Web-to-app campaigns and signal engineering for mobile growth

Turn post-install value into better ad-network decisions.

Audiencelab connects web-to-app campaigns, creative-level outcomes, and approved value signals across Meta, TikTok, Google, and supported networks. Use Audiencelab together with your current MMP stack, or as the standalone reporting and activation layer for supported ad networks.

Book a 30-minute stack reviewSee the TikTok × Nanobit results

Published proof · TikTok × Nanobit

TikTok for Business reports

2.08x

ROAS

$1.13

CPI

1.68x

Day-7 ROAS

Case-specific results reported by TikTok for Business. The campaign also used creator content, TikTok One, Events API, and Purchase Optimization.

Illustrative UI · example data

Mobile growth experience across Geeklab products and services

Official TikTok Marketing Partner

Platform

Web-to-app campaigns built for measured learning

Use eligible campaign objectives and approved events, then compare the complete funnel against a declared baseline.

Web-to-App Campaigns

Run app campaigns under the Sales objective instead of App Promotion where the network and account support it. Connect approved web and app events to a measured campaign test.

See the Performance Shift

Compare a web-to-app pilot with a declared baseline. Review the complete funnel, mature cohorts, event quality, and business outcomes before scaling.

Creative-level context

Compare aggregate revenue, engagement, and retention by creative where the required data is available.

Approved signals for network decisions

Validate revenue, engagement, retention, or governed values before delivering them to supported network endpoints.

“With Audiencelab, our campaign performance didn't just grow. It skyrocketed.”
MRMateja RadošNanobitTikTok source

[The problem]

Your stack works. Your signal flow doesn't.

MMPs measure. Ad networks optimize. Teams still need a governed workflow that connects reporting, creative learning, and the next signal decision.

SKAN protects privacy. It also limits creative learning.

SKAdNetwork remains an important privacy-safe measurement path, but delayed, aggregated postbacks give teams limited creative insight when they need to iterate quickly.

Your MMP can still govern cross-network reporting while Audiencelab focuses on web-to-app infrastructure, creative-level outcomes, and optimization signals.

Typical postback window

24 to 72h / later, you get an answer. It's just not the one you needed.

SKAN Postback Report / 48h delay

Campaign	Installs	Revenue	Creative
UA_iOS_Broad	···	redacted	n/a
UA_iOS_LAL	~120	redacted	n/a
UA_iOS_Retgt	···	redacted	n/a
UA_TikTok_01	~80	redacted	n/a

Last updated 47 hours agoStale window

Your MMP unifies measurement. Audiencelab sharpens activation.

MMPs solve a real problem: a fragmented ecosystem of DSPs, SANs, and attribution methods. They give teams a consistent way to measure and govern reporting across networks.

Audiencelab can work alongside that stack. In a post-ATT environment, network, MMP, SKAdNetwork, and warehouse views can still disagree because their windows, identifiers, and attribution methods differ — so teams need a clear source of record for each decision.

Where reporting breaks down

Definitions / should be reconciled before budget decisions

MMP vs. Network-reported, same campaign

Meta (self-reported)312 installs

Meta (MMP-attributed)187 installs

TikTok (self-reported)248 installs

TikTok (MMP-attributed)104 installs

Your reporting looks clean. But the networks that drove high-value users get the same credit as everyone else.

You're optimizing for what the algorithm can see

The algorithms aren't dumb. They're just working with limited visibility. They see installs clearly. They barely see value. And they don't see it fast enough.

So they optimize toward what's available, even when it's a weak proxy for what actually drives revenue. The result isn't wrong. It's just misaligned.

The system optimizes perfectly. For the wrong signal.

Algorithm signal visibility

Installshigh

Sessionsmedium

Revenuelow

LTV (d7)none

Creative ROASnone

The algorithm optimizes perfectly. For what it can see.

The solution

A learning and activation layer for modern UA

Connect campaign and creative context with approved outcomes, then design supported signals for ad-network optimization.

Creative optimizationCreative productionSignal engineeringData visibilityGranular reporting

Powered byoneSDK^™One available integration path alongside server-to-server events, APIs, approved MMP exports, and supported data delivery.

Define the outcomes a campaign should learn from

Audiencelab helps teams select approved value events and prepare them for supported ad-network delivery.

Signal definitions, consent requirements, source differences, and validation remain visible.

Progression milestones: level completions, mission clears
Core loop engagement: reward collection, session depth
Blended monetization: IAP + ad revenue into a single ROAS signal

CAPI Signal Stream / live

level_up

Level 122s agodelivered

purchase

$4.998s agodelivered

session_start

D7 return14s agodelivered

reward_collect

×3 combo22s agoqueued

Synced to 3 networks

Meta CAPITikTok

Compare mature outcomes at creative level

Connect campaign and creative context with approved post-install outcomes while keeping attribution definitions, windows, confidence, and source differences visible.

Three signal stages connected

Context, approved outcomes, network delivery

Creative Performance / illustrative example

Maturity window

$4.2x

Avg ROAS

Creative	ROAS	Revenue	D7 Ret.
Video_UGC_03	6.1x	$12,480	42%
Static_promo_12	3.4x	$6,230	31%
Playable_demo_07	2.8x	$4,890	28%
Carousel_lifestyle_01	1.2x	$1,640	18%

Example data only — not customer results or a performance claim.

Keep reporting definitions visible

Audiencelab can reconcile available campaign context and approved outcomes without presenting itself as universal attribution truth.

Your MMP can remain the reporting and governance layer while Audiencelab supports the learning and activation loop.

Attribution / Install #48,291

With an MMP or without one.

Audiencelab works together with your existing MMP stack, or operates as the standalone reporting and activation layer when acquisition stays within supported ad networks. Choose the model that matches your channel mix.

Already use an MMP? See how the stack works together

With an MMP

Keep broad reporting continuity.

Use your MMP for the channels and governance it already covers. Audiencelab adds its reporting, creative learning, web-to-app workflows, and signal activation for supported networks.

A practical fit for teams already using AppsFlyer, Adjust, Singular, or another MMP.
Common when the media mix includes DSPs, CTV, or traditional campaign types beyond Audiencelab-supported networks.
Reconcile definitions and windows while keeping the source your finance and reporting teams require.

Without an MMP

Run supported networks in Audiencelab.

When paid acquisition stays within supported ad networks and Audiencelab covers the required reporting and activation jobs, a separate MMP is not required for that scope.

Campaign and creative reporting for supported network workflows.
Web-to-app measurement, outcome analysis, and governed signal delivery in one operating layer.
Add an MMP later if broader media coverage or reporting requirements make it useful.

Why coverage matters

Broader eligible aggregate coverage makes reporting more complete and more accurate than a view limited to users with an available advertising identifier. Accuracy still depends on the approved sources, definitions, deduplication, windows, and supported network path.

01
Broader eligible coverage
Aggregate outcomes extend analysis beyond an IDFA-only or ATT-opted-in cohort.
02
More complete reporting
Within the supported data scope, broader coverage improves reporting completeness and accuracy.
03
Stronger signal learning
Approved purchase, ad-revenue, retention, and value outcomes give networks richer learning input and improve optimization toward valuable users.
04
Web-to-app without user friction
Audiencelab unlocks web-to-app campaign types with a direct, low-friction route from ad to app.

Nanobit evidenceTikTok for Business identifies advanced signal engineering as one of two key performance drivers in the published campaign and says combining purchase and ad-revenue data produced a more comprehensive optimization signal. Case-specific; creator strategy was the other named driver.

Web-first mobile path

Audiencelab's current web-first measurement and activation path does not use or depend on SKAdNetwork. Your MMP may still use Apple attribution frameworks elsewhere in a combined stack. The Audiencelab SDK does not invoke Apple required-reason APIs, so it adds no required-reason API declaration of its own.

* ATT, disclosure, and other obligations can still apply to the complete customer implementation.

Official partnership

Built by an official TikTok Marketing Partner

Audiencelab is built by Geeklab — an official TikTok Marketing Partner. Explore the supported TikTok signal workflow and review the official Nanobit case study for published customer evidence.

Book a stack review

How it works

Scope the path around your approved stack

Timing depends on the selected sources, destinations, access, data quality, and review requirements.

How it works

Clear milestones and hands-on integration support. Data availability and timing depend on the approved sources and destinations.

Integrate the oneSDK^™

Choose an SDK, server-to-server, or API path that fits the app and approved data flow. We scope the work with your team.

Define your value signals

We map in-app events to optimization signals together: progression, engagement depth, purchases, or blended ROAS. All tailored to your monetization model.

Launch and iterate with real data

Validate network diagnostics, compare mature cohorts, and use the findings to update signals, creative briefs, and campaign decisions.

Case studies

Named proof from Nanobit and Talofa Games

Named studios, named sources, and published campaign metrics show how Audiencelab strengthens signal quality and creative decisions.

Cost per install
$1.13
Total ROAS
2.08x
0.00x
ROAS on TikTok
Nanobit x TikTok case study
TikTok for Business reports these outcomes for a Nanobit campaign involving Audiencelab by Geeklab, TikTok Events API, and Purchase Optimization.
Review the original source
Day-7 ROAS
1.68x
Creative pipeline
TikTok One
0.00x
Day-7 ROAS
TikTok One creator campaign
TikTok for Business reports 1.68 day-7 ROAS in the same published Nanobit case study involving Audiencelab by Geeklab.
Review the original source
Starting CPI
$3.80
CPI with Audiencelab
$1.80
0%+
lower CPI
Talofa Games public case study
The public Talofa Games collaboration reports that Audiencelab reduced CPI from $3.80 to $1.80 while maintaining user quality.
Review the original source

Explore all customer stories

In the press

The story behind Audiencelab

Hear it in our founder’s own words

Peggy Anne Salz

Journalist & Writer at Forbes and Pocketgamer.biz

As featured in

Integrations

Works where you spend

Choose an SDK, server-to-server events, REST API, approved MMP exports, warehouse delivery, or customer-specific supported connectors.

Book a stack review

Platforms

Ad Networks

Delivery paths

Pricing

Two ways to work with us

Whether you run campaigns in-house or want a managed partnership, we've got you.

Product
Teams that want the data and tools to run campaigns themselves
Includes
- Comprehensive onboarding
- SDK integration support
- Ongoing technical support
Percentage of UA spend
Get Product Pricing
AgencyRecommended
Teams that want us to drive performance end-to-end
Includes
- UA strategy
- Signal engineering
- Creative research & iteration
- Campaign monitoring
- Strategic reviews
Monthly retainer + percentage of UA spend
Talk to Our Team

Review plan scope and pricing notes in the machine-readable pricing file.

Read the docs

Ready to start?

Your budget deserves better data.

Review your campaign flow, creative outcomes, and signal quality with a baseline your team can defend.

Book a 30-minute stack reviewRead the docs

Turn post-install value into better ad-network decisions.

Web-to-app campaigns built for measured learning

Web-to-App Campaigns

See the Performance Shift

Your stack works. Your signal flow doesn't.

SKAN protects privacy. It also limits creative learning.

Your MMP unifies measurement. Audiencelab sharpens activation.

You're optimizing for what the algorithm can see

A learning and activation layer for modern UA

Define the outcomes a campaign should learn from

Compare mature outcomes at creative level

Keep reporting definitions visible

Keep broad reporting continuity.

Run supported networks in Audiencelab.

Broader eligible coverage

More complete reporting

Stronger signal learning

Web-to-app without user friction

Built by an official TikTok Marketing Partner

Scope the path around your approved stack

How it works

Integrate the oneSDK™

Define your value signals

Launch and iterate with real data

Named proof from Nanobit and Talofa Games

The story behind Audiencelab

Works where you spend

Two ways to work with us

Your budget deserves better data.

Integrate the oneSDK^™