In reaction to the Mifid II regulation, the client was seeking to increase the efficiency of the research team’s activities and design new revenue models to meet strategic goals through the use of web-analytics. Research Analysts needed to gain readership insights through:
- Improved engagement measurements
- Coordination with sales to identify new opportunities
Due to regulatory changes, the organization needed to shift how it managed the research function’s revenue and costs of unbundled services
- We tagged the research website to capture tracking details using open source tools and in-house data capture to gain readership insights
- We redesigned the website dashboard reports used by the Analysts to highlight critical usage patterns revealed by newly captured web-tracking data
- We improved and streamlined the dashboard reports used by Sales and Management to highlight upsell opportunities more efficiently
The client needed to identify the geolocation data provider - out of dozens available - that best aided their investment strategy. Challenges included:
- Different preprocessing (data capture, cleansing, metric creation) logic used by vendors
- Lack of standardized evaluation criteria
- Lack of data acquisition, load and process governance/oversight
- We developed a set of evaluation metrics (e.g., data consistency, KPI correlations) relevant to the client
- We designed a vendor questionnaire that allowed us to effectively screen the vendors prior to data capture
- We decoded each vendors’ preprocessing algorithms, applied logic to bring consistency for evaluation, and developed analytics modules that evaluate a dataset in 1-2 days
- Lastly, we concisely synthesized information for the client and recommended finalists based on their needs
Fulcrum’s methodical approach and data audit framework evaluated multiple data sources through a consistent lens, quickly and effectively.
The client was looking to improve customer engagement among advisory customers with a process to deliver personalized email driven by customers’ digital behavior and advisory content consumption. The content was not classified which made personalized recommendations difficult.
- We scraped PDF and web pages from its microsites
- We categorized the content using Natural Language Processing (NLP) based on terms and phrases found in the subject matter
- We modeled topic relevancy for each customer and mapped it to the content library
- We scored the content so that the most relevant articles could be recommended to each customer via personalized email campaigns using the matching algorithms
Fulcrum enabled the deployment of a customized content delivery system to increase engagement with high value customers.
To perform exploratory analysis on the impact of IoT devices on homeowners insurance claims, the client sought to merge claim data with IoT information (provided by a third party).
The challenge was third party and the client not being able to share data across systems for data security reasons.
- Fulcrum facilitated IoT analytics by acting as a third party to join proprietary information between the two companies
- We collected sensitive data in isolation in our highly fortified security infrastructure, and performed matching at the home address level
- Then we provided an anonymized joined data set to the client and developed a framework to repeatedly supply the data transformation between the two companies
Fulcrum quickly and securely provided the neutral data matching required to support various insight needs across the organization.
The client needed to accomplish faster and more accurate decisions in making personalized offers. Fulcrum applied its experience in digital coupon operations to solve the business problem.
The client partnered with Fulcrum to utilize our hosted computing platform, Digital Fusion.
- Digital Fusion collected data across all channels and sources (POS, display ad, email campaign, web traffic) and created hundreds of micro-segments of customers with similar buying behavior
- The platform deployed stochastic frontier models for each segment to identify winnable shares for each product category
- Then Digital Fusion computed the optimal personalized offers based on purchase, coupon redemption, and digital behavior data
Fulcrum’s unification of behavioral and marketing data with predictive models produced granular personalized offers to drive more trips, bigger baskets, and higher margins.