Break Through the Noise: Find Your Audience with Data-Driven Advertising
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In this webinar, 4C's Aaron Goldman and LinkedIn's Ty Heath discuss why good data leads to great advertising. Watch the recording here: https://www.youtube.com/watch?v=zKhe9-tppms
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Break Through the Noise: Find Your Audience with Data-Driven Advertising
- 1. Proprietary and confidential. ©2020 4C Insights, Inc. BreakThrough the Noise Find Your Audience with Data-Driven Advertising Aaron Goldman Chief Marketing Officer 4C @AaronGoldman Ty Heath Global Lead,The B2B Institute LinkedIn @tyrona
- 2. Proprietary and confidential. ©2020 4C Insights, Inc. Webinar Info • Send questions via Q&A and we’ll answer at the end. • Let us know if you are having any technical issues. • Use/follow #FindYourAudience
- 3. Proprietary and confidential. ©2020 4C Insights, Inc. Our trends are contrarian by design ContrarianConsensus Wrong Right
- 4. Proprietary and confidential. ©2020 4C Insights, Inc. And our trends are “right” by replication There is no more fundamental requirement in science than that the replicability of findings be established.” – Seymour Epstein,Cognitive Scientist
- 5. Proprietary and confidential. ©2020 4C Insights, Inc. The Sub-Prime Data Crisis 01.
- 6. Proprietary and confidential. ©2020 4C Insights, Inc. Hint: That’s no better than flipping a coin. “Digital profiling is only able to accurately identify gender 50 percent of the time." Source: “How Effective Is Black-Box Digital Consumer Profiling?” MIT, MBS, GroupM 80% of the marketing industry runs on fake data
- 7. Proprietary and confidential. ©2020 4C Insights, Inc. “We’re not only not reaching the right people, we’re not reaching people at all” Fake Sites FakeTraffic - Dr. Augustine Fou, Ad Fraud Researcher
- 8. Proprietary and confidential. ©2020 4C Insights, Inc. Privately, we acknowledge our data isn’t real, yet publicly we tell a different story Of Marketers Have Confidence InThe Accuracy OfTheir Data 12% Source: Forrester Wave: B2B Marketing Data Providers, Q3 2018
- 9. Proprietary and confidential. ©2020 4C Insights, Inc. You’ve seen this movie about “AAA-Rated Data,” right?
- 10. Proprietary and confidential. ©2020 4C Insights, Inc. Start shortening your supply chain to identify real data Direct Data Direct Payment
- 11. Proprietary and confidential. ©2020 4C Insights, Inc. “…Master of cleaning, extracting, and trusting my data before I do anything with it.”
- 12. Proprietary and confidential. ©2020 4C Insights, Inc. Signal-To-Noise Ratio 02.
- 13. Proprietary and confidential. ©2020 4C Insights, Inc. What can gambling teach us about whether “big data” leads to better decisions? Source: Paul Slovich, Behavioral Problems of Adhering to a Decision Policy
- 14. Proprietary and confidential. ©2020 4C Insights, Inc. Signal-to-noise ratio explains why “big data” often leads to worse decisions I’m not saying there’s no information in big data – there’s plenty of information.The problem is the needle comes in an increasingly larger haystack.” – Nassim NicholasTaleb, Author Of “Fooled By Randomness” Source: Anti-fragile
- 15. Proprietary and confidential. ©2020 4C Insights, Inc. Separate signal from noise with long data
- 16. Proprietary and confidential. ©2020 4C Insights, Inc. Sales Uplift Time: 6 Months Marketers “trade” too much And invest too little Lead Generation “Months” Brand Building “Years” 60% 40% Leads Brand Source: IPA, The Long And The Short Of It
- 17. Proprietary and confidential. ©2020 4C Insights, Inc. Brand building and lead generation are different investment strategies “Balance Sheet” Lead Generation Brand Building Things Change Quarterly Ex: Gross Sales Cost Per Lead Things Change Annually Ex: Real Estate Share OfVoice CDP “Income Statement” Source: Craig Griffin, Macquarie Group
- 18. Proprietary and confidential. ©2020 4C Insights, Inc. “The long term is not simply the adding up of short terms” You have to produce results in the short term, but you also have to produce results in the long term. And the long term is not simply the adding up of short terms.” – Peter Drucker, ManagementTheorist Source: Anti-fragile
- 19. Proprietary and confidential. ©2020 4C Insights, Inc. The Myth Of Small Bets 03.
- 20. Proprietary and confidential. ©2020 4C Insights, Inc. A tale of two strategies: Warner Bros bets big, NBC bets small “Bet Big” VS “Test & Learn” Alan Horn Jeff Zucker Source: Anita Elberse, Blockbusters
- 21. Proprietary and confidential. ©2020 4C Insights, Inc. On a risk-adjusted basis, big bets are more profitable than small bets $1.4 billion $1.2 billion $1 billion $800 million $600 million $400 million $0 Production Budget WorldwideRevenues Green Lantern $0 $50 million $100 million $150 million $200 million $250 million $200 million Terminator Salvation I Am Legend Sex and the City Watchmen Happy Feet Two Speed Racer The Blind Side The Hangover The Hangover Part II Inception Harry Potter and the Order of the Phoenix The Dark Knight Harry Potter and the Half-Blood Prince Harry Potter and the Deathly Hallows: Part I Harry Potter and the Deathly Hallows: Part II 1:6 1:1 Source: Anita Elberse, Blockbusters
- 22. Proprietary and confidential. ©2020 4C Insights, Inc. Why are small bets are riskier? Because they’re almost guaranteed to fail. In increasingly competitive markets, breaking through the media clutter requires enormous bets on blockbuster strategies.” – Anita Elberse, Harvard Business School Professor, Author Of “Blockbusters” Source: Anita Elberse, Blockbusters
- 23. Proprietary and confidential. ©2020 4C Insights, Inc. Big returns require betting big on creative Source: Salesforce
- 24. Proprietary and confidential. ©2020 4C Insights, Inc. Big returns require betting big on distribution too 12% 10% 8% 6% 4% 2% 0% Share Of Market ShareOfVoice SOV > SOM: Brands Grow 2% 4% 6% 8% 10% 12% 14% SOV > SOM Brands Grow SOM > SOV Brands Shrink Source: Les Binet and Peter Field, Media in Focus: Marketing Effectiveness in the Digital Era, IPA, (Figure 07)
- 25. Proprietary and confidential. ©2020 4C Insights, Inc. “In my mind, playing A seemingly risky game actually minimizes my chances of losing”
- 26. Proprietary and confidential. ©2020 4C Insights, Inc. 1 Trust real data, not fake data. 2 Track long data, not big data. 3 Make big bets, not small bets. How to be contrarian and right
- 27. Proprietary and confidential. ©2020 4C Insights, Inc. Welcome to the Closed Ecosystems
- 28. Proprietary and confidential. ©2020 4C Insights, Inc. AUTHENTICATED ACCESS ENGAGING NATIVE AD FORMATS DATA-DRIVEN ADVERTISING
- 29. Proprietary and confidential. ©2020 4C Insights, Inc.
- 30. Proprietary and confidential. ©2020 4C Insights, Inc. 21% more time on social media 20% more time on broadcast TV 22% more time messaging Source: Statista, March 2020 5% more time creating and uploading videos 27% more time streaming
- 31. Proprietary and confidential. ©2020 4C Insights, Inc. 811% in COVID-related articles 55% increase in conversations 28x increase in #coronavirus conversations since January Source: Statista, March 2020 60% increase in content creation 40% of users reading more news
- 32. Proprietary and confidential. ©2020 4C Insights, Inc. Where are consumers spending their time? 19% Open Web 81% Closed Ecosystems Source: Average Time Spent with Select Media by eMarketer April 2019
- 33. Proprietary and confidential. ©2020 4C Insights, Inc. Where are advertisers spending their budgets? Sales 1st Qtr 2nd Qtr 34% Open Web 66% Closed Ecosystems Sources: Total Worldwide Media Spend by WARC 2019, Total TV ad spend by eMarketer 2019, Total 2019 ad revenue reported by public companies
- 34. Proprietary and confidential. ©2020 4C Insights, Inc.
- 35. Proprietary and confidential. ©2020 4C Insights, Inc.Source: Practical Privacy — Successfully Transition to Privacy: Preserving Marketing and Adtech by Gartner (Nader Henein and Andrew Frank) 3 April 2020. Graphic source content: Adapted from Beales & Eisenrach and Google. Lack of signal leads to lost revenue Potential impact on publishers of losing third-party cookies 52% Average revenue loss per publisher 37.5% Minimum revenue loss per user
- 36. Proprietary and confidential. ©2020 4C Insights, Inc. The Closed Ecosystems Platform
- 37. Proprietary and confidential. ©2020 4C Insights, Inc. Self-service
- 38. Proprietary and confidential. ©2020 4C Insights, Inc. Self-service Vertically integrated
- 39. Proprietary and confidential. ©2020 4C Insights, Inc. Self-service Vertically integrated Interoperable
- 40. Proprietary and confidential. ©2020 4C Insights, Inc. Self-service Vertically integrated Interoperable Independent
- 41. Proprietary and confidential. ©2020 4C Insights, Inc. Self-service Vertically integrated Interoperable Independent Intelligent
- 42. Proprietary and confidential. ©2020 4C Insights, Inc. from more to better. from black box to transparent. from horizontal to vertical. from siloed to holistic. Move…
- 43. Proprietary and confidential. ©2020 4C Insights, Inc. LinkedIn Video FEATURES RESULTS Powerful Results Financial service brand drives engagement with LinkedIn Video campaign 31% Increase in click- through-rate 48% Increase in engagement rate
- 44. Proprietary and confidential. ©2020 4C Insights, Inc. LinkedIn Video FEATURES RESULTS Engaging Video 4C increases engagement with key clients using LinkedIn Video 17% higher click- through-rate 32% higher engagement rate
- 45. Proprietary and confidential. ©2020 4C Insights, Inc. It’s all in Scope
- 46. Proprietary and confidential. ©2020 4C Insights, Inc.
- 47. Proprietary and confidential. ©2020 4C Insights, Inc. Q&A Aaron Goldman @AaronGoldman Chief Marketing Officer 4C Ty Heath @tyrona Global Lead,The B2B Institute LinkedIn #FindYourAudience
- 48. Proprietary and confidential. ©2020 4C Insights, Inc. Resources 4Cinsights.com mediaocean.com @4Cinsights B2Binstitute.org business.linkedin.com/marketing-solutions/blog @linkedin @mediaocean
Notes de l'éditeur
- Hello and welcome to our webinar: Break Through the Noise, Find Your Audience with Data-Driven Advertising. My name is Aaron Goldman and I’m the head of marketing at 4C which, as you may have heard, is being acquired by Mediaocean. We’re really excited about that and will share more at the end of our session today. I’m joined here by Ty Heath who is the global lead of the B2B Institute at LinkedIn. Ty is the former President of LinkedIn's Black Inclusion Group and the Co-Founder of LinkedIn's annual TransformHER conferences. She was also a contributing author in the recently published books "The Professional Black Woman" as well as the "Black Female Leader" and full author of "Marketers of Tomorrow: A Step by Step Toolkit for Inbound Marketing". Ty has more than 15 years of experience in digital and product marketing education at Google, consulting within IBM as a social business manager and leading a B2B agency consulting practice, Spectacled Marketer. Fun fact: she’s also a two time Olympic Trials qualifier in track and field for the 800 meters in 2004 and 2008. So we’re going to sprint though a lot of great material in the next hour. Before I turn it over to Ty, let’s cover off on a few quick logistics.
- First, a few logistics. We’ll be taking questions through the GoTo panel so feel free to submit as we go and we’ll address as many as we can at the end. Please use that panel as well to let us know if you’re having any technical issues. And we hope you’ll join in the conversation on the socials using hashtag #FindYourAudience. Now I’ll turn it over to Ty to kick things off.
- The late Seymour Epstein is one of the most well-respected cognitive scientists of our time. In the quote on the slide, Epstein makes a foundational point about the replicability of experiments. There are consequences to not being able to replicate the studies of others. What you then get are theories based on unreproducible work. You can’t build without replicability, which is why this is a focus.
- Our first two trends are about the toxic relationship between marketers and data. Now don’t get us wrong, data matters a lot, especially in B2B. But not all data is good data. In fact, most data is bad data, or fake data. We need to start seeing the difference.
- The entire digital marketing industry runs on data. Significant spend goes to programmatic, and that whole ecosystem is powered by data, mostly 3rd party. But how good is that data? Well, here’s a recent academic paper from MIT, GroupM, and Melbourne Business School. These researchers set out to test the accuracy of programmatic data. They focused on the two most commonly used data points in B2C --- age and gender. So, how accurate is gender targeting? It’s accurate 50% of the time. In other words, marketers would be better off flipping a coin. And gender was actually the most accurate facet. For age, the accuracy drops to 25%. And those are the two most accurate data sets. It gets worse the more niche you go, so you can only imagine how inaccurate most 3rd party B2B data is. Now if you don’t believe the research, you can go check this out for yourself. There are a bunch of sites where you can ask the internet who it thinks you are based on your browsing behavior. I went and checked mine right before this meeting. According to a leading data provider, les, I’m aged 35-39, I have a mortgage, and I’m both married and single --- which does sound like an interesting arrangement. Unfortunately, all of that is wrong. This isn’t big data. This is bad data. And according to the researchers, it adds up to 7 billion dollars in wasted ad spend, every single year.
- Now Jon and I are cynical people, but even we found this hard to believe, so we decided to sit down with this gentlemen, Dr. Augustine Fou. Dr. Fou is the world’s leading expert on ad fraud, and we asked him a simple question: is the research is right? Is it true that digital marketers are reaching the wrong people? And Dr. Fou looked at us like we were idiots. He said, “no, it’s much worse than that. The problem isn’t that marketers are reaching the wrong people. The problem is that marketers aren’t reaching people.” Marketers are reaching robots. When you buy display on a billion random sites, this is what happens. Some enterprising criminal sets up a fake site, like Babaganoush.com. Then he programs some bots to click on any ad that runs on the site, not too much, because that would be suspicious, but enough to beat the advertiser’s benchmarks. A day later, some media buyer sees that Babaganoush.com has a 5% click-through rate, and recommends re-allocating all the display budget to that channel. It’s hard to estimate the scale of this fraud, since it’s a criminal enterprise, but the most conservative estimate is 6 billion dollars a year. So we’re wasting 7 billion targeting the wrong people, and 6 billion targeting non-people.
- With all that wastage, you’d think marketers would be talking about this more often. But I’ve been to about 30 marketing conferences this year, and guess how many sessions I’ve seen on how to avoid fake data and fake websites? 0. Meanwhile, I’ve had to sit through about a trillion sessions on the arrival of 1:1 personalization at scale. But tactics like personalization are based on an assumption. An assumption that the data is good. And the data is not good. And the weirdest part is that we all know it’s not good. If you actually ask B2B marketers how much confidence they have in the accuracy of their own data, this is what you get back, according to Forrester. 12% confidence. And these are the same B2B marketers up on stage talking about the benefits of personalized creative. If I were a psychologist, I would call this cognitive dissonance. Since I’m not a psychology, I’m just going to call it totally cray-cray.
- This whole thing reminds me of that movie, The Big Short. Do you remember that scene with the Jenga pieces, where Ryan Gosling explains the financial crisis? According to Ryan Gosling, who I rely on for all my financial advice, the 2008 crisis happened because someone took D-rated loans, bundled them together with Tripe A loans, and sold the whole package as Triple A. It’s very similar to what’s happening in the marketing industry. We are taking fake data, bundling it together with real data, and selling it as big data. I’ve seen this movie before, and it doesn’t have a happy ending --- except for the contrarians, of course. Between GDPR and Apple wiping its cookies every two weeks, I think it’s clear this story doesn’t end with better 3rd party data. It ends with no 3rd party data. At some point, someone is going to pull out the wrong Jenga piece, and this whole ecosystem will collapse.
- So how do we prevent the Sub-Prime Data Crisis? We need data to reach B2B buyers. But we need to do a better job distinguishing between real data and fake data. How do we do that? Well I think it’s instructive to take a look at a different discipline: supply chain management. Our summer intern made the connection here. She told us that decades ago, companies started caring more about their social impact. And those companies decided that the easiest way to improve their impact was to shorten their supply chains. The more links in the supply chain, the more complex it is, the more vendors are involved, the more opportunities there are for bad things to happen. If marketers want real data, we should work on shortening our supply chains. Step 1 is to prioritize direct data over indirect data. The more vendors the data passes through, the more times different data sets get combined, the less accurate the data becomes. If your vendor can’t explain exactly where the data comes from in a single sentence, that’s a red flag. LinkedIn data comes from LinkedIn profiles, and you can go verify those profiles with your own eyes. It’s not a black box. It’s an open box. Step 2 is to prioritize direct payment over indirect payment. If you buy media on a billion sites, some enterprising criminal will find a way to take your money. Buy directly from publishers you have heard of --- there are many, many such publishers out there. Direct data, and direct payment. Those are two simple steps you can take to limit your exposure to the Sub-Prime Data Crisis.
- Like Scott Nicholson, we have to be intentional masters of cleaning, extracting and trusting data before doing anything with it.
- We just told you about real data vs. fake data, let’s imagine you have all real data. Would it help you make better decisions?
- I told you to be a data skeptic, but let’s just assume, for a minute that all the data you have is real data. Even if you had only real data - does more data lead to more informed – in essence -- and better decisions? Let’s attempt to answer that question by going to the horse races. In a famous psychology study, Paul Slovic gave a series of professional gamblers – also know as horse handicappers – their choice of and then he tracked the confidence and accuracy of their bets. What Slovic found was extremely interesting: First, he learned that having 5 pieces of data was better than having no data – the bets were more accurate, and the handicappers were rightfully more confident in their bets when using some data. However, what he found next was surprising: the more data the handicappers got, the more confident the handicappers became, but the results got no more accurate. So about as confident as they should have been with 5 pieces of data, but they got more and more confident with each additional pool of data. So they were even more confident at 10 pieces of data, even more confident at 20 pieces of data, and twice as confident at 40 pieces of data as they were at 5 pieces of data. Unfortunately, more data didn’t lead to better decisions; in fact, more data led to worse decisions. Because the more confident they were, the bigger the bets they made and the bigger the losses they saw.
- Signal-to-noise ratio explains why “big data” often leads to worse decisions. We live in a world of increasing amounts of data and nearly all marketers assume that more data leads to better decisions However, most data is just what Nassim Taleb calls “noise” – it is data that we measure, but it is data that doesn’t help us better determine which decision to make. We have to understand that with more data comes more “noise” and it is very easy to be fooled the data just like the horse handicappers were fooled by more data. We don’t just want data – we want data that carries “signal” – we want data that helps us make better decisions. Most data that we capture, measure, and optimize in the digital marketing world, sadly, is just noise. Examples of “signal” in digital data include: Category reach Ad viewability Share of voice Each of these metrics tells you that you’re reaching every potential buyer in your category (category reach), that you’re reaching them often enough to have high share of voice / share of mind, and that all the ads are being viewed. Those metrics matter – most other metrics do not.,
- Marketers are just as obsessed with big data as everybody else. But we contend that marketing should be interested in “long data,” not “big data.” To explain what I mean by “long data” let’s return to Nassim Taleb for a moment, who is fond of the phrase “time is the best judge of success.” Taleb reasons that no person, no company, no tactic, no strategy can fool us over a long enough period of time. In other words, over time signal is separated from noise. The example on the screen now explains what I mean. A fund might be able to perform well for a short period of time – say 1 month or 3 months – but few funds perform well over the arc of time / few strategies stand the test of time. As an investor or marketer, you should not judge funds or campaigns over a short time frame – you can see about that the returns fluctuate wildly over time. You simply can’t be confident in an investment unless the fund has performed well over the long-run since, after all, we are all investing for the long-run. It is also interesting that finance measures performance over 1 – 3 – 5 year periods, which are much longer than the performance measures in marketing. We should learn from finance and start measuring ”long data” as a way to separate signal from noise and as a way to make more informing – and better performing – decisions. Remember, time is the best way to separate signal from noise. Left data (1-3 months) is wrong, right data (1-3 years) is long.
- Sadly, marketing today does not think, measure, and invest in “long data.” As we all know, marketing continues to become more and more invested in “big data,” “real-time,” and “short-term.” However, the ”big data” approach fundamentally ignores that there’s two types of marketing: lead generation and brand building. As a reminder, lead generation is highly targeted, short-term marketing that tries to close an immediate sale and delivers most sales over 1-3 month timeframe. Conversely, brand building takes 6-12-18 months to deliver sales, but is the only way to reach customers who are not in-market today to prime those customers to think of your brand when enter the market at a future date. Because marketing is increasingly short-term, marketing really only measures short-term campaigns – lead generation – and attributes value to those campaigns. Short term campaigns with short-term measures appear to show that lead generation delivers more sales. However, if you have the patience and disciplne to measure marketing over a long-term horizon – 6 months or more – you see that brand building starts to deliver more sales volume at higher prices, which drives net profits. Lead generation needs to start anew every campaign, whereas brand building stands on the should of the last campaign – think Geico’s Gecko – and compounds over time. The reality is that you don’t do one type of marketing at the expense of the other - you do both. Just like the right strategy in finance is to diversify your portfolio, the right strategy in marketing is to practice brand building and lead generation. The optimal balance – according to marketing effectiveness researchers Les Binet & Peter Field – is to spend 60% on brand building and 40% on lead generation. This makes common sense – generate awareness with future buyers by marketing the Gecko and then capture leads / sales from current buyers when they move into the market and buy from one of the brands – hopefully yours – that they’re familiar with and trust.
- If marketing wants to be taken more seriously, it needs to think, measure, and report in a more financial way. How do we sell in long-term thinking to CFO? We learned a wonderful financial metaphor from Craig Griffin, who is a brilliant marketer for MacQuarie Bank down in Australia. He said, if we want to protect and grow budget, we need to frame marketing in more financial terms. Craig says that he thinks of lead generation, and it’s short-term focus, like an Income Statement. On an income statement the numbers tracked – think gross sales – change more regularly and thus can be reported on monthly or quarterly. Craig said that explains brand building in the opposite way: brand building, and it’s long-term focus, is more like a Balance Sheet. On the Balance Sheet the numbers tracked – think real estate / think this building we’re sitting in – change more slowly and thus only need needs to be reported on annually. That’s how Craig Griffin talks about and reports on the different time horizons for brand building and lead generation. In general, think longer-term to separate signal from noise and make the right investments to profit not just this quarter, but for all quarters to come.
- This next trend is called the myth of small bets.
- Let’s start with a story. We have Alan Horn who's managing Warner Bros and is in fourth place in the US market. We have Jeff Zucker who's managing NBC in first place in the US market. They adopted two completely different strategies at the same time in a wonderful natural A/B test. So what happened? Fast forward 5 years. Alan Horn and Warner Bros are now first place in the US market and Jeff Zucker at NBC are now in 4th place. Alan Horn gets poached by Disney to run Disney Studios.
- What happened is that Alan Horn invested big in the more data driven of the two strategies - what we call big bets. He realized when he put a dollar into production budget he only got $1 back when he invested in smaller budget films, what we call test and learn content. Now if you look at the opposite side of the chart what he realized was that when he put $1 in to a big budget piece of content he got $6 in return. So you can see that big bet blockbuster content is dramatically more profitable. Most marketers claim to be data driven but in this instance Alan Horn actually was. Now why are big bets more profitable?
- It has to do with your attention span. The only way that brands can really break through today is with big bets. As Anita Elberse said, small bets simply don't get the budget or the attention required to break through in what’s in this ruthlessly competitive global environment. On the surface it makes sense, it seems safer to make small bets but in fact very few small bets get the attention and budget to make themselves a success.
- The only movies that people see today (and we only see six or eight movies a year) are the big ones. We see things like Star Wars, Batman and the Lego movie. The reality is if you're not one of these big movies nobody goes to see your movie at all and you fail. The same is true in marketing. It's hard to hear, but people aren't going to read every report about cloud computing. People are going to read just the biggest reports (two or three a year maybe). Those are likely to be the ones that receive the most attention and the most people to work on them. Big bets require massive production budgets and massive distribution budgets - that's why they win. This trend is only accelerating in fact if you stay in the movie world for a minute and look at the Lego Movie. It was extraordinarily successful so what did they do for the sequel: they took one big franchise, Lego, and stacked another big franchise, Batman, on top of it. It's essentially two bets in one. In marketing, we are seeing something similar. Take Salesforce for example. Salesforce in 2014 developed a franchise called the “State of Sales. What they found was at the State of Sales was remarkably successful so they took the approach “State of” and and applied to each of their business lines, giving each one a franchise report every single year – State of marketing, sales, CRM, IT and s on. Each report has gotten more people and more budget every single year for a number of years. These big bets on production and distribution have turned their marketing from a cost center into a profit center. These reports now generate tens of millions of dollars and sales every year. This is another example of a replicable idea that gets easier and easier to produce every year. That of course makes it easier to monetize as well which is good for everyone involved.
- Now how to measure distribution? We like something called excess share of voice (eSOV.) This is a critical metric that determines the level of a brand’s market share growth. How well your brand will do in the market is something we call excess share of voice which is defined as the share of voice a brand gets against its target audience, minus it's current share of market. In simpler words: your share of voice against your audience will determine whether your share of market grows or shrinks. So if you have 8% of the market (as you can see on this chart). You’ll want your share of voice against market to be higher than 8%. If it's higher than 8% percent, you can expect your brand to grow. If you under invest, and your share of voice is below your market share, then you can expect your business to shrink. Very important way understand to understand whether you are making a big enough bet on distribution or not.
- Thank you Ty and welcome everyone to the lush closed ecosystems where everything is radiant and growth is abundant. And we’ll talk about how accurate data are the seeds that allows these gardens to grow.
- So what are Closed ecosystems and why do we believe these are the places marketers should start with their strategies and budgets? -Well, closed ecosystems are media and tech companies that publish content across multiple modalities with authenticated access and engaging native ad formats that enable data-driven advertising. -Authenticated access means consumers interact with closed ecosystems by signing in to apps or platforms. User-level consumer data is confined within each ecosystem, providing protection for consumers but also proprietary data for the closed ecosystem operators. -Closed ecosystem advertising takes advantage of the endemic environment it’s in, leveraging video, commerce, and interactive formats that are contextually relevant and allow consumers to take immediate action. -The consumer and content data available to closed ecosystem operators has allowed them to enable precise placement of ads and advanced optimization for advertisers. Targeting is data-driven beyond broad age and gender, while bid, budget, and other optimizations can be automated in flight based on performance against objectives. -Leveraging closed ecosystems to reach consumers allows marketers to be confident in the reliability of their data and to use the data that matters to identify the appropriate audiences and create engaging campaigns.
- So, what are some examples of closed ecosystems? There are the obvious ones, like LinkedIn and other digital platforms, which very clearly meet all of the above criteria, and are often referred to as “walled gardens” for the way they carefully control access to their data and inventory. While they are still evolving, TV and OTT providers like AT&T or NBCU can also be considered closed ecosystems because of their ability to combine content across multiple platforms through controlled access as well as high-impact video ads and continuing evolution towards data-driven advertising. The amount of data that flows inside the closed ecosystems is very powerful to create a picture of the person behind the device and what they’re interested in at any given moment.
- And the power of closed ecosystems is only picking up during the pandemic. We’re seeing dramatic rises in consumer activity across all these platforms. Globally, streaming is up 27%, messaging up 22%, 21% more time spent on social and 20% more time on broadcast TV. Even creating and uploading videos, which you’d think would be correlated to people being out in the world and doing things has increased during the crisis.
- When it comes to LinkedIn specifically, consumer behavior is also shifting. Comparing March 2020 to March 2019, there was been a 55% increase in conversations between LinkedIn users and a 60% increase in content creation. Since February, conversations around #coronavirus have increased 28x. 40% of LinkedIn users have reported reading more news during the crisis, and on LinkedIn, there has been an 811% increase in COVID-related articles in recent weeks.
- So, as you can see, more and more time is consolidating within closed ecosystems – 81% compared to 19% for the open web.
- However, brands aren’t yet fully following suit when it comes to media spend. 34% of advertising dollars are still going to the open web, despite consumer behavior and decreasing confidence in the effectiveness of the open web. Not to mention the crumbling of the cookie.
- Publishers on the open web were already challenged by consumer privacy laws like GDPR and CCPA. Over the next couple years, most web browsers will also be deprecating third-party cookies jeopardizing the measurement and targeting capabilities of open web advertising.
- With cookies going away, it’s even more important for marketers to make sure their data-driven advertising is based on reliable data-sets. Gartner says that without proper preparation, organizations are likely to lose an average of 52% of revenue per publisher when third-party cookies are deprecated. In closed ecosystems, identity is not solely based on cookies, meaning that data will still be actionable long beyond the death of the cookie. So how can marketers prepare for a world of closed ecosystems?
- Combining essential marketing functions and operating seamlessly across closed ecosystems, the Closed Ecosystems Platform, or CEP, allows marketers to take control of their media and reach consumers where they are most engaged. The CEPs that provide the most value for brands are self-serve, vertically integrated, interoperable, independent, and intelligent. It’s time for marketers to take the first step in preparing for the future of advertising by making the CEP the core component in their tech stack.
- Self-service gives transparency and control to marketers, allowing them to manage the entire media process across closed ecosystems from a single platform.
- Vertical integration eliminates inefficiency, as well as inflated add-on fees, across the campaign process through campaign activation combined with audiences, planning, creative, measurement, reporting, and optimization.
- Interoperability enables consistency and channel convergence with each layer of the stack across all supported closed ecosystems. Agnostic integration of measurement data, creative tools, and audience data across channels allows marketers to easily plug closed ecosystem advertising into their tech stack.
- While CEPs are connected to closed ecosystems, they must operate independently, so CEP media and performance metrics, as well as optimization levers, are transparent and designed to work best for the marketer, not to optimize ad revenue for the operator.
- By consolidating functions and closed ecosystems, CEPs can provide advertisers real-time insight into media performance and campaign processes. This intelligence, surfaced through collaborative tools and dashboards, includes recommendations for optimizing budgets, audiences, and creatives so advertisers can test and improve outcome performance. Intelligence based on data from closed ecosystems allows advertisers to be confident in the criteria they’re using to make decisions about their campaigns.
- Anchoring the marketing tech stack on a CEP enables marketers to make some key changes to how they operate as well. -While the open web provides a long-tail of reach, inside of closed ecosystems is where consumers are spending most of their time. Leveraging a CEP allows marketers to maximize performance of media within these critical consumer environments. -A CEP with a transparent cost structure separates media from audience, creative, and tech fees, instead of baking all those costs into CPMs. This transparency allows marketers to better understand how their dollars are spent, and to assess the true value of their media. -A self-serve CEP that vertically integrates audiences, creative, planning, activation, measurement, and optimization into a single user experience breaks down barriers within the marketing organization, improving efficiency and collaboration. -Closed ecosystems have and will continue to scale beyond Facebook and Google to platforms like LinkedIn and even TV and OTT. Combining multiple closed ecosystems and all marketing functions into a CEP allows teams to see trends and uncover insights across campaigns, creatives, and audiences, so budgets and other tactics can be optimized holistically.
- Let’s take a look at an example of how a well-established financial services company leveraged LinkedIn through our platform, Scope. -The brand needed to drive sign-ups and promote their competition for small businesses to win money. The team needed to achieve awareness and reach a strong click through rate at an efficient cost. -The team leveraged Scope’s LinkedIn video capabilities to promote their video campaign cost-effectively on a national level. Leveraging LinkedIn video drove high awareness among a highly qualified audience and kept them engaged at a low cost. -Compared to the pre-set benchmarks, the video campaign outperformed across the board. With Scope’s LinkedIn video offering, the campaign saw a decrease in cost-per-click as well as: 48% increase in engagement rate 31% increase in click-through-rate 17% decrease in cost-per-engagement
- The 4C Marketing team is also leveraging LinkedIn Video through Scope to connect with our existing and prospective clients. In a recent campaign, we saw video ads outperform still ads, with a 32% higher engagement rate and 17% higher click-through-rate as compared to still ads in the same campaign.
- Scope is the name of our CEP. Spoiler alert, it’s been on my shirt this entire time. Our DNA is working with APIs for closed ecosystems like LinkedIn and creating software to help marketers operate within and across them. We speak the languages required to make these independent systems accessible to and connected for marketers. Scope checks all the boxes on the five tenets of a CEP, but its superpowers lie in its vertical integration, channel convergence, and marketing intelligence. If you’re interested in learning more you can visit 4Cinsights.com/scope.
- We’re also excited to announce, as I mentioned earlier, that Mediaocean is acquiring 4C. Together, the companies will combine 4C’s intelligence and optimization with Mediaocean’s foundational platform for end-to-end media management to establish a modern system of record for omnichannel advertising. We look forward to sharing more with you about the combined capabilities in the coming weeks.
- Now let’s move to Q&A. Grace, if you can please share what’s come through the GoTo.
- Before we let you go here are some links to additional resources about the topics we covered today and the companies behind them. Thanks again to Ty for joining me and to you all for tuning in. Have a great rest of your day!