Product Strategy & Go-to-Market
I help teams translate customer needs into useful offerings and a clear reason to adopt them. My work connects customer discovery, product priorities, launch planning, and commercial learning.
Turning demand for results into a new offering
The challenge
Entertainment advertisers needed to understand whether Twitter advertising drove viewing. Answering that question was central to making Twitter a flagship partner in their media plans.
My direction
I led the cross-functional effort to source, select, implement, and launch TV tune-in and viewership measurement. I worked with partners to refine the offering and expand its applications across television, streaming, sports, and premium video on demand.
The result
By Q3 2022, closed-loop viewership measurement covered nearly one-third of annual media and entertainment revenue.
Technical details
I was directly responsible for the selection, implementation, launch, and ongoing refinement of Twitter’s Incremental Viewership measurement solutions. Originally referred to as “TV Tune-In” measurement in partnership with either Nielsen or SambaTV, our offering eventually grew to serve Television, Streaming, Sports League, and Premium Video On-Demand advertisers. This solution was vital to the Entertainment sales team’s strategy to move Twitter out of its experimental advertising budgets and into a position as a flagship partner proven to drive results.
By the end of my time at Twitter, our most popular incremental viewership offering was built on top of Twitter’s intent-to-treat methodological framework, offering a causal look at how exposure to promoted Tweets delivered incremental viewers to the advertiser and provided performance split by targeting creative and flighting strategies. In addition to these standard offerings, these reports integrated with our A/B testing rollout and even showcased the viewership behavior among those exposed to second-hand earned media generated by people exposed to the paid campaign (sometimes referred to as “paid-earned” exposure).
Giving a product launch a stronger customer story
I supervised the design and delivery of Twitter for Mobile App Promotion, a multi-industry research project that powered the go-to-market launch of Twitter’s refreshed lower-funnel advertising products. The work connected product capabilities with advertiser needs and gave the launch a research-led narrative.
Bringing self-service insights into sellers’ everyday work
The challenge
Sellers needed timely, usable research without sending every repeatable request to a specialist. Moving to self-service required a clear value proposition, a practical transition, and support for work that still needed a human.
My direction
For Reddit’s self-service research offering, Automated Quick Pulls, I shaped the seller proposition and transition communication, approved launch enablement, and addressed access barriers. I set expectations for moving eligible requests into self-service while retaining specialist support for other needs, and challenged the team to explain how usage and feedback would inform the offering’s evolution.
What it enabled
The launch gave sellers a way to generate routine research themselves and established a new model for delivering advertiser insights. The launch put self-service research in the hands of nearly 300 sellers in the first two weeks alone, moving repeatable requests out of specialist queues while preserving support for more complex needs.
See how I scaled deliveryConnecting measurement capabilities with retailers’ business needs
The challenge
Major retailers needed to understand Pinterest’s contribution across ecommerce and physical stores. Their business questions and measurement approaches varied, so the value of the platform’s capabilities depended on how well those capabilities fit each customer’s needs.
My direction
I guided measurement strategy for Pinterest’s US Retail vertical, leading managers and practitioners and aligning cross-functional measurement products and client initiatives with retailer needs. That work included measurement summits, clean-room deployments, and connecting Pinterest’s measurement systems with client methodologies.
What it enabled
I connected customer needs, measurement capabilities, and client initiatives within a $2.2B retail business. Account-tracking systems and operating rhythms helped teams align on client priorities, improve visibility, and connect execution to shared objectives.
Knowing when to change a product’s direction
A pilot report at Reddit addressed advertiser questions about brand conversation, but its campaign framing created confusion about the purpose of the offering. Following executive feedback, I directed the pilot’s withdrawal, paused supporting materials, and set priorities for the replacement.
I challenged whether the metrics were meaningful and understandable, clarified how the report should serve existing client relationships, and pressed for simpler interpretation. The work focused the redesign on a clearer customer need and a more useful product story.
The measurement expertise behind the work
My background spans the full marketing funnel, from audience understanding and message testing to incrementality and attribution. That foundation helps me connect product and marketing decisions with meaningful measures of success.
Upper & Mid-Funnel
Brand Lift
Throughout my career, I've managed the delivery of hundreds of causal attitudinal studies to assess advertising impact on consumer perceptions. At Pinterest, I oversaw the comprehensive brand lift measurement suite, which includes both our native 2Q and 6Q solutions as well as partnership with Kantar. These studies utilized native in-app polling to measure the delta between exposed and control groups, allowing advertisers to understand the incremental impact of their campaigns on brand metrics. This work required deep expertise in survey design, methodology, and cross-functional collaboration to ensure reliable results.
Causal Social Listening
Twitter’s first-party Conversation Lift campaign measurement was built upon Twitter’s Intent-to-Treat methodological foundation and aimed to capture the leading mid-funnel indicators of favorability and top-of-mind awareness by evaluating the extent to which people exposed to paid campaigns on Twitter created more—or more favorable—content after seeing an ad. From auto brands launching new models to entertainment brands launching new shows and movies, my team and I deployed these studies to help clients understand the extent to which campaigns increased their cultural relevance.
Location Lift
Building on my experience developing location lift studies with Placed/Foursquare at Twitter, I led Pinterest's partnerships with both Foursquare and NinthDecimal for foot traffic measurement. These solutions matched Pinterest campaign exposure data with first-party device location data to quantify the incremental impact of advertising on store visits. NinthDecimal's Location Conversion Index (LCI™) and Foursquare's measurement capability allowed us to demonstrate Pinterest's effectiveness in driving physical retail results.
Lower Funnel
Conversion Lift/Incrementality Testing
I've been deeply involved in conversion measurement throughout my career, from alpha testing Twitter's first Conversion Lift studies to overseeing Pinterest's sophisticated conversion measurement solutions. At Pinterest, our offering included Conversion Lift studies that tracked both online and offline conversion activity, using statistical inference methods to measure incremental ROAS and CPA. We complemented this with Pinterest Conversion Analysis, which provided deeper insights into conversion windows, time-to-convert metrics, and conversion funnel analysis. This could be enriched with customer segmentation data to compare Pinterest vs. non-Pinterest conversions.
Conversion Analytics
At Pinterest, I expanded on my previous experience to lead innovative measurement approaches that combine multiple data sources and methodologies. This included integrating channel-attributed data, customer segmentation analysis, and conversion path analysis to provide advertisers with a comprehensive view of Pinterest's impact across the consumer journey. My team worked closely with retail advertisers to develop custom measurement solutions that align with their specific business objectives and measurement frameworks.
Closed-Loop Offline Sales Lift for CPG
Powered by Oracle Advertising or Nielsen Catalina Solutions, Twitter's closed-loop sales lift reporting enabled advertisers to measure the Return on Advertising Spend (ROAS) from promoted Tweets. This approach involved matching users exposed to ads on Twitter with real-world purchase data—sourced either from loyalty card transactions or compensated research panels. The vendors then applied advanced modeling techniques to extrapolate the impact observed in the matched data to the overall purchase behavior of all exposed households. They then compared these findings with those from a synthetic control group. Successfully delivering this measurement demanded not only a grasp of the experimental design's intricacies but also a thorough understanding of the creative, targeting, and flighting strategies proven to boost offline sales.
Clean Room Measurement
Drawing from my experience with clean room measurement at Twitter, I helped guide Pinterest's approach to privacy-compliant measurement solutions. This work has become increasingly critical as the industry evolves, requiring careful balance between measurement accuracy and user privacy. We worked closely with partners and clients to ensure our measurement solutions meet both technical requirements and privacy standards while delivering actionable insights.
Buy Through Rate Reporting for Automotive
Oracle Advertising’s Buy Through Rate (BTR) reporting offered an observational understanding of automobile purchases among households exposed to in-market automotive advertising on Twitter by matching exposed users to DMV registrations. Although these reports weren’t causal and did not have a control group, they did offer clients an understanding of which targeting techniques were best aligned with likely purchasers, discover the rates at which the reached audience purchased a car from a competitor, as well as other insights about the reached audience. The offering helped capture advertising dollars for Twitter by strengthening the platform’s position as home to affluent households who purchased “more cars, more often.”
Integrated Measurement
Multi-Touch Attribution (MTA)
I was part of the team that helped deliver Twitter’s first MTA integration with Neustar to key clients in the automotive and entertainment sectors, for which I was responsible. Although the Musk acquisition cut these initiatives short, I had the opportunity to influence the product roadmap, learn about my clients’ attribution models, and provide feedback on the fidelity of our measurement API.
Marketing Mix Modeling (MMM)
Throughout my time at Twitter, we provided data to service clients’ Marketing Mix Modeling initiatives. Handling these requests often involved intricate data extraction and transmission processes. Yet, the key to success is client discovery and proactive objection handling. This involved understanding how clients structured their models, grasping the granularity at which publishers were analyzed, and assessing how closely clients' on-platform advertising adhered to best practices for driving sales. These efforts were critical for maintaining and expanding Twitter's share of the advertising budget.
Audience Measurement
Amplify Audience Measurement with SambaTV
Twitter's Amplify program, a critical strategic initiative, aimed to increase revenue by tapping into digital video advertising budgets, which were incremental to the social media advertising budgets to which Twitter was traditionally aligned. Amplify curated, relevant, high-quality, brand-safe video content—ranging from NFL instant replays to The Oscars' red carpet moments—and offered pre-roll ad space to premier advertisers. Despite its popularity, securing rights to high-quality content posed a significant, ongoing challenge.
In collaboration with SambaTV, I spearheaded the development of a custom audience measurement product for our Amplify content acquisition team, providing them with critical data and insights. These reports detailed the size and composition of the audience reached by each content provider and assessed the extent to which this audience was incremental to traditional live, linear viewership. For instance, we could demonstrate to a major sports league how their live instant replays predominantly attracted light TV viewers, boosting their audience size by 20%. Senior leaders at Twitter used these insights in discussions with C-suite entertainment executives during content acquisition and renewal negotiations.
Nielsen Digital and Total Ad Ratings
Twitter established a custom server-to-server integration with Nielsen, facilitating cross-publisher Digital Ad Ratings (DAR) dashboards and cross-channel Total Ad Ratings reporting. This integration empowered advertisers to quantify deduplicated audience measurement metrics accurately, gaining deeper insights into campaign performance across various platforms. My team and I played a pivotal role in helping advertisers configure their campaigns for DAR measurement. We guided optimal flighting strategies to maximize results and addressed any objections. Our hands-on approach ensured advertisers leveraged the full potential of Nielsen's measurement capabilities, driving impactful outcomes for their campaigns.
Campaign Optimization
Pre- and Post-Campaign Message Testing
I designed, managed, and oversaw the delivery of qualitative and quantitative consumer responses to advertising messages on Twitter. My team and I would deploy these studies before the campaign to collect feedback from partner agencies and brands. Alternatively, we would leverage this capability when triaging underperforming measurement results to identify more specific areas where a campaign could have performed better. For these studies, we engaged our in-house community panel, Twitter Insiders, in partnership with various vendors, including Sparklr and C_Space.
A/B (Multi-Cell) Testing
Twitter introduced A/B testing to its Randomized Control Trial measurement framework during my last few years with the company. Our entire research organization, including my direct reports, worked to implement this technology into the brand lift offering. I led the effort to introduce multi-cell testing into our Incremental Viewership reporting. Although this required reworking our study feasibility framework and data extraction process, it enabled us to enrich client learning agendas with more actionable and rigorous findings.
