A bags and accessories business built on repeat gifting, seasonal collections and quick after sales on hardware and zips.
60+
IRTH stores and shop-in-shops
30+
Cities and towns covered
₹150 Cr+
Accessories scale
35
Consoles live on this brand
Open
Aiera Live
Pick the sales or support agent, place a real call, and watch the conversation and quality record.
Open
Retention and dormancy
2,40,000 quiet identities across 4 segments, with a dated call list at the end.
Open
Value model
What the pilot is worth on the network figures, with every input on the screen.
What the published figures say
Positioned for the working woman, sold through own stores and online.
Collections turn over quickly, so availability messaging matters.
Hardware and zip repair is the main after sales driver.
Range and price ladder
Category
Price band
Share of mix
Work totes
₹2,600 – ₹6,500
32%
Sling and crossbody
₹1,800 – ₹4,200
27%
Wallets and small leather
₹900 – ₹2,400
22%
Occasion clutches
₹2,200 – ₹5,500
19%
Price bands follow published IRTH ranges. Mix shares are modelled from the category ladder and the store network.
Six teams, one view per head
The platform is organised the way IRTH is run, so every head opens the console that belongs to them.
Team 01
Retail and stores
Head of retail
Team 02
Clinical and quality
Head of optometry
Team 03
Customer and loyalty
Head of customer
Team 04
Marketing and campaigns
Head of marketing
Team 05
Service and fitment
Head of service
Team 06
Method
Head of finance
Platform map
Every module on the platform, the engine behind each one, and what it does on this brand.
#
Module
Engine
What it does
01
Inbound call desk
Voice
Every inbound call answered in the caller's language, coded by reason, with the outcome written back.
02
Outbound enquiry desk
Voice
Enquiries called back within the hour, with a dated next step on every record.
03
Aiera Live
Voice
The live call desk: pick an agent, place the call, watch the conversation and the quality record.
04
Appointment book
Platform
Advisor and store calendars, held slots and reminder calls before every appointment.
05
Lead scoring
Scanning
Intent read from enquiry source, category and response, so the desk calls the right record first.
06
Dormancy engine
Scanning
Continuous read of the IRTH customer book for records that have gone quiet.
07
Reactivation ladder
Voice
A five step contact ladder with a stop rule, so no customer is called twice for the same reason.
08
Loyalty desk
Platform
Tier movement, benefit reminders and the calls that keep a member from slipping a tier.
09
Campaign runner
Generation
Scripts and messages per campaign, published to the desk with the calendar attached.
10
Messaging desk
Messaging
WhatsApp and chat where a message clears the volume more cheaply than a call.
11
Service desk
Voice
Job intake, status calls and completion confirmation across 3 job types.
12
Warranty and claims
Platform
Claim intake, evidence capture and escalation with an audit trail on every claim.
13
Store network view
Platform
Store level demand, staffing pressure and conversion, region by region.
14
Store audit
Scanning
Display, stock and process compliance scored per store, with dated actions.
15
Stock and availability
Scanning
Enquiries matched to what a store actually holds, so the desk stops promising blind.
16
Quality record
Platform
Every conversation scored on the same rubric, at issue level, never at individual level.
17
Value model
Platform
Live calculator from the network figures, with every assumption on the screen.
18
Data readiness
Platform
What is connected, what is modelled and what is needed to go live.
19
Governance
Platform
Consent, retention windows, language policy and what the system will not do.
20
Marketing studio
Generation
Five campaign images and five reels generated for IRTH, with the beat sheet and channel on each.
21
AI product portfolio
Method
Five AI products scored on impact against effort, with the integrations each one needs.
22
Caller coaching
Platform
Six behaviours scored on every call, with next week's drill written from the lowest one.
23
Call analysis
Scanning
Every conversation transcribed, coded and scored, with the objection and the next step on the record.
24
Market sense
Scanning
Live web intelligence on IRTH in six buckets, read off the open web with every source linked.
25
Commercial terms
Method
Flat retainer, usage as pass through and the month six review.
Aiera Live · IRTH call desk
Two live voice agents run on this brand: a sales and enquiry agent, and a customer support agent. Both speak English with natural Hinglish switching, close within a 300 second ceiling and end with a WhatsApp or callback offer.
Agent 01
Sales and enquiry — Aditi
Calls back new enquiries, explains the range in two or three lines, and books a store or advisor appointment. Never quotes exact prices or discounts.
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Agent 02
Customer support — Neha
Takes the issue, repeats it back to confirm, states the next step and who will do it, and escalates to a senior advisor when the store or service centre is needed.
302e2ea1-be97-46e3-9fb1-892f364bd27b
Place a real call now
+91
The call is placed from the IRTH agent on this console. Only Indian mobile numbers are accepted.
How a call is recorded
Field
Written by
Example
Reason code
Agent, from the conversation
Work totes enquiry
Outcome
Agent, at close
Appointment booked
Next step and date
Agent, at close
Store advisor call in 2 days
Language used
Transcriber
English with Hindi switching
Quality score
Quality record, issue level
Rubric score on 5 dimensions
Enquiry and lead desk
Every enquiry gets a call attempt inside the hour, a reason code, and a dated next step. Nothing sits in a spreadsheet.
96,000
Enquiries a year, all sources
52%
Contact rate on the ladder
16%
Contacted to purchase
₹3,200
Average ticket on this brand
Live enquiry queue
Enquiry
Source
Category
Store
Age
Next step
A. Menon
Website
Work totes
North
40 min
Appointment
R. Iyer
Store walk-in
Sling and crossbody
West
2 h
Call now
S. Bhatia
WhatsApp
Wallets and small leather
South
6 h
Appointment
N. Das
Marketplace
Occasion clutches
East
1 day
Call now
Customer names are masked on this console. Source, category and ageing follow the live enquiry mix.
Funnel on current inputs
Stage
Volume a year
Rate
Enquiries received
96,000
100%
Reached on the ladder
49,920
52%
Converted to purchase
7,987
16% of reached
Revenue at average ticket
₹21.3 L a month
₹2.6 Cr a year
The appointment desk
An answered call is worth nothing until a slot is held. The desk holds the slot on the call, confirms it the day before, and writes the outcome back.
1,872
Appointments a month at current contact rates
79%
Honoured after a reminder call
15 min
Average time from call to held slot
Appointment types held on this brand
Type
Length
Who it is with
Reminder
Scent consultation
30 minutes
Store advisor
Call the day before, message two hours before
Gifting appointment
25 minutes
Store advisor
Call the day before, message two hours before
Corporate gifting call
45 minutes
Trade desk
Call the day before, message two hours before
Sample pick up
10 minutes
Store counter
Call the day before, message two hours before
Rules the desk follows
A slot is only offered when the calendar shows it open; the agent never promises a time it cannot hold.
Every appointment carries a named person at the store, not just a store name.
A no show is called once, the same day, and re-offered a different window.
Service and warranty desk
Job intake, status calls and completion confirmation, so the customer never has to chase the store.
Job type
Standard turnaround
Volume
Desk action
Zip and hardware repair
7 days
4,600 / month
Status call at intake, midpoint and completion
Handle replacement
9 days
1,900 / month
Status call at intake, midpoint and completion
Warranty assessment
5 days
2,300 / month
Status call at intake, midpoint and completion
8,800
Service conversations a month
78%
Handled without a store call back
1 days
Average time saved per job
Escalation rules
Any job past its standard turnaround is escalated to the store manager the same day.
A second complaint on the same job goes straight to a senior advisor, never back to the agent.
Warranty decisions are never communicated by the agent until the service centre has confirmed them.
Messaging desk
Not every conversation deserves a call. Where a message clears the volume more cheaply and more politely, the desk sends a message.
Reason
Channel
Why not a call
Appointment confirmation and reminder
WhatsApp
Nothing to discuss, only to confirm
Order, job or repair status update
WhatsApp
A date is easier read than heard
Lookbook and priced set
WhatsApp
The customer needs to see it
Store address, timing and directions
SMS or WhatsApp
Detail the caller will forget
Consent and opt out capture
WhatsApp
Written record required
6,400
Messages a month at current volumes
34%
Call volume moved to messaging
₹4.6 L
Contact cost avoided a year
Messaging cost avoidance is modelled at the difference between a messaging contact and a voice contact on Indian rates.
Retention and dormancy
2,40,000 identities have gone quiet on this brand. The engine reads the customer book continuously and produces a dated call list per segment.
Segment
Size
Action on the ladder
One bag bought, 10 months quiet
128,000
New collection call
Cart abandoned
62,000
Recovery call
Gifting buyer, occasion due
44,000
Occasion reminder
Repair completed, no repeat
16,800
Care and upgrade call
Segment builder
11,280
Customers back in a year
₹3.6 Cr
Value recovered at that rate
Segment sizes are modelled from the 60+ strong network and the published customer base. Every rate here is an editable input.
Replenishment book
Fragrance and accessories repeat on consumption, not on occasion. The IRTH book is built from bottle size and purchase date.
Cohort in the book
Size
What the desk does
Buyers with a dated last purchase
Modelled from sell out volume
Replenishment call at week 14
Bought a 100 ml, four months on
21% of buyers
Refill and variant call
Sampled but never bought
18% of sampled records
One follow up call
Gifting buyer, festival window
15% of the book
Occasion call two weeks before
How the desk behaves on it
The agent recommends by note family from the record, never by discount.
One replenishment call per cycle; a customer who declines is skipped next cycle.
Book sizes are modelled from the 60+ irth stores and shop-in-shops and comparable programmes. Each one is replaced with the brand's own figure in the first data session.
Loyalty desk
Tier movement is the cheapest growth on this brand: a member about to slip a tier is worth a call, and a member one purchase away from the next tier is worth two.
Tier
Entry criteria
Members
IRTH Insider
First purchase
420,000
Insider Plus
Two purchases in 12 months
38,000
What the desk does with it
Trigger
Call
Window
One purchase away from the next tier
Benefit and upgrade call
Within 7 days
Tier expiring in 60 days
Retention call with the benefit spelled out
Two attempts
Benefit unused for 6 months
Reminder call, no offer
One attempt
Birthday or anniversary in the record
Occasion call
Three days before
Campaigns and launches
Each campaign arrives at the desk as a script, a call list and a stop rule, not as a brief.
Campaign
Window
Channel
Desk output
Work edit launch
Quarterly
Messaging
Script, dated list, stop rule
Festive gifting
October
Voice
Script, dated list, stop rule
Category focus in the current window
Category
Price band
Share of calls
Work totes
₹2,600 – ₹6,500
34%
Sling and crossbody
₹1,800 – ₹4,200
27%
Wallets and small leather
₹900 – ₹2,400
21%
Occasion clutches
₹2,200 – ₹5,500
18%
Campaign names describe campaign types, not confirmed IRTH plans. Call shares are modelled on comparable windows.
Replenishment and launch trigger desk
Consumption clock by bottle size, plus new variant launches and gifting windows.
Trigger
Who gets called
Window
Consumption window reached
Buyers by bottle size
Replenishment call
New variant in the note family
Matching buyers
One launch call
Gifting season opens
Last year's gifting buyers
Call two weeks before
Sampled, no purchase in 30 days
Sampled records
One follow up call
Rules on the trigger
A 100 ml bottle bought 14 weeks ago opens a replenishment call window.
A new variant in a customer's note family opens one launch call.
Two declined replenishment calls stop the ladder for that customer.
A trigger only ever opens a call window. It never sends an offer, a price or a discount on its own.
Concierge desk and scent consultation
Choosing a fragrance is a conversation about notes. The desk books that conversation and sends samples first.
Service
How it runs
Who it is for
Scent consultation
Note profile built with the customer
New and gifting buyers
Sample set dispatch
Three samples chosen on the call
Undecided buyers
Gifting and engraving
Packed and personalised
Festival and corporate orders
Corporate bulk gifting
Quote and dispatch managed
Company accounts
2.1×
Conversion against a walk in enquiry
28%
Share of high value enquiries routed here
24 h
Time from enquiry to a held session
Uplift and routing shares are modelled on comparable appointment led retail. They are inputs, not claims.
Note lookbook and gifting guide
A short set by note family and occasion, priced, with the sample dispatch offered on the same call.
Set
What is in it
When it is sent
Note family edit
Three fragrances, one family
Sent on WhatsApp
Gifting under a stated budget
Priced against the customer's number
Sent inside the hour
Day and evening pair
Two bottles, stated wear
Sent on request
Accessory pairing set
Bag or belt matched to the gift
Sent with the quote
What a brief carries
Field
Written by
Example
Customer's stated budget
Agent, on the call
₹3,840
Occasion or reason
Agent, on the call
Work edit launch
Category shortlist
Desk, from the range
Work totes
Store and person
Desk, from the calendar
North flagship
Sent on
Messaging desk
WhatsApp, within the hour
Marketing studio · IRTH
Five campaign images and five reels built for IRTH from its own range, occasions and audience. Every frame is generated on brand and carries the concept, the channel and the call to action it was written for.
10
Creatives shipped on this brand
5
Campaign images, feed and catalogue
5
Reels, 9:16 storyboard
2
Live campaign windows to feed
Five campaign images
1200 × 750 · feed
Women's handbags and accessories
IRTH
Hero product still — structured IRTH handbag on a studio block
Single subject, no clutter. Used as the anchor frame for the a work to weekend bag push and cut down for stories.
Product heroWorking women, 24 to 38Instagram feed · Meta paid
Book a store visit
1200 × 750 · feed
Made for a work to weekend bag.
IRTH
A work to weekend bag campaign frame
Human moment around the product, shot to run through the a work to weekend bag calendar in every region.
OccasionWorking women, 24 to 38Meta + YouTube masthead
See the collection
1200 × 750 · feed
60+ irth stores and shop-in-shops
IRTH
Store and service frame
Retail proof for local campaigns: the room, the advisor and the process a customer walks into.
Retail experienceWorking women, 24 to 38Google Performance Max · local
Find your nearest store
1200 × 750 · feed
Vegan leather, built for a laptop and a day out
IRTH
Craft and proof frame
Macro proof frame used wherever the claim needs evidence: process, tolerance, certification, hand work.
Craft proofWorking women, 24 to 38Brand film stills · PR
Read how it is made
1200 × 750 · feed
4 ranges, one ladder
IRTH
Range and price ladder frame
Flat lay of the ladder from occasion clutches to work totes, used in CRM and catalogue.
RangeWorking women, 24 to 38Catalogue · CRM email
Browse the range
Five reels
Each reel ships as a beat sheet with its opening frame, ready to shoot or generate on approval.
720 × 1280 · 9:160:08
Women's handbags and accessories
IRTH
Three second hook reel
Opens on a structured IRTH handbag on a studio block in motion, holds one line, ends on the store CTA.
0-2s Macro push in on a structured IRTH handbag on a studio block
2-5s Pull back to reveal a pastel studio set with geometric blocks
5-8s Hold on the product, CTA card
Product heroWorking women, 24 to 38Instagram Reels · Shorts
Book a visit
720 × 1280 · 9:160:10
The a work to weekend bag film.
IRTH
A work to weekend bag story reel
One customer moment, working women, 24 to 38, shot handheld and cut tight.
0-3s The moment before: a work to weekend bag preparation
3-7s The product enters the frame
7-10s Reaction, then the brand card
OccasionWorking women, 24 to 38Reels · WhatsApp status
See the collection
720 × 1280 · 9:160:10
Vegan leather, built for a laptop and a day out
IRTH
How it works reel
Screen recorded and shot steps of the actual process, used to answer the top objection.
0-3s The question a customer asks
3-7s The process on camera: vegan leather, built for a laptop and a day out
7-10s What the customer walks away with
ExplainerWorking women, 24 to 38Shorts · store screens
Talk to an advisor
720 × 1280 · 9:160:08
Walk into IRTH.
IRTH
Store walkthrough reel
Single take walk through the store, cut to the retail and stores script.
0-2s Door opens, camera walks in
2-6s Advisor presents a structured IRTH handbag on a studio block
6-8s Appointment card, store name
Retail experienceWorking women, 24 to 38Local Reels · Maps
Find your store
720 × 1280 · 9:160:10
Why working women choose us.
IRTH
Customer voice reel
Creator style piece to camera, no studio polish, subtitled for sound off viewing.
0-3s Piece to camera, one honest line
3-7s Cut to a structured IRTH handbag on a studio block in real use
7-10s Recommendation, brand card
Social proofWorking women, 24 to 38Reels · influencer whitelisting
Book a call back
Campaign windows these creatives feed
Campaign
Window
Channel
Creative used
Work edit launch
Quarterly
Messaging
Hero product still — structured IRTH handbag on a studio block + Three second hook reel
Festive gifting
October
Voice
A work to weekend bag campaign frame + A work to weekend bag story reel
Creative concepts are written from published IRTH range and occasion language. Visuals are generated for this console and are not shot campaign assets.
AI product portfolio · IRTH
Five AI products designed for IRTH specifically, each naming the bottleneck it removes, what gets built, and the one number it moves. Scored on business impact against build effort.
5
Products in the portfolio
78/100
Average impact score
4
Quick wins: high impact, low effort
4
Shippable inside 90 days
#
Product
Moves
Impact
Effort
Horizon
Stage
Payback
01
Scent and style profiler
Trial to purchase rate
85/100
30/100
Now
Prototype
8 weeks
02
Gifting and replenishment desk
Repeat purchase rate
67/100
62/100
Next
Concept
11 weeks
03
Enquiry-to-appointment agent
Enquiry to appointment rate
78/100
44/100
Now
Pilot
6 weeks
04
Dormancy and reactivation engine
Reactivated customers per month
81/100
42/100
Now
Pilot
8 weeks
05
Conversation intelligence for the estate
Objections resolved before escalation
78/100
36/100
Now
Prototype
10 weeks
Product 01 · Now · Prototype
Scent and style profiler
The bottleneck. Choice is the barrier: a customer cannot pick from the IRTH range online, and returns follow every blind buy.
What gets built. A short conversational profiler on occasion, intensity and season that recommends two options from 4 families with a sampling or in-store trial offer attached.
Who uses it. Marketing team, e-commerce, trade counters
Why it holds. The profiler learns from repeat-purchase data, so recommendations tighten every quarter.
Preference elicitation flowFamily and note embeddingSampling offer engineAiera ConverseAiera Sense
Integration
What moves across
State
Catalogue
Families, notes, intensity and price
In build
E-commerce
Sampling offer and cart handoff
Planned
Moves: Trial to purchase rate. Impact 85/100 against 30/100 build effort, payback 8 weeks.
Product 02 · Next · Concept
Gifting and replenishment desk
The bottleneck. Fragrance and accessories are consumed on a predictable cycle, and nobody calls when the bottle is about to run out.
What gets built. A replenishment engine that estimates the empty date from size and usage band, calls with a refill or upgrade at the right week, and runs a gifting calendar for dated occasions in the record.
Who uses it. Customer team, trade marketing, e-commerce
Why it holds. Cycle estimates from the brand's own repeat data beat any generic reorder reminder.
The bottleneck. Enquiries reach IRTH faster than the floor can call them back. The ones called on day three convert at a fraction of the ones called inside the hour.
What gets built. A voice agent that calls every new enquiry within the hour in the caller's language, qualifies category and budget band without quoting a price, and writes a held slot into the advisor calendar at 60+ locations.
Who uses it. Retail and stores team, store managers, advisors
Why it holds. Trained on IRTH range language and objection handling, with the price guardrail written into the policy layer.
Voice LLM with tool callingHinglish ASR and TTSCalendar hold APICRM write-backAiera ConverseAiera Engage
Integration
What moves across
State
CRM / lead store
Enquiry in, outcome and reason code out
Live
Store calendar
Slot held before the call ends
In build
WhatsApp Business
Confirmation and reminder on the same thread
Live
Moves: Enquiry to appointment rate. Impact 78/100 against 44/100 build effort, payback 6 weeks.
Product 04 · Now · Pilot
Dormancy and reactivation engine
The bottleneck. 2,40,000 identities in the IRTH book have gone quiet, and the estate has no ranked reason to call any one of them today.
What gets built. A scoring engine that reads recency, category, ticket and last conversation, then publishes a dated call list per store with a five step ladder and a hard stop rule, across 4 segments.
Who uses it. Customer and loyalty team, regional heads
Why it holds. The stop rule and consent ledger mean the same customer is never worked twice for the same reason across channels.
Moves: Reactivated customers per month. Impact 81/100 against 42/100 build effort, payback 8 weeks.
Product 05 · Now · Prototype
Conversation intelligence for the estate
The bottleneck. Nobody at IRTH can answer what customers actually asked for last week without listening to calls one by one.
What gets built. Every call and chat transcribed, coded to a reason taxonomy, and rolled up to region, store and category, with the top rising objection surfaced weekly at issue level only.
Who uses it. Marketing and campaigns team, category heads, quality
Why it holds. A reason taxonomy built for this vertical, scored at issue level and never at individual advisor level.
Moves: Objections resolved before escalation. Impact 78/100 against 36/100 build effort, payback 10 weeks.
Impact and effort are scored by the build team on the brand's own volumes, and are re-scored at the month six review.
AI product 01 of 5 · IRTH · Now, Prototype
Scent and style profiler
Choice is the barrier: nobody picks blind from the IRTH range. A short profiler narrows it to two options and attaches a trial.
2,995
Returns avoided
85/100
Business impact score
30/100
Build effort score
8 weeks
Payback on the pilot
The bottleneck
What is broken today
Choice is the barrier: a customer cannot pick from the IRTH range online, and returns follow every blind buy.
The build
What gets built
A short conversational profiler on occasion, intensity and season that recommends two options from 4 families with a sampling or in-store trial offer attached.
How it works, end to end
Step
Stage
What happens on this brand
01
Profiled
Four questions on occasion, intensity, season and what the customer already wears.
02
Matched
Answers matched to families across 4 groups, with note and intensity embeddings.
03
Two options
Two recommendations, never a list, each with why it was picked in one line.
04
Trial attached
Sampling offer or an in-store trial at the nearest counter, with a dated follow-up.
05
Learned from
Repeat purchase and return data tighten the profiler every quarter.
The value, on IRTH numbers
Measure
Figure
How it is arrived at
Profiles completed a month
49,920
Web, app and counter
Trials issued
21,965
Sampling or in-store trial
Trial to purchase
8,347
38% of trials convert
Returns avoided
2,995
Blind buys removed by the profiler
Value from profiled trials
₹2.7 Cr
At the ₹3,200 average ticket
Moves: Trial to purchase rate. Every figure above is computed from the inputs on the value model console, so changing an input changes this table.
Quick demo: four questions to two options
Quick demo
A customer wants something for daily office wear in a humid city and dislikes sweet notes.
Input the product reads
Value
Occasion
Daily, office
Season
Humid, year round
Currently wears
A citrus body spray
Dislikes
Sweet, heavy notes
ProfilerKya yeh daily office ke liye chahiye ya evening ke liye?
CustomerDaily office.
ProfilerKaunsi cheez pasand nahi — sweet, woody, ya musk?
CustomerSweet bilkul nahi.
ProfilerDo options rakhta hoon: Work totes family se ek fresh option, aur Sling and crossbody se ek light woody. Dono ₹2,600 – ₹6,500 band mein.
ProfilerNearest counter par trial rakh deta hoon, aur 5 din baad ek follow-up call karunga.
What the product wrote back
Result
Value
Options given
2, never a long list
Trial
Counter trial reserved
Follow-up
Dated, 5 days
Expected trial-to-buy
38%
Two options with a reason beats a catalogue. The profiler improves as repeat data lands.
Who uses it, and why it holds
Users
Inside IRTH
Marketing team, e-commerce, trade counters
Moat
Why it is defensible
The profiler learns from repeat-purchase data, so recommendations tighten every quarter.
Preference elicitation flowFamily and note embeddingSampling offer engineAiera ConverseAiera Sense
Systems it needs
Integration
What moves across
State
Catalogue
Families, notes, intensity and price
In build
E-commerce
Sampling offer and cart handoff
Planned
Rollout on this brand
Window
Milestone
Owner
Week 1-2
Connect the source systems and replay 30 days of IRTH history through the model
Build team, brand IT
Week 3-4
Pilot on 8 stores in North
Regional retail head
Week 5-8
Widen to the full region, publish the weekly reason and outcome report
Desk lead, brand owner
Week 9-12
Estate rollout with the stop rule and consent ledger enforced
Brand owner, method review
Guardrails
No price, discount or making-charge negotiation on the call; the agent states published terms only.
Consent captured and logged in the first 15 seconds, with an immediate opt-out honoured across every channel.
A single stop rule across the estate: the same IRTH customer is never worked twice for the same reason.
Scored at desk, region and issue level, never against a named advisor.
Recordings retained for the agreed window, then deleted; transcripts hold no card or ID data.
Impact 85/100 against 30/100 build effort. Horizon Now, current stage Prototype, payback 8 weeks. Re-scored at the month six review.
AI product 02 of 5 · IRTH · Next, Concept
Gifting and replenishment desk
IRTH products are consumed on a predictable cycle, and nobody calls when the bottle is empty. This desk calls at the right week, and again before every gifting peak.
7,200
Gifting-peak conversions
67/100
Business impact score
62/100
Build effort score
11 weeks
Payback on the pilot
The bottleneck
What is broken today
Fragrance and accessories are consumed on a predictable cycle, and nobody calls when the bottle is about to run out.
The build
What gets built
A replenishment engine that estimates the empty date from size and usage band, calls with a refill or upgrade at the right week, and runs a gifting calendar for dated occasions in the record.
How it works, end to end
Step
Stage
What happens on this brand
01
Cycle estimated
Size, purchase date and channel used to estimate the finish week per customer.
02
Gifting calendar held
Work edit launch and the rest of the gifting calendar held alongside the cycle.
03
Nudged then called
A message at the estimated finish week; a call only if the message goes unanswered.
04
Bundle offered
Refill or the same family at the size that matches how the customer actually buys.
05
Measured
Repeat rate per cycle and per campaign window, reported monthly.
The value, on IRTH numbers
Measure
Figure
How it is arrived at
Customers on a known cycle
96,000
Purchase history with size and date
Nudges due a month
11,520
Estimated finish week
Repeat purchases from nudges
2,419
21% of nudges convert
Gifting-peak conversions
7,200
Across the gifting windows
Value from repeats
₹3.1 Cr
At the ₹3,200 average ticket
Moves: Repeat purchase rate. Every figure above is computed from the inputs on the value model console, so changing an input changes this table.
Quick demo: a refill nudge that lands in the right week
Quick demo
A 100ml purchase 11 weeks ago, bought at a counter, with a gifting window opening in 12 days.
Input the product reads
Value
Last purchase
100ml, 11 weeks ago
Estimated finish
Week 12
Channel preference
Counter, not online
Window opening
Work edit launch
DeskMessage: aapki last bottle ab khatam hone wali hogi. Nearest counter par refill available hai.
EngineNo reply in 72 hours. Escalating to a call, once.
AgentNamaste, IRTH se. Refill ke liye call kiya hai, aur Work edit launch window bhi khul rahi hai.
CustomerGift bhi lena hai ek.
AgentPhir Sling and crossbody family mein gifting option dikha deta hoon. Counter par dono rakhwa deta hoon.
EngineOutcome written, next cycle re-estimated from this purchase.
What the product wrote back
Result
Value
Contact attempts
1 message, 1 call
Outcome
Refill plus a gifting add-on
Cycle re-estimated
Yes, from this purchase
Further contact
None until the next cycle
One nudge, one call, then silence until the next cycle. The stop rule is what keeps this welcome.
Who uses it, and why it holds
Users
Inside IRTH
Customer team, trade marketing, e-commerce
Moat
Why it is defensible
Cycle estimates from the brand's own repeat data beat any generic reorder reminder.
Connect the source systems and replay 30 days of IRTH history through the model
Build team, brand IT
Week 3-4
Pilot on 8 stores in North
Regional retail head
Week 5-8
Widen to the full region, publish the weekly reason and outcome report
Desk lead, brand owner
Week 9-12
Estate rollout with the stop rule and consent ledger enforced
Brand owner, method review
Guardrails
No price, discount or making-charge negotiation on the call; the agent states published terms only.
Consent captured and logged in the first 15 seconds, with an immediate opt-out honoured across every channel.
A single stop rule across the estate: the same IRTH customer is never worked twice for the same reason.
Scored at desk, region and issue level, never against a named advisor.
Recordings retained for the agreed window, then deleted; transcripts hold no card or ID data.
Impact 67/100 against 62/100 build effort. Horizon Next, current stage Concept, payback 11 weeks. Re-scored at the month six review.
AI product 03 of 5 · IRTH · Now, Pilot
Enquiry-to-appointment agent
Every enquiry that reaches IRTH gets a call back inside the hour, in the language the customer wrote in, and ends with a slot held in a named store's book.
₹2.6 Cr
Value on the appointment book
78/100
Business impact score
44/100
Build effort score
6 weeks
Payback on the pilot
The bottleneck
What is broken today
Enquiries reach IRTH faster than the floor can call them back. The ones called on day three convert at a fraction of the ones called inside the hour.
The build
What gets built
A voice agent that calls every new enquiry within the hour in the caller's language, qualifies category and budget band without quoting a price, and writes a held slot into the advisor calendar at 60+ locations.
How it works, end to end
Step
Stage
What happens on this brand
01
Enquiry lands
Web form, WhatsApp, walk-in register or campaign response arrives with source and Work totes interest attached.
02
Scored and queued
Intent scored on source, category and response speed; Work totes and Sling and crossbody enquiries in a live campaign window jump the queue.
03
Called in the hour
Voice agent opens with consent, confirms the occasion, budget band and date, and never quotes a price.
04
Slot held
Nearest of the 60+ locations checked for advisor availability and a slot held before the call ends.
05
Written back
Outcome, reason code and dated next step written to the record; reminder scheduled for the day before.
The value, on IRTH numbers
Measure
Figure
How it is arrived at
Enquiries a month
96,000
Modelled on the network, editable on the value model console
Reached inside the hour
49,920
52% contact rate at the pilot desk
Appointments that convert
7,987
16% of contacted, matched to store billing
Value on the appointment book
₹2.6 Cr
At the ₹3,200 IRTH average ticket
Advisor hours returned a month
5,990
Callback dialling and note taking removed from the floor
Moves: Enquiry to appointment rate. Every figure above is computed from the inputs on the value model console, so changing an input changes this table.
Quick demo: an enquiry called back in the hour
Quick demo
A Work totes enquiry arrives from a North pincode at 11:04 with no budget stated.
Input the product reads
Value
Source
Website enquiry form
Interest
Work totes, ₹2,600 – ₹6,500
Region
North
Language detected
Hindi with English product words
AgentNamaste, IRTH se baat kar rahe hain. Aapne aaj Work totes ke liye enquiry ki thi. Do minute baat kar sakte hain?
CustomerHaan, boliye.
AgentYeh kis occasion ke liye dekh rahe hain, aur date kya soch rahe hain?
CustomerBehen ki shaadi hai, agle mahine ki 14.
AgentSamajh gaya. Work totes mein ₹2,600 – ₹6,500 range hai, aur Sling and crossbody bhi dekh sakte hain. Store par pieces nikalwa kar rakhta hoon.
CustomerDiscount kitna milega?
AgentRate aur terms store par published hain, main uspar comment nahi karta. Advisor aapko poori terms dikhayenge.
AgentNorth store mein kal shaam 6 baje advisor free hain. Slot hold kar doon?
CustomerHaan kar dijiye.
What the product wrote back
Result
Value
Time to first call
41 minutes from enquiry
Reason code written
Wedding purchase, Work totes
Budget band captured
₹2,600 – ₹6,500
Next step
Appointment held, North store, tomorrow 18:00
Guardrail held
No price or discount discussed
The demo shows the live agent script and the record it writes. Place a real call from the Aiera Live desk to hear it.
Who uses it, and why it holds
Users
Inside IRTH
Retail and stores team, store managers, advisors
Moat
Why it is defensible
Trained on IRTH range language and objection handling, with the price guardrail written into the policy layer.
Voice LLM with tool callingHinglish ASR and TTSCalendar hold APICRM write-backAiera ConverseAiera Engage
Systems it needs
Integration
What moves across
State
CRM / lead store
Enquiry in, outcome and reason code out
Live
Store calendar
Slot held before the call ends
In build
WhatsApp Business
Confirmation and reminder on the same thread
Live
Rollout on this brand
Window
Milestone
Owner
Week 1-2
Connect the source systems and replay 30 days of IRTH history through the model
Build team, brand IT
Week 3-4
Pilot on 8 stores in North
Regional retail head
Week 5-8
Widen to the full region, publish the weekly reason and outcome report
Desk lead, brand owner
Week 9-12
Estate rollout with the stop rule and consent ledger enforced
Brand owner, method review
Guardrails
No price, discount or making-charge negotiation on the call; the agent states published terms only.
Consent captured and logged in the first 15 seconds, with an immediate opt-out honoured across every channel.
A single stop rule across the estate: the same IRTH customer is never worked twice for the same reason.
Scored at desk, region and issue level, never against a named advisor.
Recordings retained for the agreed window, then deleted; transcripts hold no card or ID data.
Impact 78/100 against 44/100 build effort. Horizon Now, current stage Pilot, payback 6 weeks. Re-scored at the month six review.
AI product 04 of 5 · IRTH · Now, Pilot
Dormancy and reactivation engine
2,40,000 identities in the IRTH book have gone quiet. This engine ranks them daily and hands each store a dated call list with a reason on every name.
₹48
Cost per reactivated customer
81/100
Business impact score
42/100
Build effort score
8 weeks
Payback on the pilot
The bottleneck
What is broken today
2,40,000 identities in the IRTH book have gone quiet, and the estate has no ranked reason to call any one of them today.
The build
What gets built
A scoring engine that reads recency, category, ticket and last conversation, then publishes a dated call list per store with a five step ladder and a hard stop rule, across 4 segments.
How it works, end to end
Step
Stage
What happens on this brand
01
Book read nightly
Recency, category, ticket band, 2 loyalty tiers and last conversation read across the whole IRTH book.
02
Scored to a reason
Every quiet identity gets one reason: One bag bought, 10 months quiet, Cart abandoned or Gifting buyer, occasion due.
03
Ladder assigned
A five step ladder per reason: message, call, advisor call, store invite, close and rest.
04
Published to stores
Dated list to each store with the ranked names, capped so the desk is never handed more than it can call.
05
Stopped or converted
Stop rule fires on opt-out, purchase or ladder completion; billing matched back to the call.
The value, on IRTH numbers
Measure
Figure
How it is arrived at
Quiet identities in scope
2,40,000
Across 4 scored segments
Reactivated a month
11,280
4.7% of the worked list, held at the pilot rate
Value reactivated
₹3.6 Cr
At the ₹3,200 average ticket
Cost per reactivated customer
₹48
Voice desk cost per contact, one quarter of the book worked
Contacts avoided by the stop rule
43,200
Duplicate work removed across call, message and store
Moves: Reactivated customers per month. Every figure above is computed from the inputs on the value model console, so changing an input changes this table.
Quick demo: today's reactivation list for one store
Quick demo
The North store opens its list at 10:00. Names are masked; the reason and the ladder step are not.
Input the product reads
Value
Store
North, 20
List size today
24 names, capped to desk capacity
Top segment
One bag bought, 10 months quiet
Ladder step
Step 2, first advisor call
EngineR•••• S — last purchase 19 months ago, Work totes, IRTH Insider tier. Reason: One bag bought, 10 months quiet. Score 92.
EngineRecommended open: New collection call
AdvisorNamaste, IRTH North se. Aapne humare saath Work totes liya tha. Ek new arrival aayi hai jo aapki pehli purchase ke saath jaati hai.
CustomerAbhi plan nahi hai, teen mahine baad dekhungi.
AdvisorBilkul, main aapko teen mahine baad hi call karunga. Tab tak koi message nahi bhejenge.
EngineOutcome: deferred, 90 day rest applied. Every other channel muted for this reason.
What the product wrote back
Result
Value
Names worked
24 of 24, no sampling
Converted to appointment
3
Deferred with a dated recall
7
Rested by the stop rule
2
Value on the 3 appointments
₹9,600
Reactivation runs on the brand's own book. Identities are masked on this console; the live desk sees the record it is allowed to see.
Who uses it, and why it holds
Users
Inside IRTH
Customer and loyalty team, regional heads
Moat
Why it is defensible
The stop rule and consent ledger mean the same customer is never worked twice for the same reason across channels.
Connect the source systems and replay 30 days of IRTH history through the model
Build team, brand IT
Week 3-4
Pilot on 8 stores in North
Regional retail head
Week 5-8
Widen to the full region, publish the weekly reason and outcome report
Desk lead, brand owner
Week 9-12
Estate rollout with the stop rule and consent ledger enforced
Brand owner, method review
Guardrails
No price, discount or making-charge negotiation on the call; the agent states published terms only.
Consent captured and logged in the first 15 seconds, with an immediate opt-out honoured across every channel.
A single stop rule across the estate: the same IRTH customer is never worked twice for the same reason.
Scored at desk, region and issue level, never against a named advisor.
Recordings retained for the agreed window, then deleted; transcripts hold no card or ID data.
Impact 81/100 against 42/100 build effort. Horizon Now, current stage Pilot, payback 8 weeks. Re-scored at the month six review.
AI product 05 of 5 · IRTH · Now, Prototype
Conversation intelligence for the estate
Every IRTH call and chat is transcribed, coded to a reason taxonomy and rolled up to region, store and category, so the rising objection is on the leadership pack the week it rises.
1,498
Enquiries saved by script fixes
78/100
Business impact score
36/100
Build effort score
10 weeks
Payback on the pilot
The bottleneck
What is broken today
Nobody at IRTH can answer what customers actually asked for last week without listening to calls one by one.
The build
What gets built
Every call and chat transcribed, coded to a reason taxonomy, and rolled up to region, store and category, with the top rising objection surfaced weekly at issue level only.
How it works, end to end
Step
Stage
What happens on this brand
01
Captured
Telephony recordings and chat threads ingested with store, region and Work totes category metadata.
02
Transcribed
Streaming ASR handling Hindi, English and the code-switch between them, with product words preserved.
03
Coded
Each conversation gets a reason code, an objection cluster, a sentiment read and a next-step flag.
04
Rolled up
Region, store and category views across 4 regions, weekly and rolling four weeks.
05
Acted on
The top rising objection becomes next week's drill on the coaching console and a script change on the desk.
The value, on IRTH numbers
Measure
Figure
How it is arrived at
Conversations coded a month
58,720
100% coverage, replacing manual sampling
Manual review hours removed
2,936
At 3 minutes of quality listening per sampled call
Rising objections surfaced weekly
Top 5
Ranked by week-on-week movement, at issue level
Enquiries saved by script fixes
1,498
Objection answered before it becomes a lost enquiry
Value of those saves
₹7.7 L
At the brand conversion rate and average ticket
Moves: Objections resolved before escalation. Every figure above is computed from the inputs on the value model console, so changing an input changes this table.
Quick demo: last week's rising objection
Quick demo
8,800 service and enquiry conversations coded across 4 regions.
Input the product reads
Value
Window
Rolling week against prior week
Coverage
100% of calls and chats
Top category
Work totes
Top region by volume
North
EngineRising objection: "Work totes availability at the nearest store" — up 34% week on week, concentrated in North.
EngineSecond: turnaround clarity on Zip and hardware repair (7 days) — customers calling twice for the same status.
EngineThird: Sling and crossbody price band confusion after the Work edit launch window opened.
ActionStock and availability console now answers the first before the advisor speaks; Zip and hardware repair status calls automated.
ActionCoaching drill this week: name the objection back before answering it.
What the product wrote back
Result
Value
Conversations coded
58,720
Reason codes in the taxonomy
28, written with the brand
Objections cleared before escalation
61%
Script changes shipped
3
Rollups are read at issue level only. No advisor is named or ranked in any view on this console.
Who uses it, and why it holds
Users
Inside IRTH
Marketing and campaigns team, category heads, quality
Moat
Why it is defensible
A reason taxonomy built for this vertical, scored at issue level and never at individual advisor level.
Connect the source systems and replay 30 days of IRTH history through the model
Build team, brand IT
Week 3-4
Pilot on 8 stores in North
Regional retail head
Week 5-8
Widen to the full region, publish the weekly reason and outcome report
Desk lead, brand owner
Week 9-12
Estate rollout with the stop rule and consent ledger enforced
Brand owner, method review
Guardrails
No price, discount or making-charge negotiation on the call; the agent states published terms only.
Consent captured and logged in the first 15 seconds, with an immediate opt-out honoured across every channel.
A single stop rule across the estate: the same IRTH customer is never worked twice for the same reason.
Scored at desk, region and issue level, never against a named advisor.
Recordings retained for the agreed window, then deleted; transcripts hold no card or ID data.
Impact 78/100 against 36/100 build effort. Horizon Now, current stage Prototype, payback 10 weeks. Re-scored at the month six review.
Store network
60+ IRTH stores and shop-in-shops, read region by region, with demand and staffing pressure next to each other.
Region
Points of sale
Share of network
Desk load
North
20
33%
2,640 enquiries a month
West
17
28%
2,240 enquiries a month
South
15
25%
2,000 enquiries a month
East
8
14%
1,120 enquiries a month
Store level signals the desk acts on
Enquiry volume above what the store roster can answer, two weeks running.
Appointments booked but not honoured, by store and by advisor.
Requests for stock the store does not hold, so transfer replaces a lost sale.
Stock and availability
The desk stops promising blind. Before an appointment is offered, the enquiry is matched against what the store actually holds.
Category
Held at the enquiry store
Available in the region
Desk action
Work totes
66% of the plan
81% of the plan
Book at this store
Sling and crossbody
55% of the plan
68% of the plan
Offer transfer or another store
Wallets and small leather
83% of the plan
94% of the plan
Book at this store
Occasion clutches
72% of the plan
81% of the plan
Book at this store
What happens when the piece is not there
The desk names a second store in the same city before it names a date.
A transfer is raised with a dated arrival, and the customer is called when it lands.
A repeated gap in the same category at the same store is written into the store audit.
Availability percentages are modelled against the category plan. They are replaced by the live stock feed at go live.
Store audit
Display, stock and process compliance scored on the same rubric everywhere, with a dated action against every gap.
Region
Stores audited
Average score
Open actions
Oldest open
North
10 of 20
92 / 100
1
19 days
West
9 of 17
90 / 100
1
6 days
South
8 of 15
88 / 100
2
11 days
East
4 of 8
86 / 100
1
16 days
Rubric
Dimension
Weight
Checked by
Window and display compliance
25%
Photo audit, scored
Stock availability against the plan
25%
Stock read
Advisor process and greeting
20%
Mystery call
Appointment and follow up discipline
20%
Desk record
Housekeeping and safety
10%
Checklist
One audit cycle covers 50% of the points of sale in a quarter, so every point is seen twice a year or better. Scores, actions and ageing are modelled on audit cycles of comparable networks.
Conversation intelligence
Every conversation is transcribed, coded and counted, so the brand learns what customers are actually asking, not what the desk remembers.
What the conversation was about
Share
What the desk does with it
Variant availability and price
30%
Stock read, band stated
Note and recommendation questions
25%
Consultation booked, samples sent
Gifting and packing
20%
Order raised with a date
Replenishment and refills
14%
Order or store visit
Authenticity and returns
11%
Escalated with the invoice checked
What comes out of it every week
Output
Goes to
Cadence
Top ten reasons customers called
Head of retail
Weekly
Requests for stock the store did not hold
Head of retail
Weekly
Questions the script answered badly
Head of marketing
Weekly
Objections before a lost enquiry
Head of customer
Fortnightly
Store level process gaps heard on calls
Head of service
Monthly, into the audit
Coding is at issue level. No individual customer and no individual advisor is profiled or ranked.
Call analysis
Every IRTH conversation is transcribed, coded and scored: what the caller wanted, what stopped them, what was promised and what happened next. This is the record the desk, the campaign team and the store network all argue from.
58,720
Calls analysed a month
38%
Positive sentiment on close
82 / 100
Average quality score
5.1m
Average call length
A day off the desk, identities masked
Call
Caller region
What it was about
Language
Length
Sentiment
Score
Outcome
C-5247
Bengaluru · North
Variant availability and price
English
3m 07s
Neutral
85
Not now
C-5284
Mumbai · West
Sling and crossbody enquiry
Hinglish
5m 18s
Positive
90
Message sent
C-5321
Delhi · South
Gifting and packing
Hindi
7m 29s
Negative
70
Callback set
C-5358
Hyderabad · East
Occasion clutches enquiry
Tamil
3m 40s
Neutral
81
Appointment booked
C-5395
Chennai · North
Authenticity and returns
Telugu
5m 51s
Positive
86
Message sent
C-5432
Pune · West
Sling and crossbody enquiry
Kannada
7m 02s
Negative
64
Callback set
C-5469
Kolkata · South
Note and recommendation questions
Marathi
3m 13s
Neutral
96
Appointment booked
C-5506
Ahmedabad · East
Occasion clutches enquiry
Bengali
5m 24s
Positive
82
Closed
What stopped the call, and what the desk did next
Objection heard
How often
What the desk says now
Next step written
Price against a competitor quote
8% of calls
Named back, answered from the record, then a dated visit offered
WhatsApp with the range sent, callback in 48 hours
Wants a discount the desk cannot give
9% of calls
Answered from the published work totes range, never with a discount
Appointment held, reminder call scheduled
Not ready, date not fixed
10% of calls
Named back, answered from the record, then a dated visit offered
WhatsApp with the range sent, callback in 48 hours
Store is too far
11% of calls
Answered from the published work totes range, never with a discount
Appointment held, reminder call scheduled
Waiting for the rate to move
12% of calls
Named back, answered from the record, then a dated visit offered
WhatsApp with the range sent, callback in 48 hours
Wants to see the piece first
13% of calls
Answered from the published work totes range, never with a discount
Appointment held, reminder call scheduled
What the transcript is mined for
Field pulled from the call
How it is used
Goes to
Reason code and category asked for
Feeds the enquiry desk and the stock view
Head of retail
Budget band the caller stated
Sets the range the advisor prepares
Head of retail
Occasion and date
Sets the ladder and the reminder call
Head of customer
Objection and competitor named
Feeds the drill and the campaign message
Head of marketing
Promise made on the call
Checked against the job or appointment record
Head of service
Consent and language preference
Written to the record for every future contact
Head of finance
Transcript volumes and scores are modelled on the current script until the brand's own telephony is connected. Caller identity is masked in every screen and every export.
Caller coaching
Every call the IRTH desk makes is scored on the same six behaviours, and the lowest scoring behaviour becomes next week's drill. Coaching is written at desk, region and issue level, never against a named individual.
58,720
Calls in scope for coaching a month
72 / 100
Desk coaching score, rolling four weeks
100%
Calls reviewed, no sampling
6
Drills shipped to the floor last month
The six behaviours, and where the desk stands
Behaviour
Adherence
What a pass sounds like
Opening and consent
88%
Brand named, purpose stated, consent captured in the first 15 seconds
Discovery depth
63%
Occasion, budget band and date asked before anything is recommended
Objection handling
59%
Objection named back, answered from the record, not from opinion
Proof used
61%
Certification, warranty or exchange terms quoted from the published range
Next step booked
80%
A dated next step with a named store or advisor
Write back
80%
Reason code and outcome on the record before the call ends
Lowest adherence right now is objection handling at 59%. That is the drill below.
Region scorecards
Region
Stores
Calls a month
Coaching score
Coach on
North
20
19,378
91 / 100
Opening and consent
West
17
16,442
84 / 100
Proof used
South
15
14,680
77 / 100
Objection handling
East
8
8,221
90 / 100
Discovery depth
This week's drills, written from lost conversations
Drill
Built from
What changes on the call
Owner
Objection handling drill
57 calls where the enquiry was lost after this step
Objection named back, answered from the record, not from opinion
Head of retail
Work totes objection drill
Objections heard before a lost work totes enquiry
Objection is named back and answered from the published range, then a visit is offered
Head of customer
Replenishment book drill
Calls where the balance or benefit was stated wrongly
The balance is read from the record and the visit is booked in the same call
Head of optometry
Service promise drill
Zip and hardware repair calls where a date was promised before the centre confirmed it
No completion date is stated until the job record carries one
Head of service
How a drill reaches the floor
Monday: the week's calls are scored and the lowest behaviour is picked by number, not by opinion.
Tuesday: three good calls and three weak calls on that behaviour are clipped, with identities masked.
Wednesday: the script line is rewritten and pushed to both the human desk and the voice agent.
Friday: the same behaviour is re-scored and the movement is reported to Head of retail.
Scores are modelled on the current script and comparable Indian voice desks until the brand's own recordings are connected. No individual advisor is ranked, scored or named in any output.
Quality record
Every conversation is scored on the same five dimensions, at issue and store level, so quality is a number the brand can argue with.
Dimension
Weight
What a pass looks like
Identification and consent
20%
Brand named, purpose stated, consent captured
Accuracy of what was said
25%
No price, discount or warranty claim outside the record
Language and courtesy
15%
Caller's language matched, no talking over
Next step captured
25%
A dated next step with a named owner
Write back
15%
Reason code and outcome on the record
94 / 100
Current rubric score
100%
Conversations scored, not a sample
6
Script fixes shipped last month
Market sense · web intelligence
Six buckets, read off the open web for IRTH: competitor moves, category demand, the brand's own online reputation, the price and offer message in market, retail expansion, and the social conversation. Each bucket opens with the analysis — how the brand is actually doing on that front and what to do next — and the sources it was written from sit underneath it as the evidence.
60+
IRTH stores and shop-in-shops
₹150 Cr+
Accessories scale
5
Named competitors tracked
60
Sources across six buckets
Who is tracked against IRTH
BaggitHidesignLavieCapreseDa Milano
Category read as: women's handbags and accessories India. Reputation read from amazon.in, myntra.com, trustpilot.com and open consumer forums.
The read
IRTH is accelerating prime offline retail expansion toward 100 stores while facing heavy competitor discounting in core sub-₹2,500 tiers.
IRTH is maintaining strong physical retail momentum backed by Titan, opening key metro stores in Mumbai, Chennai, and Noida toward its 100-store FY27 target. The category environment is favorable, with the Indian handbag market projected to expand at an 8.8% CAGR, led heavily by tote silhouettes. However, mid-tier competitors like Accessorize and ALDO are applying pricing pressure via deep promotional discounting, while Baggit pushes international expansion. IRTH's primary action must be fortifying tote inventory and capturing direct digital feedback to defend margins without relying on price erosion.
Written off 60 sources for IRTH. Every claim is backed by the linked sources under each bucket.
Bucket 01
Competitor moves
What have the named competitors done in the last weeks that the desk should know?
Competitors are launching cross-border expansions and seasonal collections
Baggit is expanding its retail presence into Sri Lanka and teasing new product drops, while Hidesign is actively promoting handcrafted leather collections like the Rue Soleil through video reviews. Lavie and other domestic peers continue targeted mall activations and smart-casual promotions to defend market share. These moves show competitors targeting both regional expansion and higher perceived craftsmanship.
Baggit announced an expansion into Sri Lanka alongside a planned product drop for August 1, 2026.
Hidesign is driving influencer and video showcases around its 2026 handcrafted leather lines, including the Rue Soleil bag.
Lavie is executing regional offline retail promotions, including mall displays at Rama Magneto Mall.
What to do next: Monitor the commercial traction of Baggit's Sri Lanka foray to identify viable adjacent regional markets.
India Handbags Market size is expected to grow by USD 2207.4 million from 2026-2030 expanding at a CAGR of 8.8% during the forecast period.
technavio.com
Low
Bucket 02
Industry and category demand
Which way is the category itself moving, in volume and in value?
The Indian handbag market is expanding steadily at an 8.8% CAGR
Category demand remains robust, with the Indian handbag sector projected to expand by USD 2,207.4 million between 2026 and 2030. Tote bags remain the dominant silhouette globally and domestically, capturing over 41% of handbag product share. Growth is heavily supported by rising disposable incomes and demand for functional, everyday lifestyle accessories across Asia Pacific.
The Indian handbag market is forecast to grow by USD 2,207.4 million from 2026 to 2030 at an 8.8% CAGR.
Tote bags accounted for 41.21% of the global handbags market share in 2025.
The broader Asia Pacific region captured a dominant 38.5% global revenue share in 2025.
What to do next: Ensure tote silhouettes receive prioritized supply chain allocation to capture the largest share of category volume.
# Handbag Market (2026 - 2033)
$86.9B
Market Estimate, 2026
$92.3B
$146.0B
CAGR, 2026–2033
6.8%
## **Handbag Market Summary**
The market in Asia Pacific dominated with a revenue share of 38.5% in 2025. The market is driven by the growing fashion awareness and rising disposable income.
### Market Size & Forecast
# Handbags Market Size & Share Analysis - Growth Trends and Forecast (2026 - 2031)
## Handbags Market Analysis by Mordor Intelligence
- By product type, tote bags commanded 41.21% of the handbags market share in 2025, while bucket bags are projected to grow at a 5.49% CAGR to 2031.
- By category, the mass segment held
# Handbag Market Size, Share & Industry Analysis, By Product Type [Tote, Clutch, Satchel, and Others (Hobo, Body Cross, and Saddle)], By Raw Material (Leather and Fabric), and By End-User (Men and Women), and Regional Forecast, 2026-2034
## Handbag Market Key Takeaways
- The Tote segment is projected to lead the market
# Handbag Market Size, Share, and Growth Forecast, 2026 - 2033
## Companies Covered in Handbag Market
### What is the handbag market size in 2026?
-
### What are the key trends in the handbag market?
Key trends include rising demand for versatile and functional product designs, increasing penetration of digital and o
# Luxury Handbag Market
Luxury handbag sales will expand through 2036, with tote bags at a 33.8% share of the product segment in 2026. Leather leads the material segment with a 72.5% share. The market is expected to reach USD 28.9 billion by 2026-end and USD 52.81 billion by 2036 across regions.
May 06, 2026
[Rahul P
The Handbag Market, valued at USD 71.17B in 2026, is projected to reach. It will grow from $67.18 billion in 2025 to $71.17 billion in 2026 at a compound ...
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youtube.com
Low
Bucket 03
Brand online reputation
What are customers saying about the brand in public, and what is the recurring complaint?
Online consumer review visibility is clouded by unrelated brand homophones
Search visibility for IRTH on third-party consumer review sites is heavily diluted by unrelated businesses, such as software vendor Irth Solutions and domain urth.co. There is a lack of structured, verified customer reviews for IRTH handbags on open rating platforms. The brand desk currently lacks clear third-party sentiment feeds to isolate product quality complaints from search noise.
Public consumer review boards conflate IRTH handbag queries with ratings for urth.co and Irth Solutions.
No direct, verified customer review footprint exists for IRTH accessories on major open rating aggregators.
Marketplace platforms like Myntra house lifestyle catalog traffic without accessible aggregate sentiment reporting.
What to do next: Claim official consumer review profiles and deploy post-purchase review prompts to build clean brand sentiment data.
Rating 4.8(171)ishikesh has 5 stars! This company hasn't invited customers recently, so reviews may not be representative Replied to 100% of negative reviews Typically takes ...
Rating 4.8(21,027)This company invites their customers to review, whether positive or negative Replied to 98% of negative reviews Typically replies within 1 month
Rating 4.2(613)Customer reviews 4.2 out of 5 stars4.2. Customers find the rug to be of top quality, with vibrant colors and a perfect size. not like the picture. No complain ...
Rating 3.5(37)Irth Solutions has an employee rating of 3.5 out of 5 stars, based on 37 company reviews on Glassdoor which indicates that most employees have a good working ...
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CALL 614-784-8000 x2 or EMAIL support@irthsolutions.com
irthsupport.irthsolutions.com
Low
Bucket 04
Pricing and offers in market
What price and offer message is live in the market right now?
Rival brands and fashion retailers are discounting heavily below ₹2,500
The accessory market is experiencing intense promotional discounting, with brands like Accessorize London creating dedicated low-price brackets under ₹999, ₹1,599, and ₹2,499. ALDO and marketplace platforms like Nykaa Fashion are maintaining continuous markdowns across crossbodies and totes. This puts pressure on full-price realization for lifestyle brands attempting to sell above entry-level bands.
Accessorize India is actively promoting price-point tiers under ₹999, ₹1,599, and ₹2,499, cutting items from ₹6,795 to ₹2,446.
Social commerce channels are discounting tote bags down to ₹500 with 20% to 50% price cuts.
ALDO is running marked-down promotions across shoulder bags, crossbody bags, and totes.
What to do next: Defend price realization by emphasizing Titan quality assurances rather than engaging in margin-diluting discount battles.
The Premium Tax Credit is a refundable tax credit designed to help eligible individuals and families with low or moderate income afford health insurance
Irth Capital Management has lined up a financing package consisting of $725 million. Irth's bid in May 2026. The $47 per share offer price is the number that ...
Shop Women Handbags on sale at ALDO. Enjoy discounted prices on a wide range of styles, including Crossbody Bags, Totes, Shoulder Bags, and more. Price reduced ...
15-day returnsShop trendy handbags for women online at Accessorize India. PRICE + 2499/- & under 1599/- & under 999/- & under SHOP BY OFFER ・ ₹ 2,446.00 ₹ 6,795.00 ・ get ...
Qatari-backed investment fund Irth Capital this month offered to pay $47 a share to buy Papa John's International, in a second attempt ...
reuters.com
Low
Bucket 05
Retail network and expansion
Where is retail space being added, by the brand and around it?
Network rollout is scaling fast toward the 100-store milestone
IRTH is aggressively scaling its brick-and-mortar footprint with exclusive openings in Mumbai at Palladium Mall, Chennai, and Noida. The brand is executing on its plan to reach 100 stores by FY27 to help Titan's bag division target ₹1,000 Cr in revenue. Store formats are diversifying across large mall flagships and targeted 350 sq. ft. boutiques in high-traffic shopping centers.
IRTH opened exclusive brand stores in Mumbai at Palladium Mall and in Chennai.
The business opened in Noida with an active pipeline of 25 additional stores on the horizon.
Network expansion includes compact formats like a 350 sq. ft. store at Phoenix Mall to support the FY27 100-store goal.
What to do next: Track trading density and sales per square foot across compact 350 sq. ft. footprints before signing the next 25 leases.
IRTH debuts in Mumbai with its first exclusive store at Palladium Mall. Explore premium handbags designed for everyday mobility, crafted for modern women.
The new store, located on the first floor outside Allen Solly Women, occupies a 350 sq. ft. carpet area and offers visitors a carefully curated range of ...
India Handbags Market size is expected to grow by USD 2207.4 million from 2026-2030 expanding at a CAGR of 8.8% during the forecast period.
technavio.com
Low
Bucket 06
Digital and social conversation
What is the brand's conversation on social, creator and video platforms?
Campaign messaging centers on functional mobility using collaborative creator formats
IRTH's social presence is anchored by its 'Always A Little Ready' campaign, framing the handbag as a functional partner for spontaneous everyday use. The broader accessory segment relies heavily on Instagram collaboration reels and creator barter campaigns to drive discoverability. Leveraging joint collaborator posts will be critical for IRTH to widen top-of-funnel reach without inflating customer acquisition costs.
IRTH launched the 'Always A Little Ready' social campaign focusing on everyday readiness and functionality.
Accessory brands are heavily utilizing Instagram collaboration reels to pool follower reach between creators and labels.
Creator partnership calls and barter engagement remain the predominant growth tactic for Indian lifestyle accessories online.
What to do next: Measure store footfall and site visits directly attributed to the 'Always A Little Ready' creator activations.
IRTH has launched a new campaign titled 'Always a Little Ready', centred on handbags as part of everyday routines and personal organisation.
afaqs.com
Low
How each bucket is built
#
Bucket
The question it answers
What it reads
01
Competitor moves
What have the named competitors done in the last weeks that the desk should know?
Launches, store openings, campaigns, price led offers, funding and leadership news.
02
Industry and category demand
Which way is the category itself moving, in volume and in value?
Category growth, input costs, festive and season demand, regulation and duty.
03
Brand online reputation
What are customers saying about the brand in public, and what is the recurring complaint?
Reviews, complaint boards, consumer forums, service and delivery grievances.
04
Pricing and offers in market
What price and offer message is live in the market right now?
Discount events, exchange schemes, making charge and bank offers, marketplace pricing.
05
Retail network and expansion
Where is retail space being added, by the brand and around it?
New stores, city entries, franchise news, mall and high street expansion.
06
Digital and social conversation
What is the brand's conversation on social, creator and video platforms?
Creator collaborations, campaign reception, trending formats, share of voice.
Results are ranked by how sharply they read against the brand, so complaints and competitive moves surface first. Severity is a keyword read on the headline and summary, not a judgement.
Value model
Move any input. Everything recalculates. Every figure starts from the published IRTH network and is editable.
Inputs
Modelled outcome, a year
₹2.6 Cr
From enquiries answered and converted
₹3.6 Cr
From dormant customers brought back
₹44.4 L
Service handling cost avoided
₹6.6 Cr
Total modelled value, before any fee
Service saving is modelled at ₹42 of handling cost avoided per conversation the desk closes without a store call back.
Data readiness
What is connected on day one, what is modelled today, and what IRTH needs to hand over for the pilot to go live.
Input
Status
Note
Store network and locations
Published
60+ IRTH stores and shop-in-shops
Category and price ladder
Published
From the brand range
Enquiry volume and source mix
Modelled
From comparable networks of similar store count
Customer book and dormancy
Modelled
Replaced in one session with the brand team
Service job volume and turnaround
Modelled
From service desk throughput benchmarks
Loyalty tier membership
Modelled
Tier structure as published
Consent and contactability flags
Needed
Required before the first outbound call
What is needed to go live
A contactable customer extract with consent flags, in any format.
Store and advisor calendars, or a single sheet per region to start.
One session with the IRTH team to replace every modelled volume with the brand's own.
Required inputs
What the IRTH team hands over, in whatever format it already exists, for the pilot to run on the brand's own numbers.
Input
Owner
Format that is enough
Needed by
Contactable customer extract with consent flags
Head of customer
CSV or a database view
Before the first outbound call
Enquiry feed from website, store and marketplace
Head of marketing
Webhook or a daily file
Week 1
Store and advisor calendars
Head of retail
One sheet per region to start
Week 1
Category and price ladder in force
Head of retail
The current range sheet
Week 1
Replenishment book
Head of optometry
Account level extract
Week 2
Service and job records
Head of service
Export from the service system
Week 2
Telephony numbers and caller ID
Head of retail
Numbers plus provider access
Before go live
Nothing here blocks the console. Every input replaces a modelled figure already on the screen.
Method and limits
How the pilot runs on IRTH, week by week, and what the system will not do.
Week
What happens
What the brand sees
Week 1
Data session, scripts drafted, numbers provisioned
Console on the brand's own figures
Week 2
Both agents live on a small call list
First conversations and quality scores
Weeks 3 to 6
Ladders switched on segment by segment
Weekly reason codes and outcomes
Weeks 7 to 12
Appointments, service and the trigger desk added
Value model against actuals
Month 6
Review against the model
Keep, widen or stop, in writing
What this system will not do
It will not quote a price, a discount or a making charge outside the published range.
It will not claim a warranty outcome before the service centre has confirmed it.
It will not call a customer who has declined or opted out, for any reason.
It will not score, rank or profile an individual customer or an individual advisor.
It will not pretend to be human when asked directly.
Commercial terms
One flat retainer for the platform and the desk, usage billed as pass through at cost, and a review at month six.
Scope
What it covers
Commercial
Pilot, one brand
IRTH consoles, both voice agents, the desk and the quality record
Flat monthly retainer
Group scope
Every Titan brand on the same platform and identity spine
Retainer per brand, tapering
Usage
Telephony, transcription and model usage
Pass through at cost, itemised
Carried free until month six
Console build, script work, audit rubric and reporting
No charge
Governance
No individual customer is scored, profiled or ranked. Quality sits at store and issue level only.
Consent and do-not-call flags are respected on every attempt, with a stop rule per segment.
Every conversation is retained for a stated window and is available to the brand team in full.