Based solely on Viant’s Q1 2025 earnings transcript.
Revenue YoY: 32%
CxT: 25%
𝗟𝗶𝘃𝗲 𝗦𝗽𝗼𝗿𝘁𝘀 𝗶𝘀 𝗔𝗱𝘃𝗲𝗿𝘁𝗶𝘀𝗶𝗻𝗴’𝘀 𝗡𝗲𝘅𝘁 𝗕𝗶𝗴 𝗔𝗿𝗲𝗻𝗮 | Jon Schulz
https://www.linkedin.com/posts/jon-schulz-4780ba4_upfronts-ctv-livesports-activity-7318655564027215873-qDIg?utm_source=share&utm_medium=member_desktop&rcm=ACoAAAOMQksB5Fgbm_qk5Eeo-7X6VF7Vp2IJNg8
Bold #Upfronts Predictions from an #IndustryVeteran — With a Twist | Tom Wolfe
https://www.linkedin.com/posts/tomhwolfe_upfronts-industryveteran-upfronts-activity-7315732919719784448-b_Ct?utm_source=share&utm_medium=member_desktop&rcm=ACoAAAOMQksB5Fgbm_qk5Eeo-7X6VF7Vp2IJNg8
Rethinking CTV Measurement for the Streaming Age | Steven Ohrnstein
Pod dedicated to the one and only, Mikhail Berylant
People, Process, and Tools
For any company to be successful, it takes these three things. Rarely is there a person that embodies all 3, Mikhail Berlyant is one of the greats that does.
I wanted to take a moment to honor Mikhail for the #contribution he has had in my professional career. It was through Mikhail creating Potens.io, a software that sits on top of Google BigQuery, that makes it easy for someone like myself, a non-engineer who knows the business but otherwise no way to bring data to life, to automate & create solutions that empower internal employees to do their jobs and make the lives of our clients a bit easier. This Tool has been used across Viant for the last decade plus, not just Product and Engineering, but nearly every other department across the org, including Operations, Marketing, Accounting, Finance, and Sales. This same tool is the underpinning of Viant's Data Platform, which nobody in our industry can come even come close to competing with. Mikhail is on my shortlist of unsung heroes from which Viant would not exist today without. Without him, I assuredly would have attempted taking on a full-time blogging career a long time ago.
Let's continue...
When I first started reading Google BigQuery books around 2014-2015, the very first one I purchased was co-authored by Mikhail to my surprise. I’ve never met anyone so PASSIONATE about what they do and so DRIVEN towards excellence. His unrelenting enthusiasm on every call or meeting is unlike anything I’ve ever experienced, and I believe that’s a big part of his success.
Mikhail is one of the top contributors on Stack Overflow, with a reputation score of 173,230 (no idea what this means, but for comparison, my reputation is 29). He is one of the top contributors in the world in his field which speaks volumes to his expertise.
But more than anything, the only thing that gets him more excited than his work is his family, especially when he talks about his grandchildren. And that is a beautiful thing. While we work in different offices and don’t get to see each other all that often, he’s one of the few people that requires a bear hug every time I do. Thank you, Mikhail, for everything you do. I am forever indebted to your life's work.
CALL TO ACTION: For anyone else that was impacted my Mikhail, whether a colleague, friend, or one of the 14.9 million people he's helped on Stack Overflow, share your gratitude in the comments and we'll memorialize this post with an AdTech AI Files pod cast a week from today.
Mikhail's Stack Overflow link for the record: https://lnkd.in/gS_sZQDC
#AdTech #BigData #DataEngineering #AI #Innovation #TechVisionary #GoogleBigQuery #Viant #Passion #Gratitude
“What’s a Good Conversion Rate?” 🤔 The Benchmark Myth
For as long as I can remember, marketers have asked me:
“What’s a good conversion rate for my campaign?”
And here’s the honest answer… it depends.
Conversion rate benchmarks are tricky because different brands have different goals. A KPI could be downloading a coupon, signing up for an email, opening a bank account, or even buying a car, all of which have vastly different intent levels and friction points.
The head of Marketing Analytics for one of the largest global OEMs once told me “it’s all relative to the dashboard you’re looking at. There’s a million different options and providers of data, so measuring across providers doesn’t have apples to apples comparisons. Focus on the report you trust and make everything relative to what’s within the given report.”
With that, when it comes to wanting benchmarks, try these:
✅ Instead of chasing an arbitrary benchmark, focus on relative performance.
✅ Compare Campaign A vs. Campaign B, not your brand vs. a generic industry average.
✅ If one tactic is driving a 20% higher Conversion rate, that’s an insight you can actually act on.
✅ Focus on Incrementality, if your spend is driving net new sales at a lower incremental cost per acquisition than your marketing cost, keep going
Think about it this way:
Would you rather hit an “industry average” conversion rate, or actually improve what’s working for your business?
Benchmarks can be a useful reference, but real optimization happens when you focus on your own data, your own customers, and your own goals.
#ConversionRate #MarketingMetrics #DigitalMarketing #GrowthMarketing #Advertising #Attribution #AdTech
The Who, What, and How foot traffic measurement works.
Will Google’s Ad Empire Be Broken Up?
When I first started in programmatic, 2nd price auctions ensured advertisers paid a fair market rate. You could bid confidently knowing you’d only pay a cent more than the next-highest bid.
Then, about 8-9 years ago, Google led the shift to 1st price auctions (where you pay exactly what you bid) & enabling their publishers to create dynamic bid floors (to artifically increase the clearing price). This fundamentally changed how media was bought, increasing advertiser costs while boosting Google’s profits.
My First Exposure to Googles dominance was in 2016.
A programmatic trader in Google’s DSP meant to raise their bid from $5.00 to $6.25 but accidentally entered $625. No big deal, they caught and fixed the mistake just 5 seconds later.
In that 5 seconds, the remainder of their entire 200,000 daily impression budget was spent at a CPM of over $200. What should have cost $1,200 ended up costing more than $40k.
And where did that ad spend go? Straight into Google’s ecosystem.
Keep in mind Google has Unmatched Control
Today, Google dominates every part of digital advertising:
🔎 Search ads (Google Search)
📺 Video ads (YouTube)
📈 Ad buying (DV360, the largest DSP)
📡 Ad selling (Google AdX, the largest SSP)
✅ Verification & measurement (Google Analytics, Campaign Manager 360)
🌐 The largest browser in Chrome in the US and the largest Global smart phone operating system in Android.
They own the buyer, the seller, the marketplace, devices, browser, and the referee, a level of control no other company has ever had.
Will Google’s Dominance End? We’ll get an answer this summer…
In the meantime, what can you do about it?
PSA for the day: if you’re a marketer in any DSP, don’t think twice about using AI Bidding, if you can get screwed 9 years ago in 5 seconds, just imagine what the technology is today across any entity representing publishers. Pick a DSP that only represents the buyer, and let them work for you.🤔
Anyone else have a similar experience?
#GoogleAds #AdTech #ProgrammaticAdvertising #Antitrust
The Illusion of High Lift: Why Longer Lookback Windows Matter in Incrementality Testing
Marketers love seeing high lift in incrementality studies, it feels like proof that campaigns are driving real impact. But if you’re only looking at short lookback windows (1-7 days), you might be chasing last-touch credit and overestimating effectiveness.
The Problem: Short Lookback Windows Inflate Lift
When we measure lift between 1-7 days, results look strong because ads do work, they drive awareness and may accelerate conversions. But here’s the catch:
✅ Many buyers were already on the path to purchase.
✅ Your ad may have just nudged them to buy sooner.
✅ If you extend the lookback window, the control group converts too.
Cutting off analysis too early makes it seem like your ad drove the entire conversion, when in reality, it just influenced timing.
Real-Life Example: Travel & CTV
A major travel brand ran a CTV and audio, with display retargeting campaign to drive bookings. Their 1-7 day lift study showed a big conversion increase. But at 90 days, they saw:
• People go on summer vacations, the control group converted too, just at a later time.
• Many “incremental” conversions in the short window were people who would have booked anyway.
• The true lift, those booking only because of the ad, was much lower than first thought.
This insight changed how they measured success, shifting to 60-90 day lookback windows to separate actual lift from simple purchase acceleration.
Why Longer Lookback Windows Give a More Honest View
This is critical for CTV, audio, and upper-to-mid funnel media, where the goal is awareness and long-term consideration, not instant conversion.
In high-ticket industries like travel, auto, and luxury retail, brands sometimes use 60, 90, or even 180-day windows for true impact measurement. If you only measure at 1-7 days, you’re likely capturing last-touch credit rather than real incremental lift.
What This Means for Your Marketing Strategy
🔹 Short lookback = overestimated lift. Your ad worked, but not as much as you think.
🔹 Longer lookback = a more accurate read. It shows how many would have converted anyway.
🔹 Test across different time horizons. Compare short and long-term effects.
🚀 Key Takeaway: Marketing isn’t just about driving faster conversions, it’s about driving incremental ones. Ensure your lookback windows are long enough to separate the two.
#MarketingMeasurement #Incrementality #Attribution #MediaStrategy
Relative vs. Incremental Lift: How you can Leverage Both
Let’s say you own a pizza shop, and you’re running an ad campaign to get more people ordering your delicious pies. You set up a test:
• Exposed Group: They see your ad and start craving pizza.
• Control Group: No ad seen
At the end of the campaign, let’s say your control group only sold 10 pizzas and the exposed group sold 25, for a total of 35 pizzas sold.
🍕 What can Relative vs. Incremental Lift tell you?
➡ Incremental Lift answers: “How much of my total sales actually came from the ad?”
📊 (Exposed Sales - Control Sales) / (Exposed Sales + Control Sales)
• This number is always between 0 and 1. In this case 15 incremental pizzas because of your ad out of 35 total pizzas sold, which means 43% of your total sales were actually influenced by your ad.
➡ Relative Lift answers: “How much more did the exposed group buy compared to the control?”
📊 (Exposed Sales - Control Sales) / Control Sales
• This number can be over 100%, in this case your control group only sold 10 pizzas and the exposed group sold 25, your relative lift is 150%!
🎯 The Purpose of Both Metrics
🔍 Use Relative Lift to optimize performance between tactics:
✅ Which audience, targeting, geo, or creative messaging works better?
✅ Which channels are more effective within my media mix?
✅ How do I allocate spend efficiently?
📢 Use Incremental Lift to measure true impact:
✅ Is this campaign actually driving new demand?
✅ What % of sales came because of my marketing efforts?
✅ Would these sales still happen if I didn’t run this ad?
📌 Why It Matters
In the very first iteration of measurement many years ago within Viant’s Advanced Reporting, we focused solely on Relative Lift. We learned that if you focus only on relative lift, you might be optimizing for efficiency, without knowing total impact. We then added incremental lift, which if you focus only on incremental lift, you might miss ways to fine-tune performance. We found our customers appreciate both in the same UI. Your DSP should have both as well.
📢 Bottom Line
Great marketing isn’t just about improving results, it’s about ensuring those results actually matter.
#MarketingAnalytics #Incrementality #LiftAnalysis #DigitalMarketing #AdTech #GrowthMarketing #Advertising #MarketingStrategy #Lift #AdTechAIFiles
Pod cast produced from my 8 year old son to kids of all ages. Enjoy!
In honor of International Women's Day, I wanted to recognize 2 women that have had a profound impact on my life. One of them personal, another professional.
My mom, a lifelong nurse, specializing in end-of-life care (hospice) and mid-to-late-stage cancer care, always taught me that the most important thing anyone can do in their life is to CARE, whether for a person or a cause. With 8 billion people on this planet and countless causes to #care about, we each have a limited capacity to give our energy. While I’m not always great at expressing my gratitude, one of the things I care most about is the people I surround myself with, both personally and professionally.
One practice we’ve implemented in our team meetings is a “shout-out” session. We all may think positive things about our colleagues, but we don’t always communicate them. And I’ve never met someone who doesn’t appreciate a genuine compliment. A simple gesture of appreciation can go a long way, and this few minutes is the best part of any of my meetings all month long.
As a small gesture of my appreciation, I want to take this a step further and publicly recognize a colleague I deeply respect & and has had a profound impact on my life. While I’d love to see more of this across our industry, I understand that publicly vouching for someone comes with the risk of them getting “poached”. So it hear it goes…
I have had the honor and privilege to work alongside Amanda Bookout (not on LinkedIn ATM, otherwise would have linked) for the past 15 years. Amanda is Viant’s Director of Business Intelligence. There is simply no one better in our industry that understands both the data complexities that AdTech brings and the business application of that data to bring it to life for our internal stakeholders and clients. She handles the most challenging of issues with calmness and intellect through experience. Her positive, can do attitude is infectious and I’m thankful to have been able to witness it as long as I have. Amanda‘s ability to find, hire, onboard, and develop talent is nothing sort of amazing.
For those who have ever worked with Amanda, I encourage you to show your appreciation and continue this shout-out, whether it’s through internal Slack, an email, or a comment below. I’ll compile all the comments and include them in an Amanda dedicated episode of the AdTech AI Files Podcast to round out this shout out. Let’s celebrate the people who make a difference.
Throw the image in a PPT and introduce it to your next team meeting and hashtag#measure what happens!hashtag#ShoutOut hashtag#Recognition hashtag#Teamwork hashtag#NoAI hashtag#IWD25
Use it or Lose it: a Mobile Measurement Partner ofcourse
Mobile in-app environments convert 3x more often than mobile web. Think about how often you buy Starbucks coffee through the app vs. opening Safari or Chrome to place an order. For most of us, it’s a night-and-day difference, in-app is faster, more convenient, and personalized. In cases like this, app conversion rates aren’t just higher, they’re the dominant way customers engage and buy.
Yet, there are no cookies or traditional pixels in an in-app environment, meaning the standard ways most marketers measure performance don’t include mobile in-app conversions. This leaves a huge gap in understanding your true media impact.
The in-app environment is a different world, frictionless UX, higher engagement, and better retention. To truly measure the impact of your media spend, you need a Mobile Measurement Partner (MMP) integrated into your DSP.
The good news? The best DSPs can do two key things:
1️⃣ Pre-built integrations with your MMP – With simple provisioning, you can securely share data with your DSP for retargeting and measurement.
2️⃣ Off-the-shelf incremental lift measurement – The best DSPs work seamlessly with MMP data to provide clear insights into the true impact of your campaigns.
At the end of the day, it’s simple: use your mobile data or lose viability. If your measurement strategy ignores in-app conversions, you’re making decisions with incomplete data—and in a world where mobile dominates, that’s a risk no marketer can afford
#MobileMarketing #MMP #DigitalAdvertising #AppEngagement #MarketingROI #AdTech
If looking for an MMP, check out: AppsFlyer Branch Kochava Singular Adjust
Privacy vs. Blocking: The Real Story Behind Consumer Choice
There’s a big difference between consumers opting out of tracking (which would be every consumers right) and Big Tech outright blocking measurement for their own gain. Yet, the lines keep getting blurred.
Take Apple’s Private Relay, a feature that allows users to effectively be routed through a VPN while browsing in Safari, making you invisible across the web. It sounds like a major privacy shift, but in reality? After nearly 4 years of Apple pushing it, we see only ~16% of Apple related bid requests routed through Private Relay, meaning most users aren't opting-in. Perhaps due to widespread complaints of Private Relay interfering with the user's experience. I personally experienced an issue with getting onto Netflix while testing Private Relay, as Netflix couldn't verify my location properly.
Now, compare that to a marketer simply adding a pixel on their own website to share their first-party data with their preferred measurement or DSP providers. Apple’s broader privacy policy automatically block nearly 2/3rds of pixel-based measurement hits (and upwards of 85% for some marketers), regardless of whether the consumer has explicitly opted out. That’s not consumer choice, that’s a platform-driven decision that limits visibility into what’s actually driving business outcomes for all marketers alike. Benefiting Big Tech in the name of “privacy”, forcing marketers to integrate and further leverage Big Tech's products.
So what can you do about it?
✅ Leverage 1st-party data: Build direct customer relationships and own your data.
✅ Adopt clean rooms: Securely match and analyze data without relying on big tech.
✅ Use server-side pixels: Bypass browser-based restrictions to improve measurement accuracy.
The future of measurement isn’t about waiting for Big Tech’s next move, it’s about taking control of your own data strategy.
#Marketing #AdTech #Privacy #FirstPartyData #PrivateRelay #Measurement #AdTechAIFiles
Linear TV vs. Connected TV: The Frequency Problem Marketers Can’t Ignore
After running Linear TV vs. Digital measurement studies for the past decade, one pattern remains consistent:
Dolllar for dollar, more times than not, Linear TV campaigns have 3x higher frequency than CTV. And here’s the issue, without frequency capping, that’s a lot of wasted impressions.
Why This Happens:
✅ Linear can’t control frequency. If someone watches the same channel daily, they’ll likely see the same ad over and over due to the upfront nature of Linear TV.
✅ CTV is transacted programmatically, and therefore lets you set caps, allowing the marketer to control how often someone sees your ad
✅ Heavy TV viewers skew the data. A portion of the audience gets bombarded, while others barely see the ad at all.
What This Means for Marketers:
🔹 Wasted Spend: Those extra impressions aren’t incremental reach, they’re just oversaturation for the same people.
🔹 Diminishing Returns: Seeing an ad 5+ times in a week doesn’t necessarily make someone more likely to convert.
🔹 Smarter Budgeting: CTV gives brands more control, meaning less waste and more efficient reach.
How to Fix It?
📌 Use digital measurement to quantify true reach & frequency.
📌 Balance TV & digital to optimize reach without overexposure.
📌 Consider CTV as a bridge, more control than linear, but the big-screen impact remains.
Linear TV still has its place, but without frequency controls, a huge chunk of ad dollars get wasted on the same eyeballs. Smart marketers are shifting spend to platforms where they can actually control the user experience. 🚀
#AdTech #MarketingMeasurement #TVAdvertising #DigitalMarketing #CTV #Programmatic #MediaBuying #GrowthMarketing #Advertising
The Death of Third-Party Pixels: Why First-Party Data is the Future
If you launched your own website tomorrow, you’d own everything: your customer relationships, purchase history, and insights. That’s first-party data, it belongs to you, and no one can take it away.
Your same business relies on pixels to understand performance, retarget your customers that have added your product to cart but yet to purchase, to optimize and measuring success. You rely on your partners, whether measurement providers or DSPs to help in this endeavor, which makes these Pixels “Third-Party Pixels”. Easy enough…
Only 1 problem, let’s take a look at who owns the browsers and operating systems that enables your business to pass your data to your partners:
📌 Google + Apple control 97% of the mobile operating system market (Android & IOS)
📌 Google Chrome + Apple Safari account for over 85% of browser usage.
And when it doesn’t benefit BIG tech, they squash tracking in the naming of privacy (hello Private Relay and Cookie deletion), all of which is increasingly making third-party trackers obsolete.
What happens when your measurement strategy relies on pixels that no longer work?
🚫 You lose visibility.
🚫 You increasingly make decisions on a small part of the pie.
🚫 Marketers without a first-party measurement strategy fall behind.
What can you do? The best marketers don’t rent data, they own it. They need to take matters into their own hands in a way that big tech can’t touch.
Winning in a cookieless world means:
✅ Implementing server-side tracking & clean rooms.
✅ Building privacy-compliant, deterministic attribution models.
The brands that control their data will control their future.
AdTech AI Files latest Pod drop discussing this very topic. On Spotify now: https://lnkd.in/gwTMafsm
#FirstPartyData #MarketingMeasurement #AdTech #PrivacyFirst #CookielessFuture #DigitalAdvertising #DataOwnership #MarketingStrategy
Why Cookie-Based Measurement Sucks in 2025
Remember when cookies were amazing? Back in the ‘90s and early 2000s, they revolutionized online tracking. But today, they only capture 9% of online conversions. Why? Because cookies simply don’t exist in most of the places where modern digital engagement happens:
Here’s a real-world example: You see a Starbucks ad while searching the web on your phone. Later, you open the Starbucks app and place an order. Does a cookie follow you from web to app? Nope.
This is why cookie-based measurement is great for companies like Google (who control the walled gardens) but terrible for marketers at large. If you actually want to measure conversions, it has to happen at the household and person level—which, by the way, Viant may or may not have patented back in 2012.
Now, Viant is doubling down on this future, partnering with TransUnion to bring even stronger, cookieless identity resolution to marketers. With first-party data and identity-based measurement, brands can finally connect the dots across CTV, mobile, web, and beyond—no cookies required.
The digital world has moved beyond cookies. Has your measurement strategy?
#AdTech #MarketingMeasurement #CookiesAreDead #DigitalAdvertising #MarketingAnalytics #ConnectedTV #PrivacyFirst #FutureOfMarketing #DataDriven #MarketingStrategy #ConversionTracking #AdMeasurement #MarTech #CustomerJourney #OmnichannelMarketing #IdentityResolution #CookielessFuture
Based solely on Danilo Tauro (PhD) linked in post on 3/5/25 and the 110 commenters summariez using only AI.
Article for reference: linkedin.com/feed/update/urn:li:activity:7303063345098620928/
Why Incremental Lift Shrinks Over Time: The Lookback Window Effect ⏳📉
When clients ask "I thought lift would be higher/lower, my 1st question back is what lookback window are you using?"
One of the biggest factors in incremental lift measurement isn’t just the ad itself, it’s how long you wait to measure it.
✅ The shorter the lookback window, the higher the incremental lift.
✅ The longer the lookback window, the lower the lift.
Why? Because marketing works, but so does time.
At first, your test group (who saw the ad) is converting quickly, while your control group (who didn’t) hasn’t had time to act. But over time, some of the control group will naturally convert on their own, shrinking the perceived lift.
Lookback Window Impact on Lift:
📅 Day 1: 🚀 Huge lift! The test group is converting immediately after seeing the ad, while the control group has barely moved.
📅 Day 7: 🔥 Still strong lift—marketing is driving action faster than natural conversions.
📅 Day 14: 📉 Lift starts to drop as some of the control group naturally converts.
📅 Day 30: ⏳ Lift is at its lowest, as many in the control group who would have converted anyway have now done so.
What This Means for Marketers:
🔹 Short lookback windows (1-7 days) tend to overestimate lift because the control group hasn’t had time to convert.
🔹 Longer windows (14-30 days) give a more realistic picture but may undervalue short-term campaign impact.
🔹 The right lookback window depends on your product & buying cycle. A fast-moving CPG item might need a 7-day window, while a high-consideration purchase like a car or insurance policy might need 30+ days.
Marketing accelerates conversions, but time naturally fills the gap.
The key to accurate incrementality? Choosing a lookback window that reflects how real consumers behave. 🚀
#Incrementality #LiftAnalysis #MarketingMeasurement #AdTech #DigitalMarketing #GrowthMarketing #Attribution #MarketingAnalytics
Mark My Words: Contribution Will Be the Future of AdTech Measurement
We’re wrapping up our beta offering, and the feedback has been phenomenal. It just makes sense.
Take a look at the chart below—see how CTV is undervalued in traditional attribution models?
Whether it’s Last Touch, First Touch, or Linear, they fail to capture the real impact of each channel. But Conversion Contribution? It tells a completely different story.
The industry is evolving, and it's time for measurement to evolve with it. Much more to come on this. 🚀
#AdTech #Attribution #CTV #MarketingMeasurement #ConversionContribution #AdTechAIFiles
The Best Marketers Have a Strategy for Moving Their Customers Through Each Phase of the Purchase Cycle
A long-time friend once shared an interesting insight about a global candy bar brand’s marketing strategy. Their mission wasn’t necessarily to get you to buy the candy bar at the cash register—but to get you to say no to it.
Think about that for a second.
Most of the products you walk by in a grocery store don’t even register in your mind. You don’t consciously think, “Should I buy this?” You just keep walking. But if a brand can move you from complete indifference to an active consideration, that’s already a huge win.
And it all starts with awareness—because awareness all starts with your brand’s message.
If people don’t know you exist, they’ll never consider you. If they don’t understand what makes you different, they won’t engage. The best marketers don’t just hope their audience will buy—they strategically move them through every phase of the purchase funnel, from awareness to consideration to conversion.
And when it comes to building brand awareness, there’s no better tool than Connected TV (CTV). It puts your message in front of the right audience, at the right time, in a format that drives engagement and recall. If you want to start winning the battle for consideration, start by making sure your brand is seen and heard in the first place.
#Marketing #CTV #BrandAwareness #Strategy #ConsumerBehavior
Viant often gets compared a lot to The Trade Desk. Yet the big things we're working on are so different... 🤔
The Trade Desk:
1. Scale
2. Prep for Google Exit
3. Promote & protect objectivity more
4. Leverage supply and demand imbalance
5. Make CTV most effective channel
6. Audio best year ever
7. Move 100% of clients to KoKai
8. Change the way industry manages Deals
9. AI
10. Simplify Retail Offering
11. Simplify TTD platform
12. Use more data
13. JBPs
14. Grow Product Success
15. Hire Sr. Leadership
Viant Technology:
1. CTV
2. Addressability
3. AI