About Us
Scale is a strategic research consultancy that helps businesses make smarter marketing, product, and growth decisions through high-quality insights.
1,500+ projects and counting
Our researchers have delivered more than 1,500 projects to date. That experience shapes everything we do: from how we scope a study, to how we frame the insights, to how we translate findings into decisions you can act on.
Senior researchers on every project
Most agencies put juniors on the work and senior names on the proposal. We don't. Every project is led by an experienced researcher with a minimum of 15 years' experience, which is why we can deliver agency-quality research at a fraction of typical agency rates.
Client-side perspective
We've all sat in the client seat. We know what a useful report looks like: one that gets opened, referenced, and used to make insights led decisions.
Behavioural frameworks
Our expertise in behavioural economics has helped drive measurable behaviour change for our clients, with ~120 behavioural economics-led research projects delivered to date. Whether it's reshaping communications, redesigning user journeys, or rethinking pricing, we apply the principles that actually change how people decide.
Series A to Fortune 500
We've partnered with companies at every stage of the scale-up journey, from Series A Startups validating their first hypothesis to Fortune 500 brands optimising mature portfolios.
Holistic research capabilities
We offer a full spectrum of research services: Quantitative, Qualitative, CX, UX/Design, Employee Experience, Data Science & Analytics, and AI-led research. Whatever the question, we have the method to answer it.
Global reach, local nuance
We've conducted market research in 25+ countries and have the ability to survey audiences across 80+ countries worldwide. Operating at this scale means we understand both how to design research that travels and how to read the cultural cues that don't.
Our Work
Cracking the Code on Crypto (Pricing study)
The Challenge
A US crypto tax software platform was preparing to scale and needed to answer a deceptively complex question: not just what to charge, but how to structure an entire subscription architecture - across tiers, features, and transaction limits. This was challenging since it’s user base had wildly different levels of experience, confidence, and willingness to pay. With over two million possible pricing combinations to evaluate, gut instinct wasn't going to cut it.
The Approach
We fielded a 15-minute quantitative survey with 1,500 active US crypto traders. The study was purpose-built to do several things simultaneously: map the total addressable market (millions with crypto tax filing needs), diagnose the barriers keeping free-tool users from converting to paid platforms, benchmark brand awareness and loyalty across nine competing platforms, and profile the user base by experience, behaviour, and demographics. The centrepiece of the study was a Discrete Choice Experiment, ie. a conjoint-style pricing simulation capable of modelling over two million tier configurations which quantified the precise impact of every pricing and feature variable on preference share. We followed this with a latent class segmentation, classifying all traders into four distinct acquisition segments prioritised by revenue potential and conversion likelihood.
The Impact
The work gave the client a fully pressure-tested pricing architecture grounded in stated preference data, not assumption. Price accounted for a third of the total subscription decision - much higher than the weight of transaction limits, and that of other support or tax features. Adding an additional entry tier was shown to lift overall brand preference by 6% relative to the current tier, functioning as an acquisition lever into higher tiers rather than a revenue concession. The mid-tier was found to be largely price-inelastic up to a higher fee, and the top tier gained most from swapping transaction caps for unlimited access. Layered across four user segments, the findings translated directly into a differentiated feature and channel strategy for each, with state-level geographic hotspots and media touchpoints mapped for launch prioritisation.
Bringing Groceries Online (GTM Launch research)
The Challenge
A major international discount grocery retailer was preparing to launch home delivery - a significant departure from its in-store-only model. Before launch, the client needed to understand the size of the opportunity, who would actually convert, what they'd pay for delivery, which product categories would travel online and which wouldn't, and what barriers stood between curiosity and a completed order.
The Approach
We ran a mixed-method study combining in-depth Qualitative interviews with current Aldi, Coles Online, and Woolworths Online shoppers, followed by a nationally representative quantitative survey of 1,200 plus grocery shoppers across Sydney, Melbourne, Brisbane, Adelaide, and Perth. The qual sessions, including pantry and fridge audits gave us texture on shopping rituals, hero products, and the emotional role the in-store experience plays. The Quant study mapped the total market opportunity, profiled the most likely online converts, benchmarked brand perceptions against competitors, tested willingness to pay across five delivery speed tiers, modelled minimum spend thresholds for free delivery, and identified the category-by-category appetite for ordering online versus buying in-store.
The Impact
The work put a number on the opportunity: X million Australian households were identified as the immediate conversion target. Seven in ten existing in-store shoppers expressed openness to the new service, and more than half of Coles Online and Woolworths Online shoppers said they'd definitely use it; signalling genuine share-of-wallet opportunity beyond the existing base. The research produced a fully costed delivery pricing architecture across three tiers (express, same-day, scheduled), a minimum spend recommendation for free delivery, and a priority category launch sequence. Each of the four primary adoption barriers was matched with a specific intervention playbook, from first-order free delivery mechanics to substitution control features and in-app freshness guarantees.
Future Market Mapping for Acquisition (Segmentation)
The Challenge
A major online food delivery platform operating in a two-player market needed more than brand tracking - it needed to understand who its highest-value potential customers were, why they weren't switching, and what would make them. With the competitor food delivery service commanding stronger loyalty and higher consideration conversion, the client needed a segmentation framework it could actually act on: one that could feed directly into FY26–27 product, marketing, and partnership planning.
The Approach
We ran a mixed-method study combining In-depth interviews across five distinct user cohorts (ie. loyalists, lapsed users, light multi-app users, recent switchers, and heavy competitor users), with a nationally representative quantitative survey of 1,500 Australians aged 18-65. The segmentation model was built using a latent class approach across four dimensions: order frequency, average order value, willingness to consider the platform, and attitudinal motivators spanning functional, emotional, and social drivers. A MaxDiff exercise across 28 switching triggers identified the precise levers most likely to shift behaviour by segment. The qual component included full customer journey mapping — from trigger through to post-meal rewards and customer support, capturing the emotional texture of ordering decisions that quantitative data alone couldn't surface.
The Impact
Five actionable segments emerged from a market worth an estimated $X billion annually. Young families ordering weekly represented X% of category spend despite being just X% of users, making them the highest-priority acquisition target. Segment 2 showed strong openness to switching based on variety and discovery. Together, the top two segments accounted for two-thirds of total market value and became the centrepiece of the FY26–27 growth strategy. Each segment was delivered with a full profile, switching trigger hierarchy, media channel map, and specific product and comms interventions. The customer journey mapping gave the client a scene-by-scene brief for improving the experience at the moments that matter most (ie. browse and search, the wait, the handoff, and the post-meal rewards gap) that consistently left loyal customers feeling undervalued.
Market Sizing for Specialist AI Infrastructure
The Challenge
A specialist GPU and AI infrastructure provider with owned renewable energy assets needed to understand its commercial opportunity in the US market with precision. As hyperscalers continued to dominate buyer awareness by default, the client needed research-derived answers to three questions that mattered to both its go-to-market team and its investors: how large is the addressable opportunity, which buyer segments are genuinely penetrable, and what would it take to convert them?
The Approach
We ran a two-phase mixed-method study combining In-depth interviews with senior infrastructure decision-makers spanning AI/HPC-intensive organisations, data centres, frontier model builders, and enterprise buyers — with a quantitative survey with US-based decision-makers holding direct budget authority over GPU infrastructure. The quant study was structured to model the market from first principles: GPU spend by organisation type, externalization rates, multi-provider openness, sustainability premium tolerance, and stated consideration for the client. A four-dimension decision framework was derived from factor analysis, each contributing to provider choice across buyer cohorts. A needs-based segmentation was then built from these dimensions and validated against firmographic, behavioural, and growth variables, producing four named segments with full pen portraits, switching barrier profiles, and GTM prioritisation.
The Impact
The study established the US AI compute TAM, with a $X billion serviceable obtainable market along with forecasts within 12 months as GPU capacity expansion plans accelerated. Four segments emerged from the segmentation, along with key differentiators that fed directly into the 2026 investor narrative, GTM planning and multiple PR, Press whitepapers and content being shared across Social and Conferences.
Finding the Right Product (Concept Testing)
The Challenge
A UK fintech entering the buy-to-let lending market needed to validate its market opportunity before launch. With multiple distinct product concepts in development and a target audience of BTL mortgage landlords, a segment with strong existing lender relationships and acute sensitivity to rates - the client needed to know which concept would land, at what price, and with whom.
The Approach
We designed and fielded a 12-minute quantitative survey with UK BTL landlords across England and Wales, structured across seven sections: screening and market sizing, portfolio profiling, target market identification, sequential monadic concept testing across all four products, price sensitivity modelling across 17 pricing scenarios, overall preference ranking, and demographics. Each respondent was exposed to select concepts in randomised order, allowing both within- and between-concept comparison. Price sensitivity was tested using tiered APR and appreciation share scenarios, with take-up tracked against thresholds to identify elasticity breakpoints. A four-segment K-means cluster analysis was then run across behavioural and firmographic variables to produce a prioritised acquisition hierarchy.
The Impact
The study identified an immediate market opportunity of BTL mortgage landlords actively seeking short-term financing, representing a potential market value of £X billion. It also sized how many landlords expressed intent to seek a short-term loan or cash advance, with details of demand concentrated for the financing. Of the four concepts tested, 1 winning Concept emerged as the clear winner on differentiation and overall preference, achieving a high adoption rate, at the right price point. Critically, the research identified the interest levels, the deposit, and gave the client precise price ceiling for pricing decisions. The segmentation produced four actionable landlord profiles - with the first two segments prioritised for launch, and regional hotspot locations identified for pilot acquisition.
Building evidence for Brand Investment
The Challenge
A fast-growing Australian telehealth platform was preparing to run its first above-the-line campaign, spanning TV, out-of-home, and digital video across various cities. The business needed measurement architecture that could connect media spend to brand health shifts, and brand health shifts to business outcomes. With internal pressure to demonstrate ROI from ATL channels in a performance-marketing-dominated category, the stakes for getting the measurement right were as high as the campaign itself.
The Approach
We designed a three-part measurement framework spanning the full campaign lifecycle. First, we conducted a correlation and regression analysis across months of internal performance data (including new customers, revenue, etc) modelled against brand awareness tracking to establish how strongly brand metrics were already explaining business outcomes. Second, we built a modelling framework projecting short, mid, and long-term uplift ranges across key business metrics under various media spend scenarios. Third, we designed a pre/post quantitative campaign evaluation, a 750-respondent pre-test and 1,000-respondent post-test across target geographies structured to measure shifts in awareness, ad recall, consideration, brand perception, and media channel attribution, with a creative deep-dive to isolate what was driving results.
The Impact
The correlation analysis produced a nuanced, honest read on the impact of brand awareness on new customers and revenue. The findings gave the client a defensible, data-grounded case for sustained brand investment, set clear pre-campaign baselines, and established the measurement infrastructure needed to make future budget decisions with confidence.
Launching a new Wellness product (GTM research)
The Challenge
A wellness tech company was preparing to launch an AI-powered, waterless aromatherapy diffuser, a premium device in a category dominated by mass-market candle brands and traditional oil diffusers. Before committing to a go-to-market strategy, the client needed to validate product-market fit, understand the true size of the addressable opportunity, identify who would actually buy it, and determine the pricing architecture that would maximise adoption without destroying the premium positioning.
The Approach
We fielded an 15-minute nationally representative quantitative survey with 1,100 Australians aged 18–75s, covering health and wellness habits, product ownership, aromatherapy category behaviour, a full concept assessment of the device, monadic price sensitivity testing across four device price points and four refill bundle configurations, and a detailed messaging and channel attribution module. A five-segment latent class segmentation was then developed using BIC-optimised clustering across behavioural, attitudinal, and demographic variables. TURF analysis was run separately on both fragrance categories and individual essential oils to determine the minimum scent portfolio needed to maximise reach.
The Impact
The research identified X million Australians with strong purchase intent for the product, an immediate weighted opportunity to hit the client's target by 2027. Concept appeal was strong on comprehension and uniqueness, with the design, AI personalisation, and sleek aesthetic emerging as the three most valued attributes. We also provided the client with behavioural nudges to overcome barriers to trial, while the TURF analysis produced a clear fragrance portfolio recommendation, eliminating the need for a sprawling range at launch. Five customer segments were delivered with full pen portraits, purchase intent profiles, channel strategies for it’s acquisition targets.
Designing a new Telecom product line
The Challenge
The client was preparing to enter the telecommunications market with a bundle of TV, broadband, and home phone; and needed to understand whether the proposition would genuinely move customer acquisition and retention metrics, which customer segments were most likely to convert, and which of three distinct pricing constructs would perform best in market. The decision carried significant commercial and brand stakes: the wrong positioning could undermine the client’s core identity.
The Approach
We ran a staged mixed-method research programme. A Qualitative stage with focus groups across customers and non-customers established the language and attitudes shaping the category. This fed into a large-scale Quantitative stage: a 30-minute online survey with 2,600 respondents split across current customers (drawn from client’s list) and non-customers who held existing broadband or telephony products. The survey mapped ISP market share and churn behaviour, measured baseline openness to the bundled concepts before and after exposure, tested three distinct pricing constructs, and built detailed indexed profiles of the highest-propensity segments across 40-plus demographic, behavioural, and device variables.
The Impact
The winning bundle materially shifted non-customers openness toward the client, reducing the proportion of outright rejectors. Among existing customers, one in four expressed likely intent to add broadband and home phone to their current package within 12 months. Head-to-head, Bundle construct 1 outperformed the other approaches among customers. The profiling identified the highest-propensity segments for launch prioritisation, ie. Younger metro households, families with kids, Sports Fanatics, and customers currently with Dodo, TPG, and Optus. The research also flagged that ISP switching was already running at 20% annually, creating a consistent window of competitive opportunity.
Understanding Employee Engagement
The Challenge
A fast-growing services company needed an honest read on the health of its workforce. With nearly 300 employees split across two distinct operating environments (a corporate function and a large field operations centre), leadership needed to understand not just satisfaction levels, but what was actually driving engagement, and where to focus investment to move the needle. A previous internally-run survey had provided limited analytical depth. This time, they needed rigour.
The Approach
We designed the study from the ground up using three inputs: seven focus groups and five in-depth interviews conducted with a cross-section of employees two months prior, questions to enable comparison against external Australian workforce norms, and a review of the previous internal survey. The Quantitative study, administered via combined online and paper-based methodology across two Sydney sites achieved a 94% response rate across employees. To enable meaningful comparison to norm data, we developed a calibration methodology that cross-tabulated responses across scales and mapped equivalencies. Driver analysis was then run separately for the corporate and field operations cohorts, using an asymmetric approach that distinguished the factors driving high engagement from those driving low engagement - with a priority-action matrix mapping each theme by importance and current performance.
The Impact
The engagement picture was genuinely positive - responses skewed so heavily toward the favourable end that the primary analytical challenge became distinguishing the highly engaged from the merely engaged, rather than diagnosing disengagement. For the corporate cohort, Career and Professional Development and Valuing People emerged as the highest-priority themes for action: significant drivers of high engagement where current performance was weakest. Team Environment and Customer Focus were identified as existing strengths to build on and communicate. For the field operations group, Career Development was again the single priority for action, while the Nature of Work and Physical Working Conditions were performing strongly and warranted active communication to reinforce. Each theme was delivered with a granular question-level breakdown of specific strengths and improvement opportunities, giving the leadership team a precise brief for action.