QSR brands must market to machines
There is no single source of truth when it comes to knowing your customers.
Australian quick-service restaurant brands now have two customers to win over: the human and the machine deciding on their behalf, as the use of artificial intelligence (AI) has become ingrained across the population.
Nearly eight in 10 Australians use AI, according to a report by Telsyte published in June. Of these, four in five use AI at least monthly.
Speaking to QSR Media, Ross Candido, vice president for Australia and New Zealand at Meltwater, said the arrival of AI assistants as a mainstream discovery tool has created a new and largely unmanaged risk for QSR operators.
QSR Media: What are the most important shifts you are seeing in QSR operations in Australia right now, and what is driving them?
Candido: The biggest shift is from monthly, reactive reporting to continuous, proactive signal detection, and it changes what "understanding your customer" means. A lot of QSR operators today are still stitching together survey platforms, Google reviews, and social listening manually, then producing a monthly business review deck. The problem: on a month-to-month view, you don't actually see much trend; it's very reactive. A static monthly report gives you movement, not research; it's easy to only see what you already expect to see.
We're seeing operators push to flip that model, so a shift in customer sentiment surfaces as it happens rather than in a deck 30 days later. The driver is simple: leadership is asking why the business can't see problems coming before they show up in the numbers.
There's a subtler point underneath the reporting-cadence issue: a static monthly report gives you movement, not research. When you're reading a fixed deck, it's easy to only see what you already expect to see - confirmation, not discovery. The shift underway isn't just "more frequent reporting"; it's a move toward AI-assisted, question-led research, where the questions themselves surface insight you can act on.
A monthly report can help you course-correct after the fact; continuous, or question-led intelligence is what informs strategy at a fraction of the traditional cost and time.
Which costs or risks are increasing fastest for QSR operators this year, and how are the most successful companies responding?
Data shows spending on tools going up, spending on people and agencies going down; as a provider of tools, this sits in our pocket, even though we don’t always agree with it. Our research shows that changing your team structure and enhancing natural language tooling across the team, while still having a small group of analytical specialists who understand business context, is an advantage. Also, ensuring you invest time in training, or human capital, so that usage of tools and how to read outputs can separate competent and advanced users, who are much more focused on business outcomes.
This mitigates other new risks, such as rapid expansion of content and new media types, i.e. LLM recommendations, or the increase in velocity of reputational change. Allowing continued understanding of the often-present perception gap widening unnoticed. The best operators are responding by refusing to trust any single source; they centralise social, LLM recommendations, creators, reviews, transactions, and brand-perception data into one view specifically so a gap between "how we think we're doing" and "how customers actually feel" gets caught early rather than discovered after it's already shaped behaviour.
What does excellence look like in QSR execution today, and what signals indicate a business is performing exceptionally?
Excellence is a journey at breakneck speed. Realising there's no single source of truth about the customer, there's only the ability to cross-reference sources and find where they disagree. That discrepancy, the outlier, is where the actual insight lives. Currently, we’re using around 60% of the data on our own businesses; this drops off when it comes to products, industry and competitors. Data enrichment now has the capacity to make much more data usable, without the need for a degree in data science.
When social sentiment, reviews, and transaction data all agree with each other, that's not insight, that's validation. A concrete example: in one Asian market, customer feedback surfaced a specific flavour complaint on a new product line at the same time as capacity strain at a flagship store opening and unfavourable price comparisons to a local competitor: three distinct signals that only mean something when read together, and that only a 360-degree view could have caught.
What would you advise a QSR brand wanting to grow more in the next three to five years?
Build the 360-degree view of your customer before growth forces your hand, not after. Growth usually means more markets, more franchise partners, and more brand lines, and each one adds another gap between what you assume about your customer and what's true of them locally. Then don’t forget about the new customer, the machine: marketing effectively to humans and agents simultaneously ensures visibility in recommendations, clarity in narrative within LLMs on brands and products, which improves positioning in recommendations.
Looking ahead 12 months, what are your top three predictions for QSR in Australia, and which indicators will tell you if they’re on track?
Brand perception gets checked against real customer signals continuously for both humans and agents. Indicator: the time between a shift in sentiment or spend and a brand noticing it should shrink from months to days.
No single data team "owns" the customer view; social, LLM, transaction, and perception data get read together as standard practice. Indicator: reports that cite only one data source start to look incomplete rather than sufficient.
Leadership within QSR businesses gets more analytically active at testing hypotheses and sharper at spotting when their own data disagrees - reports become research. Indicator: Leadership takes a more data-led and active role in making recommendations directly to the execution layers on markets, promotions and risk. Their context becomes more mobile.
