Case Study
The First Consumer Research Operating System for Financial Services
A financial institution deployed Advia AI to change their consumer research data collection approach, which was traditionally carried out by consumer research organizations using standard quantitative primary data collection
On-Premise Consumers Data Orchestration for delivering data governance and increasing efficiency
The financial services company is a leading multifinance service provider in Indonesia, offering large-scale financing services spanning from enterprise financing, heavy equipment, and consumer automotive. And, to rationalize repetitious consumer research processes, this company used ADVIA AI On-Premise Consumers Data Orchestration.
About the company (2023)
$957+ million annual revenue
150+ branches office in Indonesia
idAAA PEFINDO Corporate Rating
Advia AI's end-to-end consumer research data orchestration gives the company full control over customer feedback, enhances data goernance, and boosts research efficiency by up to 50%, overcoming limitations of templated analytics services.
Majority of consumer research and analytics providers use templated services to connect raw data and convert it into visuals. However, given the company's complex operational issues on a daily basis, such provision may provide partial data that is disconnected from the company's metrics and fail to detect blind spots that may be holding the team back, thereby wasting the team's time and causing delays in making improvements.
The company needed ADVIA AI to deploy end-to-end consumer research data orchestration which enabled the company to have full control access over customer feedback, data governance, while also increasing their consumer research expenditure efficiency by up to 50% from the previous year.
Project Objectives
On-premise consumer research orchestration.
Capacity built of the internal research and analytics team to perform the activities by themselves.
Interconnected data dimensions and company’s metrics.
Data governance and full control on data
Interoperable insights
Project Highlights
4 weeks from kickoff to feedback completion.
Less than 0.05% margin of error.
Increased 200% valuable feedback to improve new customer SLAs.
Advia AI’s Approach
Determining taxonomy of data (e.g. demographics), location, consumer behavior dimensions, customer satisfaction attributes, needed metrics, and formulating one data dimension to another and testing the logics.
Creating e-questionnaire unique links to indicate respondents' completion rate by segment and its deployment flow, including data pipeline. Engineering to automate deployment and integration schemes to store the data in company’s data center.
Configuring analytics user interface and discriminating the insights based on users from internal stakeholders and metrics to be extracted.
Written feedback polarity analytics by using Cloud API.
Results
60%
reduction in company’s annual spending for regular consumer research activities
100%
gain in data governance and control of data
150%
reduction in average questionnaire completion time
Solution Architecture
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