Study Guide Audience (3) PDF

MODULE 2 Introduction to Linear TV Business Models TV has been both a witness and a creator of shared experiences over time, with references to key moments in history Differences between Linear, Non-Linear, OTT, and MVPD Linear TV: Traditional broadcast, real-time programming (e.g., over...

MODULE 2 Introduction to Linear TV Business Models TV has been both a witness and a creator of shared experiences over time, with references to key moments in history Differences between Linear, Non-Linear, OTT, and MVPD Linear TV: Traditional broadcast, real-time programming (e.g., over the air, satellite/cable), not streamed to specific users. Non-linear TV: Allows viewers to choose shows to watch via services like Video on Demand (VOD). OTT (Over-The-Top): Services bypass traditional distribution methods, mainly over the Internet (e.g., Netflix, Hulu). MVPD (Multi-Channel Video Programming Distribution): Subscription-based video service providers (e.g., cable, satellite). Audience measurement systems of linear TV The measurement of television audiences is crucial for the medium's role in the market. A professional, methodical, and independent approach ensures that the data is trusted by the market, making it reliable for decision-making. Diary Method: One of the earliest methods for recording TV viewing, relying on face-to-face interviews and phone calls. Pros: Simple and easy to implement in small sample sizes. Provides personal insights into viewers’ habits. Cons: Inaccuracy: Participants may forget or confuse viewing times. Bias: Responses are subjective, leading to potential errors. Limited scalability: Not effective for measuring large, diverse audiences, especially in today’s fragmented media environment. Electronic Method (e.g., People Meters, Audimeters): Uses devices that track TV viewing across multiple channels. In countries like Spain and the US, this method relies on sampling with a small panel representing a larger population. Pros: Provides real-time data and accurate tracking of what’s being watched. Measures multiple variables like channel, time, and specific viewers in a household. Sampling: Allows for cost-effective representation of larger populations. Cons: Costly: Installing and maintaining devices can be expensive. Privacy concerns: People may be uncomfortable with constant tracking of their viewing habits. Panel bias: While the sample is representative, it may not capture the full range of viewing behaviors across different demographics. Software Method (e.g., GTAM - Global Television Audience Metering): Developed to address challenges from the increasing fragmentation of media consumption, especially across TV, internet, and mobile platforms. It combines active and passive measurement techniques. Pros: Tracks cross-platform consumption, offering a comprehensive view of audience behavior. Active and passive measurement techniques offer flexibility in data collection. Adapts to new media trends, such as shifts in how people consume content. Cons: Data complexity: Requires advanced analysis due to the variety of platforms and devices involved. Reliability: Newer technologies are still evolving, which can affect consistency and accuracy. New Media (e.g., Internet Surveys, Cross-Media Measurement): Measures digital and Internet media consumption using phone and Internet surveys, tracking behavior across devices like smartphones, tablets, and computers. Pros: Comprehensive data: Captures both digital and traditional TV consumption. No special devices needed: Relies on devices people already use, such as smartphones. Cross-media insights: Helps companies understand the interaction between TV and online behaviors. Cons: Privacy issues: Data collection from personal devices can raise privacy concerns. Fragmentation: The variety of platforms makes data measurement challenging. Sampling bias: Methods based on the internet may miss certain demographics, particularly those less tech-savvy or not using specific devices. Measurement systems used in the US, Spain, UK A panel is a small group of carefully selected people (households, in the case of TV viewership) that represent the larger population. United States (Nielsen) What they measure: Nielsen is the company that tracks TV viewership in the U.S. They use a large group of households (42,000) to represent the whole country’s population (about 297 million). How they measure: They track what people are watching on TV and other devices like phones, tablets, and computers. ○ They can see what content (like shows or channels) people are watching, when, and even if they’re watching recorded shows (like on DVR or VOD). ○ They use a system that makes sure the group of people they track is a good mix of different types of viewers across the U.S. What’s the point? The data helps companies figure out what people are watching, which is super important for advertising and media decisions. United Kingdom (BARB) What they measure: In the UK, BARB does the same thing as Nielsen in the U.S. They track TV viewership in the country.  How they measure: They use a panel of 5,300 homes to represent the UK population. These homes are chosen to reflect different household types and regions in the country. ○ Over 12,000 people live in these 5,300 homes, and their viewing data is collected. How many people do they measure? The UK’s population is about 66 million. Spain (Kantar Media) What they measure: In Spain, Kantar Media tracks TV viewership. They also track households with TVs across the country. How they measure: They use a panel of households to represent the population in Spain. There are 5,720 households in the panel, representing a total of 13,829 individuals. ○ They make sure to include all kinds of people, from different regions, ages, and socioeconomic backgrounds. What they track: They track things like: ○ Region (where people live, like in the North or South) ○ Demographics (like age, gender, and income) ○ Equipment (what type of TV or device people are using) How many people do they measure? Spain has a population of 45.3 million, and Kantar tracks a sample of households to represent that number. New Projects: HBBTV and Focal Meter (Audience Measurement) SPAIN 1. HbbTV (Hybrid Broadcast Broadband TV): Combines two data sources: audience measurement panels (tracking who watches TV) and census data from the Smart TVs. This allows for a more detailed view of TV viewing. Kantar → merges these sources and distributes the results to the market. How it works: TV operators label their channels, and the system collects data from Smart TVs in real-time. The data is then merged with audience panel data to increase granularity (i.e., more specific and detailed information). Why it matters: This system reduces errors in traditional audience measurement and helps advertisers and content providers get a clearer picture of who’s watching what. It makes it easier to target ads and optimize content based on this more detailed data. 2. Focal Meter: Focal Meter is a device connected to your home internet router that tracks all the media content consumed online by devices in your household.  It records content only from platforms included in its "whitelist," like Netflix, YouTube, and others. How it works: If multiple people are watching content on shared devices (e.g., tablets or laptops), a small software is used to identify who is watching. For individual devices (like smartphones), no identification is needed. Why it matters: It provides accurate data for content providers about who is watching their content online, even across various platforms. The data is anonymous and only tracks content consumption, not personal information. Netflix & Kantar Collaboration in Spain: Netflix has partnered with Kantar in Spain to gain a better understanding of how people are consuming their content. How it helps: By tracking Netflix’s audience across different platforms, this partnership provides Netflix with a more complete view of its audience and performance in the Spanish market. Metrics: Universe, TTV, Rating, Miles, Share of Audience (SOA), Reach Universe: The total group of people being studied, typically individuals aged 4+ with access to TV in a given country. Total Television (TTV): The total number of people watching TV during a specific period, across all channels. Rating: The percentage of the reference universe watching a particular program, showing its relative audience size. Miles: The raw count of viewers (in thousands), showing the absolute audience for a broadcast. Share of Audience (SOA): The percentage of total TV viewers watching a specific program or network, showing how it performs relative to competitors. Reach: The total number of individuals who watch a broadcast for at least one minute, measuring the unique audience for a program. Programming Concept, Construction Phases of the Grid (Programming Strategies), Competition Programming Concept Television Programming is a complex process linked to culture, customs, and social habits. While international programs can make it seem like all TV is the same, programming is nuanced and tailored to each society's preferences. Levels of Programming: Involves selecting, coordinating, and ordering programs while considering how well they will connect with the target audience at specific times. Cultural Relevance: Programmers need to understand cultural peculiarities and audience preferences, using both quantitative (audience surveys, demographic data) and qualitative (cultural studies) insights to craft effective programming strategies. Global Influence on Programming: The United States sets global programming standards, which influence how television is organized in Europe and beyond, despite linguistic and cultural differences. Construction Phases of the Grid (Programming Strategies) Foundation The grid must be built with reference points that Laying structure the broadcast schedule. These foundational points help maintain continuity and connection across various time slots. Public Creating an invisible connection between Transfers different programs so that there’s smooth viewership transition between them. A strategy that considers the transfer of Staggering audiences from one program to another, of Ages ensuring a broad age appeal across different time slots. This refers to programming strategies that The Daily balance both vertical (daily) and horizontal Strip (weekly) programming structures for consistent viewer engagement. It’s challenging to broadcast a genre-specific Genre Strip product repeatedly in the same strip (block of time), as the audience for a genre can fluctuate. The most popular or strongest program in the The lineup should be strategically placed to capture Spearhead the largest viewership, often serving as the opening act of the programming block.  A strategy where programs that face tough The competition are placed strategically between two Hammock successful programs, cushioning them from direct rivalry. A less secure placement strategy that places The Mast three programs, with the strongest in the middle, hoping to boost viewership for the weaker programs on either side. Channels periodically break the routine by The Hits introducing "strikes" or unexpected content that Effects energizes the schedule and draws new viewers. When a program is performing exceptionally Duplex well, the instinct is often to extend its duration to capitalize on its popularity. Competition Junctures (Strategies) First Option: The channel that starts with a leading program has a competitive edge. Similar to Formula 1 races, it starts strong and works to maintain its lead. Period of Maximum Confusion: This refers to situations where no channel manages to secure a majority of the audience. This confusion often leads to intense switching by viewers who seek a satisfying program. The Pincer Effect: This occurs when two competing programs target different audience segments (e.g., younger vs. older demographics). This strategy can limit the entry of other competing programs. The Lasso Effect: When two channels broadcast similar content at the same time, they can create a “lasso” effect, where viewers switch between the two during breaks, boosting viewership for both. Separate Beds: A scenario where two programs air simultaneously on different channels, each targeting different genders, resulting in a split audience. Total War: A strategy where channels intensify their programming efforts as a final push to secure viewership, often without much regard for prime-time logic, using dramatic content to attract attention. Leader by Accident: Sometimes, programs unintentionally become popular due to unforeseen circumstances. These accidental leaders gain viewership by default, without the usual competitive effort. The Drag Effect: When a program becomes a clear leader, it attracts more viewers simply because it has gained popularity. The “bandwagon effect” plays a significant role here. The Prelude Effect: Programs that precede a popular program can attract viewers who want to watch the lead-in, contributing to an increase in their own audience. The Domino Effect: This happens when a failure in programming leads to a series of negative outcomes, creating a cycle of poor performance and damaging the channel's reputation. Counterprogramming Mechanism 1. The Control of the Initiative: Take charge by strategically choosing your program’s time slot (e.g. setting premiere of show after big sports event). 2. The Conquest of Territories: Target specific regions/demographics to build a loyal audience. 3. David vs. Goliath: Smaller programs challenge big ones with unique content. 4. Guerrilla Warfare: Time your program precisely to beat competitors (e.g. airing a show at a non-competitive time) 5. The Roof Theory: Recognize when a show may level off in viewership, so the channel focuses on keeping its existing audience engaged. 6. All Against One, One Wins: Multiple channels try to compete with 1 strong program but fail. 7. TV Event: Create a special, must-watch event. 8. The Infidelity of Foreign Production: Use foreign shows to fill programming gaps. 9. Development Bags: Gradually build up a program before moving it to prime-time. 10. Fit Engineering: Strategically place ads and programs to draw viewers from competitors. (e.g. a channel airs a drama with fewer ads to prevent viewers from switching) 11. Replays, Rebroadcasts, and Multicasts: Use repeats or different broadcasts to reach audiences who missed the original airing. Advertising: GRP, Target Audience, Core Targets, Commercial Targets, Aspirational vs Real. GRP (Gross Rating Points) Measures total ad exposure by combining reach (unique viewers) and frequency (how often they see it). Helps assess how effective a campaign is in getting the message to the right people and how often they’re exposed to it. The Importance of Knowing the Target Audience Research: Identifying your potential customers, where they are, and their behaviors. Segmentation: Break down the audience into smaller, more relevant groups based on demographics, behaviors, and interests. Media Planning: Once segmented, you can tailor messages and pick the best platforms to reach them at the right time. Strategic Approach: A clear strategy to connect with each group, using personalized messaging and relevant formats. Core Targets These are your primary customers—they have high purchase frequency and volume. While focusing on them is important, don’t exclude other segments. For example, a soda brand might find that a lot of consumption comes from outside the core target, like older or younger age groups. You need to strike a balance: Core targets drive sales, but broader audiences contribute to brand growth. Commercial Targets These are high-potential buyers—they may not be frequent customers, but they have greater economic capacity. Identifying these segments is key to maximizing revenue since they have the ability to make higher-value purchases. Aspirational vs. Real Targets Aspirational: Consumers you want to reach in the future. They’re ideal for your brand image, but they may not be the top spenders yet (e.g., younger, trend-driven people for luxury products). Real: The current buyers. These are the people who are already purchasing your product and driving sales today. The Balance: Focus on real targets for immediate sales, but don’t neglect aspirational targets. They help drive long-term growth and brand equity. Covid19 and the consequences on the entertainment industries. The pandemic significantly reshaped the media landscape, highlighting the importance of public media platforms like RTÉ, which earned trust by providing reliable information and updates. At the same time, streaming services like Netflix and Disney+ saw unprecedented growth as people turned to online content for comfort and connection, accelerating the shift from traditional TV to Over-the-Top (OTT) services. While traditional TV still experienced an increase in viewership, streaming platforms outpaced it, leading to heightened competition and increased subscriber churn as users moved between services. The rise of Connected TV (CTV) devices, such as Roku and Amazon Fire TV, reflected a growing demand for on-demand, convenient, and personalized content, with ad-supported models becoming more common as platforms sought alternative revenue sources. Consumer behavior shifted, particularly among younger audiences, who now favor engaging with news, social media, gaming, and streaming over traditional media. Looking ahead, the media industry must adapt to these changing habits by focusing on delivering smarter, more flexible, and personalized content to meet the evolving needs of modern audiences. MODULE 3 Definitions and differences: OTT, VOD, SVOD, TVOD, AVOD, PVOD, HYBRID VOD, FAST… 1. OTT (Over-The-Top) Definition: Services that provide video content via the internet, bypassing traditional distribution methods like cable or satellite. Examples: Netflix, Hulu, YouTube, Disney+.  Key Feature: Accessible on multiple devices, often offering content on demand. 2. VOD (Video on Demand) Definition: Video content that can be watched whenever the viewer chooses, rather than being scheduled. Examples: Content on Netflix, Amazon Prime Video, or cable-provided on-demand options. Key Feature: Offers flexibility to pause, rewind, and watch content at any time 3. SVOD (Subscription Video on Demand) Definition: A subscription-based model providing unlimited access to a library of content for a recurring fee. Examples: Netflix, Disney+, HBO Max. Key Feature: Flat fee for access to a wide variety of content; can be canceled anytime. 4. TVOD (Transactional Video on Demand) Definition: Consumers pay for specific content on a per-view basis. Subcategories: ○ EST (Electronic Sell-Through): Permanent access to purchased content (e.g., buying movies on iTunes). ○ DTR (Download to Rent): Temporary access for a smaller fee (e.g., renting a movie on Google Play). Examples: iTunes, Google Play. Key Feature: Pay-per-view model, no recurring fees. 5. AVOD (Advertising Video on Demand) Definition: Free video streaming supported by advertisements. Examples: YouTube, Tubi. Key Feature: Viewers "pay" by watching ads instead of using money. 6. PVOD (Premium Video on Demand) Definition: A premium model offering early access to content, sometimes while it’s still in theaters or shortly after. Examples: Disney's "Mulan" release on Disney+ for a premium fee. Key Feature: Pay a higher fee for exclusive or early access. 7. Hybrid VOD Definition: A combination of different VOD monetization models, such as AVOD and SVOD. Examples: Freemium models offering some content for free with ads (AVOD) and premium content for a subscription fee (SVOD).  Key Feature: Appeals to a broader audience by mixing free and paid options 8. FAST (Free Ad-Supported Streaming Television) Definition: Free streaming of linear TV content supported by advertisements. Examples: Pluto TV, Xumo. Key Feature: Offers live-streamed content without a subscription, supported entirely by ads. Future of TV and advertising OTT Growth: Streaming platforms like Netflix, Disney+, and Amazon Prime dominate, with Disney+ FAST services (e.g., Pluto TV, Tubi) are booming as free, ad-supported options. Audience Fragmentation: Viewers are spread across multiple platforms, making tools like Nielsen’s Cross-Platform Measurement essential for advertisers. Subscription Fatigue: Oversaturation of services leads to cancellations and churn. Hybrid models (ads + subscriptions) and FAST channels gain traction. Tech Advancements: Connected Devices: 69% of households own smart TVs, with streaming-friendly devices boosting access. 5G TVs: Promise sharper visuals, live VR events, and ultra-HD streaming. Algorithms: Personalize content using AI (Netflix’s Top Picks) Challenges: Ad-Fraud: Fake views and clicks hurt advertisers. Brand Safety: Tools help brands avoid inappropriate ad placements. Subscriber Churn: Netflix lost 200,000 subscribers in Q1 2022, focusing now on shared account fees to retain users. Market Dynamics: Competition: Mergers like Warner’s Max + Discovery+ aim to consolidate. Independent Studios: Innovators like A24 bring fresh content. Global Expansion: Localized content (e.g., Squid Game) attracts diverse markets. Future Directions: Emerging talent gains visibility via platforms like YouTube (e.g., Issa Rae). Hybrid models and content diversity dominate strategies. Demand for original, diverse content continues → The Witcher, Stranger Things etc. Metrics: Netflix/Disney/Hbo/Prime methodology and its metrics. Netflix Metrics: ○ Hours Watched: Netflix measures the total hours a title is streamed globally from Monday to Sunday. This metric is used for its weekly Top 10 lists (categorized by English and non-English films/TV shows). ○ Average Viewership: Calculated as total hours watched divided by runtime. This allows Netflix to compare its content with linear TV metrics. ○ Completion Rates: Watchers: Viewers who watch 70% or more of a title. Finishers: Those who watch 90% or more. Starters: Viewers who watch at least 2 minutes. ○ Retention and Churn: Tracks the percentage of subscribers leaving or staying with the service. Methodology: ○ Netflix expands its measurement window from 28 days to 91 days to allow titles time to gain traction. ○ Country-specific and global Top 10 lists are ranked by hours viewed but don’t directly show viewership per country. ○ Metrics may overestimate unique viewers by assuming full completion per watch session​. Disney+ Metrics: ○ ARPU (Average Revenue Per User): Tracks revenue per subscriber, segmented by regions. ○ Subscriber Growth: Focused on new sign-ups and retention rates in different markets. ○ Content Engagement: Internally evaluates how well specific shows and movies drive subscriptions. Methodology:  ○ Disney+ does not publicly share viewership data. Creative talent may receive partial viewership metrics for their projects. ○ By avoiding external validation (e.g., Nielsen), Disney can minimize scrutiny, especially for underperforming titles or cancellations​. HBO Max Metrics: ○ Engagement Time: Tracks the amount of time users spend watching content on the platform. ○ Retention and Churn: Measures how many subscribers continue or leave the service. ○ Subscriber Base: Total active subscribers globally and domestically. Methodology: ○ HBO Max selectively participates in Nielsen rankings. For example, it requested inclusion during the release of "Wonder Woman" but generally avoids external reporting. ○ Metrics are controlled to account for its mix of linear (traditional cable HBO) and streaming subscribers​. Amazon Prime Video Metrics: ○ Cost Per First Stream (CPFS): Measures the cost of production and marketing for a show divided by the number of new Prime members whose first streamed content is that show. ○ Demand Clusters: Subscription Drivers: High demand, low CPFS (ideal for new subscriber acquisition). Churn Reducers: High demand, high CPFS (retain existing subscribers). Niche Attractors: Low demand, low CPFS (target specific demographics). Low ROI Shows: Low demand, high CPFS (poor performance). Methodology: ○ Analyzes how shows attract and retain subscribers through detailed quadrant-based ROI assessments. ○ Integrates demand metrics with broader Amazon ecosystem data (e.g., shopping behavior)​. 5 reasons data-driven insights skyrocket OTT brands.  1. Boost Customer Experience and Engagement: Personalized recommendations and content delivery improve user satisfaction and retention by meeting individual preferences. 2. Stay Ahead of Competition: Real-time data insights enable platforms to respond faster to market trends and competitor strategies. 3. Provide Actionable Data for Teams: Developers, sales, and marketing teams can make informed decisions based on user behavior, leading to optimized campaigns and product offerings. 4. Efficient Resource Allocation: Data insights help platforms intelligently allocate funds for content production, marketing, and user acquisition, ensuring higher ROI. 5. Increase ROI: By targeting high-value users and reducing churn, platforms maximize revenue while minimizing costs​. North Star metrics vs Input metrics. North Star Metrics (NSMs): High-Level KPIs Definition: These are top-level metrics that reflect the core value a platform delivers to customers and measure overall success. Purpose: Serve as a long-term focus for growth and unify teams around key business goals. Examples: ○ Netflix: Total hours watched. ○ Disney+: ARPU (Average Revenue Per User). ○ HBO Max: Engagement time. ○ Prime Video: CPFS (Cost Per First Stream). Input Metrics: Granular, Actionable Data Definition: These are detailed metrics that influence and improve North Star Metrics. Purpose: Measure operational performance and identify specific areas for growth or optimization. Examples: ○ Netflix: % of new users who add at least three titles to their queue in their first session. Completion rates for shows. ○ Prime Video: Viewers’ demand scores for specific shows. Retention rates for niche content. Relationship Between the Two:  North Star Metrics represent the end goal (e.g., overall platform success or user loyalty). Input Metrics act as the drivers that feed into achieving these goals. Example: ○ NSM for Netflix: Customer Loyalty (NPS). ○ Input Metric: % of users adding titles to their queue on day one → Leads to higher engagement and retention → Strengthens NPS. In summary, North Star Metrics provide the big picture, while Input Metrics focus on the specific actions that contribute to achieving that vision. OTT Metrics (12 Definitions) 1. Monthly Active Users (MAU) ○ Definition: The number of unique users who opened your app or engaged with your OTT service in the past month. 2. Customer Acquisition Cost (CAC) ○ Definition: Total cost of acquiring a new customer. ○ Formula: Includes sales and marketing costs divided by the number of customers acquired. 3. Average Revenue Per User (ARPU) ○ Definition: Measures the revenue generated per user. ○ Formula: Total revenue divided by the total number of users. 4. Customer Lifetime Value (CLV) ○ Definition: The amount of money a customer is expected to spend during their lifetime. ○ Purpose: Helps optimize investments in acquiring and retaining customers. 5. Conversion Rate (CR) ○ Definition: The percentage of visitors who complete a desired action, like starting a free trial. ○ Example: If 500,000 visitors generate 125,000 free trials, the conversion rate is 25%. 6. Abandon Rate ○ Definition: The percentage of users who start but don’t complete a task (e.g., exiting during a free trial process). 7. Churn Rate ○ Definition: The percentage of customers leaving the service over a given period. ○ Example: Starting with 10M customers and ending with 9.5M gives a 5% churn rate. 8. Engagement Metrics ○ Definition: Tracks user interaction, such as app logins, videos watched per session, and specific in-app actions.  9. Inactive Users ○ Definition: Users who were previously active but are no longer engaging with the service. 10. Google Data Studio ○ Tool: A free Google platform to connect data sources and visualize performance through customizable charts and tables. 11. Subscription Billing Data ○ Definition: Tracks changes in subscriptions, renewals, cancellations, add-ons, and upgrades. ○ Purpose: Helps with revenue growth, customer lifetime value (CLV), and churn reduction. 12. Ad Server Data ○ Importance: Tracks performance for AVOD platforms, including ad failures, blockers, buffering issues, and fraud. Trends and Opportunities That Will Shape the Future of Platforms AI Integration: Enhanced personalization through algorithms, improving user engagement and content recommendations. Real-time data analysis for decision-making and content optimization. Cross-Media Analytics: Platforms adopting tools for cross-platform audience measurement and personalization. Example: Mobile phone audio-matching to track content exposure across devices. User Engagement Focus: Growth in interactive content formats and experiences to retain audiences. Importance of understanding user behavior and tailoring services accordingly. Global Expansion: Platforms investing in localized content to reach new markets. Emphasis on untapped regions with growing digital adoption. Sustainability in Revenue Models: Experimentation with ad-supported models and hybrid subscriptions to reduce churn. Focus on high-value users and optimizing retention strategies. Why OTT content publishers aren´t leveraging viewership data? 1. Lack of Transparency: Many platforms like Disney+ avoid publicly sharing detailed viewership data to reduce scrutiny and criticism, especially for underperforming titles or cancellations. 2. Limited Industry Standards: Metrics are often inconsistent across platforms, making it difficult to compare performance effectively. 3. Client Discretion: Platforms like HBO Max selectively opt out of industry-wide rankings (e.g., Nielsen) to control their narrative and maintain flexibility in reporting. 4. Strategic Reasons: Revealing detailed data could highlight weaknesses in specific areas or give competitors insights into internal strategies. 5. No Ad-Driven Pressure: Platforms without ads, like Disney+, face less demand to share data since they don't need to prove audience metrics to advertisers. OTT platforms prioritize control over their data narratives and minimize risks associated with transparency. MODULE 4 Social Media Metrics 1. Results: Represents the number of times a campaign achieves its intended outcome or goal. Common Types of Results: Website Purchases: The number of sales made through the ad. Leads: # of user sign-ups or resource downloads. Form Leads: # of people who filled out a form to provide contact information. Custom Conversions: Actions starting free trial, downloading ebook etc. Importance: Understanding which results your campaign is driving helps refine future strategies and ensures the campaign is aligned with business goals. 2. Cost per Result: This measures how much each desired result cost. Formula: Total ad spend ÷ Number of results. → If you spent $500 on a campaign and achieved 100 sales, your cost per sale would be $5 ○ The desired result will differ depending on your ad campaign ○ Cost per result can vary greatly by industry. 3. Result Rate (Conversion Rate): The percentage of desired results achieved compared to the total number of impressions → Converting viewers into customers or leads. A higher result rate indicates that the ad is well-targeted and effective. 4. Spend: The total amount of money spent on an ad campaign over a specific period. Why It Matters: Tracking spend ensures you stay within your marketing budget and allows for adjustments if the campaign isn’t performing as expected. Spend should be balanced with Cost per Result to ensure you're getting a good return on your investment. 5. ROAS (Return on Ad Spend): This metric tells you how much revenue you’re generating for every $1 spent on ads. ROAS is crucial for understanding the profitability of your ad campaign A ROAS > 1 means the campaign is profitable, while a ROAS < 1 indicates a loss 6. Impressions: The total number of times an ad or post is shown to users, including repeat views by the same user. Why It Matters: Impressions are essential for measuring the visibility and potential reach of your content. High impressions indicate your content is being exposed to many people, but it doesn’t measure engagement or conversions. 7. CPM (Cost per 1000 Impressions): This metric measures how much you’re paying for every 1,000 impressions your ad generates. Why It Matters: CPM is useful for comparing the cost-efficiency of different campaigns. It shows how much you are spending to reach a large audience, which is important for brand awareness campaigns. 8. Frequency: The number of times an individual user sees the same ad or post. Why It Matters: Too much frequency can lead to ad fatigue, where users become annoyed or ignore your ad. Too little frequency might mean that the ad is not being shown enough to drive conversions. ○ If frequency is too high, consider broadening your audience or creating new ad creatives to avoid over-saturation. 9. Reach and Organic Reach  Reach: The total number of unique users who see your content, whether through organic or paid methods. Organic Reach: The number of unique users who see your content without any paid distribution. ○ Why It Matters: Reach is essential for understanding how many people are being exposed to your content. ○ Organic reach is particularly important because it shows the organic effectiveness of your content without additional ad spend. 10. CPC (Cost per Click): The amount you pay for each click on your ad. Why It Matters: CPC helps measure how engaging your ad is. A high CPC suggests that the ad may not be resonating with your target audience, or the competition is high. 11. CPA (Cost per Acquisition): The cost associated with acquiring a new customer or completing a conversion action (e.g., purchase, sign-up). Why It Matters: CPA helps determine the cost-effectiveness of acquiring a customer through paid ads. Lower CPA means you're acquiring customers at a more efficient rate. 12. LTV (Lifetime Value): Total revenue customer generates with brand (lifetime relationship) Why It Matters: LTV helps businesses understand the long-term value of each customer. This metric guides decisions on customer retention strategies and budgeting for customer acquisition. Knowing LTV allows businesses to allocate more budget towards acquiring high-value customers and tailor marketing efforts to maximize their return over time. Special TikTok: Methodology, Insight, Creative Strategies TikTok Methodology: TikTok’s ForYou page serves personalized content from across the platform, not just from social circles. The platform has a low engagement transaction cost (short videos, minimal time commitment) and uses dynamic attention techniques to keep users engaged. TikTok Insights: Ads on TikTok are emotionally engaging and more memorable than TV or digital video ads, leading to higher future purchases and brand recall. Creative Strategies: Focus on compelling content instead of followers. TikTok’s algorithm rewards organic, non-branded content, so avoid overly commercial ads. → "Make TikToks, not Ads." Social Dynamics TikTok’s social dynamics are driven by its algorithmic content delivery, which offers content from all over the world This creates a diverse and viral content cycle where trends and challenges spread quickly. TikTok encourages engagement rhythms, keeping users scrolling longer. Platform Mechanics ForYou Page: Serves diverse content, not just from your social circle. Engagement Cost: Simple, quick interactions (e.g., scrolling) → easy for users to engage. Dynamic Attention: Rhythmic stimuli keep users immersed and engaged without much decision-making. How Can Consumer Insights Improve Advertising? Consumer Insights help businesses understand behavioral drivers behind purchases, allowing brands to tailor campaigns to consumer desires. Shift to Consumer-Centric Marketing: Brands can focus on features that resonate with customers (e.g., noise-cancellation in headphones) instead of just products. Improve Customer Experience: Insights help improve customer service, boost brand loyalty, and attract new clients through word-of-mouth. Optimize Marketing Strategies: Consumer insights identify trends and sentiments, enabling brands to adjust campaigns and stay ahead of competitors. What makes content go viral? Virality, how to measure it?... Virality: Refers to the ability of digital content to spread rapidly across social networks, reaching a large number of users in a very short time, even on a global scale 2 Types of Virality a. Spontaneous Virality: Virality driven by user reactions, occurring randomly without planning. b. Planned Virality: Content intentionally crafted and promoted to go viral, often as part of a marketing strategy. The Psychology Behind Virality Relevance: Content related to current topics and trends is more likely to be shared. Authenticity and Originality: People share genuine, unique content, making it stand out. Emotion: Emotional content (joy, surprise, anger) has a higher likelihood of being shared. Humor and Entertainment: Funny or entertaining content increases engagement/shareability  Immediacy and Ease of Use: Social media’s ability to spread content quickly Algorithms: Social media platforms amplify content with high engagement Visual Content and Attractive Design: Well-produced, visually appealing content captures attention and increases shareability. Positive and Negative Virality a. Positive Virality: Content that generates excitement, joy, or valuable engagement. Positive virality boosts brand visibility and engagement without causing harm. Example: The Eurovision campaign at 10 TV led to 1.4 million impressions and a 50% increase in audience share for Caso Cerrado. b. Negative Virality: Content that spreads due to controversy, anger, or outrage. Negative virality can increase visibility but poses reputational risks if not handled carefully. Example: A controversial campaign can lead to backlash if it is perceived as offensive or manipulative. Measuring Virality Total Reach: The number of people who view the content. More reach means more virality. Engagement and Interaction: The number of likes, shares, comments, and other interactions Increased Traffic: If the viral content is linked to a brand, an increase in website traffic or sign-ups suggests success. Conversions: The ultimate indicator of success—how many sales, sign-ups, or other desired actions were driven by the viral content. The Psychology Behind Virality: Jonah Berger’s “STEPPS” Model S → Social Currency: People share content to enhance their social image. Content that makes them appear fun, interesting, or knowledgeable is more likely to be shared. T → Triggers: External cues that remind people about content. These triggers keep content on the top of people's minds. E → Emotion: Content that triggers strong emotions (positive or negative) is more likely to be shared. Emotional content drives action. P → Public: Visible content is more likely to be shared. The more public something is, the more likely it is to be imitated and spread. P → Practical Value: Content that offers useful information or value is often shared because it helps others. S → Stories: People love to share stories. A compelling narrative makes content more relatable and memorable, which increases its likelihood of being shared.