Connected TV (CTV) is the fastest-growing digital ad channel, as more TV watchers cancel cable subscriptions and turn to lower-priced or free a la carte streaming options they can watch on TVs, laptops and mobile devices. Many streamers are also potential B2B prospects, but not many B2B marketers are leveraging CTV for advertising.
“We believe connected TV advertising is undervalued, and there’s so much that digital, data-driven marketers can do with connected TV advertising that goes beyond the scope of any other ad channel,” said Hooman Javidan-Nejad, director of performance marketing for CTV advertising platform MNTN, at The MarTech Conference.
Why we care. Hit shows on streaming services get the credit for the CTV surge. But within these mass audiences there is data for targeting and segmentation. B2B marketers ahead of the curve have also experimented with streaming for delivering on-demand video content to prospects.
Serving prospects ads on ad-supported Netflix, or managing your own video programming like a kind of B2B Netflix, is a much different experience than traditional whitepapers that recognize professionals’ changing media consumption and self-serve research habits.
CTV data. “Data-driven marketing has picked up in the last decade because the nature of all those digital channels are enabling you, and empowering you, to have access to the data and to act on it,” said Javidan-Nejad. “This is something that we never had for a TV — [traditional linear] TV advertising has always had limited or no reporting.”
Because of CTV’s digital infrastructure, ad campaigns on that channel have performance and measurement data that can be used as a market research tool.
“The beauty of approaching connected TV just like another digital channel is that you can apply the same targeting criteria you are applying today on LinkedIn, or on Facebook,” he added. “The insights that you’re getting from connected TV advertising can be applied to all the other channels, or the insights that you’re getting from the creative can be applied into the other channels.”
Finding audiences on CTV. When advertising on CTV, B2B marketers should execute multiple campaigns, or target different audiences with a single campaign.
For example, a B2B marketer could run one campaign based on job titles, and another one based on firmographic criteria. You could also launch a retargeting campaign, based on first-party data acquired from those who have visited your website and shared their info.
“For each of these audiences, you will get audience segment reporting,” Javidan-Nejad explained. “So you will be able to see which of these audiences have performed better, which of these audiences had a better verified visit rate, and all the other metrics [to discover] which audiences are performing better. And then you can take those audience insights and apply them to the other channels.”
Matched audiences. B2B marketers can also use existing customers and prospects from their CRM and match them with a CTV adtech partner, in order to deliver CTV ads to those prospects when they’re watching streaming TV.
“This is the same audience that you’re using across all the other paid social channels,” said Javidan-Nejad. “The insights and learnings that you get from CTV can be extended and implemented across the other channels.”
Testing creative. Before committing a large budget on a robust TV campaign, B2B marketers can test different kinds of creative on CTV to determine what messages and visual cues stick with customers and prospects.
While every digital ad channel has its own sweet spot for what works in video ads, some of these insights about what works best on CTV can be applied to other channels.
“We are all familiar with A/B testing,” Javidan-Nejad said. “As digital marketers, we always try to leverage this feature or functionality across all the other digital channels. Now you’re able to do that for your TV advertising.”
Although often underrated or reduced to a “networking platform,” LinkedIn has the potential to help you drive traffic to your website, increase brand awareness, and boost your revenue. How? Through LinkedIn sponsored updates or ads.
Salesforce has announced an integration between Salesforce Commerce Cloud and Google Merchant Center to help merchants highlight the availability of products in stores. The move builds on Salesforce data that suggests both the widespread use of online search in advance of brick and mortar store visits, and an increased likelihood of shopping trips when consumers can see that a store has an item in stock.
Using this new integration, merchants using Commerce Cloud will be able to turn local inventory data into local product listings on Google Search and Google Maps and in the Shopping tab.
Why we care. The distinction between digital and real-world commerce continues to collapse. Those online shopping behaviors that exploded during the pandemic will be with us for the foreseeable future, but it doesn’t mean store visits are a thing of the past.
Rather, consumers are looking for seamless connections between an online product discovery experience and in-person purchases. This integration seeks to support that aim at a granular local level.
The Salesforce data that supports the move can be found here.
Embedding commerce in discovery. The integration also braids together online discovery and the commerce experience. Just as many merchants now seek to provide a frictionless transition from finding a product online to making a digital purchase, this sees the opportunity to link discovery with in-person shopping.
This move pairs with the recent announcement of Salesforce’s Einstein GPT for Commerce that combines proprietary and generative AI models with real-time data such as customer demographic data and shopping history, to automate and tailor shopper recommendations in Commerce Cloud.
Kim Davis is the Editorial Director of MarTech. Born in London, but a New Yorker for over two decades, Kim started covering enterprise software ten years ago. His experience encompasses SaaS for the enterprise, digital- ad data-driven urban planning, and applications of SaaS, digital technology, and data in the marketing space.
He first wrote about marketing technology as editor of Haymarket’s The Hub, a dedicated marketing tech website, which subsequently became a channel on the established direct marketing brand DMN. Kim joined DMN proper in 2016, as a senior editor, becoming Executive Editor, then Editor-in-Chief a position he held until January 2020.
Prior to working in tech journalism, Kim was Associate Editor at a New York Times hyper-local news site, The Local: East Village, and has previously worked as an editor of an academic publication, and as a music journalist. He has written hundreds of New York restaurant reviews for a personal blog, and has been an occasional guest contributor to Eater.
82% of marketers believe that AI will be the future of marketing—in fact, many of them already believe AI writes better than a human (Capterra study).
Well, with ChatGPT flying past 100 million users in just two months…we’re living in the future.
AI is revolutionizing the way we work, think, and create.
I joined Content at Scale as the VP of Marketing this January in a bold move of ‘adapting or die’ for my career in content—one month in, what I’m seeing, learning, and facilitating for marketers and teams is blowing my mind. Let’s talk about it.
Reduce Content Overhead Costs and Frustrations by 5x-25x With the AIO Model
It’s now the Stone Age to sit at your computer and drum up 2,500 words for an SEO post from a blank slate.
When you can generate long-form SEO content (2,500 words or more) that’s fully original and well-written inside of five minutes or less, you’ll never want to go back.
On average, I’m seeing a 5-25x reduction in associated content creation costs (which is mind-boggling!), and a time savings of 5-10x. (My full-time writer at Content Hacker went from 7 hours per post to one hour per post after we adapted this model.)
Here’s the AIO model I’ve built out reflecting the difference of what you can do in your business and marketing by replacing the human blank-slate writing with AI blank-slate writing, based on hundreds upon hundreds of use cases from Content at Scale clients:
Artificial Intelligence as the baseline writer (replacing the human writer and blank slate)
The human writer as an optimizer of the AI baseline content
With the time and money savings, it’s an absolute no-brainer to switch to AI as the baseline.
The Human Process Involved In AIO
While we see AI perfectly capable of writing an entire 2,500 word blog from scratch, with a single keyword and one-sentence prompt:
We also see the need for the human optimization process pre-publish more necessary than ever.
Without your unique story (or client case studies/testimonials) woven in, the human touch of adding statistics, double-checking facts and cutting the fluff; AI-written content simply won’t stand out. It won’t set you apart in the content sea; it won’t drive customers and loyal fans in droves to your email list. So, the human touch is necessary.
My C.R.A.F.T. framework within AIO defines the steps writers should take to make the AI content more human and personalized once you take it from AI and get it ready to publish (from AI to O):
1. Cut the fluff
2. Review, edit, optimize
3. Add images, visuals, media
5. Trust-build with personal story, tone, links
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Humans are needed for the optimization side, and for that human touch that must be applied to the content AI generates. Content itself will never be a fully automated, 100% AI process; but AI can remove hours and hours of painstaking work from the content creation pipeline, which will save countless amounts of energy and dollars in the coming months and years when marketers adapt in full force.
Predictions About the Future of Content & AI
This year, Capterra surveyed almost 200 marketers using AI in their marketing. 82% of them said that the content written by AI was just as good if not better than human-generated content.
One of the first Generative AI experts in the world, Nina Schick (founder of Tamang Ventures, and creator of Substack project ‘The Era of Generative AI’), has told Yahoo Finance Live that she believes ChatGPT will completely revamp how digital content is created, and by 2025, software built with ChatGPT will enable us to reach 90% of all online content now being generated by AI. She said: “ChatGPT has really captured the public imagination in an extremely compelling way, but I think in a few months’ time, ChatGPT is just going to be seen as another tool powered by this new form of AI, known as generative AI,” she said.
Google Trends shows a HUGE jump in interest and traffic around the term “ChatGPT:”
Search traffic shows that the interest in AI is the highest it has ever been. The previous peak was in January 2012:
375 million jobs obsolete in the next ten years. In the next three years, it’s predicted that 120 million workers around the globe will need to be retrained and re-skilled for this new world.
Newer and better-paying jobs in AI will come on the scene, but they won’t replace the amount of jobs lost; so without retraining and reskilling, and learning how to adapt, average people will have difficulty finding new work.
Are You Ready to Join the Future?
I’m excited to see just how much AI will revolutionize human efficiency and optimization.
We’re in new times.
Are you ready to join the future of marketing and learn about all things AI?