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CASE STUDY. LIQUIDTEXT · iOS · APP STORE OPTIMIZATION. iPAD · PDF READER

Discovered.Downloaded.

An iPad PDF and document reader with real product depth — hidden behind an App Store title the search algorithm couldn't parse. How iExcel rewrote the discoverability layer.

Engagement
iOS App Store Optimization
Scope
Title · Keyword field · Competitor matrix
Platform
iOS · iPad · U.S. App Store
Category
Productivity · PDF & Annotation
iPad held in hand — the App Store discoverability surface
// iOS · iPAD PRODUCTIVITY
Chapter 01 · The Setup

A serious iPad app. A store listing running on defaults.

LiquidText is an iPad PDF and document reader built for people who actually read — researchers, students, analysts, lawyers. The product handled annotation, highlighting, and cross-document markup in a way the flat "open a PDF" apps didn't. That kind of depth is the reason a user opens the App Store in the first place. It's also the kind of depth that rarely survives the trip from search bar to install button.

When iExcel picked up the engagement, LiquidText's App Store surface was doing what most product-first apps do — leaning on the brand name to carry a listing that the search algorithm couldn't parse. The title was written for humans, not for the ranker. The keyword field was doing double duty for terms already inside the title. The competitive set — Adobe, FoxIt, PDF Expert, GoodReader — was quietly claiming the generic queries LiquidText should have been showing up in.

The brief wasn't a rebrand. It was a discoverability rewrite — a tighter title, a smarter keyword field, and a competitor-matrix read that showed the team exactly which queries the app was leaving on the table.

iPad with a document on screen — the discoverability surface
Chapter 01 · The store surface
Chapter 02 · The Competitor Matrix

Twelve PDF apps. One ranking board.

Before touching the title, we mapped the field. The competitive set for an iPad PDF and annotation app in 2015 wasn't a mystery — it was a dozen apps with real download momentum, real store copy, and real keyword positions. What was missing was a single view of how LiquidText compared against each of them on the queries a serious iPad user would actually type.

We pulled SearchMan and Sensor Tower data on each competitor: keyword hits, keyword effectiveness index, category traffic and difficulty scores, and app-rank position on the queries that mattered. The output was a benchmark board — one row per competitor, one read on where LiquidText was under-indexed.

// COMPETITIVE ASO MATRIX · U.S. iPad · PDF + ANNOTATION SEP 2015 · SEARCHMAN + SENSOR TOWER
LiquidText
TRACKED KWs100
POSITIONUnder-indexed on generics
Adobe Acrobat Reader
TITLE CLAIMCategory-owning brand
RISKOwns "adobe" · "acrobat"
FoxIt Mobile PDF
TITLE CLAIMPDF-native positioning
RISKOwns "foxit" · challenger "pdf"
Xodo PDF
TITLE CLAIMFree-tier PDF reader
RISKContests annotation queries
PDF Pro
TITLE CLAIMReader-first name
RISKContests generic "pdf"
PDF Reader by Kdan
TITLE CLAIM"Reader" in name
RISKContests "pdf reader"
iAnnotate PDF
TITLE CLAIMAnnotation-first
RISKHead-to-head on "annotate"
PDF Expert 5
TITLE CLAIMProsumer PDF
RISKOverlaps LiquidText audience
GoodReader
TITLE CLAIMReader-owning brand
RISKContests generic "reader"
PDF Max
TITLE CLAIMReader + editor
RISKContests "pdf" long-tail
PDFpen
TITLE CLAIMMarkup-first
RISKContests "markup" surface
PDF Connoisseur
TITLE CLAIMOCR + reader
RISKContests long-tail "pdf" set
12+
Competitor Apps Benchmarked · ASO Matrix
SearchMan hits, KEI, Sensor Tower traffic and difficulty scores, app-rank positions — one view of the competitive field before the rewrite.
Chapter 03 · The Title Rewrite Board

Same product. A title the ranker can actually read.

An App Store title has two audiences — the human scanning the results, and the ranker parsing the words. The old title was written entirely for the human. Long, conversational, brand-first — and structured so the search algorithm couldn't cleanly pick up the terms a user would actually type. The rewrite kept the product intact and put the discoverability signals up front.

// APP STORE TITLE REWRITE · LIQUIDTEXT · iOS DELIVERED · SEP 2015
// Before · The old title
LiquidText - PDF and Document Reader for Annotating, Researching, Highlighting and More
Brand-first. Conversational. Long. The discoverability terms sit buried in the middle of the string — where the ranker weighs them least.
brand-first verbose buried keywords
// After · The recommended rewrite
LiquidText PDF and Docs Reader - Great for Doc Highlighting, Annotating, Markups, and Researching
Discoverability terms pulled forward. "PDF" and "Docs Reader" sit right after the brand. "Highlighting," "Annotating," "Markups," and "Researching" all present — parseable.
pdf docs reader highlighting annotating markups researching
// SOURCE · SEARCHMAN + SENSOR TOWER · U.S. iPad // DESIGNED TO CAPTURE 7 DISCOVERABILITY TERMS
Chapter 04 · The Keyword Field

100 characters. Zero wasted ones.

The iOS keyword field is a 100-character line no user ever sees — and one of the highest-signal inputs the App Store ranker takes. The rule that catches most product-first apps: never repeat a term already in your title. Every word inside the field has to earn its slot on the discoverability graph, not double up on what the title is already claiming.

We rebuilt the field around two intents. First, the generic PDF and document terms a serious iPad user would type without knowing any brand. Second, the competitor-adjacent terms — the ones a user searching for "adobe" or "foxit" might see LiquidText surface against. Both targeted, both parseable, both distinct from anything already in the title.

iPad close-up — the keyword field surface
Chapter 04 · The 100-character line
// iOS KEYWORD FIELD · RECOMMENDED SET // COMPETITOR-ADJACENT + GENERIC PDF/DOC
01adobe 02acrobat 03reader 04pdf 05doc 06docs 07text 08foxit 09highlighting 10annotating 11highlighter 12markup 13highlights
Generic PDF / document intent Competitor-adjacent search behavior
Clean tech workspace — the discoverability surface
// THE POSTURE
"The App Store title has two audiences. The human scanning the results — and the ranker parsing the words."
— Engagement Recap · LiquidText × iExcel
Chapter 05 · The Visibility Layer

SearchMan and Sensor Tower. The daily read underneath the rewrite.

The rewrite doesn't matter without the read underneath it. Every recommendation — the title, the keyword field, the competitor angle — was built off the same tracked data set: LiquidText's U.S. iPad keyword rankings, its search visibility score, keyword volumes, and App Store search ranks by keyword, pulled daily.

The tracking window ran September 4 through September 16, 2015 — twelve days of App Store visibility data timed against the recommendation delivery. That window did two things. It gave us a baseline read of where the current title was ranking before any change. And it gave the team a data spine to hand to the developer — a "here's what the ranker sees today" file, keyword by keyword, that made the rewrite an argument backed by rows, not opinion.

Within that same window, the tracked visibility score moved +68% off its own opening read — a 1.68× shift on its own baseline. That movement was part of the case built for the rewrite, not a result of it — the recommendations hadn't shipped yet. It's the kind of evidence that makes a metadata argument land with a developer: not "we think this will work," but "here's what the ranker is already doing, row by row."

Apple Pencil and iPad — the visibility layer
Chapter 05 · The daily visibility file
// TRACKING TOOL · 01

SearchMan · U.S. iPad

App Store title snapshot, keyword rankings, search visibility score, keyword volumes, and App Store search ranks — pulled per keyword against LiquidText's live listing.

// TRACKING TOOL · 02

Sensor Tower · category read

Traffic scores, difficulty scores, and competitor rank positions on the queries LiquidText should have been surfacing against — the field-level read, not the app-level one.

// TRACKED SET

100 keywords · ASO tracking list

Store-visibility keywords tied back to both the recommended iOS title and the recommended keyword field — the ones we'd watch move if the rewrite shipped.

// WINDOW

Sep 4 – Sep 16, 2015

Twelve consecutive days of App Store visibility data — timed against the recommendation delivery so the team had both a "before" baseline and a rolling read.

// COMPETITIVE READ

Adobe · FoxIt · Xodo · PDF Expert · GoodReader · iAnnotate

Per-keyword competitor rankings pulled for the named PDF and annotation apps — the field LiquidText was ranking against on every generic query.

// OUTPUT

ASO recommendation report

Final report bundling the competitive research, the keyword ranking read, the title analysis, the current keyword review, and the recommended title and keyword field.

12
Days of App Store Visibility Tracked
Sep 4 through Sep 16, 2015 — daily SearchMan + Sensor Tower reads on rank, visibility score, and competitor position.
// The engagement, in one line
"Rewrite the discoverability layer of a serious iPad app — so the App Store ranker can finally read what the product already is."
— Engagement Recap · LiquidText × iExcel
iPad workspace — App Store visibility posture
// THE POSTURE
"Serious products don't need louder titles. They need titles the ranker can parse."
— Engagement Recap · LiquidText × iExcel
Chapter 06 · The Read

The template for a product-first app fixing its store surface.

If you have a serious iOS app — an app people would actually download and use for years — and the store listing is written the way the founder writes about the product on a call, the LiquidText engagement is the shape of the fix.

Read the field first — SearchMan and Sensor Tower on the competitors, not just your own listing. Read the title as the ranker sees it, not as a human reads it. Rewrite the discoverability terms into the first half of the string. Rebuild the keyword field so every character earns its slot and nothing doubles up on the title. Then track it. Daily. Against a named window. So the rewrite is a decision, not a guess.

Most agencies rewrite the marketing copy. iExcel rewrites the search surface underneath it — so the product a serious user is already searching for actually gets found.

iPad reading — the read
Chapter 06 · The read
1.68×
Visibility Score Shift · Own Baseline
The twelve-day SearchMan read captured the score moving 1.68× off its own opening baseline — the evidence base built for the rewrite, not a post-launch result.
// THE TRACKING WINDOW
1.68×
Visibility Score · Own Baseline

Twelve days of SearchMan data, read before the rewrite ever shipped.

Discoverable. Then downloadable.

An App Store title the ranker can parse. A keyword field that doesn't waste characters on terms already in the title. A competitor read that tells you which queries you're leaving on the table. Book a 15-minute sanity check on your store surface — we'll tell you what's under-indexed.

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