Okay, so maybe that’s an overstatement. But if you’re a human who scrolls or swipes on the semi-regular, you’ve surely noticed the TikTokification of just about everything. And as a B2B brand, you can’t ignore this shift in how people consume and share ideas.

Scroll through any feed and you’ll see the power of this now-ubiquitous format. A sharp, 20-second video clip can extend the half-life of your best ideas; it can pull a key takeaway out of your latest report, give it visual and emotional context, and send it rippling through executive feeds within hours. It can turn depth into reach, and thought leadership into momentum. And in 2025, the brands mastering this balance between insight and immediacy are the ones shaping the conversation.

This playbook lays out a practical framework for scaling short-form production without sacrificing your sanity (or your brand voice).

Why Invest in Short-Form Video Now?

In recent years, three converging forces have made the format indispensable.

1. Platform algorithms reward native video content. LinkedIn’s algorithm favors native uploads and visible engagement (likes, comments, and reshares) over external links. That means a short video posted directly to the feed will almost always travel farther than a link to your blog or YouTube page. YouTube itself is doubling down on Shorts as a discovery engine, logging over 70 billion daily views and driving new traffic to longer videos on the same channels.
2. Buyer behavior has fundamentally shifted. Short-form videos work because they fit into micro-moments: the scrolls between calls, inbox breaks, or quick research before a pitch. A single, well-edited clip can become both an external thought-leadership post and an internal enablement asset.
3. The ROI proof is in. HubSpot’s annual State of Marketing report notes that short-form leads in ROI, engagement, and lead generation compared to other video formats.

Here’s an example of why this format is so critical in 2025: Imagine your team hosts an insightful webinar that draws a few hundred live attendees. The response is positive, but small scale and contained. But a day later, your marketing team clips a 30-second highlight from the event, and suddenly, the insight is everywhere on LinkedIn — it’s even picking up traction on TikTok. Same idea. Same audience. Different velocity.

Formats That Work in B2B in 2025

Successful B2B video strategies rely on repeatable formats that teams can batch-produce efficiently.

These might include:

• Expert snippets and micro-takes (30–45 seconds) can work well for sharing perspectives on industry statistics/trends/reports or highlighting customer insights. Tap into your organization’s own subject-matter experts or internal data storytellers to surface fresh insights that customers or peers actually care about (e.g., a surprising trend from your latest benchmark report or a question your sales team keeps hearing).
• Explainer videos cut into digestible nuggets (30–60 seconds) break down complex frameworks, demonstrate before-and-after scenarios, or define emerging trends in three clear beats. The winning structure follows a simple pattern: Hook (identify the problem) → Core insight → Actionable step → Clear CTA.
• Behind-the-scenes content humanizes expertise while strengthening employer branding. For instance, show how customer success managers solve real client issues or how research teams uncover insights. Clips like these remind audiences that your company is made up of real people solving tangible problems.
• Series formats create viewing habits through familiar cadences like “60-Second Whiteboard,” “One Metric Monday,” or “3 Slides in 30 Seconds.” Consistent naming and timing can lower the cognitive load for viewers while simplifying planning and batch production for content teams.
• Strategic thought starters grab and maintain attention through provocative openings: “hot take” cold opens, “We were wrong about…” admissions, or direct challenges like, “If you only change one thing this quarter, make it this.”

Think of these formats as your highlight reel templates — they make it easier to share what your brand already knows, one clip at a time.

Production Techniques to Prioritize

In social feeds, clarity and pacing matter far more than cinematic production value. The most effective short-form clips hook viewers within the first second or two.

Smart editors also build in “pattern interrupts” every few seconds, swapping angles, adding B-roll, or flashing quick on-screen stats to keep attention from drifting. Because most platforms autoplay videos without sound, captions are critical. Burn them in, highlight key words for emphasis, and use visual cues like progress bars to nudge viewers toward completion.

Remember that you’re not striving for perfection; rather, you should aim to keep up momentum. An “80%-there” version published within 72 hours of a webinar or interview will outperform the flawless cut that ships a month late.

Finally, keep in mind that authenticity almost always beats polish. A quick, well-lit phone recording that feels human will connect better than a high-production shoot that feels staged.

To keep your process sustainable, treat short-form production like a feedback loop: Publish quickly, learn from watch-through data and comments, and adjust pacing or framing as you go. With accessible tools like Descript, CapCut, Adobe Premiere Rush, or VEED for editing — and Riverside, Zoom, or Loom for capture — teams no longer need full studio setups. Even AI-assisted repurposing tools such as OpusClip can help jump-start edits (though a human pass for quality and tone is still essential before anything goes live).

Platform-Specific Distribution and Optimization

Each platform has distinct engagement patterns and optimization requirements. To get the most out of every clip, tailor how you publish and frame it to match where your audience actually consumes content.

For instance:

• LinkedIn optimization centers on native uploads with strong opening lines and specific questions that encourage comments. Pin top comments with resource links and encourage authentic internal engagement within the first hour of posting to boost algorithmic distribution.
• YouTube Shorts require keyword-rich titles, series naming conventions, and dedicated Shorts playlists that encourage binge-watching while connecting to relevant long-form content on the same channel.
• Website integration through dedicated “Video Briefings” archives improves SEO through schema markup and interlinking with related guides and resources.
• Sales enablement packages should compile the top five performing clips monthly with specific use case guidance for prospecting, objection handling, and deal progression conversations.

No matter the platform, consistency beats complexity; the brands that show up regularly stay more visible.

From Long-Form to Shareable Short-Form: A Step-by-Step Guide

The most efficient B2B teams start with a single, insight-dense “anchor” asset, then break it into smaller, platform-ready pieces that keep the conversation going long after the original launch.

Here’s an example of what this process looks like step by step:

1. Choose the right anchor.

Start with something that already carries weight: a webinar, research report, executive interview, or customer roundtable. The best anchor content offers a clear point of view and connects directly to your broader marketing themes. Think: “What’s our take on this trend?” not “What can we summarize?”

2. Map out the moments worth sharing.

Before you ever hit record, list 8–15 potential short-form clips (“video atoms”) you could create from the anchor. These might include:

• A single strong stat or takeaway
• A myth your expert can debunk in 30 seconds
• A customer soundbite that illustrates impact
• A quick “how-we-did-it” tip from your team
• A question your audience asks again and again

Each one should have a rough script skeleton: a hook, a core insight (two or three lines max), a visual cue, and a clear call-to-action (CTA).

3. Batch record and assign clear roles.

Get everyone involved on the same page early. Strategists should identify anchor assets and tie them to upcoming campaigns. Subject-matter experts can block a short monthly recording session to capture multiple takes at once. Producers will handle editing, captioning, and versioning by platform. Social leads can write titles, schedule uploads, and engage in the first-hour comment window.

4. Build guardrails that let you move fast.

Nothing kills momentum faster than a 17-step approval chain. To avoid the death-by-approvals spiral, set up pre-approved brand templates for all the components you can. Maintain a short “greenlight list” of safe, recurring topics that can skip full legal review, and agree internally on a 48-hour turnaround standard from clip completion to publish.

5. Distribute and track smartly.

From one anchor asset, aim to create 10–15 video clips, a handful of static visuals, one short newsletter embed, and a quick sales-enablement reel. Assign each piece to a specific channel and goal (awareness, engagement, lead generation, or internal enablement) and monitor how each performs to refine the next round.

Turn Big Ideas into Bite-Sized Impact

The next time you publish a major report or host a webinar, keep the momentum going. Find the 30 seconds that say the most, put it in motion, and give your audience a reason to stop scrolling.

Attention may be fleeting, but influence compounds. Each short-form clip is a small opportunity to reinforce what your brand stands for — in your voice, on your timeline, and in front of the audiences that matter. When those moments stack up, they start to shape perception long after the video ends.

Learn how Contently helps B2B marketers turn depth into reach, and reach into measurable ROI.

Frequently Asked Questions (FAQs):

Q: What if my subject-matter experts hate being on camera?

Remind them that realness often performs better anyway. Try audio-over-PPT, screen recordings with voiceover, or micro-shorts where the expert speaks one idea directly. Over time, confidence follows repetition.

Q: Do I have to publish across all platforms at once?

Nope. It’s smarter to start where your audience already is (LinkedIn, Slack communities, internal channels) and scale gradually. Use your top-performing formats there before branching into Shorts, newsletters, or website archives.

Q: How do I make sure short-form video doesn’t become a siloed half-effort?

Embed it into the bigger content strategy. Map each clip to themes, campaigns or buyer stages. Use the same language, link back to related content, and integrate clips into newsletters, sales decks, or blog posts so they reinforce—not distract from—your core narrative.

The post The B2B Brand’s Guide to Short-Form Video in 2025 appeared first on Contently.

According to a report from market research firm Demand Metric, events are second only to email when it comes to the most effective B2B marketing tactics.

Per the report, 85 percent of B2B marketers say events are either “critical” or “very important” for accelerating the sales pipeline and driving revenue. In total, events make up about a fifth of marketing spend at B2B companies, according to Forrester Research and Boston Consulting Group.

It makes sense that there is still plenty of confidence in event marketing. Talk to any salespeople and they’ll tell you about the significance of face-to-face sales opportunities. The B2B space cares just as much about relationships as it does hard numbers, and events are a critical way to foster them.

But that doesn’t mean B2B events aren’t affected by the digital revolution. A recent study from eMarketer shows that a new events technology stack makes all those conferences and salons more effective than ever.

Data and ROI

It’s not uncommon for event marketers to be siloed from the rest of the marketing department. The events team gathers opportunities from sales, slots them into a spreadsheet, and then salespeople try to influence prospects and close deals during the event.

That process leads to a lot of informality. The events team can take credit for any closed opportunity that attended a conference, while salespeople are just happy to have made commission. As a result, if business is going well, both sides may be content with the status quo instead of pushing to re-evaluate and improve.

Most marketers already use CRMs like Salesforce to track and attribute deal accelerations to events. But there’s plenty of room to build a data-driven process. As of this spring, 15 percent of decision-makers don’t integrate their event data into a CRM at all.

The event stack has the power to become much more sophisticated. Marketers are increasingly beginning to track as much as they can about the event, not just deals won and lost. For example, tracking lead quality of your function offers a much more nuanced view of how to improve future events.

Integrating events into marketing automation platforms like Marketo is also becoming more common. Most B2B marketers understand the importance of quick follow-ups, and marketing automation platforms can speed up post-event sales touches and make them more personalized.

Another important practice that’s often overlooked is monitoring the performance of landing pages on your site. Optimizing landing pages for conversions is key, but so is tracking conversion all the way from landing pages to lead generation.

This all goes to show that events, despite being in-person, and should be tightly integrated into the rest of the marketing technology stack.

Beacons and the IoT

As back-end software improves the business case for events, the Internet of Things and other advanced technology is also transforming how marketers track attendee experience inside the conference hall.

Take Content Marketing World. This year, according to Cathy McPhillips, VP of marketing at CMI, attendees will now scan into sessions using radio-frequency identification (RFID) badges. As a result, CMI can get accurate views of who attended what and see which sessions were most popular—a gold mine of data for salespeople and the events team.

Other companies use apps in a similar way to track attendee flow and gather information on attendees. Of course, not everyone will download the app; the data won’t be a complete picture of every attendee. But new technologies like wearable beacons should simplify tracking the attendee experience easier. South by Southwest already uses the tech to gather massive amounts of data on when and where people go during the event.

This system benefits attendees as well. The beacons can help them find a path to the next session, provide personalized recommendations, and even connect them with fellow attendees for networking.

If it all sounds a bit creepy, well, you’re not necessarily wrong. The question for marketers is whether they can balance improving the attendee experience with asking for more data. If they can nail that balance, they can make a longstanding cornerstone of B2B marketing more powerful than ever.

The post How Technology Is Revolutionizing B2B Events appeared first on Contently.

Brinker has done an amazing job identifying and categorizing all the vendors in a space that’s expanding so rapidly. But despite the growth, there is stability at the top. Brinker found that less than 7 percent of the 5,000 vendors qualify as enterprises (which he defines as companies that have either gone public or have more than 1,000 employees).

At Contently, we decided to put together a different kind of content marketing landscape—one that looks at the royal houses of martech, if you will. Yes, Game of Thrones is back this summer, and we’re already turning everything into a Starks-versus-Lannisters metaphor.

Click on the graphic below to enlarge the map. And let us on know on Twitter @Contently if you’ve ever come across anything nerdier than a Game of Thrones-inspired marketing technology map.

The post We Made You a ‘Game of Thrones’-Style Map of the Marketing World appeared first on Contently.

Einstein. Sensai. Watson: Three important words for the future of martech and artificial intelligence. Salesforce’s Einstein launched late last year, Adobe’s Sensai two months later, and IBM and Salesforce announced a partnership to sell their AI together, earlier this month. As an IBM representative told TechCrunch, “Within a few years, every major decision—personal or business—will be made with the help of AI and cognitive technologies.”

However, not everyone is impressed. Henry Schuck, CEO of marketing and sales intelligence platform DiscoverOrg, thinks the AI arms race isn’t a new phenomenon. According to him, many martech companies are just rebranding technology that has been around for years. He isn’t the only one feeling skeptical. In a recent article on The Content Strategist that examined AI hype, Sameer Patel, CEO of the smart automation software company Kahuna, said: “There’s just a lot taking old technology [and] plastering AI on it.”

As artificial intelligence continues to grab headlines, I spoke to Schuck to get his take on evolving skill sets for marketers, where salespeople fit in an automated future, and why some marketers struggle with marketing technology.

I know you’ve expressed some skepticism about artificial intelligence. Do you think it’s going to be a big part of marketing’s future?

I’m certain AI will be a part of marketing’s future. But part of my perspective on this is the way companies use the word “AI.” It’s like a fancy word to describe something that marketers, particularly B2B marketers, have been doing for years now. It’s really just predictive lead scoring.

Marketers have been doing that for the last decade with website tracking and their own leads, all without using AI. It’s really over the last four or five years that there have been dozens of predictive lead scoring companies that have added machine learning to that process. They bring in a bunch of different data elements to help you look at your customer base and then identify which customers are your “A” customers, your “B” customers, your “C” customers, your “D” customers, all based on a complex statistical model that looks at the activities that your customers and non-customers have done. Then they identify what your ideal customer looks like.

So I think it’s interesting that there’s all this buzz around something that’s been around the B2B marketing world a long time.

Do you think in some cases it’s marketing technology companies rebranding something that has already existed, or do you think there actually has been a change in the technology itself?

No, I think they’re rebranding. My guess is, post-Salesforce announcement, the companies in the predictive lead scoring space began to rebrand themselves as companies who are in artificial intelligence.

That would not be too surprising. It seems that happens a lot, not just in marketing, but in technology in general.

Salesforce leads the way on a lot of that. DiscoverOrg was always a platform that was available on the web, but in 2010, when companies got really excited on the idea of the cloud, that’s just what we rebranded as: your data service provider in the cloud, everything in the cloud, all of your tools in the cloud. It was really because that’s when Salesforce was pressing on this cloud thing harder than they ever had before.

Do you think there is going to be a time in the future, say five years from now, when a proper AI technology can really change things?

First and foremost, I don’t think that AI ever fundamentally changes the need for a salesperson. In B2B sales, especially in the mid-market and enterprise side, there is a true skill to what a salesperson is able to do. A salesperson is able to comprehend the needs of a customer, make pattern recognition to what this customer needs compared to another customer, and so on. I don’t think that AI ever gets to a point in the near future when it replaces the art of what a salesperson does.

I don’t think that AI ever fundamentally changes the need for a salesperson.

I think what it will do, and what it’s already doing, is taking away some of the most mundane tasks that sales reps have to do. Calendar management is a place where you can see AI doing a great job.

In our business, we curate high quality information on companies and buyers that sell to companies. We have machine learning that’s built throughout the technology that we use. But one thing that we found is the last five yards, ten yards that you need, machine learning just doesn’t get you there. And sometimes those last yards make all the difference.

When you talk to some marketers and look at studies on how marketers are implementing tech, marketers are having problems with integrating everything and making sure it actually functions. Do you think that’s because marketers are not as technologically savvy as they should be, or is that more the fault of vendors not building products that are easy to use?

It’s two things. One, the industry has changed so quickly that the marketers who have those talents—who know how Marketo interacts with Salesforce, how to do campaign attributions, and how to look at different stages in the sales funnel—the number of people with real experience in that is very few. The entire universe of people who have done marketing attribution at scale is probably a couple hundred people in the United States.

Two, most of the technologies trying to help marketers are pretty new. Plus, the problems that marketers face are rapidly evolving, and the software’s trying to evolve alongside it. But it’s obviously a little bit behind.

With all AI, there are always humans behind these tools, and humans can make mistakes. Do you think there are potential problems where maybe the initial data input isn’t correct or there’s a wrench in the system that messes everything up?

With any AI, any predictive lead scoring, and really any of these analytics tools out there, they are only as good as the data that goes into them. So if you have a predictive lead scoring tool that defines a model and looks at your customer data, it’s entirely dependent on the quality of data that goes in. Once you have a bunch of the wrong contact types or incorrect industry labels, then the model is pretty useless.

With any AI, any predictive lead scoring, and really any of these analytics tools out there, they are only as good as the data that goes into them.

If you talk to any marketer about a predictive lead scoring tool, the biggest project is normalizing the data and filling holes. You spend a lot more time making the data normalized and filling gaps of the data with your own data than you do actually getting the data in and having it do the analysis.

It all comes down to how disciplined you are gathering your data, keeping your data cleansed, and making sure your data is in a format that can be easily translated into multiple systems.

So if you’re an average marketer and maybe you don’t work for the most tech savvy firm, how should you prepare for the increasing automation?

I think what you’re going to continue to see is people in marketing are going to be required to have a real technological skill set that maybe a decade ago they didn’t need to have. They could be creative and artistic and clever and probably get away with being a good marketer, but today’s marketer needs to be data-driven, technology-savvy, and able to pick up new concepts quickly.

If you look at the martech landscape, it’s almost tripled in size in the last three years. There are thousands of new marketing technologies that are coming online. Having a sense of what those things do and how they play in your environment really requires technological savvy.

We did a study where we looked at companies that grow fast and companies that don’t. For the companies that grow fast, one of the top characteristics that they looked for in salespeople that they hire is technological savvy. That contrasts against slow-growth companies that look for experience and discipline. I think it goes to the point that technologically savvy salespeople and marketers are the ones who are able to get the most out of today’s B2B sales marketing world.

This interview has been edited for clarity.

The post ‘Today’s Marketer Needs to Be Data-Driven’: DiscoverOrg CEO Henry Schuck on Artificial Intelligence and the Future of Martech appeared first on Contently.

After years of swift technological development disrupted marketing to its core, CMOs and their teams are now responsible for a bevy of critical company functions: optimizing the sales process, improving customer experience, and marketing the product across a complex array of channels. Meanwhile, CEOs understand that technology allows for accurate tracking of marketing dollars spent, creating immense pressure on CMOs to perform.

Now, another technological breakthrough is on the horizon: artificial intelligence (AI). According to many experts, AI has the potential to be the most revolutionary technology since computing itself—and marketing is first in line for disruption.

Should marketing leaders panic or celebrate? It depends on who you ask.

The artificial intelligence hype machine

2016 was a big year for artificial intelligence.

Google’s AlphaGo program defeated the world champion in the complex game of Go, a landmark in AI development. Facebook, Microsoft, Google, and Amazon all made significant investments in AI. Wired proclaimed that the world’s biggest tech companies are “remaking themselves around the technology.” In marketing, Salesforce and Adobe announced new intelligence programs, called Einstein and Sensai, respectively. We’re in the midst of an AI arms race.

“I’m astounded in how AI is going to transform every industry,” said Leslie Fine, VP of product at martech giant Salesforce. “Companies today face an imperative to integrate AI into their products and services, or risk becoming less competitive with companies who are applying AI to improve customer experiences and make more intelligent business decisions.”

But what is AI exactly? And how does it apply to marketing? The answers aren’t as simple as you might think.

Everyone seems to have a different definition for AI. Typically, though, it’s an umbrella term that refers to software that carries out tasks that would normally require human intuition. Think recommendations on Netflix, Google Translate, software powering self-driving cars, and even GPS map services such as Waze.

Marketers tend to apply the term to a variety of processes such as automation, machine learning, and optimization. But that has led to a muddled understanding of the technology. And martech vendors aren’t exactly taking steps to clear up the confusion. As AI takes its place as the industry’s buzzword du jour, companies everywhere are hoping to ride the hype.

Henry Schuck, CEO of DiscoverOrg, a sales and marketing intelligence solution, believes that Salesforce’s Einstein announcement in 2016 was mostly a rebranding of what the company formally called “predictive lead scoring.” According to him, the new terminology has led to a hysteria of “rebranding” from companies desperate to keep up.

Sameer Patel, CEO of the B2C smart automation software company Kahuna, worries this widespread adoption could have real consequences. “There’s just a lot taking old technology, plastering AI on it, putting a nice gloss on it, and saying, ‘Hey, great, I’m AI,'” he said. “No, you’re not. It’s going to give AI a bad name, ultimately, because the results won’t come out.”

Unfortunately, there is no authority that defines what exactly is and isn’t AI, and companies will likely use the term’s loose definition to hype their own products or undercut competitors. AI’s definition will always be broad—what really matters is what the technology can do.

The rise of AI

Jon Epstein—CMO at Sentient, one of the most-funded independent AI firms in the world—believes AI will be more revolutionary than the internet.

But artificial intelligence has been around for years. The difference is that recent technological innovations have propelled its rise to the front of the marketing hype train. As Scott Brinker, founding editor of ChiefMartec, wrote last year, “The horsepower and data to efficiently run AI algorithms is now within reach of everyone.”

AI is already visible in a number of marketing disciplines. Ad tech companies use AI to power programmatic ad exchanges, automatically optimizing ad campaigns that once required intense menial labor. Marketing automation software, such as Marketo, also takes care of tasks that once required hours of labor, such as sending nurture emails or qualifying leads.

“Any part of the marketing world where a marketer has to read data and make decisions based on that data will be affected by AI in one way or another in the near future,” Schuck said.

“With any AI, they are really only as good as the data that goes into them.”

While machine learning and automation tools can simplify marketing processes, many of today’s AI companies are also focused on how technology can improve customer experience. Sentient, for example, uses its “distributed AI platform,” which runs on an incredible network of 2 million CPUs and 5,000 GPUs (the horsepower in a computer), to help retail clients optimize the customer experience. One of its two marketing products, Sentient Ascend, does A/B testing in real time at massive scale.

“Normally when you’re testing … it’s pretty slow and painstaking.” Epstein explained. “Instead, using a different type of algorithm, you can test ten, twenty, thirty changes at a time, and it solves not only what changes to make, but what combination of them to achieve the highest level of response.”

To visualize this, think of testing colors and fonts on a lead form, the centerpiece of many marketing tool kits. Epstein told me that after one company used Sentient to test 380,000 form designs, its lead form conversion rate increased by 45 percent.

“The fact that you can pick up that kind of gain from what you would think of as tweaks, it’s pretty profound,” Epstein said. “We think there’s a lot of money being left on the table.”

At Kahuna, which serves mostly B2C clients, Patel values AI for the way it can help customize customer experience, using machine learning and signals to optimize for individual needs. Some companies are already showing that this customer-focused approach works.

“If you look at how quickly you can call for an Uber or pick a movie on Netflix, our tolerance and our attention span right now as consumers is wildly, wildly, wildly shorter than it used to be,” Patel said. “You’re dealing with a world where they’re expecting that you know who they are, you can understand their needs, and you can fulfill them in real time.”

From teen to neo-Nazi

While it’s easy to get caught up in the hype, AI still comes with issues. These software products rely on integrated and accurate data collection systems, but not every company has the digital infrastructure in place to take advantage of such advanced technology. Since martech is a young space, many marketers still use poorly integrated systems that lack oversight.

“With any AI, they are really only as good as the data that goes into them,” Schuck said.

In 2016, Microsoft built a Twitter bot called Tay meant to resemble a teenage girl that could communicate with users. In less than 24 hours, the bot tweeted messages like “Hitler was right I hate the Jews,” and “I fucking hate feminists and they should all die and burn in hell.”

Since the bot was programmed to take signals from users, internet trolls overwhelmed it with offensive messages and quickly turned Tay into a neo-Nazi bot. The controversy was an embarrassing example of AI’s potential to spiral out of control.

AI also dregs up criticisms often leveled at the adtech industry: namely, the reliance on over-personalization. Privacy concerns about too much targeting could lead to an “uncanny valley,” where customers are creeped out by AI’s abilities to predict their wants and needs.

However, most marketers remain confident the value outweighs these concerns. “I feel like we’re getting to a place where, as long you’re not messing with the user’s trust, people want personalization,” Patel said. “I think we’re moving from being okay with that to actually expecting that.”

The ghost in the machine

So here’s the big question: Where does artificial intelligence leave the marketer? Technology has already reshaped blue-collar industries, eliminating the need for jobs. Won’t automated systems threaten to destroy traditional marketing roles as well?

AI proponents concede that technology will replace some roles, but they believe AI has the potential to create just as many new jobs. Plus, they argue, software could free up marketers to focus on creative, strategic work rather than day-to-day processes.

“Ninety-five percent of the people who came to marketing did not come to this data-driven world. They came for the soft side of marketing. ” Patel said. “Because of AI, you can be that creative person you always wanted to be. You now have systems that don’t require you to become a mathematician.”

“Because of AI you can be that creative person that you always wanted to be.”

Perhaps there’s a compromise in the future. Patel and Schuck both expect a new breed of marketer to emerge—someone part data scientist, part creative, who can work directly with AI systems.

“AI will significantly simplify the user experience for many of the martech tools that marketers use, as well as automate a tremendous amount of the ‘manual’ labor associated with marketing programs today,” Brinker added. “It’s unlikely that we’ll be lounging around while robots feed us grapes.”

Currently, Sentient is working on building an “AI that writes AI,” a holy grail that could exponentially accelerate the sophistication of existing software. What happens if a competitor gets its hands on such technology while your company cannot? As AI develops, marketers will have to adapt quickly, and some of them may not be prepared.

“We’re at the very beginning of something,” Epstein said. “Seeing what our own technology can do, the stuff we’re doing research on—we ain’t seen anything yet.”

The post Marketing’s Artificial Intelligence Revolution Is Here appeared first on Contently.

“Oh, we’re B2B,” someone said. “We don’t think anyone’s looking for our content on Facebook. We only want to use LinkedIn.”

I hear this response meeting after meeting. I get the instinct to assume LinkedIn is the only worthwhile place to pay for content distribution if you’re a B2B company. LinkedIn has incredible ad targeting for B2B brands. When you’re selling a very specific product (say, enterprise content marketing software) to a very specific buyer, it’s incredibly useful to be able to target someone by job title, location, and company. On any other social network, it’s a crapshoot that people will accurately provide that information. On LinkedIn, it’s pretty much required. If I want to target the CMO of Pepsi with an e-book, LinkedIn is the first place I go.

But B2B marketers don’t eschew other social networks just because they love the targeting LinkedIn provides. They also believe users won’t be interested in work-related content on other social networks—particularly Facebook.

From all the data I’ve seen, the idea that people don’t care about B2B content on Facebook is a myth. Our strategy team runs content analysis for hundreds of niche B2B marketing topics each month, and consistently, we see that people love to share work-related content on Facebook. For topics ranging from demand generation marketing to logistics, Facebook accounts for the majority of shares for specialized B2B content.

This trend shouldn’t come as a surprise. Facebook accounts for over 40 percent of all traffic to publisher sites, eclipsing Google. Over 90 percent of all content sharing occurs on Facebook, compared to just 2.5 percent for LinkedIn. It’s the biggest media empire in the world, and people share and consume every kind of content through the Facebook feed—wedding pictures, political analysis, cat videos, and yes, even white papers and articles about the insurance industry.

While Facebook seems like a network that’s separate from our work lives, it’s really not. Think about the people you engage with most on Facebook. You probably see a ton of content from college classmates and coworkers—the people you’ve spent most of your life with since Facebook came on the scene. These also happen to be individuals who likely have similar professional interests. I don’t think twice about sharing a work-related piece about marketing or tech, because half of my “friends” work in marketing or tech.

If you’re still skeptical about using Facebook for content distribution when you already have LinkedIn, consider these two additional reasons: It’s cheap, and the targeting is really good.

The incredible amount of time that people spend on Facebook (50 minutes per day) means that Facebook has a supply of attention that no competitor can match. In most ad campaigns we’ve run for Contently, Facebook is consistently 10 times cheaper than LinkedIn ($0.20 – $1.00 per click on Facebook versus $2.00 – 10.00 on LinkedIn).

This isn’t to say that marketers should ditch LinkedIn. Far from it. As I’ve written before, one of the biggest problems in content marketing is brands don’t allocate enough of their budget to distribution. They create a ton of content, put it on a blog, and expect people to just show up. But they’d be better served creating fewer stories and investing extra money in paid distribution to ensure their target audience actually reads them. Unless you already have a mature audience and dominate the conversation in your industry, you probably want to allocate at least 25 percent of your budget to content distribution.

That means using LinkedIn and Facebook in conjunction. While LinkedIn only accounts for about 2.5 percent of social shares of all content, it still drives at least 25 percent or more of shares for content focused on B2B topics. Clearly, users look for more work-related content when they’re on LinkedIn. The targeting capabilities are especially helpful if you’re running an account-based marketing program. To oversimplify a bit, the strategy mix I usually recommend looks like this:

Top-of-funnel content: Facebook, since it’s a very efficient way to build an audience.

Gated lead-gen and bottom-funnel content: LinkedIn. When the payoff is bigger, the targeting and context make up for the price tag.

This year, B2B marketers need to experiment more aggressively with paid content distribution. But if they view LinkedIn as their only option, they’ll be doing themselves a disservice. Whether you love or hate Zuckerberg’s empire, it’s still one of the most powerful tools content marketers have.

The post B2B Paid Content Distribution: Facebook vs. LinkedIn appeared first on Contently.

Starting a marketing summit at 8 a.m. is ambitious. But xAd, an ad-tech firm based out of New York, didn’t have to worry.

At eight on the dot, the lobby of Skylight Modern, a venue in the Chelsea neighborhood of Manhattan, was already full of guests. It was a big day for the employees of xAd who were looking to connect with current and prospective clients over the company’s location intelligence technology. The packed summit, called “On Location,” took place on September 22. It was the company’s first conference and included new product demos as well as a number of ad-tech panels. The goal was to entertain and inform an exclusive group of data-collection experts in tech, retail, fashion, and advertising.

After breakfast, guests were directed downstairs to a larger, darker space with hundreds of cushioned chairs. Plastered across the walls were inspirational quotes from tech giants like Carly Fiorina (“The goal is to turn data into information and information into insight”) and Alan Kay (“The best way to predict the future is to invent it”).

High ceilings accommodated ten-foot industrial lighting trusses. And toward the back of the room was the “Location Lab,” where people could play with the company’s mapping software, called Blueprints, on desktop computers.

xAd hoped the summit would be one to remember, which is why its marketing team enlisted freelancers to cover the event for the company’s website. Jessica Meyers, marketing manager for xAd, handpicked writers with ad-tech and data-collection expertise from the Contently freelancer network to report on the panels and overall experience. In addition to covering panel topics, the event was an opportunity for the writers to learn more about xAd and where the company is headed in the future.

“Our summit gave us a great opportunity to nurture specific Contently writers and educate them on our company as well as industry-specific topics,” Meyers said. “Our team was confident that our longform content was in good hands so we could focus our efforts on making sure the event came together.” 

The reporters were assigned to cover specific event tracks: the general session, a data panel, and a lifestyle presentation.

“We invited clients from our agency, programmatic, channel, and brand direct divisions,” said Kimberly Konstant, VP of brand and buzz at xAd. “We trusted that our partnership with Contently would yield great content about the event with a quick turnaround.”

Tessa Wegert, a veteran Contently freelancer, covered the first two morning sessions on “Turning Data Into Action” and “The Future of Location.” Almost as soon as the panels commenced, she began conceptualizing the stories.

“My goal is to find a balance between reporting on the event and covering the key points for the people who weren’t able to make it,” Wegert said. “Because there were new product announcements, I’ll also include a few of the themes that are important to xAd.”

A few weeks after the event, xAd published Wegert’s article on the company blog. (The articles are positioned from the xAd team, so they do not reveal Wegert’s byline.) In “‘Big Data Is Not a Strategy’: 5 Tips for Making Location Intelligence Work for Your Brand,” Wegert breaks down how to translate the concept of big data into a strategy with specific action items—a valuable subject for xAd’s target audience.

A few weeks later, xAd published Wegert’s second piece, “How to Gain Consumer Context by Using Location Intelligence in 2017,” followed by a story on augmented reality by Haniya Rae, another Contently freelancer who covered the event.

The goal of the coverage was to fuel conversations about location-based advertising and communicate its importance for brands. It appears the strategy is working.

Two hundred marketers attended the summit, but the results of the conference extended well beyond the attendee list. From September to October alone, xAd event coverage played a role in boosting blog traffic up to 4x and increasing social media engagement by 36 percent. Part of this success can be attributed to Wegert’s location intelligence article, which was the most-viewed story in October.

For the xAd marketing team, stories about the conference served not only as a tool to spark social engagement, but also as a source of evergreen content. “Contently writers helped us extend the life and messaging of the event with focused blog posts that can be shared months after,” Konstant said. “The outcome of this partnership is that we have content that long outlives any single-day initiative.”

The post Contently Case Story: How Event Coverage Helped xAd Boost Site Engagement appeared first on Contently.

Data, optimization, and automation have now become central parts of marketing strategies. In many cases, software gets implemented across a variety of functions to help handle the increasing complexity of the digital world.

Put simply: It’s a complicated time to be a marketer. Luckily, there are people like Scott Brinker to help navigate it.

Brinker—the founding editor of Chief Martec, program chair of the MarTech Conference, and co-founder of his own martech company, ion interactive—has been a leading voice in the space since 2008. I spoke with him about martech’s automated future, where content fits into the marketing stack, and what marketers get wrong about martech.

You write a lot about the importance of strategy. A report came out recently that suggested strategy, not integration, is actually the most challenging part of martech. That’s interesting because strategy is the one thing that you can’t really “solve” with technology. So how can marketers up their strategy game?

Strategy is one of these words that means different things to different people. A very high-level business often wants clarity around position in the marketplace, its value proposition, how it compares its positioning to competitors, and so on.

If I’m looking from a content marketing perspective, you have to think strategically about, “Okay, which keywords do I want to dominate in search engine results? What sort of influencers am I looking to connect with in social media circles?” It’s work to really go through that process of identifying “where do we think the best investments are for what we want to achieve?”

Then, once you have that clarity at different levels within the organization, you start looking at technology as a way of solving: “Okay, how do we achieve that? If we know search engine optimization is incredibly important for us, what are some of the tools that we can use to support better SEO efforts?”

What are your thoughts on attribution and tagging? There seems to be a lot of pushback against it lately—Chief Martec even had a post about that. Do you think that pushback is warranted?

The guy who wrote that guest post on Chief Martec was making the case that, scientifically, it’s impossible to ever have perfect attribution. There are too many variables that we don’t have the data on. We can’t quantify what went into everyone’s decision-making process.

His point was that it’s very important to have realistic expectations. If we’re looking for this magic machine that we press a button and it tells us, “Do X, Y, and Z, and you’ll be guaranteed that people are going to buy”… We’re just not going to get there. It’s very damaging for the profession as a whole because we’re going to miss the bar.

“Few things in marketing are about achieving perfection. They’re largely about doing a better job than your competitors.”

This is not a knock against data-driven marketing. One of the places where he indicated there’s tremendous success is using partial attribution as a way to do things like media mix modeling, designing how much budget is best spent in different channels, and going after different segments and different messaging ideas that have been tried.

It’s not perfect, but few things in marketing are about achieving perfection. They’re largely about doing a better job than your competitors.

It seems to me like a lot of people buy software and then expect it to solve all their problems.

[Laughs] It would be nice if it worked that way. Unfortunately, it does not.

Another thing you write about a lot is consolidation and expansion within the martech industry. What are your thoughts on that? Do you think it’s still expanding, or is it contracting?

I think it’s a combination of both, which is what makes it such a tricky space. You certainly do see some consolidation. There continues to be a fairly healthy [mergers and acquisitions] market in the martech sector.

We’ve got two challenges in the other direction. One is there continues to be new startups that enter the space who think they can do better. Second, the boundaries of marketing seem to be expanding, particularly as we talk about things like digital business transformation. Marketing isn’t just about running campaigns independent of the rest of the company. Increasingly, marketing gets built into these new kinds of products and services that companies are offering.

Same thing with additional channels. We’re starting to play around with things like Amazon Alexa, or IoT, or augmented reality. All these new things that keep appearing on the horizon, they all become new opportunities for new kinds of software that marketers can leverage. That keeps the field large and vibrant.

Another thing emerging recently is artificial intelligence. In martech, there’s Einstein (Salesforce), Watson (IBM), Sensei (Adobe), and more. Do you think AI will ultimately be supplementary, just giving recommendations, or do you think it will actually take over a lot of the marketing processes?

Some of that will be our choice.

One of the arguments I hear in favor of giving more control to the algorithms is that marketing has become so complex that a human has a very hard time managing all these different levers. At that point, maybe the only way you can manage the complexity is to turn more of it over to a computer.

“The sense of control having been lost is very uncomfortable. I think that’s what we will wrestle with in adopting AI in marketing.”

But as we turn over more of these functions to algorithms, they might end up taking actions that are going to affect our brands. You could use the metaphor of the self-driving car. I think most people believe that self-driving cars will be safer than human drivers. But the moment we have news stories of self-driving cars getting into accidents and killing people, it’s going to really freak people out. The sense of control having been lost is very uncomfortable. I think that’s kind of what we will wrestle with in adopting AI in marketing.

There’s been a lot of recent rulings, like with the FCC and in Europe, around data collection. It seems more people are pushing for consumer protections. Yet at the same time, consumer data is so important for different marketing functions. Do you think there will ever be a point when regulations will undermine martech’s effectiveness or growth?

Yes, to a certain degree. There is a big portion of martech today premised on the idea that increasingly targeted analytics and greater personalization is really the best way for marketing to improve its effectiveness. Those strategies are at great risk if regulation clamps down on the very data those things need to be effective.

I’m actually pretty confident that the marketing technology space, as a whole, is going to continue to thrive, even if there are very tight regulations around data. A big part of martech isn’t just about the analytics or personalization but about creating better experiences for people. It’s taking the insights from user experience, applying it, and building better websites, better mobile apps, and managing the way we interact with people through social media in a way that’s more effective.

What do you think are the biggest mistakes that people make when it comes to martech and implementing martech solutions?

The biggest mistake, by far, is underestimating the people and processes side of these adoptions. When people say, “Hey, we’re having difficulty integrating these six different products,” there’s truth to that. People do still have integration challenges, but those challenges pale in comparison to the challenges the companies tend to end up with. Once they’ve got the software installed, and they’ve got it integrated, they throw the switch, and then they’re like, “Okay, now what?”

“The truth is that most of the marketing world doesn’t really know what to do with this stuff yet.”

The truth is that most of the marketing world doesn’t really know what to do with this stuff yet, and they’re still going about the process of marketing the way they always had before. They’re not really doing anything different with the technology, and not surprisingly, they don’t get much return from it.

You see companies that are willing to invest in training their people and promoting more experimentation, and those are the ones that tend to have greater success. It doesn’t feel like we bang that drum loud enough, sometimes.

Do you think that’s partly the fault of martech vendors as well? That they’re not informing their customers how best to use their software?

I think you’re absolutely right. Martech vendors, and I say this being a martech vendor myself, are looking to sell things. They tend to think their job is best fulfilled by reducing the number of things that a prospect has to think about.

What tends to not get brought up in that process is, “Oh, and by the way, you’re really going to want to make sure that you’ve got these training programs for people. And the way you’ve been managing your marketing team probably isn’t going to be as effective as perhaps shifting to more of an agile marketing methodology.”

That’s the really good advice of how people can get the greatest effectiveness out of these tools. Sadly, I think most martech vendors don’t really have an incentive to tackle that education.

Where do you think content marketing technology fits into most companies’ marketing stacks, and where do you think it fits into the landscape overall?

For most marketers, content marketing is a necessary part of what they’re doing. There is a question of degree. Generally speaking, B2C businesses still have need for content, but it tends to be a different quantity of content or a different depth of content, compared to B2B.

Content marketing really seems to be driving a tremendous amount of the buyer’s journey with B2B. Buyers are really hungry to get that depth of insight and information on how they do their early evaluation of solutions and who they want to do business with. I think it’s a pretty important part of the stack.

Do you think content marketing software will be swallowed up by big players, like Adobe, or will continue to grow as maybe its own niche sector within the martech landscape?

Well, one of the questions is how do you define content marketing software? There are literally hundreds of tools within that space, and they are not all competitive with each other. In a lot of cases, many of them are complementary. There might be a couple big pieces of software in there, but I find for a lot of content marketers, their toolbox includes at least a dozen web services or very small, fast things that they use for different tasks within developing content and getting it distributed.

I’m sure there will be some consolidation of tools, particularly the larger tools, into the major marketing clouds, but I think you’re still going to have a robust landscape of more niche providers that complement those for a very long time.

You run Chief Martec, which has been very successful. It’s a huge resource for a lot of people, yet at the same time, there’s a lot of talk about the death of blogging. So what’s the value of Chief Martec? Why do you still blog?

The number one reason I blog is because I find it helpful for myself. They say if you want to learn something really well, figure out how to teach it to someone else. By studying and trying to write, hopefully, some sort of coherent analysis of it, it helps clarify things for me that I find useful in my work. Even if no one was reading it, it would still have a lot of value.

It’s interesting coming from more of a publishing perspective. I feel like there are these legacy models in the industry where we think of publishers that publish largely news stories, or maybe they do (relatively light) features. They’re in the publish or perish business—cranking out as much of that as possible.

“Sadly, I think most martech vendors don’t really have an incentive to tackle that education.”

On the other end of the spectrum, you’ve got these analyst firms, the Gartners, the Forresters, folks like that, who publish much less frequently. Very often they have some sort of paywall, and it is a very expensive paywall. Like if you want to read this research report, please fork over $4,000.

I’d say that there’s actually an opportunity there. There’s a space between those two models that bloggers can jump in the middle of. You can have bloggers who are truly specialists in their fields.

Final questions: What do you think is the future of marketing technology? What do you think the marketer’s job is going to look like five to 10 years down the road?

At the rate at which things are changing, I think it’s hard for me to have clarity of what this is all going to look like in 10 years. But the thing that I find most exciting in the foreseeable future is—and I know this is an overused term, but it’s a powerful movement—this idea of digital business transformation.

Look at companies that are the digital natives—like Amazon, Netflix, and Uber—and the way they operate, the way they’ve grown, the way they manage relationships with their customers. As the world just becomes more and more digital, it is clear that almost every business is going to need to develop some sort of capability along those lines for the way they connect and build relationships with their customers.

I think that’s a tremendous opportunity for people who are in marketing and marketing technology to think beyond the campaign and to think much more holistically about what the future digital business relationship with our audience looks like. How do we create an incredible customer experience in that world? That’s going to be really exciting.

The post The Contently Interview: Scott Brinker on the Pitfalls and Promise of Martech appeared first on Contently.

“We want to sound like Vice.”

As a content strategist at Contently, I hear this type of editorial ambition all the time: Brand X wants to be like Vice, Vox, The New York Times. Brands now understand that the voice and tone of their publications will impact audience development. They know that an influx of branded content across the web means their voice and tone are often the most important competitive differentiators.

Yet one of the biggest challenges companies face is deciding what they want to sound like. How do they know if they should model their voice after Vox or The Economist? Are they more research-focused like The New York Times or listicle-based like BuzzFeed? Even if brands decide on a tone, their publications can still struggle to staff the right creative team to bring this decided voice to life.

To address some of these identity issues, we built a tone analyzer at Contently. Here’s how we began.

The tricky business of tone

If you’ve ever been in an argument, you know that tone can determine the meaning of a person’s words and impact your ability to find a resolution. Tone is what we use to interpret if “I’m fine” actually means someone is upset.

In a single piece of writing, tone can be described as the writer’s attitude or approach to the subject matter. It can express a particular mood, feeling, or character. For an entire publication, tone establishes the ethos of a company and the values of its authors.

Sometimes, it’s easiest to recognize characteristics of tone and style when they’re not quite right. Many brands come to Contently because their previous efforts to sound authoritative and professional come off as condescending or detached. Others want to develop a more approachable personality if they have a reputation for being unrelatable.

When deciding how to move forward with tone, our clients often reference a blue-chip publication they want to emulate, but whose editorial focus has little or nothing to do with what they offer. For instance, a company that sells insurance may want to sound like a notoriously colloquial political mag.

When that dissonance shows up, brand marketers need to be able to give guidance to their creative teams. Especially when working with freelancers who write for a variety of publications, it is crucial to prep creatives on the right tone for their audience. Articulating that they want to be more Vox, less Wall Street Journal is an important distinction—and one that writers will understand.

But the result of these high-level instructions too often leads to a road of strategic dead-ends. Lofty comparisons are full of paradoxical concepts that make it hard to publish. When a consumer packaged goods brand wants to sound like an episode of Last Week Tonight With John Oliver in its video product launch, or an insurance company wishes to capture the je ne sais quoi of Real Simple, what does this mean for the people creating and measuring the impact of this content?

Time and again, there is a disconnect between creatives who have the right tone but the wrong expertise. (John is a former Vox writer, but he knows nothing about the complexities of insurance.) The reverse can also be the case. (Joanna is an insurance expert, but she writes like a dry academic.)

Our goal on the strategy team is to marry tone and expertise so an insurance company, for example, doesn’t have to choose between risk assessment knowledge and punchy prose.

Enter the tone analyzer.

The tone analyzer test

The Five Factor Model, or the “Big Five,” is a personality classification system that bases its framework on major traits: openness, conscientiousness, extraversion, agreeableness, and emotional range (sometimes called “neuroticism”). The model emerged in 1961 and came from psychologists Ernest Tupes and Raymond Christal at the Air Force’s Research Division.

Building on the work of earlier psychologists who extracted nearly 18,000 words from the dictionary that related to human personality traits, Tupes and Christal reduced this list and lumped the remaining terms into five key groups based on recurring factors. Today, the Big Five remains a useful set of building blocks in understanding not only who we are but also how we communicate.

At Contently, we’ve taken the principles of the Five Factor Model to construct our own tone analyzer that will make pairing writers and brands more data driven. Because we’re analyzing content, rather than actual people, we’ve given each traditional trait a new, more editorially friendly name.

How does it work? The analyzer scrapes a website for as much text as possible, then assigns this aggregated content with a numeric “score” for each of the Big Five personality traits. The process is the same for analyzing a writer’s body of work. Scores range from zero to one.

By assessing the trait scores, we can detect the character of the publication or writer, and match the two accordingly.

The publication score

As a test, I ran Vice’s three most-shared pieces over the past year (this, this, and this, if you’re curious) to get a sense of the publication’s tone. Based on these articles, Vice scores 0.79 for expressiveness, 0.26 for formality, 0.28 for sociability, 0.15 for empathy, and 0.32 for emotion.

Using the Big Five personality key, here’s what we can deduce from these scores:

• Expressiveness 0.79: A high score for expressiveness suggests Vice’s writing is imaginative and that writers are willing—and allowed—to take risks.
• Formality 0.26: The low formality score lets us know the tone lacks authority. It is extremely laid-back and casual.
• Sociability 0.28: A lower score for sociability reveals Vice is restrained and confident in its approach, as opposed to being highly empathetic or open to new ideas.
• Empathy 0.15: Low empathy signals a significant amount of skepticism and comfort in embracing confrontation.
• Emotion 0.32: The low-to-middle emotion score points to a somewhat relaxed attitude. The site doesn’t rely too much on data.

The writer score

Once we go through this same process for creatives, we can pair writers to a brand publication based on that company’s desired tone. It’s worth noting that the point of the tone analyzer isn’t to just find writers with the same voice. If a brand wants to be more emotional, it might target authors with a higher emotional score than its own.

For the second part of the experiment, we scraped the portfolios of three of our TCS editors to find out who would be the best fit for Vice Magazine—or a brand that wants to mimic its tone.

Senior editor Jordan Teicher and associate editor Dillon Baker both ranked high in expressiveness, meaning, like Vice, their writing is imaginative, capable of explaining abstract concepts, and uses anecdotes to strengthen the narratives. But Jordan’s sociability and empathy marks were too high for Vice. [note]Fun fact: He’s written three stories for Vice[/note] Dillon’s formality, sociability, and emotion scores were significantly different from Vice’s as well.

Meanwhile, marketing editor Erin Nelson ranked low for empathy, meaning she is comfortable writing punchy prose that gets the audience to question the status quo, which lines up well with Vice’s approach. Her expressiveness and sociability splits were also close.

When we look at the differences, we see Erin most closely resembles the Vice voice across the five factors. (The closer to zero, the better the score.) If this were a real Contently staffing situation, and Erin had the most relevant industry experience for the brand, the tonal analyzer would suggest she’s the best person for the job.

Toning up

Ultimately, many factors play into the “talent matching” process at Contently. Finding the perfect team of writers for your content operation depends on the depth and relevance of their experience, location, availability, and more. But when a brand considers how it wants to sound, the tone analyzer can help quantify abstract goals and get team leaders to think about the type of writers who can create content that fulfills those goals.

So if an appliance company wants to sound as relatable as Vice Magazine, it’s our job to make sure the content creators can bring the right edge, even if they’re talking about blenders and washing machines.

The post This Tone Analyzer Could Help You Sound Like Your Favorite Publisher appeared first on Contently.

My customer account for Pizza Hut linked to Messenger in seconds and didn’t require any new payment information. One large pepperoni, please. Same as last time? Yes, please. But instead of dealing with a stranger or another checkout screen, I was typing to a chatbot instead. No small talk. No dropped calls. The bot offered me a few promo items, but otherwise, the whole exchange was quick, easy, and largely indistinguishable from a human interaction. Is this still my address? Yep. The receipt came via email.

The company credited with selling the first item on the internet is now making the e-commerce even easier. Pizza Hut recently announced its new chatbot ordering feature as part of a massive social media rollout that debuted a few months ago. Conversational commerce is hotter than a Samsung battery right now, and the largest pizza chain in the world knows it, following competitors and contemporaries alike into a space still very much evolving.

But what if businesses are approaching chatbots all wrong?

What is the secret sauce?

Magnus Jern, president of mobile solutions company DMI, recently told the BBC that when chatbots try too hard to be natural, it diverts from the purpose of conversational commerce. Jern helped launch IKEA’s Anna chatbot in 2005, which was recently retired after 10 years. “In the beginning, we tried to impersonate a person, and we found that there was no reason to do that,” he said.

But the move is a curious one, especially when chatbots are on the rise. Earlier this year, KPCB’s Mary Meeker referred to them as the “secret sauce” of messaging in her keynote on digital trends.

However, academic research has suggested that consumers don’t want robots that can talk like humans. Some would argue, instead, that all we want is a smoother ordering process. A Harvard Business Review report from 2010 found that “loyalty has a lot more to do with how well companies deliver on their basic, even plain-vanilla promises than on how dazzling the service experience might be.”

In his book, Influence, Dr. Robert Cialdini, a professor who teaches psychology and marketing at Arizona State University, concluded that we’re more motivated (to act, purchase, click, etc.) when choice is limited.

Also, there’s a difference between talking to a human and a bot that technology may never be able to reconcile. According to a study published by JAMA, conversational agents like Siri or Google Now simply don’t understand the difference between “I’m dying” and “I’m dying of hunger” in a crisis.

In other words, ordering a pizza via chat isn’t so unique anymore, but predicting how that conversation might look in the future is a bit more challenging.

The commerce of chatbots

The term “chatterbox” was coined in 1994, the same year Pizza Hut filled its first online order. Today, the company is the largest pizza chain in the world—with roughly half of its orders coming through digital channels and more than 60 percent of those via mobile devices, per internal data.

“We all have to become students of human behavior,” Baron Concors, Pizza Hut’s global chief digital officer, told a MobileBeat audience in June.

Conversable, the Austin-based company behind Pizza Hut’s chatbot technology, is turning the study of human behavior into a thriving business. The software company is partnering rapidly with major brands like TGI Fridays and Whole Foods, using conversational messaging for self-service and on-demand content.

For some companies, customer service is one long conversation. For others, the conversation ends with a pizza delivery.

The chatbot ecosystem is exploding. Facebook now supports over 11,000 chatbots, plus a dedicated store. Apple recently debuted its own iMessage app store with iOS 10. And messaging apps, well suited for brand chatbots, have never been more popular. WhatsApp, for example, now has over 1 billion users. WeChat and Viber have hundreds of millions.

In June, Tommy Hilfiger announced its own chatbot designed with the help of Facebook’s Creative Shop and bot creator Msg.ai. According to TechCrunch, the social giant caught flack for hosting too many clumsy bots from outside developers. The partnership with Tommy Hilfiger lets the company reclaim some control over its new chatbot platform, while heeding the call for online concierges among high-end fashion brands.

As Tommy Hilfiger himself told TechCrunch, “We are obviously distributed in our own stores and in department stores, but going directly to the consumer is really part of the motive and the future of the omni-channel process.” Gigi, named after supermodel Gigi Hadid, will answer customers in a more natural style since, as CMO Avery Baker argued, no one wants to feel like they’re talking to the corporate animal anyway.

Calls for conversation

For some companies, customer service is one long conversation. For others, the conversation ends with a pizza delivery.

“Even the most digitally tuned-in customer will want to know that they are connected with someone who can put themselves in their shoes,” said Simon Hunt, director of customer experience at Firstsource Solutions, a business-process outsourcing firm based out of India.

In August, the travel app Skyscanner estimated a layover of 413,768 hours to a shocked consumer looking for a cheap flight. When the man posted about the error on Facebook, a Skyscanner rep responded with a clever and lighthearted comment that eventually went viral and generated press coverage. To clarify, the technology screwed up, and then a human came in to clear things up.

“Bots are easy. Conversations are hard.”

Conversocial’s CMO Paul Johns told Digiday that such unscripted rapport is a growing trend. Proving a resolution is great, but opening up a meaningful dialogue may be even better. Per CeBit, 71 percent of people who receive a quick response from a brand on social media are likely to recommend that brand to others. It’s no surprise that chatbots are being considered to automate the job.

But despite these developments, there’s still a weird tension surrounding the conversational commerce movement. People want quick, straightforward service, but they also seem to value human empathy. Is it possible for a chatbot to provide both, even if consumers know they’re talking to an algorithm?

Conversations are hard

Ben Lamm, the CEO and co-founder of Conversable, probably said it best: “Bots are easy. Conversations are hard.”

In the race for creating tech with personality, businesses seem stuck on naming their bots after anything other than a tool. Anna. Gigi. Facebook even has a bartender bot named Shaky.

But chatbots don’t care what we call them, and, let’s face it, expressing our trust in AI impacts my comfort, not their effectiveness. That’s why we’re still anthropomorphizing machines.

“Giving something a human name is a way of exerting control over it,” writes Adrienne LaFrance in The Atlantic, “a reminder that it works for you, that it exists within a human construct, even when the machine itself is wholly indifferent.”

It’s hard to pinpoint how much conversation and functionality is necessary, but it’s safe to say that functionality is ultimately what will drive revenue.

Chris Messina, the developer who coined the term “conversational commerce” about two years ago (and also came up with the word “hashtag”), gave a talk at the MobileBeat conference where Pizza Hut made its bot announcement this summer. Messina showed the audience his own bot, an integrated messaging platform, and went over the evolution of the bot movement.

Toward the end of his presentation, Messina went over a few rules for both ethics. “A bot should be able to describe itself,” he said. “What it does, how it handles information, if there’s a human on the other end monitoring stuff. Bots should have a similar type of disclosure statement.”

That’s all well and good, but for the most part, the only rule I care about is if the bot can get my order right the next time I want a pizza.

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