Inside Australia’s loyalty industry: what the ACCC report revealed

28 August 2023
Susan Walsh

In the dynamic landscape of customer engagement, loyalty programs have been undergoing a technological evolution, with cutting-edge innovations reshaping their strategies. It is important to consider top technology trends. As businesses strive to forge deeper connections with their customers, technology emerges as a pivotal catalyst. Artificial Intelligence (AI), Digital Wallets, Predictive Analytics, and Digital Beacons stand out as the top technology trends driving loyalty programs into the future.

From predicting customer behaviour to enhancing engagement through personalised experiences, these trends promise to redefine the way loyalty is fostered and nurtured. Let’s delve into each trend’s transformative power, exploring their potential to revolutionise loyalty programs and empower brands in creating lasting customer relationships.

Artificial Intelligence (AI)

AI-driven trends in loyalty programs offer remarkable benefits. One major benefit is the ability to advance your loyalty program with AI to offer better customer support and better interactions at a more personal level. Other benefits include personalisation, engagement, and efficiency, yet warrant careful consideration of data privacy and potential bias. As AI shapes the loyalty landscape, businesses must balance innovation with ethical and customer-centric practices.

Pros

  • Personalisation: AI enables tailored rewards, creating a more engaging and relevant experience for customers
  • Data-driven insights: AI-driven analytics provide valuable customer behaviour insights, aiding in better decision-making
  • Enhanced engagement: Gamification powered by AI adds fun and competitiveness to loyalty programs, driving participation
  • Efficiency: AI streamlines program operations, making them more cost-effective and efficient
  • Omnichannel integration: AI facilitates seamless experiences across online and offline touchpoints, enhancing consistency

Cons

  • Data privacy concerns: Extensive data usage for personalisation raises privacy issues and regulatory challenges
  • Algorithm bias: AI algorithms might inadvertently introduce bias, affecting reward distribution and inclusivity
  • Customer dependence: Over-reliance on AI might reduce human interaction and personal touch in loyalty programs

Digital Wallets

The continual integration of digital wallets in loyalty programs presents a promising future, which will continue to offer convenience and personalisation. Digital wallets have grown to become one of the top technology trends. However, it also requires addressing security and accessibility challenges.

Pros

  • Convenience: Digital wallets offer a streamlined and convenient way for customers to access and manage their loyalty rewards
  • Accessibility: Users can store loyalty points, discounts, and offers in one place, making it easier to engage with loyalty programs on-the-go
  • Integration: Digital wallets can seamlessly integrate with mobile apps, allowing for a cohesive user experience and real-time updates
  • Personalisation: These wallets enable personalised recommendations and rewards based on user behaviour and preferences
  • Multi-currency and loyalty points: Future digital wallets might support multiple currencies and integrate loyalty points across different brands and programs

Cons

  • Digital Literacy: Not all customers are familiar with digital wallets, potentially excluding some demographics
  • Security Concerns: Storing personal and financial information in digital wallets might raise security concerns
  • Dependency on Technology: Reliance on digital wallets could pose challenges for users in areas with limited internet connectivity
  • Data Privacy: Collecting user data for personalised experiences might raise privacy concerns

Predictive analytics

Predictive analytics is poised to revolutionise loyalty programs, offering insights into customer behaviour and paving the way for personalised experiences. However, businesses must address ethical concerns and balance data-driven approaches with human-centric interactions.

Pros:

  • Personalisation: Predictive analytics enables tailored rewards and recommendations, increasing engagement
  • Customer insights: Access to data-driven insights helps in understanding customer preferences and trends
  • Retaining high-value customers: Identifying high-value customers allows for targeted retention strategies
  • Behaviour reinforcement: Predictive analytics reinforces positive customer behaviour, driving repeat purchases
  • Effective campaigns: Anticipating customer needs enhances the effectiveness of marketing campaigns

Cons:

  • Data privacy: Collecting and analysing customer data raises concerns about privacy and ethical use
  • Algorithm bias: Ensuring fairness and impartiality in predictive models is a challenge
  • Technical complexity: Implementing predictive analytics requires skilled personnel and advanced tools
  • Overdependence on data: Relying solely on analytics might neglect emotional and human aspects of loyalty

Digital Beacons

Digital beacons are emerging as a transformative trend in loyalty programs, offering proximity-based engagement and personalised experiences. However, businesses must navigate privacy concerns and technical challenges to harness their benefits effectively.

Pros:

  • Proximity engagement: Digital beacons enable real-time interactions and offers when customers are in physical proximity to a store, enhancing engagement
  • Personalised offers: Beacon technology allows for tailored promotions based on user behaviour and preferences
  • Customer insights: Data collected from beacons provide valuable insights into customer movement and behaviour, aiding in targeted campaigns
  • Seamless experience: Integrating beacons with mobile apps creates a seamless and convenient user experience
  • Enhanced loyalty: Interactive beacon-driven experiences can strengthen customer loyalty and incentivise repeat visits

Cons:

  • Privacy concerns: Collecting customer location data via beacons might raise privacy and data security concerns
  • Dependency on mobile apps: Effective beacon utilisation often relies on user adoption of mobile apps
  • Technical challenges: Deploying and maintaining beacon infrastructure requires technical expertise
  • Signal interference: Physical barriers or interference might affect beacon signals and accuracy
  • User experience: Overwhelming users with too many notifications can lead to annoyance

Overall

The convergence of cutting-edge technologies such as AI, Digital Wallets, Predictive Analytics, and Digital Beacons are redefining the very essence of customer engagement and brand loyalty. Understanding and utilising these four top technology trends is essential for any loyalty consultant. These trends are not isolated; instead, they intertwine to create a holistic and seamless loyalty experience. AI breathes life into personalisation, digital wallets introduce convenience, predictive analytics empower foresight, and digital beacons bridge the online-offline gap. In essence, these technologies collectively paint a vivid picture of loyalty programs where customers are not merely patrons, but cherished partners in a tech-driven journey towards mutual benefit and satisfaction.

References:

How AI Will Shape the Future of Loyalty Programs

How AI Can Enhance Loyalty Programs

Prediction: The future of customer experience

AI and the Impact on the Loyalty Industry

Digital Wallet Vs Mobile Wallet for Your Loyalty Program

The 10 Most Important Pros and Cons of Loyalty Programs

The Future of Digital Wallets: Multi-Currency, Loyalty Points …

The Beginner’s Guide to Building a Customer Loyalty Program

New loyalty program analytics lead to better strategies

How beacons can help brands improve loyalty programs

Digital Loyalty – Beacons lighting the way to the future

The Beginner’s Guide to Comparing Loyalty Program

ACCC logo

Drawn from the report Loyalty & Reward Co produced for the Australian Competition and Consumer Commission, June 2019.

Almost 80 per cent of Australians belong to at least one loyalty program. That figure, from Mastercard research,1 shows how deeply loyalty programs are woven into Australian consumer life. It does not tell you how much value members actually receive, how the largest programs earn their profits, or what the design choices behind the points mean for competition. Those questions are harder to answer, and until 2019 no one had answered them in public.

In 2019, the Australian Competition and Consumer Commission (ACCC) commissioned Loyalty & Reward Co to produce the first comprehensive, publicly available report on the Australian loyalty industry. The report examined the major programs with more than one million active members, most of them coalition programs, and set out how they are designed, how they are monetised, how they use member data, and what effect they have on competition and on consumers. You can read the full report on the ACCC website. The findings remain a useful reference for anyone designing or operating a program today.

This article summarises what the report found, and what each finding means for program operators.

A market that reaches into almost every industry

Loyalty programs have operated in Australia for several decades and now appear across almost every consumer industry. Estimates of how many programs the average Australian belongs to range from four (Adam Posner, For Love or Money 2018)2 to 6.1 (Mastercard).1 The report concentrated on the four largest coalition programs, Qantas Frequent Flyer, Woolworths Rewards, Velocity Frequent Flyer, and flybuys, because their scale and partner networks give them influence over a large share of Australian spending. A coalition program is one run by a central operator, where a network of partners rewards members with a common currency such as points.

The modern coalition program traces back to 1980, when American Airlines launched AAdvantage, the first frequent flyer program built on a reward currency of miles. Qantas Frequent Flyer followed in 1987 using points. Over the following decades, hotels, banks, supermarkets, and retailers built or joined coalition networks of their own.

Much of the recent history is a contest between two competing partnerships. In 2009, Woolworths partnered with Qantas Frequent Flyer, which grew the supermarket’s member base and gave Qantas a large population of members who rarely flew. Coles took full control of flybuys in 2011 and relaunched it, using cheaper points and supplier-funded bonus offers to compete. When Woolworths relaunched as Woolworths Rewards in October 2015 and replaced Qantas Points with a new currency earned only on selected products, members responded with sustained criticism, and the supermarket reversed much of the change within a year. By 2016, the industry had settled into two camps, Woolworths Rewards with Qantas Frequent Flyer, and flybuys with Velocity.

For operators: a currency change removes something members already value, and members tend to feel that loss more sharply than the gain meant to replace it. The Woolworths experience shows how quickly members react when a redesign reduces perceived value.

The psychology built into program design

The report set out the behavioural research that underpins program design. Several findings are worth knowing.

Operant conditioning (Skinner, 1948)3 holds that behaviour which is reinforced tends to be repeated. Bonus points for a specific action encourage members to repeat it. A related insight is that not all points are equal: the large airline, bank, supermarket, and hotel currencies are desirable enough to change where members choose to shop.

Social identity theory (Tajfel, 1978;4 Bhattacharya and Sen, 2003)5 holds that people fold the brands they identify with into their sense of self. Status tiers apply this directly. A Platinum frequent flyer receives lounge access, priority boarding, and upgrades, and that recognition can build an emotional connection to the airline. Status also raises switching costs, which can keep a member spending even when a competitor charges less for the same product.

The endowed progress effect (Nunes and Drèze, 2006)6 was demonstrated in a car wash study. Members given a card with two of ten stamps already filled redeemed at 34 per cent, against 19 per cent for members given a blank eight-stamp card, even though both groups needed eight stamps. Artificial early progress increased persistence toward the goal.

The goal-gradient effect (Hull, 1934;7 Kivetz, Urminsky, and Zheng, 2006)8 holds that effort increases as a goal comes closer. Members have been observed to accelerate their spending as they approach a status threshold.

Size heuristics describe how one hundred points can feel more rewarding than the one dollar of value it represents. Points let a program present value at a low cost to itself.

Surprise and delight can lift satisfaction well beyond what met expectations achieve. Berman (2005)9 reported that a delighted Mercedes-Benz customer had an 86 per cent likelihood of buying again, against 29 per cent for a merely satisfied one.

For operators: these mechanics work, and that is why they carry a duty of care. Design that manufactures progress or leans heavily on status can drive engagement, and it can also erode trust if members later feel the value was overstated.

How the largest programs earn their profit

A small number of coalition programs are highly profitable. Qantas Loyalty reported revenue of $1,546 million and earnings before interest and tax of $372 million in 2018.10

The report set out the standard coalition model with a worked example. A member spends $1,000 and earns 1,000 points. The program invoices the retailer at around 1.5 cents per point, so the retailer pays $15. When the member later redeems, the program values each point closer to one cent, or $10 for the 1,000 points. The program keeps the difference, roughly $5, a margin of about 33 per cent on that transaction. Across the hundreds of billions of points a large program can sell each year, those half-cents accumulate.

Two further mechanics matter. The first is breakage, the industry term for points that expire unused. Programs set expiry rules, for example 18 months of inactivity for Qantas Frequent Flyer, 24 months for Velocity, and 12 months for flybuys, and higher breakage translates directly into higher profitability. This is why some programs employ actuaries to model it. The second is deferred revenue. A program sets aside enough to cover future redemptions, and a holding of several billion dollars is not unusual for a large Australian coalition program, earning interest in the meantime.

Redemption value also varies by reward. A point redeemed on a flight might be worth one cent, on a gift card half a cent, and on a toaster around 0.25 to 0.35 cents. Pricing steers members toward redemptions that keep cash inside the business.

For operators: breakage and value-steering improve margins, and they sit in tension with member value. A program that optimises breakage too aggressively risks the disengagement that produces breakage in the first place.

The data behind the points

A loyalty program is one of the most effective ways to build a marketing database, because it links transactions to an identified individual over time. The report traced how far that data capability now extends.

Woolworths bought a half-share in analytics firm Quantium in 2013, gaining the ability to turn data from around 8 million loyalty cards into personalised offers. Data exchanges such as Data Republic, backed by Qantas Loyalty, Westpac, NAB, and ANZ, connect a broad network of organisations for secure data sharing. Data brokers can match a single member against tens or hundreds of external datasets, and one broker cited in the report, Rokt, described using billions of user records to personalise offers in real time.

For operators: members increasingly expect transparency and control over their data, a point the report emphasised. A program that collects widely without explaining clearly risks the trust that makes personalisation acceptable in the first place.

The competition question

The report examined whether loyalty programs affect competition, and the evidence points in more than one direction.

Consumer behaviour shows the effect is real. A 2018 Canstar Blue survey found that 21 per cent of shoppers who switched supermarkets did so to earn reward points, and 54 per cent of those who did all their shopping at one supermarket did so because of points.11 International research reaches similar conclusions. Lederman (2003)12 linked frequent flyer enhancements to gains in airline market share, with larger effects at hub airports. Cairns and Galbraith (1990)13 argued that programs raise switching costs and act as a sunk cost that a new entrant must match to compete. McCaughey and Behrens (2011)14 found frequent flyer members in the Netherlands willing to pay a premium of up to 6 per cent. Reichheld (1996)15 found that programs can reduce a member’s sensitivity to competing prices.

The concern is sharpest for smaller companies and new entrants. In a market of dominant duopolies, when the leading players both run large, engaged programs, the competitive tension between them can be neutralised while the barrier facing a new entrant without a comparable program rises. Norway took this seriously enough to ban the earning of points on domestic routes for a period, lifting the ban only in 2013 once domestic competition was judged robust.16

The evidence is not one-sided. Caminal and Claici argued that loyalty pricing can enhance competition by steering business between firms and lowering average transaction prices.17 Aldi, meanwhile, has campaigned directly against points-based programs, arguing that members who chase points routinely spend more, which suggests competitors view those programs as effective.

For operators: a program is a genuine competitive asset, and that same strength invites scrutiny where it raises switching costs or dampens price competition. Designing for real member value, rather than lock-in alone, is the more durable position.

Are members getting what they are promised?

The report closed on the question that matters most to members: the value they actually receive.

Value varies widely. Members of some programs receive as little as half a cent for every dollar spent, while others return 10 per cent or more. Some programs have also reduced value quietly over time. A $100 Barbeques Galore gift card that cost 13,500 points on the Velocity store in 2009 later cost 18,000 points, a 33 per cent increase. A $100 Myer gift card on the Qantas Store rose from 13,500 to 17,770 points, a 31 per cent increase, for a product whose value had not changed. Those increases outpaced the roughly 9.5 per cent inflation over the same five years, and members were not notified.

Some advertising also risks over-promising. The report noted a Qantas credit card campaign using the line “Latte, Latte, Latte, London”. Taken literally, a member would need to buy 20,000 to 40,000 cups of coffee to earn a flight to London, which at one or two cups a day could take up to 55 years. No reasonable consumer would read it literally, and that is the point: broad promotional claims can imply that value is more accessible than it is.

For operators: transparency around expiry, devaluation, and realistic earn rates protects the trust a program depends on. Members forgive a modest return far more readily than a value promise that does not hold up.

What the report means today

Australia’s loyalty industry is sophisticated, profitable, and built on well-understood behavioural science. The ACCC report showed that the same features which make programs effective, the psychology, the data, the coalition scale, and the points economics, are also the features that deserve the most care. A program earns durable loyalty when its design, its data practices, and its promises all hold up to a member reading them closely.

Loyalty & Reward Co produced this report as the loyalty consulting experts, and have since delivered more than 160 loyalty projects for leading brands worldwide. For the full detail, figures, and sources, read the complete report on the ACCC website.

References

Primary source: Shelper, P., Lyons, S., & Savransky, M. (2019). Australian Loyalty Schemes: A Loyalty & Reward Co report for the ACCC. Loyalty & Reward Co. Available at: accc.gov.au

The numbered sources below are cited in the article above. Full footnotes for every industry, media, and program source referenced throughout the report are provided in the ACCC report itself.

  1. Mastercard (2018). Achieving Advocacy and Influence in a Changing Loyalty Landscape.
  2. Posner, A. (2018). For Love or Money 2018, edition 6.
  3. Skinner, B. F. (1948). “Superstition in the pigeon”, Journal of Experimental Psychology, Vol. 38, pp. 168-172.
  4. Tajfel, H., & Turner, J. C. (1978). “An integrative theory of intergroup conflict”, in The Social Psychology of Intergroup Relations, pp. 33-47.
  5. Bhattacharya, C. B., & Sen, S. (2003). “Consumer-company identification: a framework for understanding consumers’ relationships with companies”, Journal of Marketing, Vol. 67, pp. 76-88.
  6. Nunes, J., & Drèze, X. (2006). “The endowed progress effect: how artificial advancement increases effort”, Journal of Consumer Research, Vol. 32, No. 4, pp. 504-512.
  7. Hull, C. L. (1934). “The rat’s speed of locomotion gradient in the approach to food”, Journal of Comparative Psychology, Vol. 17, pp. 393-422.
  8. Kivetz, R., Urminsky, O., & Zheng, Y. (2006). “The goal-gradient hypothesis resurrected: purchase acceleration, illusionary goal progress, and customer retention”, Journal of Marketing Research, Vol. 43, pp. 39-58.
  9. Berman, B. (2005). “How to delight your customers”, California Management Review, Vol. 61, No. 1, pp. 129-151.
  10. Qantas (2018). Qantas Annual Report 2018.
  11. Canstar Blue (2018). Consumer survey on supermarket switching and reward points, as cited in the ACCC report.
  12. Lederman, M. (2003). Do enhancements to loyalty programs affect demand? The impact of international frequent flyer partnerships on domestic airline demand, mimeo, MIT.
  13. Cairns, R., & Galbraith, J. (1990). “Artificial compatibility, barriers to entry, and frequent-flyer programs”, Canadian Journal of Economics, Vol. 23, pp. 807-816.
  14. McCaughey, N., & Behrens, C. (2011). Paying for status? The effect of frequent flyer program member status on airfare choice, Monash University Department of Economics.
  15. Reichheld, F. (1996). The Loyalty Effect: The Hidden Force Behind Growth, Profits and Lasting Value, Harvard Business School Press.
  16. OECD (2014). Airline competition: note by Norway, Directorate for Financial and Enterprise Affairs, Competition Committee.
  17. Caminal, R., & Claici, A. (2007). “Are loyalty-rewarding pricing schemes anti-competitive?”, International Journal of Industrial Organization, Vol. 25, pp. 657-674.
<a href="https://loyaltyrewardco.com/author/susan/" target="_self">Susan Walsh</a>

Susan Walsh

Susan is a Loyalty Director at Loyalty & Reward Co, the leading loyalty consulting firm. Loyalty & Reward Co design, implement, and operate the world’s best loyalty programs for the world’s best brands. Susan has previously worked in product, marketing and business roles at Optus and Virgin Mobile, Catch Connect Mobile, Coles Mobile, Proactiv Skincare and ABC Shops. Susan applies her skills across all aspects of the business, including implementation and operations, loyalty program design, member engagement and digital marketing.

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