Overview
Data Science | Marketing Science | Behavioural Science
Hello
My name is Mark Razzell.
I offer assistance with evidence, data and strategy to businesses and brands through WTQ Consulting.
Most people call me ‘Razz’, which is great, because it makes me sound much cooler than I am.
I trained as a behavioural scientist, transitioned to the commercial world, leaned into strategy, and applied my data science skills to do that better. Now I am a customer intelligence and insights leader, with notable strengths in natural language processing, synthetic-research systems, and the application of AI to business development.
My background in behavioural science gives me a ruthless curiosity and the ability to manipulate data with code. My commercial knowledge fast-tracks my understanding of a situation, and the diversity of my exposure allows me to collaborate fluidly within matrixed organisations.
Whatever I am doing, there’s one place I always start.
What’s The Question?
Not a slogan, a method.
Every defensible strategy starts as a well-formed question, and every good question begets the next one. That’s how science progresses, and it’s how good commercial outcomes are manifested too; simple, iterative, and fun.
WTQ is an independent advisory, offering services within three quantitative time frames:
- Foresight; where is this category heading, and what’s the probable shape of the opportunity?
- Nearsight; what’s the sharpest way to execute against that opportunity, right now?
- Hindsight; did it work, and what does that tell us to ask next?
I’m most useful where the stakes or the ambiguity are high: a decision that will be expensive to get wrong, a question nobody has answered properly yet, or a capability that needs building from nothing.
I work with marketers, innovators and service providers who need rigorous evidence and a perspective from outside the room.
The underlying edge is breadth: fifteen-plus years spanning strategy, data science, and applied research, working across categories from FMCG and finance to retail and healthcare. That cross-domain pattern-matching, knowing how a pricing problem in banking rhymes with a positioning problem in FMCG, is often the difference between a plausible answer and the right one.
Core strengths:
- Data Science quantitative rigour, from segmentation to synthetic testing to NLP-driven text analytics
- Marketing & Business Strategy grounded in how categories, brands, and P&Ls actually behave
- Cross-Domain Knowledge pattern recognition earned across industries, not just one
Notable Experience
The proof of the pudding is in the eating
Outcome: NAB’s “More than Money”
Process: I led the research, guided the strategic thinking, and defended it. Netnography, quant, and experimentation.
Question: “When people think ‘bank’, what do they really think?”
Outcome: Myer’s brand direction as ‘customer-first’
Process: Built a customer-intelligence layer, stitching voice-of-customer survey data to transactional behaviour for a commercially actionable segmentation model and custom recommendation engine.
Question: “Who is the real-and-ideal Myer customer?”
Outcome: Great Northern Brewing Co.’s grow-and-defend media strategy
Process: Led customer research to define customer and non-customer cohorts, guided stakeholders around strategic pitfalls, and defined a sensible pathway to growth through geographic segmentation and custom algorithms.
Question: “How do you grow when you’re already the biggest?”
Outcome: Hootsuite’s ‘Social Performance Score’
Process: Instructed by sales-and-marketing, I partnered with Hootsuite’s product and engineering teams to develop the theory and prototyping using predictive NLP and custom text cleansing features.
Question: “Can we help our customers improve their engagement by benchmarking them against their category?”
Writing
I write about where this is all heading, usually with the working out shown.
- SEO let brands fake customer-centricity for twenty years. Answer engines won’t. Original experimental research into how large language models form and express brand preference, and what it means for discovery. Read it
- Five things I’ve learned running a boutique intelligence consultancy. My honest musings on founding a company, what it’s taught me, and what I had to learn. Read it
- What you need to know about AI. Read it
- Digital transformation: Let’s check our enthusiasm Read it