Case Studies – DANFORTH

The Price of Short-Term Thinking

Every strategist has lived through this moment: you run deep generative research, flag risks, recommend caution, and watch the company barrel ahead anyway. Months later, the fallout is exactly what you predicted.

The recent enforcement of a $25 minimum budget per job posting on Indeed is one of those moments. It may look like a small tweak in pricing. But to those in the field (recruiters, agencies, programmatic buyers), it’s a blunt instrument that strips away flexibility, inflates costs, and erodes trust.

What Changed

Until mid-2025, employers using sponsored jobs on Indeed could average their budgets across multiple postings. A campaign budget of $250 might cover ten jobs, but recruiters could rotate postings in and out based on weekly priorities.

That flexibility ended July 1, 2025. From that date forward, every job ID required its own $25 minimum allocation. Add a new job to an existing campaign? That’s another $25. Remove one and replace it? Another $25.

Strategy vs Tactics

Here’s the uncomfortable truth: this isn’t “strategy.” It’s revenue desperation dressed up as discipline.

Strategy is about positioning, resilience, and durable advantage. Tactics are the levers you pull for a mid-strategy correction or quarterly bump.

Consider the context: Post-COVID hiring volumes from 2021-2022 were never sustainable. The market cooled, volumes normalized. This wasn’t a shock; it was obvious. Rather than prepare investors for a cyclical downturn, Indeed chose to squeeze customers for near-term revenue.

Meanwhile, recruiters drowning in applicants needed agility, not more friction. Instead, the platform raised barriers and eroded goodwill.

Strategic Path Not Taken

A strategically focused company would have prepared both sides of the house (customers and shareholders) for the inevitable cycle. Instead of implementing revenue-extraction tactics, they could have invested in operationalizing AI in ways that entrench buyer operations and build loyalty.

What “operationalizing AI” could have meant:

Budget optimization assistants: AI tools that help recruiters dynamically allocate spend across jobs, based on performance signals and hiring urgency
Job rotation intelligence: Instead of punishing rotation, AI could automate it by pausing low performers, boosting high performers, surfacing recommendations
Candidate-fit triage: Reducing recruiter screening burden with models that prioritize quality applicants, especially when application volumes are high
Market insights dashboards: AI-powered labor market data to position Indeed as a trusted advisor, not just a job board

These are sticky features. Once recruiters bake them into daily workflows, churn drops.

This is the difference between investing in R&D and executing a stock buyback. One builds long-term capability and customer value, while the other merely manipulates a short-term metric. It is the choice between building for tomorrow and scrambling for today.

Competitive Reality

We’re at the early bubble stage of LLM hype. Investors are rewarding companies for credible AI narratives, not raw revenue grabs. A story of “we are transforming recruiter workflows with AI to capture the next decade of market share” would resonate with both shareholders and customers. Indeed chose to stress-test customer relationships at exactly the moment those customers were most cost-sensitive and sitting on abundant applicant supply. This misstep is magnified by the competitive landscape.

The competitor landscape for Indeed makes its inflexibility even more glaring. LinkedIn operates on pay-per-click models with cost-per-click typically ranging “$1.50 to $4.50 for generic roles,” allowing recruiters to “only pay when someone clicks” and “adjust in-flight” with daily and total budgets. ZipRecruiter uses subscription-based models with “predictable expense for companies hiring continually” and “job slots” for multiple concurrent roles. Both preserve the agility that buyers prize.

What this means strategically: when recruiters hit budget pressure, they now have clear alternatives that offer the flexibility Indeed just eliminated.

Backlash and Risks

On paper, the $25 floor looks like revenue optimization: predictable ARPU per job ID, simplified enforcement, fewer micro-budgets to manage.

The market response has been swift and negative. Across Reddit recruiting forums, industry podcasts, and trade publications, recruiters are expressing frustration. Chad & Cheese industry podcast reported recruiters saying roles that “don’t justify the $25 minimum just won’t run” and planning to “reduce our Indeed spend by 15–20%.” CXR community members are calling the change “monumental,” noting that “post 100 jobs you pay $2,500.” The AIM Group trade publication noted “pushback from recruiters may give a boost to competitors like ZipRecruiter, LinkedIn, niche boards.”

This isn’t just grumbling; it’s budget reallocation. Even a 15-20% spend reduction across thousands of employers compounds quickly.

The risks also compound:

Customer goodwill erosion—Recruiters feel trapped and exploited
Budget leakage—Even modest reductions in spend per customer aggregate to meaningful revenue loss
Brand damage—Once recruiters perceive you as extractive rather than enabling, recovery is slow
Competitive opening—More flexible pricing models suddenly look friendlier

Strategy is supposed to anticipate second-order effects. This move ignored them entirely.

Looking Ahead

We’re entering a period where the hype cycle around large language models will cool—likely within 2 to 3 years. Investors will punish companies that used AI as a story without building real, durable customer value.

The winners will be those that are prepared by strengthening customer operations, building loyalty through indispensable workflows, and using AI to entrench themselves in buyer processes.

The Lesson for Strategists

Ultimately, this isn’t a story about a pricing change. It’s a cautionary tale about strategic integrity. The core mandate of strategy isn’t to optimize for the next quarter’s earnings call; it’s to build a system of advantages that compounds over time.

True strategy is the discipline to choose the second option, especially when the first one is so tempting. That is how durable legacies are built, and how market leaders are truly separated from the pack.

Why Your Million-Dollar Strategy is Collecting Dust

You’re digging through your company’s document repository when you find it: a deck from a top consulting firm you didn’t even know had been hired. Inside, the analysis dissects challenges identical to what your team is struggling with today. In fact, you found it while searching for material for a presentation you’re drafting to describe the same problems. When is this from… 2019?

You find more, plus a $2.5 million statement of work. That’s a lot of money for this to be collecting dust. You look more closely at the deck. The content is still relevant, the team appears highly skilled, and the methodologies look solid. What happened? Why has nothing been done with this?

Why does this happen so often?

Why Great Strategies Don’t Get Implemented

Large consulting firms operate on an assembly-line approach. Senior partners diagnose and sell the vision. Mid-level managers translate it into diagrams and proprietary language. Analysts execute data gathering. With each hand-off, context evaporates. Nuance dissolves. Accountability diffuses until no one truly owns the outcome.

A CIO I once spoke with during a cold call crystallized a common bias. “Why hire you?” he asked. “If I hire [Big Four Firm], they’ll back a truck up filled with smart people. I can get stuff done very quickly.” He saw headcount as velocity. I see fragmentation risk. Bodies mistaken for strategic coherence. The reality is that no amount of capacity can move faster than people’s ability to adopt change. This makes effective internal socialization and change management critical.

An oversimplification problem compounds this. A director of product management at a major publisher once asserted to me that he knows a good idea if he can understand it in one sentence. This preference for repeatable methodologies, while operationally sound for firms managing hundreds of engagements, often reduces complex strategic problems to familiar frameworks. The result is lazy thinking: “We’re like Yelp, but for people.” “We’ll use micro-A/B testing, like Amazon.”

To be fair, when stars align, big firms can deliver exceptional results. For example, McKinsey’s partnership with ING Netherlands on its agile transformation is a masterclass in strategic continuity. McKinsey didn’t just deliver a report; they embedded consultants within ING for years. These consultants worked side-by-side with ING’s teams to co-design and co-implement a new operating model, effectively acting as coaches and teachers. This ensured the strategy was not just understood but fully owned and executed by ING’s people, building the internal capability to sustain the new model long after.

But these success stories are the exception due to structural constraints. Research from the firms themselves reveals the pattern: McKinsey finds that roughly 70% of transformations fail to achieve their intended impact, while Bain’s classic analysis estimates that 37% of strategy value is lost between planning and execution due to “significant value erosion” during implementation.

The big brand promise of lower risk is hollow against the industry’s 70% failure rate. Brilliant partners sell the vision, but execution gets handed to less experienced teams while the brand primarily protects the firm, not your success. For mid-market companies especially, this creates catastrophic mismatches in cost, culture, and scale.

A large consulting firm can deliver a “perfect” strategy, but if it was developed in a black box without building buy-in, training, and political capital within the client organization, it will die on contact. The failure of the hierarchical hand-off model is that it is structurally designed to prevent this necessary co-creation. It’s a delivery model, not an integration model.

Embedded Strategic Continuity

Complex problems demand a different approach: embedded continuity. Unlike a static plan, strategy is a dynamic process of adaptation. Market shifts, technical constraints, and user feedback will force pivots. The critical question is whether your core insights survive these changes or get lost in translation.

This requires a highly capable strategist who acts as a teacher, not a hierarchical team. The value isn’t in limiting resources but in strategic coherence. When the same expert mind connects initial research to mid-course corrections, it replaces fragmented hand-offs with coherent ownership, ensuring the core insight not only survives but intelligently adapts.

Value comes from cross-functional fluency that connects domains and stakeholders. This builds internal resilience by coaching teams through complex problems and maintaining strategic coherence from research to execution. The deliverable is not a deck, but a capable team and a living strategy your organization can evolve independently.

This approach is enabled by its focus on outcomes, not utilization. Without the burden of supporting armies of junior consultants, an independent strategist’s incentives are aligned solely with client success. This allows for candid advice.

For example, I once joked to a CEO that he needed to “fix your org structure first” before an expensive intranet. We laughed because it sounded absurd. But his high-growth startup had unclear team ownership. The intranet was a good idea that would have failed at that moment. Because my value wasn’t tied to that specific project, I could point out the real obstacle. We paused, clarified, and launched successfully later. The business model makes honesty possible.

Why an Independent Strategist is a Smart Financial Bet

If both big firms and independent strategists have a chance of failure, the one that costs significantly less presents a far better risk-adjusted return. A failed $2.5M project is a catastrophe. A failed $250k engagement is a learning experience.

The math is simple, but makes the point. For the independent’s expected value to be worse than the big firm’s, the potential gain from success would have to be negative. A skilled strategist who chooses engagements well should achieve a significantly higher success rate than 30% because their entire model avoids the top causes of failure.

The Future of Consulting

The value of large teams for data aggregation and slide production is plummeting. LLMs can now perform first-pass synthesis and drafting in minutes.¹ The future value of a strategist lies in high-order judgment, nuanced stakeholder management, coaching, and decision-making under uncertainty. These are precisely the skills championed by the embedded guide model.

These evolving capabilities connect to broader questions about where human expertise creates irreplaceable value. As I’ve explored elsewhere, the most strategic applications of technology require deep understanding of human behavior and organizational dynamics. These particular capabilities can’t be automated away.

The word “strategy” itself has become so diluted it’s applied to everything from banner colors to major pivots. When tactical decisions get elevated to “strategic” status (often because strategy commands more respect and budget), it creates confusion about what genuine strategic thinking actually involves. Real strategy isn’t about optimizing for next quarter. As I examined in The Price of Short-Term Thinking, it’s about building systems of advantage that compound over time.

Choosing the Right Approach

The consulting model must be matched to the problem, but you have more options than big firm versus independent consultant.

Internal resources make sense when you have available strategic talent with bandwidth for deep thinking. Current market realities complicate this. Many organizations lost senior strategic expertise during recent workforce adjustments, creating capability gaps where strategic work gets assigned to people already managing operational responsibilities.

Hiring from the now large available talent pool is another option. However, a professional consultant brings a distinct advantage: they are specialists in the art of external problem-solving, equipped with proven frameworks to navigate complexity from day one. Seasoned, dyed-in-the-wool strategy consultants excel at hyper-discovery, can provide stepped results immediately and avoid the pitfalls of large-scale hand-offs.

Stop Building a Strategy Graveyard

Complex challenges need guides, not decks. The goal is to build something vital with clarity and resilience, growing your capability, not your document folder.

When you commission strategy work, consider whether you’re building internal capability to navigate complexity or creating another deliverable. The embedded continuity approach focuses on developing organizational resilience that continues after the engagement ends.

Ready to build capability? The conversation starts with diagnosing whether your challenge needs strategic coherence or analytical horsepower—and choosing your approach accordingly.

This approach isn’t theoretical:
As an embedded guide, I coached senior Merck product and marketing leaders through an adapted design thinking process. Together, we moved from patient interviews to tested concepts, building the team’s capability while identifying digital health opportunities. The result wasn’t just a report; it was a patient-centered strategy and a more innovative team. Take a look: Merck’s Chronic Illness Research

References

“How to beat the transformation odds.” McKinsey & Company 2015.
“Leading organizations…” McKinsey & Company 2017.
“The agile at scale paradox.” Harvard Business Review 2018.
“ING’s agile transformation” McKinsey & Company 2017.
“Management Tools & Trends 2023.” Bain & Company 2023.

While LLM capabilities for synthesis continue advancing rapidly, current limitations in context, judgment, and stakeholder dynamics require human oversight for strategic applications. ↩︎

About the Author
Dorothy is a digital strategist who helps companies navigate complex challenges through embedded, continuous partnerships. She focuses on building internal capability and living strategies, ensuring insights survive from initial research through execution.

Stop Using Unattended LLMs for Candidate Screening. Do This Instead.

The other day I saw a post about using LLMs for candidate screenings, i.e. fully unattended systems, no human-in-the-loop. As in many current discussions about AI, opinions seemed to split into for and against. As someone who has researched and written about human-centered AI usage, I thought this was a good opportunity to explore issues specific to AI in hiring. I did, after all, work a stint at Indeed.

Let me be clear. I am not against using LLMs in hiring. I’ve been a technology consultant for *checks notes* a million years. I have witnessed promising new technologies applied in ways that ultimately limited their potential to serve us and improve our lives. The goal is smart, human-focused application. This means moving beyond the hype and fear to identify sustainable, win-win use cases that serve both organizations and candidates.

The current trend of deploying unattended LLMs for first-tier screenings is a strategic misstep. Even in an employer-favorable market, it risks brand damage and candidate alienation. When the market inevitably swings back, this practice will become active poison for talent acquisition. A 2025 Harris Poll shows 84% of candidates prefer a human for the initial screen, and Pew Research found 66% would not apply to a company using AI in hiring decisions. This isn’t sustainable innovation; it is a short-term gambit with long-term consequences. No bueno.

It is all well and good to critique what is broken. Real value, however, lies in envisioning what comes next. So let’s ask the question: what might a more human-centered AI collaboration in hiring actually look like?

The shift required is fundamental. We must stop asking how AI can replace humans and start designing how it can augment them. Consider the common frustrations on both sides of the interview table. A candidate often struggles to decode the true priorities hidden within a job description. A hiring manager, juggling endless meetings, may have only glanced at the résumé before the call. This creates an inefficient dance where both parties waste time simply establishing basic alignment.

This is where a transparent AI copilot shows promise. Imagine a system that analyzes the résumé against the job description before the interview, surfacing qualitative matches (not just keywords) and potential gaps. That analysis is then shared on screen with both the candidate and the hiring manager at the start of the conversation. The LLM provides suggested talking points or areas for clarification that the hiring manager can use or overrule. It becomes a collaborative tool. The hiring manager gets cognitive relief to lead a more focused discussion. The candidate gains agency to clarify or expand on points in real-time. The AI isn’t the judge; it’s the moderator ensuring both parties start on the same page.

Something like this was once logistically challenging, but post-COVID, the ubiquitous nature of remote meetings makes an AI-assisted first-tier interview a viable implementation. If successful, the candidate can progress to more open-ended rounds in person or remotely. I don’t propose this as a baked solution, but as a thought experiment for how human-centered AI might be operationally leveraged. No doubt some companies are already thinking this way or even building it. The core principle is that sustainable application requires transparency and shared benefit for both the hiring manager and the candidate.

The value here is derived from two non-negotiable principles: radical transparency and shared benefit. The hiring manager gains efficiency through reduced cognitive load and sharper focus. The candidate gains agency through visibility into the process and the opportunity to clarify context. This isn’t about replacing human judgment; it’s about enhancing its quality and fairness. This approach is best suited for roles requiring nuanced evaluation, not high-volume, low-complexity hiring where its advantages are diminished. No worries, we can come up with empathetic alternatives for that as well…with a little nuanced thought.

Humans are true experts at that.

The debate around AI in hiring does not need to be a battle between evangelists and skeptics. The most strategic path forward rejects this false dichotomy. We do not need to be uncritical advocates who deploy technology blindly, nor do we need to be reactionary opponents who dismiss its potential entirely. The goal is to thread the needle to enhance efficiency without eroding trust. Good vibes only.

Final thought from my heart to those struggling in this job market who might be reading this. If you are unemployed, or underemployed, we’re in an objectively soft employment market and AI is now crashing the party. The odds are stacked, but there are many of us in tech working on this. We see you. Take a deep breath. Remember who you are; the same amazing person you were before the market shifted. You are unique, powerful, and you’ve got this. The following song is my encouragement to you. Push on. ??

Case Study: Shaping Crypto Innovation for Schwab

How can a trusted financial institution like Schwab innovate in the rapidly evolving world of cryptocurrency while maintaining its credibility and regulatory alignment?

As Schwab’s leadership grappled with how to approach the crypto market, they were facing substantial outflows, losing hundreds of millions of dollars each month as investors turned to competitors for crypto investments. They needed a strategy that would recapture these investors while preserving their reputation for trustworthiness and regulatory adherence. I led research for an initiative within Schwab’s Innovation Accelerator to explore whether, how, and to what extent they should enter the crypto space. Through in-depth market analysis, investor research, and strategic ideation, we developed a path forward to provide Schwab with a competitive edge without undermining the brand’s core values.

In collaboration with the Innovation Accelerator team, I provided crucial decision-making insights, revealing the mindsets of both existing Schwab clients investing in crypto elsewhere and crypto-focused investors not yet using Schwab. Our evaluation of key competitors such as Fidelity and Robinhood informed a risk-reward analysis for various entry strategies. Beyond a direct crypto offering, we identified a valuable opportunity for Schwab to enhance its position by providing advanced decision-making tools—offering investors clarity while aligning with Schwab’s trusted brand image.

Results Snapshot:

Key Market Opportunity Uncovered: Our research identified a major opportunity for Schwab to provide advanced decision-making tools for crypto-curious investors, bridging the gap between the brand’s trusted reputation and the growing interest in cryptocurrency.
Data-Driven Insights for Executive Decision-Making: Provided Schwab leadership with comprehensive data on crypto investor mindsets, including both existing clients investing in crypto elsewhere and new investor segments. This data was crucial for evaluating market entry options.
Competitive Analysis for Strategic Differentiation: Offered an in-depth comparison of competitors like Fidelity and Robinhood, highlighting the risks and rewards of various entry strategies. Schwab’s competitive edge was tied to a differentiated platform focused on credible, robust decision-making tools.
Positioning Schwab for Strategic Growth: Our work provided a comprehensive strategy that positioned Schwab as a forward-thinking leader in the crypto space, offering a path to maintain brand trust while exploring new market opportunities.

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Case Study: Redesigning Job Budget Allocation for Indeed’s Enterprise Employers

How do you increase user trust in an automated system they don’t understand?

Indeed Enterprise was facing a growing problem. Employer clients were increasingly frustrated with the lack of transparency in a recently implemented automated payment allocation algorithm. The behind-the-scenes process distributed funds to job postings based on market conditions and other metrics. While well-intended to help employers maximize the value of Indeed’s advanced job market advertising model, users didn’t trust the system. Many employers bypassed the algorithm entirely, manually allocating funds per job, which led to inefficiencies, misaligned priorities, and mounting dissatisfaction.

As Senior UX Researcher, I led research for a redesign initiative to address these concerns, focusing on creating a more transparent, user-centered solution. Through in-depth user research and iterative prototyping, we developed a system that empowered employers with greater control over job postings’ budget allocation. The new solution not only increased user engagement and trust in the algorithm, but also shaped the product roadmap for future enterprise clients.

Results Snapshot:

Higher User Engagement: Clients who adopted the new workflow reported greater confidence and efficiency in managing job priorities and budget allocation, resulting in better overall platform satisfaction.
Increased Trust in Algorithm: The added transparency and control features significantly improved trust in the automated system, leading to higher adoption rates.
Strategic Product Influence: The success of this project directly shaped the future direction of Enterprise product strategy, influencing key roadmap decisions.
Model for User-Centered Design: The initiative was widely recognized internally as a benchmark for applying user-centered design principles, setting a new standard for the organization.

Case Study: Transforming Merck’s Chronic Illness Research Through Design Thinking

Can design thinking methodologies uncover new opportunities for patient engagement while ensuring innovation readiness for senior teams?

In an effort to engage patients more deeply with the Merck brand and explore new digital opportunities, I led a design thinking initiative focused on chronic illness research. The project aimed to mitigate the risk of Merck’s pharmaceuticals losing exclusivity to generics by identifying digital solutions that would enhance patient engagement. This initiative was also part of a broader digital transformation to build digital acumen across the organization. The challenge was twofold: develop patient-centered digital solutions while guiding senior team members to embrace new methodologies and strategies.

As a design thinking coach, I introduced the team to the Design Thinking model, guiding senior product and marketing leaders through iterative research processes. Together, we uncovered actionable insights into patient behaviors and attitudes, enabling Merck to explore new health-tech solutions that aligned with patient expectations and extended the value of their pharmaceutical offerings.

Results Snapshot:

Identified Health-Tech Opportunities: The research uncovered areas where Merck could introduce digital health solutions that aligned with the needs of chronic illness patients and physicians, extending their engagement beyond traditional pharmaceuticals.
Leadership Empowerment with New Methodologies: Senior market researchers and product leaders gained hands-on experience with design thinking and new digital research methods, which helped them adopt more innovative approaches across other initiatives.
Paved the Way for Future Digital Initiatives: The project laid the groundwork for future patient engagement strategies, positioning Merck to explore further digital transformations in the healthcare space.

Case Study: Enhancing Wawa’s Self Serve Kiosk for New Dinner Options

How can Wawa introduce new dinner options while ensuring an intuitive, high-quality ordering experience for customers in both established and new markets?

As Wawa expanded into new markets and introduced a dinner menu, the company faced unique challenges: maintaining their reputation for high-quality, made-to-order food, and overcoming the negative connotations associated with traditional gas station fare. Additionally, Wawa needed to enhance the functionality of their self-serve kiosks and mobile app to support these new dinner options, while making the ordering experience smoother and more intuitive for users.

I was engaged as a UX Research Consultant, drawing on my expertise in customer research and menu taxonomy to help Wawa tackle these issues. Our goal was to refine the kiosk and mobile app experience, using qualitative and quantitative methods to gather insights into customer behavior, and ultimately improve both satisfaction and order completion rates.

Results Snapshot

Optimized Menu Taxonomy: Streamlined the ordering process by revising the dinner menu structure and improving overall navigation.
Improved User Satisfaction: Real user feedback drove enhancements that boosted customer satisfaction with the kiosk and mobile app experience.
Actionable Insights: Delivered key findings on user preferences, helping Wawa introduce new offerings while maintaining brand consistency across markets.

Case Study: Streamlining Carton Tracking Workflows for Enhanced Efficiency

How do you transform a legacy logistics system into an efficient, user-centered platform without major infrastructure overhauls?

PCSTrac, a carton tracking solution for online retailers, had proven its value in core functionality but was hindered by a cumbersome user interface and workflow inefficiencies. Although technically robust, users often relied on time-consuming workarounds that slowed down operations. My role was to collaborate with senior engineers to bring a user-centered perspective, aligning design improvements with the existing technical constraints of the legacy platform.

Through contextual inquiries, persona development, and usability testing, I led the research that informed both workflow optimizations and interface redesigns. The project resulted in more streamlined processes that significantly improved user satisfaction and system usability. Additionally, the PCSTrac team embraced user-centered design principles, applying these to future product development.

Results Snapshot:

Balanced Technical Constraints and User Needs: Despite the limitations of the legacy system, the user-centered design approach introduced practical solutions that enhanced the user experience without necessitating expensive system overhauls.

Increased Efficiency through Streamlined Workflows: By addressing key workflow bottlenecks, the system allowed users to eliminate redundant manual processes, leading to measurable improvements in operational productivity within 3PL operations.

Improved User Satisfaction and Task Efficiency: The redesigned interface, with a cleaner and more intuitive layout, led to increased satisfaction among users who had previously been frustrated by the outdated interface. This improvement enhanced task efficiency and reduced friction in daily operations.

Case Study: Uncovering New User Segments for Comcast’s WiFi On Demand Service

How did unexpected user insights help Comcast re-engage customers and improve product workflows?

Comcast’s WiFi On Demand service experienced unexpected growth among various user demographics, including low-income users and former subscribers. Originally designed for business travelers, our research revealed that many users viewed the service as an alternative to traditional home internet, especially during life transitions. These insights provided Comcast with an opportunity to re-engage these customers with targeted payment plans, as well as enhance the product’s application interface to address key pain points and workflow inefficiencies.

Through buyer interviews, personas, user journey mapping, and surveys, I led a comprehensive research effort to understand these diverse behaviors and pain points. This informed strategies to re-engage key user segments and improve the interface design, ultimately increasing recurring pass purchases and expanding the service’s reach across underserved demographics.

Results Snapshot:

Re-engaged Former Customers: Comcast developed targeted re-engagement strategies for lapsed customers who had switched to daily passes due to overdue bills. This included customized payment plans aimed at bringing them back into monthly subscription services.
Enhanced Workflow and UI Efficiency: Direct improvements to the product’s user interface and workflow design were made based on the pain points identified during user research. These changes optimized the service’s overall usability and reduced friction in the ordering process.
Increased Revenue from Underserved Demographics: Insights revealed untapped customer segments, leading to increased recurring pass purchases from previously overlooked user groups, including recent movers and transient users.