Digital Publishing Archives

Tim Wolff and Tom Raponi Join Futuri, Expanding Reach for Its Content, Audience, and Revenue AI for TV Broadcasters and Digital Publishers

February 16, 2021/0 Comments/in Digital Publishing, Industry News, New at Futuri, Press Release, Television /by Zena

TV and digital publishing industry executives join Futuri’s growing team.

Cleveland, Ohio, February 16, 2021 — Futuri, the leading provider of AI-driven audience engagement and sales intelligence technology for media, today announced two new senior leaders on its team who are focused on developing its suite of offerings for local, network, and cable television and digital publishers. Futuri’s AI-powered software for media includes TopicPulse, the story discovery and social content system that uses predictive AI to get ahead of topics trending with local audiences, and POST, Futuri’s enterprise podcasting system.

Tim Wolff joins Futuri as Vice President, TV and Digital Publishing Innovation. In this newly created position, Wolff will guide Futuri’s product strategy for TV and digital publishing solutions, translate user feedback into actionable product guidance, and develop R&D studies and content related to technology innovation in this space.

Wolff is a digital and broadcasting leader who’s led top-performing TV and digital publishing teams. In Wolff’s 20+ years of experience, he’s held content executive roles at stations including KSDK-TV St Louis, WHAS-TV Louisville, and WHIO-TV Dayton. Wolff joins Futuri from Cox Media Group Ohio, where he oversaw digital for one of the country’s only converged newsrooms. His group included three daily newspapers, three radio stations, WHIO-TV, Dayton.com, and several other digital products.

Tom Raponi joins the Futuri Board of Advisors. Raponi will advise on strategy for Futuri’s content, audience, and revenue AI for TV broadcasters.

Raponi is a respected veteran of the broadcast space, having spent the bulk of his 39-year career in VP/General Manager and senior-level sales management roles at major-market stations, including WFXT Boston and KTVU/KICU in the San Francisco Bay area. During his career, Raponi has worked extensively with news, marketing, and sales research. Before starting his media career with Katz Communications in 1979, Raponi was signed to a professional contract with the Detroit Tigers.

“TV broadcasters and digital publishers are all struggling to grow their content, audience, and revenue, and Futuri technology has been proven to deliver results on all fronts,” said Futuri CEO Daniel Anstandig. “Adding the considerable skill, experience, and insight of Tim Wolff and Tom Raponi to our team is a privilege, as Futuri solutions become even more essential and helpful to the TV broadcasting and digital publishing industries.”

“Futuri has elegant solutions that cut through the BS to fix real problems in TV broadcasting and digital publishing. They have a spirit and ethos of working with journalists to help them create stronger connections with their community,” said Wolff. “Working with Daniel Anstandig and the Futuri team, I can use my experience and knowledge to help not just one newsroom, but newsrooms around the country.”

“Senior leaders in the TV business are in a challenging time where growing content, audience, and revenue requires the ability to combine the science of predictive AI and research with the art of storytelling to maximize their results and stay relevant,” said Raponi. “Driving growth for its partners is core to what Futuri and Daniel Anstandig do every day, and I’m thrilled to join the team and help drive growth for the TV industry.”

Podcasts were big, then people forgot about them, now they’re huge. What happened?

February 15, 2021/0 Comments/in Digital Publishing, Podcasts, Television /by Zena

Here’s what changed that made podcasts skyrocket more than a decade after they first started — and why your news brand can’t miss out on this audience.

By Tim Wolff, Vice President of TV and Digital Publishing Innovation, Futuri

In 2005, I created one of the first video podcasts (vodcasts) in our market. We used it for high school sports highlights, and I was pleased we grew to about 50 users. Still, it took about a day to process the video, and the effort wasn’t really worth it at the time. Like most media outlets, we put our focus elsewhere.

By 2006, we had generally done that with podcasts in general. They had taken off as “the next big thing” after the iPod was launched (thank goodness they aren’t called Zunecasts!), but after a few years podcasts seem to fade from everywhere other than NPR. The market was too small and the work too involved for most media outlets to invest in it.

Several years later, Serial became a podcast hit, and suddenly podcasts were the next big thing again. Everyone from newspapers to bloggers scrambled to create podcasts, while NPR had been there the whole time.

What changed?

As in many industries, the key changes were about distribution, production costs, and a singular hit to capture people’s attention.

By 2014 the biggest barrier to consumer podcast listening had changed. Users no longer needed an iPod or to go through iTunes (these days, Apple Podcasts); the podcasting app had become native to every iPhone. This was a key distribution change, making it easier and automatic for millions of people to quickly get into listening to podcasts. Serial was the first big benefactor of this, shattering previous records for podcast downloads.

Now, with smart speakers and phone connections in cars, podcasts are readily and easily available everywhere.

Meanwhile, processing speeds have become exponentially faster. What took hours to process a decade ago can now be processed in seconds. With equipment becoming cheaper and online tutorials abundant, anyone can make a podcast quickly and easily now.

But what about money?

Most of the 1,700,000 podcasts out there don’t make any money. So why should local news brands get involved?

The main reasons revolve around the key goals for any media outlet: Audience reach, consumer loyalty, brand expansion, and revenue generation.

Podcasts today reach a demo that is highly sought after for media companies and advertisers. Stitcher reports that the most popular group who uses podcasts are adults 18-34. Podcasthost.org shows that 41% of US podcast listeners have a household income over $75k, which is 10% higher than the US average. Civic Science data shows that 1 in 3 podcast listeners made a purchase after hearing an ad on a podcast. Sound like an audience you want your brand to reach?

As sources of news expand from traditional media to social, OTT, podcast,s and everything else, legacy brands need a way to stay relevant everywhere. By reaching your target consumers in as many distribution channels as possible, you build loyalty to your brand and personalities.

You also reach new people. Podcast listeners are 10% more likely to follow news closely (AudienceScan data), but might not be traditional consumers of your media products. Getting them content in a podcast may remind them of the value your media brand brings, whether that’s through television, radio, newspaper, magazines, or a digital outlet.

And that brings the big challenge: Can you monetize podcasts directly?

It’s about your goals and the audience you want

Most of the time, we think about podcasts with huge audiences in order to generate any revenue. To have a huge audience, you probably need a podcast with a national or worldwide scope, likely focused on a key area of interest (football, for example, or true crime). This seems like a problem for local media outlets, because the audience they are targeting is one of local consumers, limited by the geographic reach of the brand. Unfortunately, too many local media decision-makers get to this point in their consideration, and then stop. They don’t see the monetization model that makes sense for them, so they choose not to do podcasts. They end up missing out on two key opportunities.

First, local interest sponsorships are a big opportunity. Any sales person in a market with a major sports team can tell you that there are advertisers who have key interest in reaching those fans. And every television executive can tell you that weather coverage is a key driver of viewing. Advertisers are actively looking to sponsor great weather brands. Combine these key areas of your media company’s strength with advertiser needs, and podcasts make a lot of sense.

Second, local media often overlook the key interest areas that would expand far beyond geography. Say your market is home to a major Navy base, and you have reporters who are well informed on the base, as one of your biggest employers. Use their expertise to launch a Navy-focused podcast, and suddenly you have the potential of a worldwide audience. Maybe instead of military interest, you have a sports team with a worldwide following. Or maybe you have Civil War experts or auto manufacturing or shipping companies as huge parts of your market. Starting podcasts around those areas can tap in to the national or global interest, and build a large audience that resonates with advertisers, and provides outreach for you to grow subscribers to your own products.

Where to start?

Once you see the value podcasts can bring to your newsroom, you need to know how to grow the reach of your podcasts. Using social media, youtube (the second largest search engine) and your own websites are all key. So is having a partner that can distribute to every platform at once. POST by Futuri is perfect for that; you can post to multiple platforms at once, and they can instantly turn your audio podcast into video, for maximum reach. The Futuri team even has tools to help you monetize your podcasts.

The US is expected to have 100 million podcast listeners this year. If your newsroom is truly committed to reaching and serving your community, it’s time to get into podcasts. You can’t afford to miss out on this audience.

Tim Wolff is Vice President of TV and Digital Publishing Innovation at Futuri. He has 20+ years of experience as a digital and broadcasting leader who’s led top-performing teams across the country at companies including Gannet, Belo, and Cox Media Group Ohio, which includes three daily newspapers, three radio stations, WHIO-TV, and more. Wolff, who holds a Master’s in Journalism from the University of Missouri, also makes a mean green chile stew.

AI, big data, and the newsroom: It's Time

AI, big data, and your newsroom: It’s time

February 15, 2021/0 Comments/in AI, Digital Publishing, Television /by Zena

Adjusting strategies and tactics in newsrooms used to take months of work (and a lot of faith in limited info). Now, AI and data tools can help you learn and make changes in minutes. It’s time for your newsroom to catch up.

By Tim Wolff, Vice President of TV and Digital Publishing Innovation, Futuri

It was the big moment in every newsroom: the day the sweeps ratings arrived. Early in my career, “diary markets” were prevalent. A small sample of viewers would be given books to write down what they watched each day. At the end of the sweeps month, they would mail those books to the ratings company, who would compile them, turn them into ratings spreadsheets, and send them to the stations. Newsrooms wouldn’t find out how many people watched their newscasts until weeks or months after the newscast aired (assuming, of course, people religiously wrote down exactly what they watched and when they watched it, which was far from a sure thing).

That was why I couldn’t wait every day for the overnight ratings, driven by meters placed on some viewers’ televisions. As a news producer, I wanted to see what kind of impact the hundreds of little decisions I made had on the ratings. Getting a spreadsheet the next day that showed how the newscast performed in 15-minute increments was the best I could do in trying to figure out whether my strategy and tactics had worked.

In truth, it didn’t help much on an individual day. Seeing a tenth of a point change day over day in a quarter hour could be from so many factors, ranging from the quality of the newscast to the weather outside to the level of excitement in a baseball game on another channel. There were rare occasions when it would show a dramatic mistake—like country music interviews at 10pm that saw our second quarter drop 10 points—but those were rare. Having overnight ratings was valuable in long-term assessments, but not so much for all the decisions that go into a live television newscast.

Then I began to get really excited about minute-by-minute reports. These were detailed reports, showing each minute of the newscast with ratings increases or decreases, and included all the other channels, too. That way, I could see if my B-block tease kept viewers around or sent them flipping to the competition. It gave some idea about which stories were retaining viewers, and which were turning them off. It wasn’t perfect, since many stories are shorter than a minute, or overlap into different minutes. It also wasn’t available until 3 days after the newscast aired, at which point I’d usually forgotten what was even in that newscast. Still, with a lot of tracking and work, I could use them to learn about what did or didn’t make viewers go away.

The digital metrics rush

When I first came to digital in the mid-2000s, the availability of metrics was like an adrenaline rush. I could see how well each individual story performed. It wasn’t in real-time then, with a lag of a few hours and a full report not ready until the next morning. Still, it was amazing to me, as I could track all these individual stories to learn the trends of what performed well on our website (there were no apps or real social media then).

I moved back to broadcast for a while, and metrics tools improved. Eventually, we had a tool that showed real-time performance for individual stories on a monitor right above my desk. I’ll never forget how shocked I was when I glanced up and saw a relatively minor story getting 600 live page views (about 10 times our typical top story then). I asked one of our digital team members what was happening. It was Facebook, she told me; the story had gone viral, and it appeared there wasn’t much rhyme or reason to it.

Over time, as I returned to focusing on digital, the measurement tools got faster and helped us focus on which stories to spend our limited resources perfecting and promoting. But they were all really doing the same thing: tracking metrics. All these tools could tell us what our consumers were consuming, but the tools couldn’t tell us why, or what might work next. For that, we needed teams of smart people analyzing and tracking what worked so we could refine our strategies and help our producers figure out what they should post—and when they should post it. Given the mercurial nature of which stories take off on social and which ones fail, it was still a guessing game.

Data helped define strategy…slowly

As we gathered more data on our social brands (and even on our talent’s social brands), we were able to continuously refine strategies, and help give everyone a better chance of creating winning social posts. But even with our team focused on the metrics, it was a ton of data to manage, especially as we tried to be competitive with posting 24/7. What I really wanted to be able to do was track data across our entire market, not just on our brands. Of course, there was no way our team was going to be able to effectively do that. Having people dive in to generate reports just on our pages and our competitors’ pages was already an onerous task—and accounted for just a slice of the social media usage among our consumers. More and more, the data was becoming available, but there was no way for us to track and analyze it all.

That’s where “big data” processing and machine learning really began to come into play. We needed tools that could ingest data from all the millions of posts our consumers were seeing, then take that data and present it in a way we could learn from it and use it. The next game-changer was machine learning, the artificial intelligence that could spot the trends in all that data. As more and more data came into the machine, the AI could learn not only what was working, but what was likely to work. This created an amazing opportunity.

Futuri’s TopicPulse is at the forefront of this AI in the newsroom revolution. With years of data from more than a hundred thousand sources, the tool has insights from the performance of trillions of posts. With AI, TopicPulse uses those insights to be able to predict which posts are going to go viral—and which ones are about to lose all their momentum. This gives newsrooms actionable, immediate information that our digital producers and social teams can use to truly engage their consumers, drive traffic, and make sure that they are spending their time on the stories the community wants.

Even with our great team using human eyeballs to pore over a (relatively) small data set, we would never be able to use data like that. Instead, our team could focus on writing better posts instead of staring and spreadsheets and looking for trends.

AI is coming…AI is here

AI has a growing presence in newsrooms in other ways, too. There are a number of projects that have studied how journalists write stories, and AI allows computers to take a set of facts and create stories that read as though journalists wrote them. These are common in financial reporting and sports (some video games like FIFA and Madden were early adopters). You’ve probably read these stories and not even realized they were written by computers.

Recommendation engines on websites have been powered by data and personalization for years (what did Lilly do before those AT&T commercials?). There are even AI-powered broadcast anchors on television, like China’s Xin Xiaowei.

For local newsrooms, these kinds of advances in AI are coming from many directions. The great benefit is that the data helps newsroom leaders make better, more informed decisions. They can also spend more time on creating great newscasts instead of slogging through limited and late-arriving data.

We have come a long way from waiting a month to find out whether anyone wrote down that they watched.

The demo targeting you’re probably getting wrong

February 15, 2021/0 Comments/in AI, Digital Publishing, Television /by Zena

Every newsroom has a plan for targeting its key demographic groups. But the assumptions we make can do more harm than good. Here’s what newsrooms really need to focus on.

By Tim Wolff, VP, TV and Digital Publishing Innovation, Futuri

It’s a situation that probably sounds familiar to any television executive. At a TV station where I used to work, I was in a meeting where our management team was reviewing research, trying to figure out how to stop what we were told was a slide in viewing among a key demo: women 25-39.

(Note—while this meeting happened to be focused on this demo, I’ve found what’s true in this demo is true in any demo.)

We thought this demo was sliding because the consultant presenting the research quite gravely pointed out that favorability among women 25-39 had dropped nearly 2%. No one seemed to care that the entire research tracking study only had 500 participants, and only about 60 were in this demo… meaning exactly 1 person had rated us as less favorable than the previous tracking study.

Just because numbers seem alike doesn’t mean they are alike

As it happened, we were in the middle of making a decision about the hiring of an anchor. The first conclusion our team jumped to was that, if we are trying to attract women 25-39, we should hire a woman who is between the ages of 25 and 39. It may seem like a reasonable assumption, but it is, in fact a very large assumption—and assumptions are a poor proxy for data.

That was something I’d learned early in my news career. At another station where I’d worked, they had followed this exact approach when naming a chief meteorologist. She was quite good and very well-liked, but one of the managers told me they had really been surprised—her biggest fans were women 60+. “They love her because they remind them of their daughters or granddaughters,” this manager told me. She actually did not perform particularly well among the younger female demographic.

It was that experience that helped me understand the value of what one of the leaders said in the room. It was something along the lines of, “If we are going to try to target one demographic, shouldn’t we do some testing to see if this demo has a preference for a news anchor?”

Everyone agreed this was a great idea—even the VP who had to pay the consultant for another round of research.

What the research showed

When it came back, it turned out that women in the DMA between 25-39 years old did appear to have a slight preference for one demo. The researchers had asked about trustworthy news among 6 different potential anchors, using a variety of pictures as representation: Females or males in the ages of 25-39, 40-55, and 55+. Each person in the research — again, women 25-39 —chose one as they’d most trust and want to watch in a local newscast:

Male 40-55: 22%
Male 55+: 20%
Female 40-55: 18%
Female 25-39: 17%
Female 55+: 13%
Male 25-39: 10%

But even this research is misleading, as the margin of error was staggeringly high, and the margins so small as to hardly be definitive. But it did show us that our proxy for data, our assumption that people in a given demo have a strong preference to watch news delivered by someone in that same demo, was not a very good proxy at all.

The newsroom leader who was making the decision on hiring an anchor used all of this very wisely, deciding that what it really meant was just that we needed to hire the best anchor; someone who was both a strong journalist and a great communicator (and in this case happened to be a woman in her late 30s).

And while this particular case was focused on women 25-39, I’ve seen similar truths about men and women of all ages. If a sports radio station is targeting 25-49 year old males, it does not mean that the best anchors they could hire should be men 25-49. There is simply very little correlation to how much they trust someone or want to watch someone and the coincidence of whether that person happens to be in their demo.

That’s not to say representation doesn’t matter—it does, and it is critical for all people in your DMA to see people they can connect with, or to see someone who looks like them and the people they know. This is especially critical in traditionally under-represented communities.

But which demo your anchors happen to fit into is actually not very important in whether a viewer will choose to watch your newscast. And there is a very simple reason for that: YOUR VIEWERS ARE NOT SHALLOW.

It’s about substance

News viewers care about substance. They care about their community, and they know their community is intertwined with people of every age, gender, lifestyle and hometown in your DMA. They live with and love people outside of their demo, and they care about news from every demo.

(Tip: To help your assignment desk and anchors quickly find content that suits your target audience demo, try Futuri’s TopicPulse. Its AI-powered feeds tell you what topics people in your target audience are seeing and sharing, and even clues you in to which ones aren’t yet getting a lot of news coverage.)

That’s why the best path for you, and the most critical way to move forward, is to focus on the representation in the substance of your content, not in the demo appearance of your talent.

Track what you’re doing

This was the biggest realization for me, and the way I found we could have the biggest impact on every demo. We started tracking our content topics, and we started tracking who we were interviewing…and made a discovery both startling and familiar. The overwhelming majority of our interviews were with officials, and, in our market at the time, the overwhelming majority of officials were white males over 50.

This presented a few problems; first, it meant that we were getting an overabundance of one perspective; second, it meant that we were getting a lot of boring soundbites that just stated information.

So I started by using a proxy goal; have the numbers of people we interview align more closely with the breakdown of demographics in our DMA. It wasn’t a perfect proxy, but what it did do was open our content to having more perspectives that our viewers were used to in their lives and communities.

Most of us don’t spend our lives talking with “officials.” Most of us talk to people throughout our interwoven communities (social media bubbles in a pandemic will be a topic for another time), and want to hear the perspectives of real people affected by stories.

Over time—and it didn’t take very long—as we tracked who we interviewed, we made a dramatic difference in the perspectives of our stories, and in the quality of our news. It also made a big difference in our research; our ratings and our favorability scores went up with every demo.

If you’re in local news, and you’ve been tasked with raising ratings in a particular demo, I hope that you, too, will focus on your content and your community. Because that’s what your viewers will focus on.

How to win breaking news (hint: it’s not just about being first)

February 15, 2021/0 Comments/in Digital Publishing, Television /by Zena

Webinar: Winning Breaking News: Hint! It’s Not Always About Being First, is taking place on March 11th at 1 PM ET! Click here to learn more.

“Winning” breaking news is a non-stop battle. But if you think the only goal is to be first, then you’re missing the most important parts. Here’s what every newsroom needs to know about winning breaking news.

By Tim Wolff, Vice President of TV and Digital Publishing Innovation, Futuri

In the newsroom days of my youth, I thought this was how we would win breaking news:

Word would come into the newsroom that something big was happening, something worth breaking into programming for. The assignment desk editor, simultaneously on the phone and shouting at the producers, would be staring at the televisions with the competitors on the screen, sweating and hoping they didn’t break in first.
Then, my station’s animation would start, and we’d be on the air first.
The assignment editor would say something like, “Yes, we won the breaking news!”

What I didn’t realize then is that we hadn’t won breaking news. At least not yet.

As winning the breaking news battle moved online, then onto mobile, the adrenaline is the same, but the methods are different. Now, when word comes of breaking news, one poor digital or assignment desk staffer frantically types out a push alert (maybe even taking a second to proofread it) while the rest of the newsroom stares at their phones, hoping the competition doesn’t push it first.

When we’d “win,” there’d be an audible sigh from that poor person who had to get the push alert out with the weight of the newsroom on them.

But what was true in television is true in digital: being first doesn’t win breaking news.

I’ve known assignment editors and digital staff who were judged by station leaders almost solely on how well they did in being first, especially if research showed that viewers thought their station was losing at breaking news.

But here’s the thing about viewers: they don’t remember who was first. And they don’t really care.

It’s about the coverage

If a viewer sees you break in on TV, but your coverage is terrible, they will flip to the other stations. When those stations are on the air, the viewers will stay with the one doing the best job; and that is who they will credit with winning breaking news.

It’s true for breaking weather, too. At one station where I worked, we had so thoroughly proven that we were the leader in weather that when our competitors would break in with severe weather, their ratings would go down. Their viewers knew we had the best coverage, so they would turn to us immediately.

It works that way in digital, too. If I get a push alert from the first station to break the news, and I open the story and there are two sentences there, that’s fine. It’s breaking. If, 20 minutes later, there are still only two sentences there, then I’ve moved on and I’m reading the competitors who’ve added context and information. I won’t easily come back to that first brand, and I certainly won’t think they won the breaking news.

This is an area where newspapers have made gains on TV stations in breaking news. In most cases, the newspaper staff is immediately working to add context around breaking stories, with more immediate depth and information around the who, what, when, where and why–and the immediate history of the location. On the national stage, digital publishers like Heavy have made a business out of this.

Getting the second-day story today

Locally, newspapers have also been quicker to adapt to what we used to think of as the “second-day story.” On the first day of big breaking news, it’s about getting the facts out, and letting people absorb that information before hitting them with what it means, or the perspective, or the investigation into the conditions that led to the breaking news. Those used to be the second-day stories. In today’s media environment, however, consumers have gone to every site to look at what they have about the breaking story. And they have absorbed all that information quickly, immediately pivoting to how something could have happened, or what it means. They may go on Twitter or Facebook, or other forums, to get perspective. In other words, they are looking for the second-day story, and they are looking for it almost immediately. The “second-day story” is now the “second-hour story.”

Inside the newsroom, we’d find those stories by getting together and throwing out ideas. Someone (like the news director) would pull out a sharpie and start writing out all the angles to pursue on a whiteboard. Now, this may be happening on video chats with Slack, but the concept is the same: everyone shouts out every angle they can think of.

Of course, we’d always have way too many angles to pursue, especially immediately. It would fall to the newsroom leaders to use their experience to judge which ones to focus on. Almost invariably, later that night a different station would pick a different angle, and we’d be kicking ourselves for missing that angle. And because we didn’t have ways to do much new reporting overnight, it would fall to the next day for us to catch up on it.

There are two ways to avoid that. First, having experienced leaders who are always right in their judgment will help a lot (OK, I caught you there—any experienced news person will tell you they don’t always get it right).

Second, there are tools today that can help. We now have the ability to tell, in real-time, what questions are viewers are asking about the breaking news.There are SEO tools that show what is being searched, and social tools that show what is being shared. One tool, Futuri’s TopicPulse, will even show you the stories a specific target audience is likely to share, and further notes which ones aren’t getting much news coverage yet—giving you a huge advantage in knowing which big-story angles to pursue first.

Practice, train and have a plan

Each of these elements happens quickly, and your news team can’t be recreating the wheel every time breaking news happens. No matter how big or small your staff, each person working needs to know what to do, and they need to know the priority order. Just as critical, when you build your plan, don’t just build it for the workday when you’re there; build it for overnights and weekends, too, when you might just have one person in the newsroom.

It might look something like this: Get information – Alert others in newsroom – send push alert – post basic story – keep getting info to whoever is publishing or on air – update digital story – when basic info is covered, start working second-day angles – source info from search and social – add and update stories.

Of course, depending on the position and your structure, those elements will vary. The point is that there needs to be a plan anyone can follow, from your most experienced journalists to your entry-level desk workers covering weekend overnights.

Having a plan helped our newsroom when a mass shooting happened early one Sunday morning. The inexperienced, part-time desk employee knew exactly what to do, and it made all the difference in our brand being first with important information. The news team that came online knew what to do next, and that gave our coverage context and the ability to add the right angles long before the competition. Most of all, combining our experience with search and social listening helped us answer our community’s most important questions in a time of crisis.

This won’t be the only time I write about winning breaking news; there are a million key actions to take by everyone involved, and they are all worth diving into. But I hope these steps help you turn your newsroom into a breaking news winner long after that first push alert goes out.

The keys:

Have a plan
Practice
Publish quickly and update with context
Listen to the questions your audience has
Answer those questions with facts and perspective
Ask yourself later not just whether you were first, but whether you were best

One final note: if you fail, learn from it. Do an honest, open deep-dive debrief with everyone involved. Failing on one breaking news story won’t kill your brand; failing to learn how to be better will.

To register for the free webinar: Winning Breaking News: Hint! It’s Not Always About Being First, fill out the form below! To learn more about the webinar, click here.

Innovation19 Podcast: AI and the Future of News

November 30, 2020/0 Comments/in Digital Publishing, Podcasts, Television /by anuj

Tim Wolff and Tom Raponi Join Futuri, Expanding Reach for Its Content, Audience, and Revenue AI for TV Broadcasters and Digital Publishers

TV and digital publishing industry executives join Futuri’s growing team.

Podcasts were big, then people forgot about them, now they’re huge. What happened?

Here’s what changed that made podcasts skyrocket more than a decade after they first started — and why your news brand can’t miss out on this audience.

AI, big data, and your newsroom: It’s time

Adjusting strategies and tactics in newsrooms used to take months of work (and a lot of faith in limited info). Now, AI and data tools can help you learn and make changes in minutes. It’s time for your newsroom to catch up.

The demo targeting you’re probably getting wrong

Every newsroom has a plan for targeting its key demographic groups. But the assumptions we make can do more harm than good. Here’s what newsrooms really need to focus on.

How to win breaking news (hint: it’s not just about being first)

“Winning” breaking news is a non-stop battle. But if you think the only goal is to be first, then you’re missing the most important parts. Here’s what every newsroom needs to know about winning breaking news.

Innovation19 Podcast: AI and the Future of News

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© 2021 Futuri Media

TV and digital publishing industry executives join Futuri’s growing team.

Here’s what changed that made podcasts skyrocket more than a decade after they first started — and why your news brand can’t miss out on this audience.

Adjusting strategies and tactics in newsrooms used to take months of work (and a lot of faith in limited info). Now, AI and data tools can help you learn and make changes in minutes. It’s time for your newsroom to catch up.

Every newsroom has a plan for targeting its key demographic groups. But the assumptions we make can do more harm than good. Here’s what newsrooms really need to focus on.

“Winning” breaking news is a non-stop battle. But if you think the only goal is to be first, then you’re missing the most important parts. Here’s what every newsroom needs to know about winning breaking news.

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