Product Design · Retail Systems · 2026

Designing for Conversion, Not Screens

A retail intervention that turned an outdated quoting workflow into a system projecting ~$2.2M in incremental annual sales across 11 stores.

Client
D1 Store
Authorised DJI Retailer
11 stores, 4 states
Role
End-to-end Product Designer
Deliverables
Research, Service Design
Prototyping, Analysis
Team
Dayal (Design)
Jai (PM) · Jeff (Ops)
Matt (Engineering)
Impact
~$2.2M projected annual uplift across 11 stores

A modern product sold through an outdated workflow

DJI is known for frontier-level consumer drone technology and professional-grade tools. D1 Store is their authorised Australian retailer, selling across 11 physical stores. Despite representing a cutting-edge brand, the in-store retail experience had not evolved at the same pace.

Stores were busy and interest was high, but conversion was inconsistent. Customers spoke with staff, explored products, asked for discounts — then left. Sometimes with a paper quote. Sometimes with nothing. Once they walked out, the store lost the thread.

A modern product was being sold through an outdated retail workflow — creating measurable conversion loss once customers left the store.

How sales actually happen on the shop floor

I started on the shop floor. Interviewing customers directly wasn't viable — disrupting live sales wasn't an option. Instead, I focused on staff as high-volume observers of real behaviour. In the Pitt Street Mall flagship, weekend footfall reached 150–200 customers, with each staff member interacting with ~40–50 customers per day.

I shadowed live sales conversations end-to-end: how customers browsed, where staff stepped in, how pricing was communicated, how quotes were created, and what happened when customers hesitated.

View:
Baseline — original in-store flow Kiosk intervention
Step Visits Store Browses Products Engaged by Staff Views Demo Pricing Discussion Quote Issued Undecided — Leaves Guided to Kiosk Selects Items Email Captured Quote Emailed 1–14 Days Later Returns & Purchases
Physical Evidence Store signage
A4 posters
Demo units
Price tags
Demo unit
TV display
Drone & accessories Pricing sheet
Calculator
Breakdown 2
Paper quote slip
Intent lost
Kiosk terminal Kiosk screen Customer's phone Quote on phone Email, website link Order confirmation
AusPost tracking
Customer Actions Enters store,
looks around
Explores range
independently
Asks questions,
discusses specs
Watches demo,
handles unit
Discusses price
& accessories
Breakdown 2
Receives paper
quote
Intent lost
"I'll think about
it" — leaves
Walks to kiosk
with staff
Selects items
on kiosk
Enters email
address
Receives digital
quote via email
Considers purchase,
reviews quote
Returns in-store
or buys online
Line of Interaction
Staff Actions
Front stage
Greet customer,
offer assistance
Discovery
conversation
Live demo,
explain specs
Breakdown 3
Upsell accessories,
negotiate discount
Write paper
quote
Guide customer
to kiosk
Assist product
selection
Prompt email
entry
Line of Visibility
Staff Actions
Back stage
Foot traffic
logged manually
Breakdown 3
Manual discount
calculation
Breakdown 2
No system
record created
Intent lost
No follow-up
possible
Quote saved
to backend
Automated
follow-up email
Order processed,
AusPost dispatch
Technology & Support POS (idle) A4 posters
TV display
Demo units Demo units
Tablet
POS, pricing sheet
Calculator
Breakdown 2
Paper only —
no system record
Kiosk
(price sync)
Kiosk interface Email capture
via kiosk
Backend: quote
stored + emailed
Email system,
quote link
Payment &
shipping system
Breakdown 2 No digital memory of intent Breakdown 3 Staff-dependent upsell & discounting Intent lost High-intent customer disappears

Service blueprint — end-to-end in-store journey mapped across customer, staff, and backend touchpoints.

The service blueprint exposed a core issue: the store had no digital memory of intent. Every quote was a dead end.

Three breakdowns in the retail system

Service blueprinting, shop-floor shadowing, and staff interviews surfaced three core breakdowns:

Breakdown 1

Lack of Customer Autonomy

Many customers, especially CALD and first-time buyers, struggled to understand specs and differences between models without heavy staff involvement. With little ability to explore independently, customers deferred decisions to "research at home" and didn't return.

Breakdown 2

No Digital Memory of Intent

Quotes lived on paper, not in the system. Once a customer left with a handwritten price, there was no reliable record of the interaction — high-intent customers simply disappeared.

Breakdown 3

Staff-Dependent Upsell

Accessory recommendations and discounting varied by who was on shift. Outcomes depended on staff confidence and experience, leading to inconsistent attach rates and missed value.

To ground the work in measurement, I tracked only delayed conversions — quotes that converted one or more days after being issued, using paper quotes as the baseline. This avoided inflating results with same-day purchases and ensured each intervention could be evaluated on whether it preserved intent beyond the visit, not just whether it drove immediate sales.

Each intervention was designed to eliminate a possible lever — until the real one remained.

A broad test to find the conversion lever

The first intervention introduced a customer-facing kiosk as a deliberately broad test, allowing multiple assumptions to be evaluated in parallel. It tested whether customer autonomy, digital intent capture, and embedded accessory prompts would meaningfully improve conversion.

The kiosk allowed customers to browse and compare drones visually, see compatible accessories in context, and generate a digital quote via email — without staff involvement.

Intervention 1 — customer-facing kiosk prototype deployed at Pitt Street Mall flagship

Where conversion fell apart

Returning to the shop floor revealed why the kiosk underperformed as a conversion tool. Two distinct customer patterns became clear:

Browsers were price-sensitive and well-researched, wanting quick reassurance on price. The kiosk introduced friction. Staff frequently bypassed it, giving verbal quotes instead. Without paper quotes during the pilot, many of these customers left without any usable reference point.

Buyers intended to purchase in-store and valued staff expertise. For them, the kiosk proved useful as a staff-led visual aid — not as a self-service tool.

The kiosk improved exploration and attachment, but weakened delayed conversion after the visit. Autonomy itself wasn't driving conversion. At that point, I made the call to abandon it as the primary lever and refocus entirely on pricing speed and intent persistence.

Conversion hinged on fast, staff-led pricing reassurance — setting the direction for a staff-led, digitally persistent quoting flow.

Restoring speed and digital memory

The second intervention shifted focus to the moment where decisions were actually being made: pricing conversations led by staff. A full POS integration was considered and deliberately rejected — the existing system was bloated and tightly coupled, making it high-risk to modify.

Instead, we built a lightweight sidecar: a staff-assisted quoting flow on a tablet, designed to be as fast as a paper quote while creating a durable digital record. Staff manually added products and generated a price instantly. The interface was deliberately constrained — we pivoted from a discovery hierarchy to a search-and-add hierarchy.

Each staff member logged in under their own ID, allowing quotes to be attributed and tracked. The tablet was handed to the customer to enter their email. The quote was generated immediately, emailed, and stored in the system.

Intervention 2 — staff-assisted quoting flow on tablet, built to match the speed of a verbal quote while creating a digital record

Pricing speed was restored and intent finally persisted beyond the visit — creating a stable foundation for further optimisation.

The logic engine

The third intervention refined what was already working. Internally, we called this layer a "logic engine" because it formalised decision rules that previously lived only in experienced staff members' heads.

Accessory suggestions were embedded directly into the quoting flow — when a core product was added, relevant accessories surfaced in context. Pricing tiers replaced manual discount calculations: staff selected from predefined levels that balanced competitiveness with margin.

This reduced cognitive load, improved consistency across staff and stores, and kept quoting fast under pressure. Email capture was made opt-in, reframing it as a benefit rather than a requirement.

A principle proven in sequence

~$2.2M
Projected annual impact
across 11 stores
30s
Quote generation
down from 3–5 minutes

A 14-day pilot at Pitt Street Mall flagship tested each intervention in sequence against paper quotes as the baseline. Testing in sequence was deliberate: each version isolated one variable to prove causality, not correlation. Only delayed conversions — quotes that returned one or more days after issue — were counted, isolating intent persistence from same-day purchases.

Intervention 3 delivered +11 delayed conversions over the 14-day pilot — the only version to outperform paper quotes on the primary metric without regressing on the others.

Secondary metrics — pilot results vs. baseline

Kiosk Staff tool Logic engine
Sales per hour +0.20 +0.35 +0.38
Accessory attach rate +6.4% +1.5% +8.5%

Attach rate dipped under the staff tool after accessory prompts were stripped to simplify the flow. They were re-embedded in the logic engine — attach rate recovered and exceeded the kiosk.

From pilot to projection

  1. Pilot uplift +11 delayed conversions 14-day flagship pilot
  2. Monthly equivalent × 2.14 (30 ÷ 14) ≈ 24 conversions / month
  3. Average order value × $1,100 AOV ≈ $26k / store / month
  4. Network scaling 3 flagship × 100%  +  8 standard × 50% ≈ $185k / month
  5. Annualised × 12 months ≈ $2.2M / year

Conservative model. Standard stores discounted to 50% of flagship performance. Only quotes converted one or more days after issue were counted, to exclude same-day intent.

This project concluded deliberately without replacing the POS — several tempting directions were left on the table, each of which would have added surface area without addressing the core failure point: pricing hesitation at the moment of intent. By narrowing the system to that moment, the design shifted behaviour without asking staff or customers to change how they already acted.

This reinforced a principle I now apply across complex, high-intent systems: meaningful impact comes from identifying where decisions stall, proving the true leverage point, and designing the smallest possible system that removes friction at that moment — and resisting everything else.

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