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Geeks & NomadsAI for Businesses

Industries · Retail & D2C

Retail, D2C & Ecommerce

Two things changed for retail at the same time: customers started asking on WhatsApp instead of raising a ticket, and they started asking ChatGPT instead of Google. Most storefronts are built for neither.

Support that scales without headcount, and a storefront the AI engines can actually read.

What this sector loses today

The leak is rarely where the budget goes.

Four patterns that recur across this sector. If two of them are recognisably yours, there is a costed answer — and it is usually smaller than the programme you were being sold.

01

"Where is my order" absorbs most of the support queue.

Support headcount scaling with order volume for a question a system can answer.

02

Pre-purchase questions on WhatsApp and Instagram go unanswered for hours.

The highest-intent moment in the funnel, missed.

03

Product content produced one asset at a time.

Catalogue expansion limited by copywriting throughput.

04

AI engines describe your category and name a competitor.

Lost consideration that never appears in any analytics you own.

What changes

How the system behaves, before and after.

These are properties of the architecture, true from the day it goes live. We baseline the numbers underneath them before we build, so the delta is measured against your own starting point rather than against an industry average.

TODAYONCE IT IS RUNNINGOrder-status queriesA support ticketAnswered live, in secondsPre-purchase questionsAnswered next morningAnswered at the moment of intentCatalogue contentOne asset at a timeA pipeline with an approval gateAI engine answersUnmeasuredTracked, and structurally fixable

Applications

Where AI actually pays here.

Each of these is a defined build with a number against it, delivered by one of our five services. They can be scoped and bought individually.

01

Order status and support agent

AI Agent Development

Reads live from your commerce platform and logistics provider to answer order, delivery, return and exchange questions, and escalates the ones that need judgement.

The number that moves

Containment rate · cost per contact · first-response time

02

Pre-purchase WhatsApp agent

AI Agent Development

Sizing, materials, compatibility, stock and delivery estimates from your own catalogue, with the ability to complete or recover a cart.

The number that moves

Enquiry-to-order rate · after-hours capture

03

AI search visibility for your category

Growth Marketing & Search

How six AI engines describe your brand and products against named competitors, where they cite others, and the structural fixes to your content and data.

The number that moves

Share of voice in AI answers · citation rate

04

Catalogue and content production at volume

Growth Marketing & Search

Product copy, variants, translations and campaign assets through a brand-trained pipeline with human approval on every piece.

The number that moves

Cost per asset · time to publish · catalogue coverage

05

Commerce platform engineering

Digital Platform Engineering

Shopify or custom, built for Core Web Vitals, structured so engines can parse your products, and integrated with your CRM and logistics.

The number that moves

Conversion rate · Core Web Vitals · time to publish

What we would build first

Order matters more than ambition.

Doing these in the wrong sequence is the most common reason AI work in this sector stalls. This is the order we would argue for, and the diagnostic is where we test it against your actual numbers.

01

Take the repetitive contacts out

Order status first. It is the largest, most mechanical share of the queue and it needs no judgement at all.

02

Answer before the purchase, not after

Pre-purchase questions on the channel they actually arrive on. This is the one that moves revenue rather than cost.

03

Fix how the engines see you

Structured product data and answer-shaped content, so you are named when somebody asks an AI engine for your category.

Before your risk function signs

What they are going to ask.

In this sector the review is the schedule. We design for these from the first architecture session rather than retrofitting them when the security questionnaire comes back.

  • Customer data handled under a documented retention and deletion policy
  • The agent never invents stock, delivery dates or specifications — it reads live or it escalates
  • Refund, return and goodwill decisions gated to a person above a threshold you set
  • Brand voice enforced through the content pipeline, with human approval on every published asset
  • Model and infrastructure costs billed at cost against a ceiling you approve

Questions we get in this sector

The ones that decide it.

Will it make up a delivery date if the courier data is missing?

No. It reads live from your platform and your logistics provider, and where the data is not there it says so and escalates. Refusing is a designed behaviour, not a failure — an agent that invents a delivery date creates a worse problem than the one it solved.

Can it handle returns and refunds?

It can handle the process and the information. The decision is gated to a person above whatever threshold you set, because the cost of being wrong is real money and a customer relationship.

What does AI search visibility actually change for a D2C brand?

A growing share of category research now happens inside AI engines, which name one or two brands and never send a click. We measure how six engines describe you against named competitors and fix the structural reasons you are skipped — product data, entity clarity, answer-shaped content. It runs on GenAI Ranker, the platform we built and operate, which is why the first scan costs you nothing.

Put a number on it

The support-queue cost, as arithmetic

Four lines. Most people can fill in the first and not the rest, and that gap is usually the whole problem. The blanks are deliberate — they are your numbers, not an industry average we invented. We complete it with you on the call.

Support contacts per month____
Share that are order status or delivery____ %
Fully loaded cost per contact₹____
Containable spend= ____ × ____ % × ₹____

The second number is usually between half and two thirds, and almost nobody has measured it. The demo measures it on your real ticket mix.

Free live demo

Point us at your store. We will show you an agent answering “where is my order” from live data — and what six AI engines say about your brand.

Two demos in one, because in retail the cost problem and the demand problem are the same conversation.

0148 hours

Order status, answered from live data

Connected to a copy of your commerce platform. Ask it about a real order and watch it refuse rather than invent when the courier data is missing.

0248 hours

A pre-purchase agent on your catalogue

Sizing, materials, compatibility, stock. The conversation that happens at the highest-intent moment and currently waits until morning.

0324 hours

What ChatGPT says about your category

Live, across six engines, against your named competitors. This one takes a day and costs us almost nothing, because we own the platform.

0448 hours

Product copy at volume, in your voice

Send five existing product pages. We show the pipeline producing the next fifty in the same voice, with an approval gate.

What should we build?

Free. No card, no commitment, and the demo is yours to keep.

Stop reading about it. Watch it work.

Tell us the one thing that is costing you most, and we build it on your own material within 48 hours. Free, yours to keep, and the fastest way to find out whether any of this applies to you.