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

19 Junio 2026
David Schneider

Google announced the biggest change to its search product in more than 25 years at Google I/O in May 2026. The familiar list of ranked links is giving way to AI Search. AI Search will include AI-generated summaries, interactive comparisons built on the fly, and background agents that monitor the web on behalf of consumers.

In a recent blog article, Loyalty Programs in the Age of AI Agentic Commerce, Loyalty & Reward Co CEO Philip Shelper examined how AI agentic commerce is changing what happens when an AI agent executes a purchase, and why loyalty programs need to be ready for that moment. This article examines a different part of the same shift. It explores how consumers decide which brand to commit to in the first place, and how Google’s changes are altering the competitive dynamics at that earlier stage.

What Has Google Actually Changed?

At Google I/O in May 2026, Google described these updates as the most significant change to search since the search box launched over 25 years ago. Four specific changes matter most for loyalty program operators: AI Overviews, AI Mode, Generative UI, and information agents.

  1. AI Overviews are now used by more than 2.5 billion people each month. They synthesise answers from across the web into a single summary positioned above traditional link results.
  2. AI Mode, Google’s conversational search experience, has reached 1 billion monthly users. Consumers can ask follow-up questions without returning to a search box, with Google maintaining context across the conversation.
  3. Generative UI enables Google to build custom interactive comparison experiences in real time. Each response is assembled for that specific query, with no predefined templates.
  4. Information agents are persistent background monitors. Consumers can instruct them to track specific conditions on the web and receive synthesised updates when those conditions change. Both Generative UI and information agents are rolling out free to all Google users in the coming months.

Google’s AI is doing more of the evaluation work consumers previously did by clicking through links and comparing options themselves. The scale of this shift is already measurable with zero-click searches, where a consumer receives an answer without visiting any external website, now accounting for approximately 60 per cent of all Google queries, according to recent analysis. The I/O 2026 announcements are likely to push that figure higher.

Why Does This Matter for Loyalty Programs?

Attracting new members is one of the core functions any well-designed loyalty program must deliver. A program’s ability to do that depends, in part, on being visible and compelling when consumers are deciding which brand to commit to.

Historically, consumers made that decision by clicking through search results, comparing programs across multiple websites, and assessing value propositions directly. Google’s AI does more of that work now. Consumers receive synthesised evaluations rather than a list of sources to check.

A June 2026 survey of 3,000 US and UK consumers by business agency GALE found that 56 per cent are now comfortable with AI filtering their brand communications entirely, and nearly one in three have already used ChatGPT, Gemini, or Copilot to prioritise certain brands over others. GALE estimates that the proportion of consumers who regularly instruct AI to manage their brand preferences could reach 60 to 70 per cent within three years.

In Australia, the timeline is immediate. Australia is the first APAC market to launch Google’s Universal Commerce Protocol, with Loyalty & Reward Co client THE ICONIC among the Australian retailers signed on as one of the first pilot brands. Google reports that 73 per cent of Australians now make faster purchasing decisions using AI Overviews and AI Mode. Connecting to Google’s commerce infrastructure puts a retailer inside the checkout experience. How a program’s loyalty value appears to a consumer who is still deciding where to shop is a question that comes earlier, and one this post addresses.

The challenge here differs from the one Loyalty & Reward Co has written about at the transaction stage. Philip Shelper’s article asked whether AI agents can read and apply loyalty benefits at checkout. This article asks whether Google’s AI gives consumers an accurate picture of a program’s value when they are still deciding which brand to commit to. Both questions matter, and each requires a different response from program operators.

What Does Generative UI Mean for How Programs Are Compared?

When a consumer searches for something like “best supermarket with a loyalty program” or “which airline rewards program gives the best value,” Google no longer returns a ranked list of links. It builds an interactive comparison. That comparison reflects what Google’s AI can extract and evaluate from publicly available information about each program.

Programs with clearly stated earn rates and tier benefits are easier for the AI to represent accurately. Programs whose value is buried in terms and conditions, or described in language that means little to an algorithm, will be underrepresented. In some cases they will not appear at all.

Loyalty & Reward Co’s Essential Eight™ principles include Differentiating as a core requirement for best-practice program design. In the context of Generative UI comparisons, differentiation carries additional weight. A program that looks identical to its competitors in an AI-generated comparison gives the consumer no reason to choose it. A program with genuine differentiation that is poorly described publicly will not receive credit for it.

The most defensible loyalty programs include benefits that are harder to copy or reduce to a price comparison. Benefits such as priority access, exclusive event access, experiential rewards, status recognition, and well-constructed earn-and-burn partnerships. These are also the hardest for an AI comparison to flatten into a single line.

How Do Information Agents Change the Competitive Pressure on Programs?

Google’s information agents create a new set of problems for programs that already have members. Consumers can instruct an agent to monitor specific conditions and receive alerts when those conditions are met. A member could set an agent to flag when their points are approaching expiry, or when a competitor launches a promotion they have not seen before.

A member’s agent could alert them to expiring points before the program has sent its own reminder. If the agent gets there first, the program has lost a re-engagement moment it should have owned. An agent tracking bonus earn events across multiple programs will surface whichever is offering the best opportunity at any given time. A program with an infrequent or poorly timed promotions calendar is exposed in that comparison in ways it was not before.

An agent could also surface a competitor’s welcome offer at the moment a member is showing signs of reduced engagement. The agent does not need to make an active recommendation. Surfacing the information is enough.

What Should Loyalty Program Operators Do?

The response to Google’s Search changes does not require a program redesign. It requires an honest assessment of how the program presents itself publicly and whether its value reads clearly in AI-generated comparisons. As loyalty consultants we see five areas that are worth prioritising.

Search your own program in AI Mode

Use Google’s AI Mode to search for your program and your closest competitors. Look at what the AI says about earn rates, tier benefits, and redemption options. Is the description accurate? Is it compelling relative to what competitors receive? If the AI is misrepresenting your program’s value, the fix is almost certainly on your own web properties rather than a conversation with Google.

Review how your program’s value is described publicly

AI systems extract and synthesise information from the pages that exist. If a program’s most attractive benefits are described inconsistently across the website, buried in PDF terms and conditions, or written in language that is difficult to parse algorithmically, that is worth addressing. Clear, consistently stated benefit descriptions across all public touchpoints will improve how the program reads in AI-generated comparisons.

Participate in Google’s Direct Offers for loyalty benefits

Google launched Direct Offers in January 2026 and has confirmed it will expand the format beyond price discounts to include loyalty benefits and product bundles directly inside AI Mode. This gives program operators a direct way to make loyalty value visible at the exact moment a consumer is choosing which brand to buy from. Operators should assess eligibility and test this channel as it becomes more widely available.

Audit your member communication timing

If a member’s information agent alerts them to expiring points before the program’s own communications do, the re-engagement strategy has a timing problem. Real-time or near-real-time member data access is the foundation for a communication approach that stays ahead of what an agent can surface. Programs that communicate after the moment has passed will find that agents have already done the work.

Invest in benefits that resist commoditisation

Experiential benefits and status recognition are harder to flatten into a comparison table than earn rates alone. AI comparisons tend to reduce undifferentiated programs to interchangeable options. Programs with something genuinely difficult to replicate are easier for Google’s AI to represent clearly, and more likely to earn a consumer’s commitment.

How Loyalty & Reward Co Can Help

Loyalty & Reward Co works with brands globally to design and evolve best-practice loyalty programs. If you want to assess how your program is positioned for the changes underway in AI search and commerce or you are thinking about designing a loyalty program fit for the AI era, get in touch with our team.

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.

Referencias

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/david-schneiderrewardco-com-au/" target="_self">David Schneider</a>

David Schneider

David is a Loyalty Director at Loyalty & Reward Co, the leading pure-play loyalty consulting firm. Loyalty & Reward Co design, implement, and evolve award-winning loyalty programs for global brands. David has worked in global advertising and media roles for over seventeen years with a focus on CX. He has delivered award-winning work for brands such as BMW of North America, Toyota Motor Corporation Australia, Anytime Fitness, Suncorp and GSK. David applies his skills across all aspects of the business, including loyalty program design, strategy development, customer experience, lifecycle management and the effective collection and use of data.

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