Industry

Client challenge

The client was seeking innovative data-driven solutions to identify clients’ trade interests through the use of predictive models and a machine learning feedback loop.  In particular the client sought to:

• Assess and prioritize opportunities for business development
• Maximize the deal values by anticipating the end-clients’ needs more efficiently
• Provide customized offers to strengthen end-client relationships

How we helped

• We combined internal data (e.g., transaction history, inventory lists, client holdings, etc.) and market data (e.g., interest rates, currency fluctuations, market volatility, etc.)
• We applied predictive analytic techniques to identify clients most likely to be interested in trading specific products in the bank’s portfolio
• We built a user feedback loop to continually update the process to identify better opportunities

Fulcrum effectively prioritized end-clients and provided a matching engine to allow the client to stay competitive in the market.

Client challenge

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.

How we helped

• 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.

Client challenge

In reaction to regulatory requirements to retain and classify payment records, the client needed help creating a cash transaction classification system for regulatory reporting and compliance, looking specifically to solve for following challenges:

• Migrating away from using Excel that applied the classification rules with a manual process
• Implementing scripts to allow for processing a greater amount of data
• Needing to improve operational scalability rather than rules being created small chunks at a time
• Improving repeatability, decreasing processing time, and reducing error

How we helped

We developed a text mining and reporting engine in R that efficiently runs against the client’s full data warehouse

• We automated code in R to be applied against the data warehouse for fast and accurate classification
• We built a front-end UI to allow business users to create and modify rules to refine business logic and improve resulting classification rate
• We created reporting on summary statistics and classification rate, including the impact of the addition of new rules
• We created a next generation text mining process to prioritize the new candidate classification rules

Fulcrum created a scalable and sustainable solution to comply with regulations, which provided significant time-savings from manual labor, increased accuracy of classification, and introduced a mechanism to easily create and integrate new rules.

Client challenge

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

How we helped

• 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.

Client challenge

A regional bank’s Human Resources (HR) group was seeking a solution to incorporate market and competitive data to improve personnel evaluation and optimize resource planning.

How we helped

• We integrated external data (e.g., publicly available competitor data, footprint demographics, etc.) with internal data (e.g., staff experience, branch performance, etc.) and developed new data elements on branch-level market share
• We created a deposit growth segmentation to benchmark branch growth and market penetration, controlling as many factors as available, excluding manager talent
• Lastly, we performed branch performance forecasting for each segment

Fulcrum streamlined the ability to identify exceptional managers, which impacted compensation formulas and recruiting efforts, and also enabled optimized resource planning through forecasting.

Client challenge

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

How we helped

• 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

Fulcrum improved website visitor tracking and built more actionable reporting aligned with goal setting and decision making.

Client challenge

A Retail Bank wanted to understand the attractiveness of their local markets and how they fare against market competition but faced the following challenges:

• Public data is available to answer these questions – but come from multiple sources and need aggregation
• Some data sources are extremely large and most have quality issues
• Manual analysis for any given store, branch, or collection of local markets is time consuming and prone to error
• Exploratory analysis requires technical expertise and access to data and computing resources – business users can’t easily answer “what if” questions

How we helped

• Fulcrum built an automated process to retrieve, clean, and combine dozens of distinct public datasets to create a master database of local market performance and demographic data for the entire US across 8 years of historical data
• We automated creation of detailed reports for the retailer and reduced the time needed to create a tailored presentation from weeks to minutes
• We built an interactive application to allow business users to explore the data and create custom charts to answer questions related to company performance

Fulcrum’s web application aggregates, normalizes, and allows instant visualization of massive public datasets for business analyst use.

Client challenge

A retail bank in the US sought to understand its customer satisfaction and loyalty relative to those of its competitors, along with relative strengths and weaknesses across a battery of brand characteristics and attributes across several customer groups:

• “Direct Customers” for a general customer satisfaction survey
• “Advised Customers” who were using the bank’s investment services through an Advisor to understand their customer experience
• “Lapsed Customers” who had drawn down their account to nearly nothing and had no activity for a certain period of time to understand the reasons for reducing their relationship
• “New Customers” were surveyed within the first 2 weeks of opening a new account to understand the new customer experience

How we helped

We collaborated with the client on the design of the original questionnaires, and throughout the duration of the tracking study. While each survey had its own objectives and benchmark metrics, certain brand attributes were measured consistently across customer groups for comparison as well as for additional time-based assessments of changes.

Fulcrum tracked customer attitudes from different phases of customer journey to help develop strategies for operational and website changes, identify areas of improvements (including benchmark scores) and simplify forms while optimizing the timing of communications within different accounts.

Client challenge

The client was seeking a streamlined method to organize their disparate data sources into a single location to start generating business insights. Some of their challenges included:

• A massive amount of disjointed information including internal and external data
• The lack of a unified view of the customer because the source systems are managed by different siloed teams
• The internal IT team was backlogged, and analysts needed support testing the latest big data tools

How we helped

The client partnered with Fulcrum to utilize our Agile Analytics Lab to experiment with big data solutions

• We created reusable data processing pipelines to allow easy data loading into Hadoop and data preparation for analysis
• After establishing the central repository, we then cubed the data using Hive and Spark for fast querying of metrics
• Output tables are stored in HBase and Impala is used for queries to gain rapid response while Tableau is utilized for dashboard reporting

Fulcrum’s lab enables a holistic view of the data to unlock insights and allows rapid testing of various open source tools. Our data experts guide the process allowing the clients to modernize their analytics team.

Client challenge

A regional financial services company was seeking:

• A database marketing partner to help improve the efficiency of its acquisition of Home Equity Line of Credit customers
• In-depth testing of new creative and informed targeting to reduce the number of total mail pieces while holding responses and conversions at existing levels

How we helped

• Through the analysis of existing customer data, we built a model to predict which customer households were most likely to respond to outreach and be approved for a line of credit offer
• Produced dashboard and ad hoc reports to bring transparency to campaign summary metrics, campaign response details, and financial details for each campaign

Fulcrum utilized past campaign response data to build a predictive model that improved campaign ROI, and created the accompanying reports to enable transparency into campaign performance and faster decision making.

Client challenge

A Fulcrum client wanted to measure a mass media campaign’s impact on new customer acquisition at the local and store level.

The challenge was measuring advertising impact at the local and store level, as each market included in the campaign had stores with varying performance levels, competitive pressures, and demographic compositions.

How we helped

• We built matched control groups at the store and market levels by matching stores in treated markets with comparable stores in untreated markets, based on a number of relevant criteria
• We calculated the results of the campaign’s impact at the local market level as well as aggregated for total campaign performance
• The finely matched control group process allowed forresult measurement by other important dimensions such as store format, population density, and proximity to competitors

Fulcrum’s quasi-experimental design allowed for macro and micro level results analysis.

Client challenge

Fulcrum tracked consumers’ brand associations and satisfaction with various metrics over the years, identified levers for improving upon desired outcomes, and identified competitive threats and opportunities during a period of upheaval in consumer banking.

How we helped

• We designed and executed a study over the course of several years, collaborated with the client on the design of the questionnaire and managed the respondent recruitment throughout the duration of brand tracking
• We performed a driver analysis at the conclusion of each survey to identify the brand metrics that were impacting the satisfaction, retention and NPS ratings

Fulcrum tracked consumers’ satisfaction with various metrics over the years, identified levers for improving upon desired outcomes, and helped identify competitive threats and opportunities during a period of upheaval in consumer banking.

Client Challenge

The client sought to retain an at-risk multi-million dollar portfolio.  In an effort to find a solution, the client needed help with insurance claims data analysis identifying risk drivers and preventing losses.  In particular the client wanted to utilize their massive amount of unstructured adjusters’ notes to bring more detail-rich information to the risk consulting team aiming to prevent loss and reduce costs, and to identify additional risk drivers to support ongoing pricing strategy.

The key challenge was the inability to process massive amount of unstructured data (i.e., adjusters’ notes), limiting opportunities to quickly generate insights.

How we helped

• We performed Natural Language Processing (NLP) on their unstructured adjusters’ notes data including Term Frequency-Inverse Document Frequency (TF-IDF) and topic modeling (LDA)
• We enriched the input data to the pricing models through text mining that led to increased prediction accuracy
• We developed an interactive risk analytics tool to deliver loss and cost insights

Fulcrum helped the client with enhanced coverage insights and pricing inputs through the introduction Natural Language Processing on unstructured data.

Client challenge

The client needed help flagging fraudulent medical insurance claims. The goal was to:

• Determine logic to flag suspicious behavior and identify providers of interest
• Leverage billing data to analyze suspicious providers

How we helped

• We performed fuzzy matching to link multiple claim records to the same provider(s)
• We used geocoding to create physical distance calculations between providers and between providers and claimants
• We applied statistical methods (e.g., logistic ridge regression with sparse matrices, T-Score calculation, bootstrapping, etc.) to billing data to build propensity scoring models to rule claims as valid or invalid
• Based on our modeling results, we created the fraud flagging logic to identify suspicious behavior and providers of interest
• The team collaborated with the investigative unit, billing unit, and legal unit to create a provider fraud action plan

Fulcrum’s data preparation procedures and predictive analytical models provided the quantitative basis for the provider fraud action plan.

Client challenge

The client was seeking to apply predictive models to improve its rating structure, moving away from subjective rating. Key challenges included:

• Highly subjective rating process based on individual underwriter’s experience, without data-driven guidelines
• Lack of experience and resources evaluating external data sources

Furthermore, the client wanted to explore options to incorporate and build machine learning into the rating structure

How we helped

• We identified pricing key drivers through LASSO regression
• We developed a statistical model (using GLM) that was implemented for predictive ratings scoring
• We used advanced techniques (including GBM, Random Forest, etc.) to improve model performance
• We created benchmarking models with SVM and NN to ensure model performance (i.e., how close the model can perform when compared with a simulated one without restrictions)

Fulcrum’s data-driven rating structure standardized future underwriting and increased pricing  transparency.

Client challenge

The client was seeking to transform a labor-intensive pricing process to a seamless, sustainable and transparent operation. Key challenges included:

• Lack of standardization in reporting across types of policy (e.g., auto, GL, etc.) which made it difficult to analyze account-level performance at a glance
• Manual data pulling, and copying/pasting during the data preparation created high human-error risk
• Difficulty tracking changes and updates to quotes

How we helped

• We mapped out user stories to better understand various user needs and experiences
• We developed a platform-flexible front-end pricing tool that accounted for user needs (e.g., metrics, reports, etc.) utilizing real-time data ingestion
• We developed automated scripts for consistent data pulls and to reduce labor hours
• We built a job management framework to provide pricing governance and monitoring

Fulcrum’s development of a reliable and sustainable process resulted in an 80% reduction of manual labor hours, increased pricing transparency, and yeilded faster quote turnaround.

Client challenge

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.

How we helped

• 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.

Client challenge

The client was seeking to streamline their multi-step and labor-heavy scoring process of a pricing model to improve efficiency. Key challenges included:

• Labor intensive monthly/quarterly updates that involved manually updating hard-coded parameters
• Because it was a multi-step scoring process, it was prone to errors and difficult to troubleshoot
• Required underwriters and actuaries to performmanual steps that were tedious and time consuming
• Model inputs and performance were not monitored for anomalies and/or population shifts

How we helped

• We parameterized and centralized configurationfiles to reduce turnaround time and errors
• We built QA checks within scripts to provide quickdiagnosis for unexpected results
• Then we streamlined the feedback process and standardized the input template to minimize room for error
• Lastly, we developed a model tracking report that refreshed upon each update to track population shifts and performance changes

Fulcrum developed an automated model scoring and monitoring process that enhanced efficiency, improved decision making, and increased confidence in results.

Client challenge

The client was seeking a streamlined method to organize their disparate data sources into a single location to start generating business insights. Some of their challenges included:

• A massive amount of disjointed information including internal and external data
• The lack of a unified view of the customer because the source systems are managed by different siloed teams
• The internal IT team was backlogged, and analysts needed support testing the latest big data tools

How we helped

The client partnered with Fulcrum to utilize our Agile Analytics Lab to experiment with big data solutions

• We created reusable data processing pipelines to allow easy data loading into Hadoop and data preparation for analysis
• After establishing the central repository, we then cubed the data using Hive and Spark for fast querying of metrics
• Output tables are stored in HBase and Impala is used for queries to gain rapid response while Tableau is utilized for dashboard reporting

Fulcrum’s lab enables a holistic view of the data to unlock insights and allows rapid testing of various open source tools. Our data experts guide the process allowing the clients to modernize their analytics team.

Client Challenge

The client needed help flagging fraudulent medical insurance claims. The goal was to:

• Determine logic to flag suspicious behavior and identify providers of interest
• Leverage billing data to analyze suspicious providers

How we helped

• We performed fuzzy matching to link multiple claim records to the same provider(s)
• We used geocoding to create physical distance calculations between providers and between providers and claimants
• We applied statistical methods (e.g., logistic ridge regression with sparse matrices, T-Score calculation, bootstrapping, etc.) to billing data to build propensity scoring models to rule claims as valid or invalid
• Based on our modeling results, we created the fraud flagging logic to identify suspicious behavior and providers of interest
• The team collaborated with the investigative unit, billing unit, and legal unit to create a provider fraud action plan

Fulcrum’s data preparation procedures and predictive analytical models provided the quantitative basis for the provider fraud action plan.

Client challenge

A leading eyewear distributor was looking for analytical guidance to power their sales and marketing efforts and overcome challenges related to:

• Cross brand affinity
• Returns
• Ideal price point
• Customer lifetime value

How we helped

• We provided deep analysis and customer relationship management consulting using advanced data modeling and analytics
• We provided campaign management, campaign contact strategy, and campaign operations for multiple brands in the portfolio
• Our Anvil™ platform hosted the CRM database and leveraged APIs with the client and its third party data sources

Fulcrum’s advanced data modeling and technology platform enabled a data-driven end-to-end sales and marketing operation.

Client challenge

A leading medical insurance company was seeking data driven campaign strategy, models, and marketing operations to accelerate their acquisition efforts.

How we helped

• Our Anvil™ platform securely hosted the HIPAA-compliant marketing database, and managed APIs, householding, suppressions, NCOA updates, opt-outs, etc. 
• We built predictive models to improve sales and marketing targeting and efficiency, including retention models for renewals. 
• Through building and implementing response, attrition, and best customer look alike models we evaluated data sources while providing cross-channel campaign solutions.

Using Fulcrum’s Anvil platform we built, hosted, and maintained a HIPAA-compliant and model-driven marketing database for cross-channel campaign solutions.

Client challenge

A medical supplier of blood glucose monitors and strips was seeking to increase their sales. 

They sought to identify the needs and habits of their customers and the feasibility of increasing sales through the offering of competitors’ products on its website.

How we helped

• We acquired customer and prospect lists from the manufacturer and analyzed existing customers and prospects’ blood glucose strip spending habits
• We designed a questionnaire to probe on blood glucose strip purchase behavior and blood glucose testing behavior and determine where blood glucose strip users get supplies, brands used, and the frequency in which they test
• We uncovered key behavioral and target audience information to better convert individuals into repeat customers

Fulcrum securely handled client and prospect lists for telephone survey recruitment, designed the questionnaire, administered the survey, analyzed results to determine the best course of action, and provided key targeting and strategy information for increasing eCommerce sales.

Client challenge

A well known weight loss service provider was seeking to:

• Deepen analytical insights for maximizing campaign effectiveness
• Analyze customer spending and attrition behavior 
• Conduct campaign analysis and reporting metrics

How we helped

• We developed a robust marketing database on Fulcrum’s Anvil™ platform to integrate data from multiple sources.
• We provided analytical models for customer spending, attrition, lifetime value, and segmentation to inform marketing campaigns
• We measured campaign success and refined future campaigns through a process of continuous improvement

Our team facilitated a data-driven direct-to-customer marketing operation with ongoing ROI measurement and a feedback loop of continuous improvement.

Client challenge

A leading blood glucose monitor manufacturer sought to:

• Modernize its communication streams 
• Develop cross-channel communication coordination

How we helped

• Our Anvil™ platform securely hosted the HIPAA-compliant marketing database and managed APIs. 
• We built predictive models to improve customer retention and winback in the context of customer lifetime value.  
• We provided ongoing cross-channel campaign experimental design and response analysis. 
• We designed and carried out customer research to fine tune multi-channel communication messaging and strategy

Our data science team built comprehensive predictive models to execute upon cross-channel factors that retain customers while conducting deep market research to maximize relevant communication.

Client challenge

The client was seeking support in evaluating various clinical programs. Key challenges included:

• Many clinical programs were operating without a randomized control group
• Historical evaluations were done in a time consuming and ad-hoc fashion
• There was a lack of consistency in evaluation scope and methodology across different clinical programs
• All of the above made it difficult to track changes and updates

How we helped

• We built matched control groups at the patient levels by matching patients enrolled in certain clinical programs with comparable patients who were not enrolled, based on a number of relevant criteria
• We calculated various outcome metrics to evaluate the program’s impact at the patient level
• The finely matched control group process allowed for result measurement by other important dimensions such as severity of illness, market, etc.
• We developed automated scripts to reduce labor hours for future updates

Fulcrum’s quasi-experimental design process allowed for program result measurement where there was no hold-out control group. We also developed automated scripts to increase consistency in methodology and reduce labor hours for future program measurement.

Client challenge

A major healthcare insurance company wanted to do a deep dive into their provider designation framework, in particular the cost-efficiency component, in order to generate insights.

How we helped

• We conducted sensitivity analysis on the cost-efficiency component of CCD and evaluated the impact on final designations
• We evaluated providers on multiple dimensions to offer better understanding of behaviors of PCPs, single vs. multi-specialty groups, etc.
• We performed a network analysis to measure provider connectedness

Fulcrum’s sensitivity analysis, multi-dimensional evaluation, and network analysis provided a deeper understanding of healthcare providers.

Client challenge

The client needed to accurately predict the cost for emerging and ongoing HCC and capitalize on better management through clinical outreach programs.

How we helped

• We refined internal data assets with stakeholders across the organization
• We set up a framework for a predictive model that would produce accurate cost predictions for emerging and ongoing HCC
• We used market basket analysis to identify key events for HCC

Fulcrum refined data assets to better align with key stakeholders and their goals, and then used those assets to identify key events that lead to HCCs in order to improve cost predictions and efficiency.

Client challenge

The client was looking to optimize their marketing spend by improving their targeted direct marketing practices to senior prospects of the Medicare Advantage Program.

How we helped

• We developed a model to generate prospect-level plan enrollment probability
• We reduced the cost of customer acquisition

Fulcrum developed a model to optimize marketing spend by identifying audience members who would most likely be willing to enroll in a specific program leading to a reduced customer aquisiton cost.

Client challenge

The client wanted to increase customer retention by prioritizing customer outreach.

How we helped

We developed a machine learning model to prioritize customer outreach while considering resource constraints resulting in increased efficiency in customer retention.

Fulcrum developed a machine learning model that incorporated customer data with internal resource constraints in order to create prioritized lists of customers for outreach, resulting in increased efficiency and customer retention.

Client Challenge

The client needed an easy to access and fully automated tool that would help them understand the impacts of price, marketing campaigns, and discount levels on their profits and sales numbers across all products.

How we helped

• We developed and implemented dashboard reporting to automatically provide standard business focused metrics such as spend per household, average spend, basket size, etc. to a wide range of users, with filtering available by product, line of business, region, and store
• We applied regression techniques to the observed data to provide visualization of trends and generate insights
• We programmed the reporting tool to provide recommended best price ranges for each product based on past weeks performance and conditions (price, quantity sold, and profit)

Fulcrum developed and implemented specialized metrics via flexible and easy to use dashboard reports to optimize pricing and promotions.

Client challenge

The client was seeking to improve incremental customer spending through personalized product promotions delivered via email, as well as integrating delivery with digital coupons on loyalty cards, all while tracking user experience end to end — from email delivery, to open, to click to add coupon/redemption.

How we helped

• We built an offer bank of product-specific promotions to individuals based on prior purchase and cross sell optimization models we built
• We delivered a personalized set of promotions via email and built an interactive pop-up micro site to add promotions to the customer’s loyalty card in real time
• We developed online dashboard reporting on ROI and individual promotion performance

Fulcrum developed tools to formulate and offer granular, personalized offers based on product opportunities, a big data platform hosting the end-to-end of the process, and implemented testing to determine the optimal means to drive more trips, build bigger baskets, and yield higher margins.

Client challenge

A Fulcrum client wanted to measure a mass media campaign’s impact on new customer acquisition at the local and store level.

The challenge was measuring advertising impact at the local and store level, as each market included in the campaign had stores with varying performance levels, competitive pressures, and demographic compositions.

How we helped

• We built matched control groups at the store and market levels by matching stores in treated markets with comparable stores in untreated markets, based on a number of relevant criteria
• We calculated the results of the campaign’s impact at the local market level as well as aggregated for total campaign performance
• The finely matched control group process allowed for result measurement by other important dimensions such as store format, population density, and proximity to competitors

Fulcrum’s quasi-experimental design allowed for macro and micro level results analysis.

Client challenge

• The client sought to build and enact a relationship marketing operation that would increase sales revenue and profit from existing customer relationships
• To enable this strategy, the client needed help developing a powerful customer segmentation and predictive modeling toolset

How we helped

• We built and implemented a multi-dimensional segmentation solution that assigned customer households into unique segments and sub-segments based on relationship cycle, purchase behaviors, value contribution and demographics
• We also built and implemented a relationship marketing experimental design environment to support sophisticated and accelerated testing that aimed to increase customer value, sales revenue, and profit from direct marketing investments

Fulcrum built and implemented a multi-dimensional segmentation and experimental design solution that enabled the client to test and refine its relationship marketing strategy, resulting in increased revenue, profit, and customer value.

Client challenge

A pricing software company used a process of measuring sales lift from its in-store marketing collateral service, but sought an expert review of its test design and measurement process.

They were seeking:

• A deep evaluation of their statistical methodology used to calculate lift
• An assessment of its client deliverables and claims about lift and significance
• Recommendations on a more efficient and standardized measurement process

How we helped

• Fulcrum independently created a matched control group design and performed the sales lift analysis without reference to the analysis already conducted
• The matched control group parameters were tested for sensitivity, and all data was checked for quality
• We compared our results to the original results and documented recommended improvements in sampling and experimental design

Fulcrum independently validated the measured outcomes, provided more granular insights, and suggested process improvements.

Client challenge

An eCommerce platform provider had a homegrown php system for their entertainment industry clients.

Initially, they had limited Adobe analytics tagging on their site, but the tagging javascript put into their php template was becoming cluttered and upgrading their system of tagging and tracking was cumbersome.

How we helped

• Fulcrum helped take all of the tagging out of the php templates and put it into a tag manager tool and standardized the capture rules
• We audited the tagging rules and added more as needed for analysis
• We built a vendor-neutral data layer to notify other marketing tools of capture events and variables

Fulcrum identified how to best upgrade the eCommerce tagging and tracking system, methodically audited tagging rules for best results, and implemented code to capture events and variables necessary to stay ahead of the competition.