Turning Data Into Impact

Higher Customer Lifetime Value

The company prioritized customer investment and treatment on a first-come, first-serve approach favoring the newest customers.
Built CLV data infrastructure and models with team of data engineers & scientists.
Evangelized CLV as a decision tool to prioritize customer investment and treatment.
Expanded CLV toolset to include commercial customers, sales channels & acquisition strategy.
Churn declined several basis points in the highest CLV segment, resulting in >$1B incremental aggregate value.

The company was losing market share when customers were moving within its footprint.
Led an end-to-end review of the moving experience and built a 3-point game plan to regain share.
- Built a data environment to track relationships across addresses, providing a more complete and accurate view into share gain and loss.
- Redesigned and branded the moving experience to enable simple and easy transfer of services.
- Launched trigger marketing programs targeted to customers likely to move, powered by machine-learning predictive models, and to recently vacated homes.
Program drove a 6 ppt increase in retention of movers within footprint, contributing 150k incremental customer relationships.

One of the company’s theme parks did not have insights into key customer-level metrics like lifetime value, total revenue per visit, or repeat visits.
Built first unique customer-level master data environment integrating transactional data across multiple source systems.
Published customer-level metrics and insights, highlighting value of ancillary revenue sources (parking, food & beverage, retail).
Created customer & prospect behavioral, value-based segmentation models to improve marketing yield.
The theme park realized 3-5% incremental attendance (off-peak) and 1-3% lift in revenue per visit (peak).

The company had launched a new service offering but consumer uptake was slower than expected.
Led consumer research efforts to understand and address barriers to sales.
Redesigned go-to-market process to accelerate timing.
Aligned sales agent incentives and compensation with company’s growth targets.
Grew new service revenues 226% year-over-year, tripled customer base, increased revenue per customer by 8% and improved gross margin 6 ppt.
Reduced ramp-up time in newly launched markets to 2-3 months from 6+ months.

The company launched a CX transformation to improve industry-low customer satisfaction, but did not have a master data environment, measurement strategy, or CX analytics infrastructure in place.
Secured investment for CX data & analytics support from Executive Leadership Team.
Partnered with data management team to build the master CX data environment.
Recruited, incubated & grew CX analytics team.
Customer Net Promoter Scores (NPS) improved 35 ppts over the multi-year transformation.

The company had lost a record number of subscribers for one of its services over the trailing 12 months.
Led collaborative effort to define retention strategy and identify key levers through root cause analysis.
Tested and scaled new save offer playbook & agent compensation plan to align incentives.
Secured incremental customers & revenue through implementing “stair-steps” at end of promotions.
800k fewer pay TV customers & 200k fewer broadband customers disconnected service than in the preceding year.

The company had large volumes of customers whose aggressively priced promotional offers were ending, creating significant risk of customer and revenue erosion.
Built first-ever company-wide dataset tracking impact from promotional expiration on revenue and churn.
Determined optimal price increase for each promotional offer to balance revenue per customer and customer growth.
Revenue yield 3 months after promotional offer ended increased by >$1 per customer.

The company’s movie production studios did not have first-party data or insights at scale on viewers of their niche, independent films.
Built marketing database integrating first-party data collected across all of the company’s web and direct-to-consumer platforms.
Partnered with data science team and external vendors building look-alike models to scale target movie audiences.
5-10% incremental box office performance ($0.5-3m per film).

A mobile phone operator was searching for growth opportunities in adjacent markets.
Identified a particular segment in the U.S. wireless market as large and underserved, with needs closely aligned to company’s offerings.
Built business case and assessed strategic partners.
Developed product trial plan to validate opportunity.
The company launched tailored products nationwide under a flanker brand. The company was acquired less than 3 years later at a 10% premium.

Viewership for a marquis sports property was declining at an accelerating rate, putting advertising and affiliate revenue at risk.
Ingested viewership data and built knowledge graph to map relationships in viewing patterns.
Segmented sports property viewers using supervised & unsupervised machine learning algorithms.
identified cross-promotional opportunities to stabilize heavy viewing segments and spark growth in under-penetrated segments.
Arrested viewership decline & stabilized advertising & affiliate revenue.

The company collected large volumes of unstructured data that either lay fallow, untapped for insights and impact, or were manually read by employees in a labor-intensive, subjective process.
Evangelized and sourced use cases for a solution that could ingest & categorize data into topics, and summarize sentiment and insights on each topic.
Led team of data engineers, data scientists & AI developers to build, test & scale solution using Generative AI and Natural Language Processing (NLP).
Solution saved 250 hrs+ annually in manually reading and categorizing employee & customer feedback, and contributed to a 5 ppt improvement in adding a strategic new product to each customer sale.

The company’s core business was declining, and the company needed to overhaul its sales channels to compete in the evolving marketplace.
Led 3 15-person teams:
- First team identified and prioritized opportunities as part of a rapid diagnostic.
- Second team developed a turnaround plan for the largest channel.
- Third team revamped retail channel and partnership development strategy to expand reach and quality of distribution in stores.
The company realized $75+ million in annual EBITDA improvements and a 10-15% increase in customer acquisitions.