backlash when a retailer terminates its loyalty program is primarily determined by the competitive context: in industries where most competitors operate programs, termination produces significantly negative customer reactions [17]. This confirms that in high-penetration categories, loyalty programs have transitioned from strategic differentiator to competitive necessity.

The ALA/Power Retail 2024 study of Australian retail found that 62% of consumers held at least one retail loyalty membership, with FMCG reaching 93% penetration, and that 69% of consumers reported having brand preferences that loyalty programs could influence [30].

Travel and Hospitality

Travel loyalty programs are among the most commercially significant in existence. Lederman (2007) demonstrated significant effects of frequent flyer programs on airline market share in the US, with enhancements to earn and redemption opportunities directly associated with increased market share and with stronger effects at hub airports where program reach is greatest [31].

Mattila (2006) examined hotel loyalty programs directly and found that points accumulation alone did not predict loyalty (β = -0.304, not significant), while value-added benefits and affective commitment strongly predicted it (β = 0.847, p < .05) [32]. This challenges the assumption that accumulation mechanics drive hotel loyalty. The perceived switching costs in hotel programs were also measured as relatively low (3.67 out of 7), suggesting less durable retention than airline programs.

The BCG (2024) data shows that hotel and airline programs are among the least likely to drive exclusive brand loyalty, despite their historical prominence as loyalty pioneers. This may reflect the growing tension between the commercial value extraction airlines and hotels have pursued through program devaluation and the customer trust this erodes [22].

Servicios financieros

Fourie, Goldman and McCall (2023) found, in a study specifically focused on financial services loyalty programs, that social and exploration benefits were substantially stronger loyalty determinants than monetary and entertainment benefits, and that recognition had no significant effect [33]. This directly challenges the assumption that financial services customers are primarily motivated by financial rewards.

Current State of the Market: Key Data Points

Recent large-scale industry research provides the most current benchmarks for program performance:

Antavo (2026), across 3,000 professionals, 10,000 consumers, and 500 million platform interactions: 92.7% of program owners who measure ROI report a positive return; the average reported ROI is 5.3X. Satisfaction among program owners reached 83% in 2026, up from 50.6% in 2022. Despite this, 74% of members disengage silently within the first two months [19].

Bond Brand Loyalty (2025), across 22,000+ US consumers: 85% of members say programs make them more likely to continue doing business with the brand; 74% modify their spending to maximise program benefits. However, only 33% strongly agree that programs offer “good value for money”, and average active memberships per consumer declined year-on-year. For the first time in a decade, access to exclusive experiences and products has overtaken financial rewards as the primary driver of loyalty [25].

BCG (2024), across 10,000+ consumers in nine countries: US consumer loyalty declined 20% and engagement declined 10% between 2022 and 2024 as program proliferation intensified. Paid memberships (credit cards, streaming) now generate the strongest loyalty; hotel and airline programs, despite their historical prominence, are among the weakest [22].

EY (2025), across 1,600+ consumers and 350+ loyalty professionals in the US: 92% of consumers are enrolled in at least one program. Loyalty programs are the single most cited reason consumers remain loyal to a brand (41%). Only 28% feel very or extremely connected to their programs [20].

Deloitte (2024), across 9,800+ consumers in the US, UK, India, and Brazil: 73% of consumers say personalisation is important, but only 60% are satisfied with current personalisation. 70% of surveyed consumers already participate in at least one paid loyalty program [42].

The Conditions Under Which Programs Work

Synthesising the academic and market evidence, the question “do loyalty programs work?” is best answered with a set of conditions rather than a binary response.

Programs are most likely to work when they are designed to create both behavioural and attitudinal loyalty, not just the former. Belli et al. (2021) found that behavioural loyalty was more consistently stimulated than attitudinal loyalty across their meta-analysis, and Day (1969) established that behavioural loyalty without emotional attachment is fragile [8, 36]. Programs that invest in emotional engagement, community, recognition, and non-monetary value alongside earn mechanics are better positioned to deliver durable retention.

Programs create their greatest incremental value among light and moderate buyers (Liu, 2007) [3]. Designs that concentrate investment on heavy buyers, who are already loyal and whose behaviour the program does not materially change, misallocate resources and inflate redemption costs without generating incremental revenue.

Competitive context shapes program effectiveness more than any design variable in markets with high program penetration. Bombaij and Dekimpe (2020) found that competitive LP penetration rate was the strongest country-level moderator of program effectiveness, more powerful than program design choices [23]. In highly competitive markets, program quality rather than program existence is the differentiator.

Non-monetary program elements consistently outperform monetary ones for generating genuine loyalty. Melnyk and Bijmolt (2015) found that monetary savings had no significant effect on loyalty at program introduction or termination, while non-monetary elements (recognition, member-only access, events) both built and sustained loyalty [17]. Liu-Thompkins’ (2022) meta-analysis confirmed affective factors as the dominant loyalty driver [9]. The Bond (2025) finding that access has overtaken financial rewards as the primary loyalty driver reflects this academic finding in current market behaviour [25].

Stage-matched design is the emerging frontier. Kim, Steinhoff and Palmatier (2021) established that the same program element can help at one relationship stage and harm at another [7]. Programs need different psychological emphasis at acquisition, onboarding, expansion, and retention.

Conclusión

The scientific evidence on whether loyalty programs work is, after decades of research and two comprehensive meta-analyses, sufficiently clear to support a robust answer. Loyalty programs do work, effectively and commercially, when they are designed with competence, executed with discipline, and measured with rigour. The meta-analytic evidence of Belli et al. (2021) and Liu-Thompkins et al. (2022) confirms this at the highest level of research evidence available [8, 9].

The conditions matter enormously. Programs that rely solely on monetary earn mechanics, fail to invest in emotional engagement, operate in markets saturated with competing programs, and concentrate reward expenditure on already-loyal heavy buyers are unlikely to deliver meaningful commercial returns. The academic and market research is now sufficiently mature to specify not just whether programs work, but precisely under which conditions and through which mechanisms they do so.

For businesses seeking to invest in loyalty or assess an existing program, the evidence points consistently to:

• create both behavioural and emotional loyalty, not just repeat purchase
• invest disproportionately in moving light and moderate buyers rather than rewarding existing heavy buyers
• differentiate through non-monetary value, access, and recognition
• design for the relevant customer relationship stage
• measure with sufficient rigour to distinguish genuine behavioural change from pre-existing loyalty in your member base.

Loyalty programs, designed and operated using evidence-based principles, represent one of the most comprehensively researched and validated tools available for building durable customer relationships and sustainable commercial growth.

Read case study examples of loyalty programs that have been proven to work.

To access further guidance on desiging a best practice loyalty program underpined by proven scientific principles, engage Loyalty & Reward Co

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