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ADA helped a leading Direct-To-Consumer player automate data collection to help accelerate business decisions

Case Study

ADA helped a leading Direct-To-Consumer player automate data collection to help accelerate business decisions

The Results
Eliminated manual data collection requirements.
Eliminated data discrepancy issues.
The Execution

The customer is a leading Direct-To-Consumer (D2C) player that invests in developing e-commerce capabilities for digital-first brands in the beauty, fashion, and personal care sector.

The company was previously collecting data from their managed brands manually which resulted in data inaccuracies and delays in getting business insights for decision making activities. They also had no visibility on data from their managed brands ecommerce platforms and marketplaces.

ADA helped to build and end-to-end data pipeline and data warehouse on Amazon AWS to gather insights from many different data sources for sales, returns, inventories, and finance. ADA also built bespoke API connectors for various eCommerce platforms to enrich collected data.

The new data warehouse helped to provide up to date and accurate data for data analytics and data science team to make business intelligence dashboards and construct ML models.

The Approach
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This chart demonstrated the accuracy of ADA’s robust modelling technique in the forecasting model.

We observed close alignment between the actual sales and predicted values for Y2023, with difference of only 6.8%:

– Prediction for Y2023: 21,339 units (overall)

– Actual for Y2023: 22,067 units (overall)

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Content
Results
Challenge
Solution
Execution
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ADA used AI and Tech to improve sales forecast, inventory management and marketing strategy for a client

Case Study

ADA used AI and Tech to improve sales forecast, inventory management and marketing strategy for a client

The Results
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Sales forecast accuracy, with error deflection of less than 3.7% in model validation.
Improved sales forecasting leads to better inventory management to meet sales demand
Enhanced marketing campaigns and effectively allocate budgets based on sales forecast
The Execution

A Malaysian subsidiary of the global automotive giant saw an immediate need to solve the challenge of parts inventory management and allocating marketing budgets efficiently based on anticipated sales for each vehicle model per outlet. The current flaw has impacted the sales and marketing departments – hindering campaign performance and potentially missing sales targets.

With ADA’s expertise in data management and predictive modelling, we implemented a data-driven solution by first unifying all sources of data in a Customer Data Platform (CDP), developing a forecasting model and building a dashboard for analysis and monitoring.

The automation has greatly improved sales forecasting accuracy, reduce parts inventory shortage, and ultimately,  empowering the client to invest resources to areas where they can generate the highest impact.

Content
Results
Execution
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We boosted app installs for blu by BCA Digital, resulting in record-breaking new accounts and cost-effective conversions

We boosted app installs for blu by BCA Digital, resulting in record-breaking new accounts and cost-effective conversions

The Results

100%​ Accuracy in migration of 90% of the datasets | 3 months​ Successful migration of 400+ tables and 200+ stored procedures

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Accuracy in migration of 90% of the datasets.​
0 months
Successful migration of 400+ tables and 200+ stored procedures.
The Challenge

Increased competition in the Indonesian digital banking market made it challenging for blu to stand out and acquire new users effectively.

The Solution

An eminent Indian ecommerce entity specializing in fashion, beauty, and lifestyle products, faced the significant challenge of migrating its data warehouse from AWS to Microsoft Azure. ​

This strategic move necessitated a data engineering partner proficient in both cloud platforms, with a deep understanding of the nuanced data requirements essential for their business and technical objectives. ​

ADA spearheaded the migration. The team replicated the existing AWS Redshift data structures and objects onto Azure Synapse, optimizing them for enhanced performance and ease of use. ADA employed shell scripts to automate the migration of data from AWS S3 buckets to Azure Blob storage, leveraging Azkaban for batch workflow scheduling to oversee the migration process efficiently.​

This also positioned the company to capitalize on Azure’s advanced data warehousing capabilities, marking a significant milestone in its data management evolution.​

The Execution

Previous systems

New system

 

Results
Challenge
Solution
Execution
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Let’s turn your data and AI into measurable outcomes!

ADA helped a leading ecommerce brand increase order value and customer retention rate

ADA helped a leading ecommerce brand increase order value and customer retention rate

The Results
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Reduction in the time allocated for the task
Introduced an effective fraud detection approach. All team members involved in this task now consistently rely on the tool for their daily work. 
The Challenge

Our client is a global leader in consumer electronics, home appliances, and mobile communications. One of its subsidiaries, Hi-Care Solutions, specialises in providing maintenance services to customers who have contracted rental services of various LG electronics products, such as air purifiers, water purifiers, and more. Periodic customer management and routine visits are conducted to ensure the seamless operation of all related services following the rental contract agreement.

Recently, a challenge surfaced as several sales representatives unintentionally received bonuses through the contractual process. This has resulted in financial discrepancies and losses for our client.

The Solution

ADA developed a three-phased solution to effectively address the identified challenges.

In the initial phase, ADA aided in the transformation by constructing custom dashboards and transitioning fraud detection from a manual to an automated process. These dashboards were seamlessly integrated with the client’s base system data, utilising the existing detection logic.

Next, the detection logic underwent expansion, addressing complexities and volumes of data processing that were beyond the capabilities of human intervention.

In the final and ongoing phase, ADA introduced specialised artificial intelligence (AI) to enhance fraud detection, leveraging the insights derived from the collected data. This approach ensures a robust and adaptive solution to counteract potentially fraudulent activities.

Following that, the PDCA (Plan – Do – Check – Analyse) cycle was initiated. A series of interviews and workshops were held to optimise the solution. This proactive approach allowed for the rapid collection of feedback, facilitating the continuous improvement of both the detection logic and dashboards. The iterative process ensured that adjustments were made swiftly, leading to an increasingly accurate and effective solution.

The Execution

Upon conducting a thorough review to identify instances of fraud, it became evident that the manual process was too time-consuming and could not efficiently cover all cases. There was a pressing need for automation to effectively detect fraudulent activities within the workplace.

ADA automated the fraud detection process by building specialised dashboards and implementing AI, resulting in a reduction of fraud incidents.

Results
Challenge
Solution
Execution
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How Lotte Rental Achieved 21% Conversion Lift in 3 Months with Customer 360

How Lotte Rental Achieved 21% Conversion Lift in 3 Months with Customer 360

The Results

21% conversion increases | 10 distinct customer personas identified

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conversion increases
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distinct customer personas identified
The Challenge

Lotte Rental, a leading vehicle rental company in South Korea, had a sales effectiveness problem. Contact centre salespeople had almost no information when customers called, just a phone number and a name. No rental history, no preferences, no context about what the customer might need.

Meanwhile, IoT data from rental vehicles sat unused. Every rental generated driving behaviour data refuelling patterns, locations, driving styles that could have informed customer understanding. But this data was siloed and invisible to sales teams.

The Solution

ADA implemented Treasure Data CDP to build Customer 360 profiles with preferences, usage patterns, and purchase considerations. These profiles integrated directly with the contact centre, giving salespeople real-time customer context during every conversation.

Custom analytics on driving behaviour revealed 10 personas that had been invisible before. The personas enabled dynamic pricing based on driving risk. Within 3 months, conversion rate increased 21%.

Results
Challenge
Solution
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How an Indonesian Real Estate Developer Achieved 5.5X Appointment Increase with CDP

How an Indonesian Real Estate Developer Achieved 5.5X Appointment Increase with CDP

The Results

5.5X increase in appointments per month | 18% increase in booking deposits | 30% increase in total deposit value

0 x
increase in appointments per month
0 %
increase in booking deposits
0 %
increase in total deposit value
The Challenge

A leading Indonesian real estate developer with 76+ projects across 33 cities needed to improve digital marketing for new development launches. Generic ads reached broad audiences without personalization, prospects interested in luxury condos received the same messaging as those interested in affordable housing.

Without unified customer data, there was no way to personalize targeting. Each campaign started from scratch with no ability to leverage insights from previous interactions.

The Solution

ADA implemented Treasure Data CDP with personalised targeting for Facebook and Google campaigns. The CDP unified data from website visits, past inquiries, and property preferences into profiles that could drive segmentation.

Instead of broad audiences, campaigns reached segments defined by demonstrated preferences: project type, budget range, location preference, and purchase timeline signals. Appointments increased 5.5X per month. Booking deposits increased 18%. Total deposit value increased 30%.

Results
Challenge
Solution
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How a Top 5 Auto Manufacturer Generated $500M in Sales with CDP-Powered Intent Segmentation

How a Top 5 Auto Manufacturer Generated $500M in Sales with CDP-Powered Intent Segmentation

The Results

11% conversion rate | $500M sales generated

0 %
conversion rate
0 $
million in sales generated
The Challenge

A Top 5 global auto manufacturer in Malaysia had an 800K customer base but was treating them all the same. Marketing campaigns used broad targeting with generic messaging. Without the ability to distinguish high-intent customers from general audience, advertising costs were high relative to results.

Customer data sat in multiple systems, CRM, dealer management, website analytics, service records with no unified view. There was no way to identify purchase signals or score intent.

The Solution

ADA unified customer data using CDP, integrating showroom visits, website behaviour, service history, and previous purchases into single profiles. Identity resolution matched the same customer across systems.

Propensity scoring identified high purchase intent customers based on behavioural signals: website visits to specific models, service appointments suggesting vehicle aging, digital engagement patterns correlating with purchase timing. High-intent segments activated through app push, dealer personal selling, and Facebook Lookalike. The result: 11% conversion rate and $500M in sales.

Results
Challenge
Solution
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ADA successfully raises funds for a global NGO’s pandemic journey with consumer insights & creative content

ADA successfully raises funds for a global NGO’s pandemic journey with consumer insights & creative content

Results
  • Overall donations exceeded target by 37%
  • Overall Cost Per Acquisition reduced by 273%
  • An overall whopping 68% uplift in ROI (*2.5 times above target)
  • 87% positive sentiments from influencers’ community
0 %
higher donations vs target
0 x
ROI vs target
0 %
reduction in Cost per Acquisition
Challenge

Running a Ramadan fundraising campaign meant competing with many charities during a highly crowded giving season. Rising media costs, shifting post-COVID donor behaviour, and inefficient mass targeting made it difficult to reach new donors while keeping cost per acquisition low.

At the same time, the campaign needed to balance global brand consistency with strong local cultural relevance across markets, and use influencer voices authentically to inspire trust. The core challenge was to cut through seasonal noise, find high-intent audiences, and drive more donations with better ROI on a limited nonprofit budget.

Solution
  • ‘Old-meets-new’ targeting approach: By amalgamating current audience behavior, social trends, and past Ramadan data, we honed in on a specific target audience.
  • Glocalising the campaign: Infusing local elements into the global campaign, we aimed to resonate with communities on a personal level and evoke their generosity.
Execution
1 Leveraging audience insights

We leveraged pre-COVID data from schools and identified top religious app users to create lookalike audiences. Additionally, we segmented audiences based on their affinity with the holy month, optimizing our outreach during peak engagement times.

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2 Engaging local influencers

Recognizing the surge in influencer conversations surrounding Ramadan, we collaborated with local influencers to humanize the refugees’ plight through compelling storytelling.

3 Amplifying through local channels

Partnering with local channels, we disseminated tailored content pieces that resonated with specific cultures, bringing the ‘Imagine’ theme to life.

Awards
  • Gold in Not-for-Profit / Charity category at The Drum Digital Advertising Awards APAC 2021
  • Silver in Excellence in Data-Driven Marketing at Marketing Excellence Awards 2021
Results
Challenge
Solution
Execution
Awards

Let’s turn your data and AI into measurable outcomes

How a Global Hospitality Group Unified Data Across 400+ Properties

How a Global Hospitality Group Unified Data Across 400+ Properties

The Results

400+ Hotels | 6 Data-Sources Consolidated 

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hotels unified
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data sources consolidated
The Challenge

A global hospitality group’s APAC operations had reporting scattered across Redshift, Salesforce, CSAT platforms, Eloqua, CSVs, and BigQuery. Each source had its own schema and its own definition of what “occupancy” or “revenue” meant.

When regional leadership needed performance insights, analysts spent days pulling data from six systems and reconciling conflicts manually. Different teams ran the same query and got different answers. With 400+ hotels, leadership couldn’t trust any number they saw.

The Solution

ADA designed an enterprise reporting ecosystem using Alteryx for ETL automation, pulling from all sources into a consistent schema in an MS SQL Data Mart. Power BI dashboards with role-based access ensured everyone worked from the same underlying numbers.

Automated pipelines replaced days of manual consolidation. Regional leadership could compare properties, track trends, and make decisions based on numbers that finally matched.

 

Results
Challenge
Solution
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How a Leading Indonesian Telco Modernized their Data Foundation Mid-cloud Migration 

Solution type

How a Leading Indonesian Telco Modernized their Data Foundation Mid-cloud Migration 

The Results

100% migration accuracy | 400+ tables migrated | 200+ stored procedures migrated

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migration accuracy
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tables migrated
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stored procedures migrated
The Challenge

A leading fashion ecommerce company needed to migrate their data warehouse from AWS Redshift to Microsoft Azure. The migration had to happen without disrupting business operations, dashboards, reports, and analytics all needed to keep running while the underlying infrastructure changed.
Any data loss or inconsistency would break downstream reporting and erode trust in the platform. The company needed migration that was fast, accurate, and seamless.

The Solution

ADA replicated AWS Redshift structures to Azure Synapse, automating the migration using shell scripts and Azkaban orchestration. The approach ensured business continuity throughout, parallel running validated accuracy before cutover.

400+ tables and 200+ stored procedures were migrated in 3 months with 100% accuracy across 90% of datasets. No data loss, no business disruption.

Results
Challenge
Solution
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Let’s turn your data and AI into measurable outcomes!