Customer story

Every search ad was precise. The landing page was not.
ACT Fibernet ran carefully targeted paid search campaigns across 23 cities — reaching buyers at the exact moment they were searching for WiFi, broadband, or fiber internet. But every click, regardless of city or search intent, landed on exactly the same generic page. Fibr gave every search ad its own contextually matched landing experience. The result: 40% more leads, from the same spend.

Company Overview
ACT Fibernet, at a glance.
India's third largest broadband provider, connecting homes and businesses to high-speed fiber internet across 30+ cities. A single platform covering plan selection through to last-mile installation and ongoing support — serving millions of individuals who depend on the internet for work, streaming, gaming, and everything in between.

The Challenge
Every search was specific. The page that received it wasn't.
Performance campaigns ran across 23 cities, reaching buyers across four distinct search categories — WiFi, Broadband, Fibernet, and Internet. Each keyword represented a different use case and a different stage of the buying decision. But regardless of city, search category, or intent, every visitor landed on the same page: the same hero, the same form, the same generic "Get Offer" CTA — with no reference to their location, their search, or the plan they came looking for.

The Solution
One URL. Infinite matched experiences.
Fibr tackled the problem in three deliberate steps — analysis to expose the gaps, signals to structure personalization, and setup to deploy at scale. From one generic page to 1,500+ matched experiences, without a single engineering ticket.
Step 1
The Analysis — two experience gaps costing conversions
Analysis of landing page performance and consumer behaviour patterns revealed two clear problems. First: the page didn't reflect the search category — a visitor searching for WiFi in Chennai or Broadband in Hyderabad arrived at a page that acknowledged neither. Second: the experience had no use case or geo connection — the category, the city, and the intent were all present in the keyword and the ad, but none of it appeared on the page.

Step 2
The Signals — three dimensions every search was already carrying
Fibr's URL Agent structured the personalization around three signals already present in every search: product category (Internet, WiFi, Broadband, Fibernet), city-level geo-targeting across 20+ cities, and primary use case (Working & Meetings, Streaming & OTT, Gaming & Networking, Smart IoT Hub). Every combination got its own matched page.

Step 3
The Setup — 1,500+ pages, zero engineering tickets
Every personalized variant was built from ACT Fibernet's own brand guidelines, competitor positioning, and keyword context — without involving the engineering team once. Each page was pre-reviewed for brand accuracy, hallucinations, compliance, and copy quality before sign-off. Every matched experience loaded without visual flicker, personalised from the very first frame.

One URL, Infinite Experiences
The same page. A different experience for every search that pointed to it.
A visitor searching "best wi-fi plans for work from home" saw a work-focused form. A visitor searching "broadband full home wifi coverage" saw a full-home broadband message. A visitor searching "high speed internet for gaming" saw a gaming-tailored experience — all from the same URL.

The New User Experience
Every screen after the click carried the context of the search that started it.
Category, city, and use case followed the visitor all the way through — from the Google search, to the first fold, to geo-targeted plan pricing, to use-case specific content. Nothing was lost between the ad and the page.

Part A — The Pilot
Personalized pages outperformed the control on every metric.
The pilot ran a controlled experiment comparing personalized landing pages against the original generic page. Personalized variants won across every metric measured.
Form Fill Rate
↑11.6%
More form fills and MQLs
Creating a wider top of funnel without increasing spend or changing the ad strategy.
Conversion Rate
↑24%
More form fills and MQLs
Creating a wider top of funnel without increasing spend or changing the ad strategy.
Adjusted CPL
Stable
More form fills and MQLs
Despite industry-wide CPC rises driven by festival seasonality, the adjusted CPL remained stable.
Adjusted CPA
↓20%
More form fills and MQLs
Consistently generating more qualified leads lowered the adjusted CPA across the pilot period.
At ACT, we quickly adopted Fibr AI to align our ads with personalized landing pages, achieving great results with minimal effort. We're excited to scale this across our campaigns for increased growth and improved team productivity.
Ravi Karthik
Chief Marketing Officer · ACT Fibernet
Ongoing Campaign Results
Scaled Pan-India. Consistent uplift across every city, every month.
After the pilot, the campaign rolled out across 23+ cities. The conversion uplift was consistent — every high-volume city, every month the campaign ran, with quality score moving from 3 to 8 across ad groups over 8 months.
Key Insights
What this teaches us about high-intent paid search.
Insight 01
Page relevance converts — and makes every dollar go further.
When the landing page matched the search, Google's quality score moved from 3 to 8. That improved ad auction performance, brought more suitable visitors through, and lowered adjusted CPA by 20%. The page improvement paid back through the entire campaign economics, not just the form fill rate.
Insight 02
What a buyer calls their need is not semantic. It is a page brief.
WiFi, Internet, Fibernet, and Broadband are four different buyer mental models at four different stages of the decision. A page that treats them as interchangeable gets the argument wrong for all of them. Matching the page to the category was what unlocked the 32% acquisition uplift.
Insight 03
Regional content is the trust signal that supports the connection decision.
In metros, Netflix is a strong signal. In Tier 2/3 Southern cities, regional OTTs like SUN TV resonate more. Showing low-relevance content for a region means the page fails the last mile of conversion even when everything else is right.


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