AI CoPilots

XACT CoPilot Marketplace

ADA’s XACT CoPilot is a robust data repository housing over 400 million profiles and 1 million points of interest and unique apps. It identifies consumer personas, interests, affluence, mobility patterns, and more to fuel business growth.

XACT CoPilot extracts both online and offline data to paint a clear picture of consumer insights, helping your business achieve desired results. Make the most of data generated daily to gain a deeper understanding of your customers and engage with them on a personal level.

Get a taste of what XACT data can do for your business and download your FREE ADA XACT datasets now to find solutions to your business challenges.

Clarify Business Uncertainty with Actionable Insights

Explore practical, real-life use cases for enterprises aiming to expand their business, amplify footfall traffic, and improve customer retention strategies.

XACT’s Unique Edge in Scale and Precision

With over 400 million profiles and data from 1 million apps and locations, ADA XACT delivers actionable insights for hyper-targeted ads that drive engagement.

We turn data into strategy with advanced analytics, AI, and cutting-edge tech.

We tackle your toughest data and insight challenges at every stage

Our AI-driven analytics unveil insights to help you acquire customers, discover new markets, and maximise ROI, all while reducing costs.

Turn uncertainty into clarity with meaningful insights.

Comprehensive Suite of Consumer Data

With insights into consumer personas, affluence levels, interests, device brand preferences, brand affinities, places of interest, and mobility patterns, you can now craft impactful strategies.

Our extensive range of solutions makes it all possible.

ADA XACT

Use Cases

Explore practical, real-life use cases for enterprises aiming to expand their business, amplify footfall traffic, and improve customer retention strategies.

5.0

New Business Expansion

Objectives

Penetrate new markets or products with expansion to ideal new locations

Roles

Decision Makers, Sales Managers

Industry

Businesses with physical store locations

Description

Businesses can estimate the potential market size and opportunity within a new geographical area by evaluating ADA’s XACT attributes for psychographic behaviour.

A sample of psychographic attributes in ADA XACT data sets:

Attribute
Sample Values
Online Interest (Personas)

Wealth Managers, Social Butterflies, Health Fanatics, Gamers, Entertainment Junkies, Budget Managers, Workout Warriors, Bookworm, Creative Crowd, Phone Enthusiast

Offline Interest (Places of Interest)

Healthcare, Sports, Mall, Education, Travel

To evaluate potential store locations for new business expansion, a business may use the attribute filter to identify suitable geographical regions.

Online and offline interest in Malaysia, Indonesia, the Philippines, and Thailand markets:

Distribution of online and offline interest by geographical areas:

Outcomes / Business Value (if applicable)
  • The quantitative measure of a geographical location's potential for a store is based on the relevance of consumer insights, interests, and personas.
  • The insights on the percentage of consumers with relevant interests and personas help the client determine whether a new opportunity is worth pursuing, serving as an indication of the untapped market’s potential.
  • The example above shows that only 10% of consumers are identified as Health Fanatics. The low percentage suggests that the new business idea may need to be reassessed.
  • If the outcome supports proceeding with the new business idea, the next step will involve strategic retail location planning for distribution expansion, which can be evaluated with XACT’s location and area data.
  • The example above shows that the Tapah area is ideal, with about 50% of consumers visiting health-related POIs compared to other areas, where 36% or fewer consumers visited such locations, making it a better choice for opening a new outlet.

5.0

Footfall Traffic

Objectives

Attract higher footfall traffic by gaining a better understanding of the target audience—comparing clients with competitors’ customers

Roles

Sales Managers, Data & Insights Leads

Industry

Transportation, delivery, oil & gas, etc.

Description

Businesses can identify targeted audience groups through polygonal or radial geofencing of selected locations or Places of Interest. For example, a business can create a 300-metre radial geofence around their branch location to analyse patterns of store visitors and compare them with non-visitors within a polygonal geofence of surrounding areas.

By evaluating insights into the following factors, businesses can plan to improve footfall traffic:
Footfall Density

Identify top areas and POIs with higher footfall traffic to target both visitors and non-visitors.

Active Visiting Day and Time

Determine peak traffic hours by analysing visiting patterns acrossweekdays, weekends, and various times of the day.

Frequency of Visits

Track the number of visits to a POI within a week.

Distance of Travel from/to POI

Assess the visitor’s willingness to travel to the client’s or competitors’ outlets.

Home and Office Locations

Differentiate between residents and workers to target distinct audience groups effectively

Competitor Landscape

Evaluate the presence of competitors in areas or POIs of interest. Additional insights can be developed by utilising ADA’s XACT attributes

An example of a footfall traffic comparison based on petrol preference between two separate locations:

In the example dataset, we can compare footfall density among major petrol station brands in different geographical areas. Additionally, we can analyse the specific demographics and behaviour of visitors and non-visitors for a particular brand in the two areas.

Outcomes / Business Value

The insights of footfall density being associated with attributes of demographics, preferences, interest, personas, etc. at different location area could be leveraged to :  

  • Improve current visitors’ footfall traffic with better understanding of their behavior
  • Attract non-visitors who are lookalike with current visitors in those attributes  

Assumptions

Geo-fencing requires GPS coordinate input for branch locations and Places of Interest from the customer.

Granularity of consumer insights captured is dependent on sufficiently tracked device ID’s.

5.0

Customer Retention Strategies

Objectives

Maintain the loyalty of at-risk customers by precisely identifying dual users of the client’s and competitors’ products. Regain lost customers by gaining insights into direct competitors.

Roles

Strategy & Planning Managers, Data & Insights Leads

Industry

Telco, Infrastructure services.

Description

Businesses can segregate customers into different groups to develop targeted retention strategies:

New customers

Device IDs detected only this month but not in the past few months.

Loyalists

Device IDs that have been present for the past few months up to the recent month.

Churners (Lapsers)

Device IDs that were present in the past few months but not in the recent month.

Dual Users (Potential Lapsers)

Device IDs detected using both the client’s and competitor’s brands within the same month.


ADA’s XACT attributes and insights can be used to define the target groups based on:
Demographics

Affluence level, age group, gender, etc.

Psychographic Behaviour

Actual consumer behaviour (rather than recalled behaviour) including personas, online interests, offline interests, etc.

Device Usage

Brand, model, platform, or price tier of the device.

Carrier Usage

Telco brand, level of data usage, etc.

Home/Office Locations

Differentiation between home fibre internet and mobile internet usage.

For example, a Telco business can:

  • Identify which competitors their dormant customers have switched to and gain insights into these customers’ profiles, behaviours, and usage patterns. This enables the Telco business to develop specific offerings to address potential customer churn.
  • Offer discounted bundled data plans with an upgrade to new smartphones that align with consumers' current spending tiers.
  • Understand consumer preferences between home fibre internet and mobile data internet and tailor promotional activities based on the geographic availability of services.

Outcomes

  • Improved precision in retention strategies tailored to consumer profiles, interests, preferences, and device/carrier usage.
  • Improved retention of customer loyalty and minimised risk of customer port-outs.

5.0

Digital Campaign Cost and Performance

Objectives

Drive new customer acquisition through refined audience targeting in digital campaigns

Roles

Marketing Managers

Industry

Communication services, property, banking, automotive, manufacturing, insurance, etc.

Description

Digital campaign performance can be optimised through a refined targeting approach that creates ideal audience clusters based on ADA’s XACT attributes, including:

Affluence Targeting

High, Mid, and Low affluence groups

Personas / Online Interest Targeting

Wealth Managers, Social Butterflies, Health Fanatics, Gamers, Entertainment Junkies, Budget Managers, Workout Warriors, Bookworm, Creative Crowd, Phone Enthusiast, etc.

Businesses can optimise their digital campaign costs via A/B testing with a minimal budget spend (e.g., 5% of the total digital campaign budget) to identify the ideal target clusters. After identifying the best-performing target group, the remaining 95% of the digital advertising budget can be allocated to maximise campaign performance.

Outcomes

Below are potential improvements for digital campaigns using refined audience targeting:

  • Increase in Reach
  • Increase in Conversion Rate (CVR)
  • Increase in Click-Through Rate (CTR)
  • Reduction of Cost per Acquisition (CPA)
  • Decrease in Cost Per Click (CPC)   

Case Studies

We excel at solving complex challenges for our clients. With our expertise and experience, we deliver exceptional solutions tailored to your needs.

Data Resource Center

Data & Insights Repository

Explore our complimentary ADA XACT datasets and discover how they can address your business needs.

These datasets offer insights into Personas, Places of Interest, Demographics, Telco Profiles, Mobile Carriers, Affluence, and Brand Preferences—empowering you to make data-driven decisions with confidence.

This section provides key technical details, including the Data Schema Overview, Sample Queries, and Geographical Coverage, to help you seamlessly integrate our data into your solutions.

Find your target audience with ADA’s XACT

FAQ

Where do you get your data?

  • Behaviour and interests are captured through ad-enabled apps. When an ad is about to pop in the app, the phone will relay a signal to ad exchanges that will in turn highlight the relevant ad. This relayed signal will also transmit non-PII data which is then acquired by ADA for our XACT database
  • Location data is captured by leveraging on apps that have location tracking features.
  • Additional attributes such as affluence are modelled by ADA using the attributes that were captured from the ad exchange data and additional third-party data such as device retail prices and property prices
  • Points of Interest (POI) data are coordinates data that is captured which requires ADA to clean and classify the locations.

What is an IFA?

IFA can be considered as the identification number for each smart device that is unique to each for the purposes of advertising. IFA stands for Identification for Advertisers (which is also known as IDFA) which is used for Apple/ iOS devices whereas Android Advertising IDs (AAID) is used for Android devices.

What is the data update frequency?

Datasets are updated monthly. Data is primarily used observing historical trends rather than real-time insights.

How is audience data captured at a particular location?

We will geofence/ map the desired location and capture any IFAs that were seen within the geofenced area during the specified period. The geofence can either be done radially or polygonal. Radial geofence is for when we are assessing a wide area whereas polygonal geofence is for when we want to assess the audience within a specified outlet.

What is the accuracy of the location data?

Our location data leverages on GPS data. As such, our capabilities are to pinpoint the mall, but we are unable to assess the individual stores within the mall. As our data leverages on GPS data, it will not be 100% accurate. For Google Maps, the GPS data tracks users’ location up to around twenty meters.

How is gender and age group derived?

The demographics details are initially obtained from those apps that require the users to declare their information. We then build a prediction model to categorise those without self-declaration information based on similar traits exhibited by those with self-declared information. An example of the logic would be users with period tracker app are likely to be a female.

How is affluency level derived?

The affluence model is derived from three main indicators – home location property price, frequented locations and the retail price of the device used. We split our affluence into low, medium, and high affluence by splitting them into percentiles (30:40:30). Our affluence is to be used to understand the spending power of the audience and not to be taken as their income level.

How is work and home locations derived?

Locations that audiences are seen during night-time will be their home location while locations that the audiences are seen at during working hours on weekdays are considered their work location.

How are personas derived?

Our standard ten personas are derived based on the apps that are used (e.g., Gamers are those that avidly spend their time on gaming apps).

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