Biznology

Videos for Indecisive Buyers

Bruce McKenzie — Wed, 16 Oct 2024 22:41:55 +0000

Do you know any conflicted laggards? Disinterested laggards? Reluctant followers? Sure you do, but that’s probably not what you call them.

Those are the psychographic profiles used by Gartner to describe technology buying teams who reach decisions very, very slowly, if at all.

This chart is taken from Gartner research on “The New Chasm,” an extension of Geoffrey Moore’s influential Crossing the Chasm (1991).

Of course, no technology seller knowingly wastes resources on organizations who will inevitably “decide not to decide.”

But the fact that a whopping 50% of the buyers in the market are unlikely to do anything until they are forced to doesn’t mean that sellers can afford to do nothing.

Gartner analyst Hank Barnes has written about Gartner’s research (here and here). In a recent post (source of the above chart), Barnes recommends giving consideration to the “mini-commitment” tactics suggested by sales guru Anthony Iannarino.

Commitment to Video

The idea of mini-commitments aligns well with the multi-threading tactics I wrote about last month. Multi-threading is, essentially, reaching out to as many buying team members as you can in order to contend with the large number of members on today’s buying teams (average:28).

Several of the mini-commitments Iannarino talks about sound like they are talking about video.

Commitment of Time. Buyers value videos because they see video as a time-efficient way to learn something. But they want to be sure their time won’t be wasted. That’s why you should to tell them in advance what’s covered in a video.
Commitment to Explore. Use-case videos, webinars and other non-sales-y videos fit in here. The more closely you can target different roles on the buying team, the better.
Commitment to Change. Obviously, video can argue the need for change quite dramatically. On the other hand, we often need to remind our clients that one of the best ways to keep a video short is to avoid telling people stuff they already know.

A Steady Stream of Videos

Reluctant or not, buying team members need to collect information, and they’ll be glad to get it in the form of videos. Implementing these strategies will be easier and more successful if you think about producing videos that your sales team will be eager to share, regardless of length. If it’s useful for decision-making, It doesn’t really matter if it’s a webinar, a tutorial, a traditional explainer, or just somebody answering an interesting question.

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Multi-threading and Video

Bruce McKenzie — Thu, 22 Aug 2024 20:48:53 +0000

Today’s enterprise technology buying teams have more players than the active roster of a major league baseball team (28 vs 26). (SMB buying teams have NHL-size rosters: 22). These numbers, from research by Foundry help explain why the concept multi-threading — getting results faster by spreading the work — has expanded from software engineering into sales and marketing. You can download the infographic here (registration required).

In sales, building relationships with more people on the buying team has been shown to produce more wins in less time. But implementing a multi-threading strategy does complicate the sales process. Among the complications, multi-threading requires targeted content to engage more people with different roles and interests from more angles and with different approaches and messaging. Since nearly all tech buyers watch videos about new solutions, this includes new types of video content. Here are three approaches to consider.

Line-of-business Videos

Let’s start with who’s on the buying team. Today’s teams, Foundry’s research says, are split almost evenly between IT roles (15) and business roles (13).

Most technology videos address business benefits at some point, but they are not primarily designed to engage line-of-business folks. So, when you’re making a video about how new features and upgrades benefit IT, you should routinely add on teasers or repackage excerpts, to catch the attention other line-of-business roles on the buying team such as application owners or logistics execs.

To plan new video content you can build on existing relationships: asking IT buying team members you know about the concerns of non-IT team members — and enlisting your subject matter experts for brief on-screen responses to these issues.

Use Case Videos

It’s well-known that IT decision-makers want to know about real-world use cases. Most tech company webinars and software platform demos contain brief sections demonstrating how some task can be accomplished better, faster, and cheaper. Such demos aren’t hard to expand into short use-case videos for buying team members who wouldn’t otherwise see the webinar they come from.

Third-party Endorsement Videos

Ninety-five percent of tech buyers say they watch videos for business purposes. Their top viewing choices are:

Industry research/tech analyst reports – 44%
In-depth product reviews – 43%
Interviews with industry experts – 38%

You can’t count on all 28 members of a buying team to watch all these videos of reports, reviews, and interviews. But you can reach more of them with short videos built around why outstanding features noted by analysts could make a big difference to certain buying team members.

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High-value Offers for High-value Prospects

Bruce McKenzie — Mon, 10 Jun 2024 18:58:26 +0000

The High-Value Offer is a customer interaction with so much business value that the buyer feels compelled to engage. It’s an account-based marketing concept recommended by Gartner for customer acquisition, too.

A high-value offer’s business value depends on

timely topics
meaningful discussion
a unique opportunity not readily available elsewhere — like the opportunity to explore solutions with your experts

One obvious difficulty here is that the high-value offer includes direct interaction with sales — something most buyers are working to avoid.

Also, coordinating your experts to focus on a prospect’s situation in an online meeting can be a challenge.

The role of video in crafting high-value offers

Here are some ways you can use video to add value to your high-value offer.

A short video invitation highlighting the kinds of things you will demo, graphics you’ll discuss, and the expertise available.
Marketing video and demo excerpts. I don’t recommend showing marketing videos in online meetings, but you should assemble brief excerpts from recorded demos, webinars, and tutorials that fit your offer. An animated GIF can deliver a lot of information without looking sales-y.
Pre-recorded video messages. Your experts talk about a prospect’s specific pain points or relevant use cases and provide tailored recommendations.
Video follow-up. Post the recorded version (or excerpts) on your website and share links to key takeaways.

Keep in mind that it’s a video meeting. Viewers become restless when there’s no movement on the screen. Use explanatory diagrams, charts, and punchy word slides to keep things moving.

The value of a video library

Traditional videos — explainers, webinars, even customer testimonials — aren’t suited to the problem-solving interactivity that defines high-value offers. But they can help deliver a solid explanation visually

Spend time examining your existing video library for material that can be repurposed to enliven online meetings. Look for

problems addressed in software demos
use-cases and other anecdotes
quotes from thought-leadership videos
process or conceptual animations in explainer videos (edited)

The more effort you put into making it clear that you really value the buyer’s time, the more they will value your offer as time well-spent.

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Team Flow Institute Releases Recommendations on How to Prepare for the Successful Integration of AI

Jen McClure — Tue, 07 May 2024 19:39:42 +0000

Earlier this year, the Team Flow Institute Fellows published our first paper, Envisioning the Future of Human Work in the Age of AI: The 2024 Forecast and Research Agenda. Our latest paper, How to Prepare for Successful Integration of AI to Achieve Business and Human Success, builds upon that work, offering practical guidance to organizations on how to prepare to successfully implement AI by rethinking the role of AI in the workplace using team flow principles.

While many organizations are focused on the potential productivity and efficiency gains and cost savings that using AI can provide, the Team Flow Institute Fellows recommend rethinking and reframing the role that AI can and should play in the workplace, focusing on:

How AI technologies can augment and elevate human work rather than just automate tasks
Empowering employees rather than replacing them and placing more value on human work
Measuring “progressivity” as opposed to productivity as a key success metric
Envisioning new opportunities and possibilities with the addition of AI technology, rather than just adopting a new technology and conducting business as usual

In addition to this rethinking and reframing of the role that AI can and should play in organizations and placing more value on the role that humans play, the Team Flow Institute Fellows recommend embracing the Team Flow model as the foundation for this preparation, fostering a culture of collaboration, communication, and innovation.

Team Flow Model

This approach establishes the foundation for an ethical governance framework for AI integration and development within organizations. The Fellows stress the importance of implementing AI within a larger digital and business transformation strategy, supported by governance, training, skill development, and enablement, investing in intensive change management and change communications, and an assessment of organizational design, structures, teams, roles and responsibilities, and capabilities. In addition to these recommendations, the Team Flow Institute Fellows have developed a set of 20 questions that organizations should ask as they implement AI.

We hope that thinking about this approach, asking these questions, and considering these actions will enable organizations to be successful as they seek to position themselves at the forefront of AI adoption to achieve business and human success.

You can read the rest of our paper here >

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The Case for Video Use Cases

Bruce McKenzie — Tue, 07 May 2024 15:53:21 +0000

Product demonstrations and tutorials. Tech tips and how-to’s. Case studies. These categories — let’s call them “use cases” — invariably show up near the top in surveys of content preferences of IT decision-makers. Use cases help buyers develop budgets and justify spending, especially for larger investments. Relevant use cases that map to an organization’s priorities can help make a stronger business case for the spend. Use cases also aid in gathering requirements. By examining use cases, IT teams can better understand the capabilities that are needed to address their specific use cases and evaluate how a given solution meets their needs. Since 95% of B2B buyers say videos play a crucial role in their purchase decisions, according to Spiceworks, it’s easy to make a case for video use-cases.

Key Subject Areas

The phrase “use-case” implies a story where the hero overcomes a difficulty. You’ll want to highlight key areas that will resonate, such as improved security, better system performance and uptime, easier administration and maintenance, and positive impacts on end-user productivity and experience.

Credibility

The ideal use-case video features a real customer happily solving a real problem that viewers are struggling with. Realistically, customers don’t have the time or the motivation to share details on how they solve their problems. On camera.

However, you can dramatize trusted user reviews and published customer case studies to good effect. Your sales engineers and other subject matter experts know what types of problem-solution stories will resonate.

Repurposing Existing Assets

There may be lively use-cases hidden away in your recorded demos. They will need a little sprucing up for wider distribution, but probably not too much.

Length

Use-case videos should be concise, while still allowing time for a coherent storytelling arc with a beginning, middle and end. There should be enough arresting details along the way so that viewer doesn’t feel “marketed to.” Two to three minutes is a good length.

Attracting Viewers

Once created, make your use-case videos easily discoverable by IT audiences at multiple touchpoints — your website, social channels, email campaigns, virtual events, and more.

You may want to create a “trailer” from the finished video to attract viewers and spread the message.

IT decision makers today are highly video-oriented. By prioritizing interesting, credible, and educational use-cases, you increase the probability that the video — and the confidence it engenders — will be shared among buying team members.

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The AI Adoption Ship Has Already Sailed

Steve King — Thu, 28 Mar 2024 20:16:31 +0000

As many organizations are still trying to figure out the strategy and rules of the road to introduce generative AI into their processes and workflows, the AI adoption ship has already sailed.

According to the Pew Research Center’s recent study on the adoption of ChatGPT, the adoption of Gen AI at work is rising very quickly, especially among younger workers. Overall, about 20% of workers report using ChatGPT at work, with 31% of younger workers reporting using it.

While estimates of the share of workers who could use Gen AI in their work, i.e., workers who use a computer at work, have Internet access, have a work reason to use it, etc. are still being debated, current estimates range from 60% to 80%.

That means that already between 25% to 33% of workers who could use Gen AI at work say they’re already using it—and the share of users is rapidly increasing. Yes, these numbers probably overstate actual usage due to the false positive effect caused by asking people in surveys about trendy technology. But even if you reduce the usage by 25%, Gen AI is gaining use by workers at a pace dramatically faster than any technology we’ve ever studied — and we’ve looked at technology diffusion for decades.

So, now those executives overseeing corporate AI adoption strategies and policies need to try to catch up with the actual adoption and usage of Gen AI by workers.

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The Looming AI Bias in Hiring and Staffing Decision-making

David Strom — Tue, 19 Mar 2024 17:48:26 +0000

Remember when people worked at jobs for most of their lives? It was general practice back in the 1950s and 1960s. My dad worked for the same employer for 30 or so years. I recall his concern when I changed jobs after two years out of grad school, warning me that it wouldn’t bode well for my future prospects.

So here I am, ironically now 30-plus years into working for my own business. But this high-frequency job hopping has also accelerated the number of resumes that flood a hiring manager, which in turn has motivated many vendors to jump on board various automated tools to screen them. You might not have heard of companies in this space such as HireVue, APTMetrics, Curious Thing, Gloat, Visier, Eightfold and Pymetrics.

Add two things to this trend. First is the rise in quiet quitting, or employees who just put in the minimum to their jobs. The concept is old, but the increase is significant. Second and the bigger problem is another irony: now we have a very active HR market segment that is fueled by AI-based algorithms. The combination is both frustrating and toxic, as I learned from reading a new book entitled The Algorithm, How AI Decides Who Gets Hired, Monitored, Promoted, and Fired and Why We Need to Fight Back Now. It should be on your reading list. It is by Hilke Schellmann, a journalism professor at NYU, and it examines the trouble with using AI to make hiring and other staffing decisions. Schellmann takes a deep dive into understanding the four core technologies that are now being deployed by HR departments around the world to screen and recommend potential new job candidates, along with other AI-based tools that come into play to evaluate employees performance and try to inform other judgments as to raises, promotions, or firing. It is a fascinating look at this industry, fascinating and scary too.

Thanks to digital tools such as LinkedIn, Glassdoor and the like, sending in your resume to apply for an opening has never been easier. Just a few clicks and your resume is sent electronically to a hiring manager. Or so you thought. Nowadays, AI is used to automate the process: These are automated resume screeners, automated social media content analyzers, gamified qualification assessments, and one-way video recordings that are analyzed by facial and tone-of-voice AIs. All of them have issues, aren’t completely understood by both employers and prospects alike, have spurious assumptions and can’t always quantify the important aspects of a potential recruit that would ensure success at a future job.

What drew me into this book was that Schellmann does plenty of hands-on testing of the various AI services, using herself as a potential job seeker or staffer. For example, in one video interview, she replies to her set questions in German rather than English, and receives a high score from the AI.

She covers all sorts of tools, not just ones used to evaluate new hires, but others that fit into the entire HR lifecycle. And the “human” part of HR is becoming less evident as the bots take over. By take over, I don’t mean the Skynet path, but relying on automated solutions does present problems.

She raises this question: “Why are we automating a badly functioning system? In human hiring, almost 50 percent of new employees fail within the first year and a half. If humans have not figured out how to make good hires, why do we think automating this process will magically fix it?” She adds, “An AI skills-matching tool that is based on analyzing résumés won’t understand whether someone is really good at their job.” What about tools that flag teams that have had high turnover? It could be two polar opposite causes: a toxic manager or a tremendous manager that is good at developing talent and encouraging them to leave for greener pastures.

Having my own freelance writing and speaking business for more than 35 years, I have a somewhat different view of the hiring decision than many people. You could say that I either had infrequent times that I was hired for full-time employment, or that I face that decision multiple times a year whenever I get an inquiry from a new client, or a previous client that is now working for a new company. Some editors I have worked for decades as they have moved from pub to pub, for example. They hire me because they are familiar with my work and value my perspective and analysis that I bring to the party. No AI is going to figure that out anytime soon.

One of the tools that I have come across in the before-AI times is the DISC assessment that is part of the Myers-Briggs, which is a psychological tool that has been around for decades. I wrote about my test when I was attending a conference at Ford Motor Co. back in 2013. They were demonstrating how they use this tool to figure out the type of person who is most likely to buy any particular car model. Back in 2000, I wrote a somewhat tongue-in-cheek piece about how you can use Myer-Briggs to match up our personality with that of our computing infrastructure.

But deciding if someone is an introvert or an extrovert is a well-trod path, with plenty of testing experience over the decades. These AI-powered tools don’t have much of this history, are based on data sets that are shaky with all sorts of assumptions. For example HireVue’s facial analysis algorithm is trained on video interviews with people already employed by the company. That sounds like a good first step, but having done one of those one-sided video interviews — basically where you are just talking to the camera and not interacting with an actual human asking the question — means you aren’t getting any feedback from your interviewer, either with subtle facial or audio clues that are part of normal human discourse. Eventually, in 2021, the company stopped using both tone-of-voice and facial-based algorithms entirely, claiming that natural language processing had surpassed both of them.

Another example is capturing when you use your first person pronouns during the interview — I vs. we for example. Is this a proxy for what kind of team player you might be? HireVue says they base their analysis on thousands of questions such as this, which doesn’t make me feel any better about their algorithms. Just because a model has multiple parameters doesn’t necessarily make it better or more useful.

Then there is the whole dust-up on overcoming built-in AI bias, something that has been written about over the years going back to when Amazon first unleashed their AI hiring tool and found it selected white men more often. I am not going there in this post, but her treatment runs deep and shows the limitations of using AI, no matter how many variables they try to correlate with their models. What is important, something Mark Cuban touches on frequently with his posts, is that diverse groups of people produce better business results. And that diversity can be defined in various ways, not just race and gender, but by people with disabilities both mental and physical. The AI modelers have to figure out — as all modelers do — what is the connection between playing a game, or making a video recording, and how that relates to job performance? You need large and diverse training samples to pull this off, and even then you have to be careful about your own biases in constructing the models. She quotes one source who says, “Technology, in many cases, has enabled the removal of direct accountability, putting distance between human decision-makers and the outcomes of these hiring processes and other HR processes.”

Another dimension of the AI personnel assessment problem is the tremendous lack of transparency. Potential prospects don’t know what the AI-fueled tests entail, don’t know how they were scored or whether they were rejected from a job because of a faulty algorithm or bad training data or some other computational oddity.

When you step back and consider the sheer quantity of data that can be collected by an employer: keystrokes on your desktop, website cookies that record the timestamp of your visits, emails, Slack and Teams message traffic, even Fitbit tracking stats — it is very depressing. Do these captured signals reveal anything about your working habits, job performance, or anything really? HR folks are relying more and more on AI-assistance, and now can monitor just about every digital move that an employee makes in the workplace, even when that workplace is the dining room table and the computer is shared by the employee’s family. (There are several chapters on this subject in her book.)

This book will make you think about the intersection of AI and HR, and while there is a great deal of innovation happening, there is still much work to be done. As she says, context often gets lost. Her book will provide plenty of context for you to think about.

This article was originally published here.

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Preparing for Your Next Job in the Age of AI

Bruce McKenzie — Mon, 18 Mar 2024 23:10:48 +0000

The hottest job in corporate America is “Executive in Charge of AI” according to a recent New York Times headline. That probably sounds right on the money to most readers of these pages. If you happen to be up for an executive position in AI in sales and marketing, the conversation is sure to turn to video. Here are some questions and answers) that might help you prep for that next big interview.

How is AI currently best used in creating marketing videos?

AI is most helpful with speech-to-text, language translation, automated subtitling, and basic editing tasks.

Can AI help generate video ideas and scripts?

Yes and no. AI tools can analyze content performance data and suggest new video topics that align with customer interests. But it doesn’t have a good grasp of how to communicate visually with your customers.

Is AI advanced enough to produce marketing videos?

No. But it can make production more efficient.

Can AI be used for targeted personalized video?

AI is better at identifying and segmenting targets than it is at figuring out what to show or say.

Will AI ever automate the video production process?

No, but would you want to live in a world like that? AI is getting better every day at automating editing tasks. In the right hands, AI cuts costs, improves quality, and speeds production.

Can AI help manage video content libraries?

Absolutely. AI is better at tagging, managing, and searching big archives than humans are. This capability is already widely used in academia and corporate training. You might find lots of content than can be repurposed and shared more widely.

Can AI predict which videos drive the most conversions over time?

Probably, assuming sufficiently large data sets of historical performance.

Will AI potentially displace human jobs in video production?

Maybe a few in low-complexity production tasks. But creative people will almost always be able to do more creative things better.

What regulatory concerns are there with synthetic video?

For starters, protection for original content, watermarking assets, auditing of synthetic media origins. Regulated or not, there are all sorts of privacy, bias, and fairness issues, too.

Which expert perspectives should guide our AI video strategy?

A thorough-going strategy should comprise insights from legal, compliance, creative leadership, technical architects, and customer advocacy, as well as your video experts.

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Team Flow Institute Research Fellows and 2024 Research Agenda

Jen McClure — Tue, 20 Feb 2024 16:51:34 +0000

I was honored recently to be invited to join the newly formed Team Flow Institute, as an advisor and senior fellow to lead the institute’s research fellowship program, along with co-founder and Managing Director, Chris Heuer. We’re now extremely pleased to announce our Founding Research Fellows. This impressive group comprises respected business leaders, scholars, futurists, and technologists. They bring a broad range of valuable expertise to the Institute’s work, and we look forward to working with them on their research initiatives to produce the latest insights in the evolving world of work in the age of AI.

The Team Flow Institute Founding Fellows include:

Zora Artis, GAICD SCMP CPM leading Alignment, Brand, and Communication Strategist, Advisor, Facilitator, CEO of Artis Advisory and Co-Founder of The Alignment People
Alan Berkson, Corporate strategist, advisor, and storyteller
Gina Debogovich, Digital leader, innovator, and implementer
Rachel Happe, Organizational and Business Strategist, Product Executive, Systems Designer, and Community / Culture Change Leader; Founder of Engaged Organizations
Shel Holtz, SCMP, Renowned author, podcaster, corporate communications expert, and Senior Director of Communications for Webcor
Steve King, Partner, Emergent Research, focused on the intersection of the future of work. small businesses and the gig economy
Sharon McIntosh, Certified Professional Coach (CPC), President of And Then Communications & Coaching and Advisor to Executive Communication Council
Jef van den Hout, world’s leading authority on team flow, Founder of Flow Concepts® Group, Author, Positive Organizational Psychologist, Associate Researcher and University Lecturer at Eindhoven University of Technology

You can read more about our fellows and research fellowship program here.

Together, we will collaborate on research initiatives, educational offerings, and the establishment of best practices focused on shaping the future of human work with team flow as the foundation, as disruptive technologies such as artificial intelligence are transforming how people live and work. We will publish in-depth quarterly papers, as well as articles and online educational offerings and briefings, and will conduct quantitative and qualitative research studies. During 2024, we will focus on a number of hot topics, including:

Tips for successfully introducing AI into organizations
Achieving and sustaining high performance via team flow for decentralized teams
What separates the best teams from the rest
Creating alignment and cohesion in blended teams
Activating collective ambition to transform poorly performing teams
Emerging practices that leverage AI and team flow principles to improve collaboration, communication and community

Our first report, entitled Envisioning the Future of Human Work in the Age of AI, sets the foundation for our work for 2024 and beyond. It provides key insights and practical advice to business leaders on how to successfully integrate AI into their collaborative practices and organizational design to augment human labor and unlock the full potential of their teams.

If you are conducting research in this area, or would like more information on the Team Flow Institute Fellowship program and research initiatives, or to sponsor a study, please contact us here.

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Envisioning the Future of Human Work in the Age of AI: The Team Flow Institute 2024 Forecast

Jen McClure — Tue, 20 Feb 2024 16:16:19 +0000

As technological change and the adoption of new technologies like artificial intelligence (AI) accelerate, the future of human work will be characterized by disruption, uncertainty, and opportunity. As 2024 approached, the Team Flow Institute Research Fellows gathered for a roundtable to discuss their visions for the future of human-focused work in the age of AI.

As described by the institute’s co-founder and Managing Director, Chris Heuer, “The Team Flow Institute is an organization dedicated to shaping a human-centric future of work as we face the choice of augmentation or automation in every industry and every function. This transformational decision will reshape what we call work and society itself, requiring us to abandon business as usual and finally design business as possible.”

The Team Flow Institute Research Fellows’ roundtable discussion delved into the potential opportunities and challenges of this technology revolution driven by the institute’s “mission to gather like-minded individuals and organizations to steer our collective destiny toward a more sustainable future, where the essence of humanity and human work is valued and preserved as we increasingly adopt AI tools and technologies, explained Jennifer McClure, Senior Research Fellow, and Advisory Board member.

From exploring the promise and recent progress of AI in the workplace as well as the potential risks and downsides to preparing for the future of work and advocating for team flow as the key to human-AI synergy, this article analyzes key insights from the discussion, offering a glimpse into the evolving workplace landscape of 2024 and beyond.

As the Team Flow Institute embarks on its inaugural fellowship program, this analysis holds particular significance as it seeks to equip individuals with the knowledge and skills necessary to thrive in the evolving landscape of AI-enabled work. Through this program, the Team Flow Institute aims to foster a community of leaders who can guide organizations and individuals toward a future where humans and technology collaborate to create a more sustainable and fulfilling work environment.

Read the full paper here >

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