How TVA Group (Now Part of Dentsu) Used AI to Discover Influencers Who
Authentically Talk About Their Mothers—Repeatedly
Context
TVA Group, now part of Dentsu, was tasked with launching a heartwarming influencer campaign around
motherhood and family bonding for two clients simultaneously—StyleUp (Aditya Birla Group) and
Flipkart Fashion. The goal went beyond finding popular creators.
"Find creators who don't just mention their mom on Mother's Day—but actually talk about her
across multiple posts, like she's a real part of their story."
The campaign required influencers whose connection with their mothers came through naturally
and frequently—something no basic search method could surface.
Challenges
Hashtag-based filtering (#mom, #mothersday) was too seasonal and surface-level
Bios rarely reflect personal relationships
Visual scans couldn't capture the context of the relationship
Manual review of post transcripts was unscalable under a fast campaign timeline
Solution
Topic Detection Through NLP-Powered Caption & Transcript Analysis.
Galvor's AI-powered influencer intelligence platform leverages advanced Natural Language
Processing to semantically analyse influencer content across platforms.
How it worked
Parsed post captions, video transcripts, and audio descriptions from over 800 lifestyle creators
Detected recurring patterns linked to "motherhood": sentimental phrases, narrative anecdotes, daily mentions and role-modelling references
Distinguished between genuine mentions vs one-off promotional posts
Scored influencers on Frequency, Depth of reference, and Engagement on mom-specific posts
Sample platform output — frequency of mom-related content per creator
Impact
✦A qualified list of influencers who had consistently talked about their moms across multiple posts
✦Annotated post samples showing context-rich maternal mentions
✦Audience engagement metrics specific to "mom" content, helping the brand predict emotional resonance
The right influencer isn't just someone with reach—it's someone with a real story to tell.
AI-based topic modelling lets you discover influencers who align with the
emotional depth of your campaign, scale storytelling-specific discovery without
compromising nuance, and deliver campaigns that feel genuine and audience-aligned.
Emotion + intelligence = resonance.
How V Perfumes Found Hyper-Local, Language-Aligned
Influencers to Connect with Immigrant Audiences
Context
V Perfumes, a premium UAE fragrance house known for its modern take on traditional scents—
oudh, bakhoor, and musk—was planning a storytelling-first influencer campaign across major
GCC cities. In a country where immigrant communities form the cultural majority, the brief
wasn't about showcasing luxury. It was about speaking in their languages.
The brand needed influencers using the hyper-local voices heard in homes, souks, salons,
and taxis—ensuring products felt culturally familiar, not aspirationally distant.
Challenges
Standard influencer tools could filter by country, follower count, and general category. But they couldn't answer:
Does this influencer speak Hindi or Malayalam?
Do they use Sudanese Arabic or Egyptian slang?
Do they code-switch between Urdu and Khaleeji in their stories?
Manually checking every post and video would be slow, subjective, and impossible to scale under a tight timeline.
Solution
Language-Driven Vetting with Galvor AI
Parsed captions, video/audio transcripts, and speech patterns across a large pool of UAE-based creators
Applied natural language detection to tag influencers by primary language, informal/colloquial speech (Hinglish, Arabizi), and code-switching patterns
Curated a shortlist of 150+ influencers open for barter collaborations
Impact
4–5
Days of manual vetting eliminated
150+
Language-verified creators shortlisted
↑
Organic engagement via native-language content
The campaign didn't just showcase fragrance—it evoked memory, belonging, and personal identity. Content in native tongues felt like a conversation, not a promotion.
Why it matters
In diverse markets like the UAE, hyper-local relevance beats broad appeal. For brands
serving immigrant or multicultural audiences, heritage products, or community-first campaigns—
language is the bridge to trust.
Accelerating Influencer-Brand Fit: Visual Attribute-Based Discovery at Amazon India's Live Commerce Platform
Context
Amazon India runs high-impact creator-led campaigns on its live commerce platform—where
brands showcase products and engage buyers in real-time. Every product demands a very
specific kind of influencer. Shaving kits need bearded, fashion-forward creators. Baby
care products need parenting influencers—but not just any parent; ones with kids under 3.
Challenges
The manual process before Galvor:
Discovery based on follower count and engagement metrics
Manual review of hundreds of profiles
Manual visual checks to validate influencer relevance
~2–3 man-days per campaign just for shortlisting
Time-intensive, inefficient, and subjective—especially for fast-turnaround live commerce events.
Solution
For the Baby Care Products Campaign, the brand needed parenting influencers with kids under 3.
Galvor AI-powered Visual Discovery
Analysed over 500 influencers in the Family & Parenting category
Filtered using profile photos, bio keywords, and latest media posts
Shortlisted only those with a young child visible in recent content, matching engagement and follower criteria, and showing authentic parenting content
Final output — verified child age per influencer
Impact
2+
Man-days saved in influencer discovery
⚡
Highly relevant shortlist delivered instantly
↑
More time for scripting, pre-production, and creative
Why it matters
AI can drastically reduce time-to-launch, even when nuanced criteria like
"parent with a toddler" are involved. You don't need to compromise between speed and specificity.
If your team is scaling live commerce or category-specific influencer pushes,
visual attribute discovery gives you an unfair advantage.
How Sharaf DG Drove MacBook Air M4 Footfall with
Brand-Safe Creator Selection in Dubai
Context
For the MacBook Air M4 launch in 2025, Sharaf DG—the UAE's leading electronics retailer—had
two goals: build a brand-safe creator roster that authentically represented the Apple ecosystem,
and convert online buzz into real footfall across its flagship stores in Dubai.
In a market saturated with creator-led tech content, one misaligned post from an influencer
who'd previously endorsed Windows laptops could undermine the entire campaign. Getting the
creator selection right wasn't just a brand safety exercise—it was the foundation for driving
people into stores on launch day.
Solution
Phase 1 — Brand Safety Vetting with Galvor AI
Parsed historic posts, captions, tags, and hashtags across all platforms
Flagged any mention of Windows-based devices, Windows logos or product placements, and hashtags linked to competitor campaigns
Ranked brand fit score based on topical consistency and product category overlap
Delivered a confidence report within minutes: 0 instances of Windows endorsements in the last 12 months
Example — AI scan for Windows-based content in the past 3 months
Phase 2 — Driving In-Store Footfall for the M4 Launch
Identified Dubai-based tech and lifestyle creators whose audiences had strong overlap with key Sharaf DG retail catchment zones
Briefed creators to anchor content around the in-store experience—live demos, early-access events, and launch-day offers—with YouTube UTM tracking on every link
Coordinated content drops in sync with launch-day store openings, converting online buzz into physical foot traffic
Impact
250k
Content views across the campaign
1,200+
In-store visits tracked via UTM links
0.5%
View-to-visit conversion rate
100%
Brand safety — zero competitor conflicts found
Why it matters
Brand safety and commerce aren't separate goals—they're two sides of the same coin.
Getting the right creator locked in is what makes a launch campaign credible online
and effective on the ground.
Precision in selection = performance at every touchpoint.
How Halo Care Launched Fast and Iterated Even Faster with Structured Creator Experimentation
Context
Halo Care, a fast-growing men's personal care brand offering face washes, shaving kits, and
beard oils, came to Galvor with a two-part brief: get a nationwide creator campaign live
fast, then figure out what was actually working—fast. They didn't just want reach;
they wanted a system for continuously optimising which creators, regions, and content tones
drove the best results with urban millennial and Gen Z audiences across India.
Challenges
Traditional outreach looked like this:
Export influencer lists from discovery tools
Manually find and message creators via Instagram or email
Wait days for replies, then re-explain the brand in every thread
Track responses, budgets, and contracts across scattered spreadsheets
Time-consuming, repetitive, prone to drop-offs, and difficult to manage for 50+ influencers simultaneously.
Solution
The brand partnered with Galvor's Influencer Onboarding Team—a dedicated service arm that handled end-to-end coordination with shortlisted creators.
What Galvor delivered as a service
Influencer Outreach: Reached out to 70+ pre-approved creators with personalized communication; shared briefs, timelines, and sample creatives; managed all back-and-forth
Qualification & Vetting: Held intro calls to evaluate tone, content alignment, and professionalism; flagged potential brand fit issues
Rate Negotiation & Contracting: Negotiated within target CPM brackets; finalized scopes of work; secured digital sign-offs
Hand-Off: Delivered a fully onboarded list—ready with content ideas, schedules, and point-of-contact details
Part 2 — Creator Experimentation for Faster Iteration
Rather than committing the full budget to a single creator archetype, Halo Care and Galvor
ran simultaneous tests across distinct cohorts—enabling sprint-by-sprint learning.
✂️
Bald creators vs. non-bald creators
Testing whether a men's grooming brand resonated more authentically with creators who were visibly invested in their own appearance and grooming journey
🗺️
Regional South & West vs. North East creators
Exploring how regional dialect, cultural nuance, and audience affinity shaped trust and purchase intent across different Indian demographics
🎭
Content tone — comedic/relatable vs. tutorial-led/aspirational
Identifying which format drove stronger engagement and conversion intent for personal care
Creator cohort tracking — Galvor platform
Galvor's tagging and performance analytics layer enabled sprint-by-sprint insights—the brand
didn't wait weeks for a post-campaign debrief. Each iteration fed directly into the next:
sharper creator shortlisting, tighter content direction, and faster time-to-launch every cycle.
Impact
10→5
Days to onboard creators — cut in half
70+
Creators reached with personalised outreach
3x
Cohorts tested simultaneously for faster creative learnings
Why it matters
Launching fast is table stakes. The real edge comes from building a system that tells you
what's working fast enough to act on it. Structured creator experimentation—with the
right analytics layer—turns every campaign into a learning loop.
Launch fast. Learn faster. Scale what works.
How TVA Group (Now Part of Dentsu) Unlocked Deep Content Intelligence
for Flipkart Fashion's Creator Campaigns
Context
Flipkart Fashion, one of India's largest fashion e-commerce platforms, engaged TVA Group
for a full social audit spanning 6 months of content, ad spend, and influencer activity.
The ask: go beyond vanity metrics and surface the specific content formats, tones, and
creator archetypes that actually drive followers, engagement, and cost efficiency.
Galvor's AI-powered analytics engine processed 242 posts, ₹30L+ in video ad spend, and
a sample set of creator profiles — delivering an intelligence framework that feeds directly
into future briefs.
Account Overview — Last 6 Months
332K
Followers
242
Posts in 6 months
Nov
Peak engagement month (Diwali season)
1,211
Avg. likes per post
431
Avg. comments per post
10.97%
Engagement depth (high-intent)
Content Type Analysis
85% of all content is Video, with 100% of ad spend directed at Video.
Carousel posts — despite being less than 2% of content — delivered the lowest Cost Per
Follower (CPF) and highest engagement depth, making them a significantly underutilised format.
Post Type
# Posts
Followers Gained
CPF (INR)
Audience ER
Engagement Depth
Carousel
4
1
—
0.10%
6.17%
Image
36
17,650
—
0.06%
2.98%
Video
237
250,172
₹18
0.09%
3.85%
Image & Carousel — Visual Analytics
Contest and giveaway posts — and content tied to Big Billion Day — drove significantly
higher engagement. Posts around generic Independence Day themes or plain product displays
consistently underperformed.
Text Hook Sweet Spot: 20–30% of Screen
Galvor's visual AI analysed pixel coverage of text across all image and carousel posts.
Both likes and comments peak when text occupies 20–30%
of the post frame — and decline sharply beyond 30%.
Top 30% posts — dominant keywords: contest, giveaway, follow, tag, Big Billion, Wrogn, lucky winner
Bottom 30% posts — dominant keywords: independence, fashion, spirit, free — plain posts with no interactive hook
Note: Creator data based on sample set of 1 post each. Abhinav Mahajan and Aditya Vashisht
lead on raw likes & audience ER; Abhishek Kumaarr leads on comments and engagement depth.
Why it matters
This audit turned 6 months of content into a playbook. Funny hooks beat plain styling.
Contests beat product shots. Text coverage of 20–30% beats both zero and too much.
And the cheapest follower acquisition (CPF ₹6–₹18 via Video) coexists with the deepest
engagement (Carousel at 6.17% depth). You don't have to guess at what works—
Galvor makes the brief write itself.
