ROGERS INSIGHT
CASE EXAMPLE 01   /   CONTENT & CONSUMER INSIGHT
Decoding Discovery

Viewer journey research strengthened film sales pitches and informed new approaches to content discovery.

Faced with growing choice paralysis - with viewers spending approximately 40% longer searching for content than four years earlier - I conceived, funded and directed a substantial qual and quant study with MTM to understand how audiences decide what to watch. I brought the findings to major broadcaster and platform partners, initiating practical experiments and strengthening Sony's position as a valuable insight-sharing partner.

RESEARCH LEADERSHIPAUDIENCE BEHAVIOURPARTNER COLLABORATION
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01 / THE CHALLENGE

More choice. Harder decisions.

The explosion of entertainment choice has made discovery a growing challenge for viewers - and for the businesses trying to connect the right programmes with the right audiences.

THE GROWING DISCOVERY CHALLENGE

~40%
Increase in US content-search time, 2019–2023
10.5 min
Average US search time in 2023
Source: Nielsen, 2023. Earlier figure approximately 7.5 minutes.
02 / THE RESEARCH APPROACH

Decoding the decision journey.

The study explored the journey from becoming aware of a programme to choosing to watch it. A behavioural framework helped distinguish the different decisions people make along the way.

01 / AWARENESS

Prime

Awareness, recommendations and familiarity influence which titles viewers notice.

02 / ATTENTION

Catch

Artwork, titles and positioning help content stand out when people browse.

03 / EVALUATION

Consider

Viewers weigh personal preferences, mood and details such as genre or synopsis.

04 / CONFIDENCE

Convince

Reviews, ratings and other quality cues can provide reassurance before a choice.

03 / AN AUDIENCE INSIGHT

Who really chooses
what's on?

Content discovery is not always an individual decision. The study examined how influence works within households - including those who actively search and recommend, and those who are happy to let someone else narrow the choices.

Shepherds

Take an active role in finding, filtering and recommending what the household watches.

Sheep

Are comfortable allowing others to shortlist options or guide the final viewing decision.

04 / THE BUSINESS APPLICATION

From research to collaboration.

Beyond understanding the audience, the ambition was to make the findings useful to Sony's broadcaster and platform partners - opening discussions about what could be tested and improved in the discovery experience.

01

Research with purpose

Conceived, funded and directed a substantial mixed-method research programme with MTM.

02

Partner conversations

Translated audience behaviour into practical discussions with major broadcaster and platform partners.

03

Practical experimentation

Helped initiate joint experiments and strengthened Sony's role as an insight-sharing partner.

Commercial application and platform relevance

The research strengthened Sony's commercial storytelling, demonstrating the stopping power of film during the Catch stage. Recognisable Hollywood imagery helped titles attract attention, while familiarity with films and associated perceptions of quality strengthened the proposition for broadcasters and streaming platforms.

The framework also identified opportunities to improve content discovery. For example, the research highlighted Sky's strength at Catch and an opportunity to provide greater reassurance at the Convince stage. Following our presentation, Sky introduced user reviews to its mobile app, addressing a gap the research had identified.

05 / INDUSTRY PERSPECTIVE

Why it resonated.

The findings were relevant well beyond a single organisation, prompting discussion about how commissioners, marketers and product teams could help viewers navigate abundance.

“This work highlights the overwhelming environment we've created for our viewers to offer an "all you can eat buffet" of content. I challenge anyone to apply this to their own life and realise there is indeed a "Shepherd" and "Sheep" in their household. Knowing this, we can absolutely arm our content, marketing & product colleagues with new ways to identify & reach these viewers better.”
Sarah Clarkson
Director of Insight, Channel 4
CASE EXAMPLE 02   /   AI & INSIGHT TRANSFORMATION
AI & Streaming Measurement

Delivered a working studio-first AI prototype for faster analysis of third-party streaming measurement data.

I originated the concept for a business-led AI initiative built around large external streaming-measurement datasets, secured senior backing through LA-based stakeholders and AI governance processes, and led collaboration with IT, Data Science and Research colleagues to assess tools, design the approach and deliver a successful proof of concept.

AI INNOVATIONSTREAMING DATACROSS-FUNCTIONAL LEADERSHIP
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THE APPROACH & APPLICATION

Exploring AI-enabled streaming intelligence.

Making complex third-party streaming measurement more accessible while maintaining research judgement and governance.

Challenge and ambition

As more title-level streaming data became available, extracting meaningful, consistent answers required contextual understanding as well as growing analytical capacity. The objective was to explore how emerging AI tools could expand insight capabilities and improve analytical efficiency while retaining research rigour.

My Input

  • Defined the concept, potential business use cases and research workflows.
  • Built senior sponsorship and funding support through US stakeholders and AI governance processes.
  • Worked with IT and Data Science on data structure, contextual definitions and phased testing.

Proof of concept achieved

The initiative achieved a successful proof of concept, demonstrating that an internally developed AI analysis tool could apply the required methodological rigour and accuracy to large, complex third-party datasets while accelerating analytical workflows.

The work validated the feasibility of the original vision and established a foundation for future development of AI-enabled insight capabilities.

AI ANALYSIS FRAMEWORK

Human expertise shapes every stage.

The proposed framework combines reliable data access with research methodology, context and ongoing evaluation.

INSIGHT CREATORS

Human expertise drives the questions, judgement and commercial interpretation. AI expands analytical capacity, accelerates exploration and enables new opportunities to generate insight.

AI ANALYSIS ASSISTANT / AGENT

Natural-language interaction, analytical task planning and tool orchestration, with analyst review.

VALIDATED DATA ACCESS

Governed queries, verified metric calculations and checks on the underlying data.

RESEARCH & METHODOLOGICAL CONTEXT

Methodology documentation, real-world representativeness, qualitative interpretation, minimum sample sizes and internal best practices. RAG can retrieve relevant guidance; critical rules are enforced in the analytical tools.

DATA FOUNDATION

Internal and external datasets, harmonised definitions, quality checks and secure data storage.

EVALUATION & GOVERNANCE - CONTINUOUS THROUGHOUT

Defined from the outset, tested during each build iteration and revisited in use. Includes verified benchmark questions, calculation accuracy, methodological compliance, access controls and human review.

CASE EXAMPLE 03   /   AI & CONTENT INNOVATION
Synoptimiser

AI-powered qualitative research at scale to optimise programme synopses.

Partnering with an emerging AI research agency, I commissioned a new approach to evaluate how programme descriptions influence audience interest. Working with US-based Marketing colleagues, I designed the research stages, directed analysis and translated the learning into improved content signposting and clearer communication for the future content pipeline.

RESEARCH INNOVATIONCONTENT SIGNPOSTINGAI-ASSISTED ANALYSIS
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THE APPROACH & APPLICATION

Qual at scale, human judgement and digital twin testing.

Using qualitative understanding to identify the variables worth testing, then exploring hundreds of synopsis variations through simulated audience responses.

The project combined qualitative research at scale with human-led decision-making to improve how programmes were described and positioned.

Qual at scale helped reveal how audiences talked about films, what they responded to in programme descriptions, and which elements were most likely to influence interest. Those findings then informed internal decisions about the variables worth testing - including tone, genre description, cast references, awards, message hierarchy and platform-specific character limits.

Digital twins were then used to test hundreds of synopsis variations built from those variables. Unlike traditional A/B testing with real respondents, this approach allowed the full simulated sample to assess all versions, with settings designed to prevent prior exposure influencing later responses.

The result was a faster, lower-cost and more scalable way to optimise programme descriptions - unlocking a new capability that would have been difficult to achieve through conventional testing alone.

HOW THE APPROACH WORKED
01
◎

Qualitative research at scale

Understand how audiences talk about films and what matters in a synopsis.

02
✧

Human decision-making

Define the variables: tone, genre, cast, awards, message hierarchy and platform character limits.

03
◇

Digital twin testing

Assess hundreds of synopsis variations, with memory reset controls to avoid carryover between versions.

04
✓

Optimised descriptions

Improve programme signposting and create a repeatable new optimisation capability.

Faster learningLower research costNew capability

The opportunity

Understand how audiences talk about films and respond to programme descriptions, then evaluate combinations of creative and platform-specific variables that would be impractical to test through conventional human A/B studies.

My Input

  • Partnered with an emerging AI research agency and commissioned a new research approach.
  • Directed the research stages and analysis, working with US-based Marketing colleagues to prioritise the variables worth testing.
  • Applied the findings to programme signposting and future content pipeline communications.

What it enabled

A faster, lower-cost way to assess hundreds of synopsis combinations, opening up an optimisation capability that was difficult to achieve through conventional testing alone.

CASE EXAMPLE 04   /   CONTENT & CONSUMER INSIGHT
Content Testing

Embedded audience testing in film and TV Marketing and Production.

Beginning with a more audience-led Distribution sales process, I established new testing approaches and scaled them across major EMEA markets. I worked with Global Marketing colleagues in Los Angeles to inform programme concepts, positioning and artwork, while partnering with Producers to evaluate pilot episodes scene by scene, identifying opportunities to strengthen storytelling and audience engagement.

CREATIVE DEVELOPMENTMARKETING STRATEGYRESEARCH LEADERSHIP
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THE APPROACH & APPLICATION

Embedding research into creative decisions.

Bringing audience insight into the process early enough to influence content, marketing and commercial outcomes.

How it evolved

What began as an audience-led approach to improving distribution pitches became increasingly integrated with marketing and production decision-making.

My Input

  • Established stakeholder confidence through hands-on research and senior readouts.
  • Scaled consistent testing approaches across major EMEA territories.
  • Worked with Global Marketing colleagues in Los Angeles on concepts, positioning and artwork.
  • Partnered with Producers on pilot episode testing, including scene-by-scene audience reactions.

The value

Audience evidence informed film and television pitches, programme positioning and creative development, while scene-level feedback gave Producers a more detailed understanding of viewer responses to pilot episodes.

CASE EXAMPLE 05   /   STRATEGY & ORGANISATIONAL CHANGE
Re-Imagine

Shifted Sony Pictures Television EMEA towards insight-led strategy and sales.

Across Sony's EMEA business, I expanded insight and strategy capabilities and integrated Research into commercial strategy, client conversations and content sales. The evolved model combined central expertise, locally embedded roles, new methods and a focus on decisions rather than reports.

FUNCTIONAL LEADERSHIPOPERATING MODELCOMMERCIAL IMPACT
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THE APPROACH & APPLICATION

An insight function built around decisions.

Rethinking structure, operating practices and stakeholder engagement to make research more commercially relevant.

The ambition

Move beyond research reporting and inbound requests towards proactive, integrated commercial partnerships, with locally embedded insight contributors and a connected EMEA strategy.

My Input

  • Set the EMEA insight agenda and service model, aligning research priorities with commercial decision-making.
  • Built and expanded locally embedded Research capability, adding five new territory-based roles and strengthening support within market teams.
  • Recruited, coached and developed talent, while leading teams and external research partnerships.
  • Combined primary research with streaming, linear and market data to create more comprehensive commercial intelligence.
  • Introduced shorter, more actionable communications tailored to the decisions stakeholders faced.

Why it mattered

Research became an active part of the commercial team, joining client conversations and contributing insight directly to content pitches and sales strategy. Five new territory-based roles embedded that capability closer to market teams.

Let's explore what's possible.

Together, we'll turn insight into impact.

Get in touch