Galaxy X tech

App Marketing Lexion

A

The advertiser is a person or legal entity focusing on generating sales and leads through serving ads that convey the right message to the right audience at the right time. In mobile advertising, the advertiser is on the client-side and is the one interested in promoting an app.

Also known as Google Advertising Identifier. A unique device identifier that Android generates and assigns to every device. Advertisers can use this to track user activity across apps, show them personalized ads, and attribute ad interactions.

The strategy a publisher employs to earn money from their app. This can be done through in-app advertisements, paid membership, and charging for premium features or an ad-free experience, among others. For example, some gaming apps are free to download and play, but users may need to pay in order to progress to the next level quickly.

The privacy framework from Apple that, among other things, manages the process of obtaining user consent before accessing their Identifier for Advertiser (IDFA).

A method of identifying the touchpoints a user has encountered within a specified period before making a conversion.

Refers to the process of identifying which conversions belong to which preceding click or impression.

A role played by an MMP to credit the in-app activity of users to the correct media sources.

A specific time frame that is taken into consideration when determining the source of a user’s action.

C

A bill that enhances privacy rights and consumer protection for residents of California, United States. The CCPA took effect on January 1, 2020.
The CCPA provides these rights to consumers:

Know what personal data is being collected about them.
Know whether their personal data is sold or disclosed, and to whom.
Say no to the sale of personal data.
Access their personal data.
Request a business to delete any personal information that was collected from that consumer.
Equal service and price, even if they exercise their privacy rights.

A measurement framework developed by Google that works without device IDs. It measures the incremental uplift of one or more conversion events, removing the influence of other campaigns and organic conversions. Used to assess the effect of ID-less campaigns. Similar to measuring the effect TV ads have, the principle is based on running campaigns on identifiable sub-markets (test group), while leaving other sub-markets unexposed (control group).

A type of targeting that works with contextual signals only, such as location data (country, city, postal code), language setting, mobile operating system, device model, as well as publisher information.

Within the sphere of app marketing, this refers to the group of devices within the target audience that are not shown ads from a specific campaign in the test. The actions on these devices are then compared to the actions on the devices in the test group.

D

A link that sends users directly to a specific in-app location, instead of the app marketplace. Deep links bypass the steps needed to go through to reach a conversion point, bringing the user directly to where they can perform the intended action e.g. completing a purchase, buying coins, placing an order.

A company that works with advertisers to purchase ad inventory across ad networks. Their platforms are built to identify a desired ad space and place bids on it. Compare with: Supply-Side Platform

Also known as a dynamic ad. It is dynamically assembled based on the user’s behavior and information sourced from a feed. This type of ad delivers a tailored experience for individual users.

E

The percentage of devices within a test group that received at least one ad impression, versus the total number of devices within the test group targeted within a campaign during an uplift test. For example, if 900 out of 1,000 users are shown an ad, the exposure rate is 90%.

G

A regulation under the EU (European Union) law on data protection and privacy within the EU and the EEA (European Economic Area), that grants users control over how their data is stored and used by organizations. To comply with GDPR, programmatic sellers must clearly communicate to users how their data will be stored and used. When a user gives consent to an organization to process their data, it enables targeted advertising.

A testing methodology that shows devices in the control group an ad ran by another advertiser on the platform, therefore removing any additional cost for clicks and impressions. The control group behavior is then marked with a ‘ghost impression’, which gives the information on which control group users would have been exposed.

An incrementality testing methodology based on Ghost Ads, adapted for retargeting campaigns. The difference is that it removes all devices that are not seen on ad exchanges, or that would not be bid on, from both test and control groups, to reduce noise. A bid is placed as usual for the test group, while the control group is tracked with ‘ghost bids’ (bids that could have been placed, but weren’t in the end).

I

A unique random device identifier Apple generates and assigns to every iOS device. Advertisers can use this to track user activity across apps, show them personalized ads, and attribute ad interactions.

The deployment of the ad to the ad placement. An impression might not necessarily mean that the ad has been viewed.

Actions made by a user within the app, such as log-in, registration, completion of onboarding, or purchases. These events can be tracked with the help of an MMP.

The estimated amount of conversions caused directly by the campaign. Formula: Test group conversions – control group conversions (scaled) = Incremental conversions

A KPI used to evaluate the cost of incremental conversions. Formula: Ad spend ÷ [test group actions – control group actions] = iCPA

A KPI used in calculating how cost-efficient a campaign is. This is used to evaluate the relationship between incremental revenue and the amount of money spent on the campaign. The figure is typically represented in percentage. Formula: Percentage: [IRevenue ÷ ad spend] × 100 = IROAS% Ratio: IRevenue ÷ ad spend = IROAS

The estimated revenue caused directly by the campaign. Formula: Revenue from test group – revenue from control group = iRevenue

A method of measuring the impact of a specific activity, on top of organic and other activity.

An incrementality testing methodology where no ads from the campaign are shown to devices within the control group. Also known as a ‘holdout test’. Cost-free and easy to implement, but with a relatively high level of noise. This method compares the behavior of all users in both groups. In the test group, this includes both exposed and unexposed users

K

The key metrics used to assess the effectiveness of an effort in achieving its objective. In programmatic advertising, the common types of performance indicators depend on the goals and nature of each campaign. These can include ROAS, cost per action, and retention rate.

L

Refer to: Attribution Methodology

The amount of revenue generated by the user for the App Developer during the entire duration of the relationship with the user, beginning with the app install.

M

Within the sphere of app marketing, MMPs are a service provider that specializes in measuring activities that are happening within and leading to the app. An app publisher may incorporate an MMP into their app to track activity and events e.g. time spent on a certain screen, sources of incoming traffic, app opening frequencies etc.

O

A digital marketplace where ad inventory from multiple publishers are available for advertisers to bid on in real time.

A user’s behavior not directly attributable to specific marketing efforts.

P

The automated process of buying and selling advertising space through digital platforms.

An incrementality testing methodology where devices in the control group are shown PSA ads, like donation drives or road safety reminders. By serving real ads, information on the devices within the control group that would have been exposed can be obtained. Unexposed devices are excluded from the measurement to reduce noise.

Within the sphere of app marketing, a publisher is an App Developer that gets paid for placing ads within their app. For example, an advertiser wants to reach their users via App Y, so they pay App Y to display their ads.

Q

The number of ad placements a DSP is able to process in order to determine on how to bid on them.

R

A method that randomly separates a specific population into two groups that are as similar to each other as possible, namely the test group and control group.

The process by which individual ad placements are bought and sold via programmatic auctions that happen instantaneously. With real-time bidding, ad buyers bid on an ad space, which, if the auction is won, instantly displays the buyer's ad. This lets demand-side players such as advertisers or DSPs optimize the purchase of ad placements from multiple sources.

Reshuffle indicates the randomization and marking of users when they were once part of a test or control group. In incrementality measurement, reshuffling the group assignment for a specific application fights aggregated bias over time where one group doesn't see any ads while the other group is constantly exposed to them. Reshuffling is relevant in cases where a test has been running for a long time and/or in campaigns the experience more extensive changes to the campaign setups, segmentation, or creative strategy.

A type of marketing channel used by an app owner to engage with their existing users through other channels within the same device. Usually, the aim is to encourage users to complete a particular task e.g. completing a purchase, buying in-game currency, placing a first order. The conventional way of retargeting relies on user IDs, such as AAID and IDFA.

The share of users active in the app within certain time frames after install, reengagement, or other events.

A KPI that measures the relationship between the revenue generated by specific advertising efforts and the money spent on them. Formula Percentage: [Revenue ÷ ad spend] × 100 = ROAS% Ratio: Revenue ÷ ad spend = ROAS

S

A group of users with common attributes such as location, demographics, activity level, value or amount of purchases, and how recently they last opened a specific app.

An ad network like Meta, Snap, and Twitter, that attributes its traffic internally, without the involvement of third-party MMPs.

Stands for Store Kit Advertising Network. Apple’s measurement framework for tracking mobile attribution. Introduced in 2018 and widely implemented in 2020 with the iOS 14.5 update.

A company that works with publishers to sell ad inventory across ad networks.

T

Within the sphere of app marketing, this refers to the group of devices that may be shown ads from a specific campaign in the test. The actions on these devices are then compared to the actions on the devices in the control group.

U

A report by GALAXYX showing the results of an uplift test. It presents the incremental revenue generated, on top of organic and other marketing-driven conversions. Also contains observed values such as ad spend, group sizes, amount of conversions, converters, and revenues per group, plus other metrics.

A randomized control trial test conducted by GALAXYX to measure the incremental impact of one or more campaigns.

A mobile marketing effort used to attract new users to an app. Paid UA may refer to ads shown in mobile ad networks or social media channels, while non-paid UA involves app store optimization and promotion on the advertiser’s own channels.

Careers

Position 1: Overseas Global Business Development (BD) - Remote Part-time Accepted

Description:

Develop and maintain relationships with overseas gaming clients, understanding their marketing and promotion needs.
Formulate and execute sales strategies, track sales progress, report sales data, and achieve sales targets
Ensure orderly client settlements, timely collection of related payments, and overall control of payment risks.
Familiar with internet advertising and marketing models, able to identify market and client needs, with excellent client development and service capabilities.
Participate in market research and competitive analysis, providing market feedback and suggestions.

Requirements:

Experience in global advertising sales, with knowledge of the gaming market.
Experience with major media platforms such as Facebook, Google, TikTok, and DSP.
Excellent communication, coordination, and negotiation skills.
Proficiency in English, including listening, speaking, reading, and writing.
Strong team spirit and a high level of work responsibility.

Position 2: Algorithm Engineer

Description:

Participate in data analysis and strategy optimization for advertising recommendation systems, including DMP, DSP, and ADX businesses.
Drive strategy optimization through data mining and analysis across the entire advertising process.

Requirements:

Proficient in one or more programming languages such as SQL, Python, or Java, with strong coding skills.
Familiar with common data analysis and data mining methods, with good logical thinking abilities.
Background in mathematics, computer science, or business analysis. Experience in computational advertising, search ranking, or recommendation systems is preferred.
Strong data analysis skills and insight, with a curiosity and enthusiasm for new things.

Position 3: Senior R&D Engineer

Description:

Support the iteration of requirements for advertising systems such as DSP and ADX, including the integration of new businesses and the upgrade of various targeting and filtering functions.
Optimize system stability and response time to ensure service reliability.
Enhance system usability and improve strategy iteration efficiency.
Support the development of some offline functions.

Requirements:

Familiar with the Linux development environment and proficient in one or more programming languages such as C/C++, Go, Python, or Java, with strong coding skills.
Preferred experience in computational advertising, search ranking, or recommendation systems, and online retrieval development.
Familiar with common offline technology stacks such as Hive, Kafka, Flink, etc.
Strong problem-solving skills, with curiosity and enthusiasm for new things.

Position 4: Senior Algorithm Engineer

Description:

Participate in algorithm optimization and strategy formulation for subsystems like DSP and ADX within the advertising system:
DSP: Optimize business metrics such as CTR, CVR, eCPM, and profit through audience targeting optimization, predictive models, etc.
ADX: Improve business effectiveness through personalized bidding, price inquiry optimization, etc.
Drive strategy optimization through data mining and analysis across the entire advertising process.

Requirements:

Familiar with the Linux development environment and proficient in one or more programming languages such as Python, SQL, or Java, with a strong algorithm foundation and excellent coding skills.
Familiar with common machine learning and data mining techniques, with good logical thinking abilities.
Preferred experience in computational advertising, search ranking, or recommendation systems, and strategy experience in ADX/DSP.
Strong data analysis skills and insight, with good communication abilities.

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GALAXY TECH LIMITED

Primary Business Areas

Data Management Solutions

Programmatic Buying Solutions

Cross-Platform Advertising Solutions

Core Competencies

Strategic Business Partnerships

Case Study

Lazada

Shopee

Aliexpress

App Marketing Lexion

A

Advertisers

Android Advertising identifier (AAID)

App Monetization

App Tracking Transparency (ATT)

Attribution

Attribution Methodology

Attribution Provider (AP)

Attribution Window

C

California Consumer Privacy Act (CCPA)

Causal Impact Analysis

Contextual targeting

Control Group

D

Deep link

Demand-Side Platform (DSP)

Dynamic Product Ad (DPA)

E

Exposure Rate

G

General Data Protection Regulation (GDPR)

Ghost Ads

Ghost Bids

I

Identifier for advertisers (IDFA)

Impression

In-app Event

Incremental Conversions

Incremental Cost Per Action (iCPA)

Incremental Return On Ad Spend (iROAS)

Incremental Revenue (iRevenue)

Incrementality

Intent-to-Treat (ITT)

K

Key Performance Indicator (KPI)

L

Last-Click Attribution

Lifetime Value (LTV)

M

Mobile Measurement Partner (MMP)

O

Open RTB

Organic Behavior

P

Programmatic Advertising

Public Service Announcement Ad (PSA Ads)

Publisher

Q

Queries Per Second (QPS)

R

Randomised Controlled Trial (RCT)

Real-Time Bidding (RTB)

Reshuffle

Retargeting

Retention Rate

Return on Advertising Spend (ROAS)

S

Segment

Self-Attributing Network

SKAdNetwork

Supply-Side Platform (SSP)

T

Test Group

U

Uplift Report

Uplift Test