10 Useful Things I Learned in 5 Years at Sprinklr

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Techmeme, November, 2016

I’m excited to say that after 5+ years working at Sprinklr, the market leader for customer experience management and social media marketing for the world’s biggest organizations, I have resigned from my job and I’m soon on to my next adventure!

I thought I’d take this time to share some of the things I learned from my experience there.  I hope that some of the lessons I learned and some of the experiments I succeeded with will be useful for you, my friends, to help advance the practice of continuous, life-long, social-web-enabled, professional development and to support your success in work.  Let’s share and make the network smarter!

My time at Sprinklr consisted of helping the company grow from $100M in annual revenue to nearly $500M, from 1K employees to 3K, and through an IPO. That was amazing. I held VP level responsibilities for analyst relations, influencer relations, competitive intelligence, data journalism, social publishing, the customer community, live chat customer care (all at once), and some really cool custom market research projects to advise some of the biggest companies in the world.  (Don’t take on too many responsibilities at once, that’s one thing I learned.)  And of course I spent some time working on the influencer marketing product, but not that much. It’s been rebuilt inside of Sprinklr and I used it myself right up to my last day on the job.  Thanks to the Sprinklr product team for that. (I’ll be ok without it; my therapist used to ask all the time, and I’ll be fine.)

In a few weeks, I’ll write about what I’m doing next. I have an awesome new volunteer side-project that’s very important to me and a new job I’ll be beginning soon, which is so amazingly well-suited for my long running interests that I am beside myself with excitement about the opportunity.

But first, want to hear about my experience for the last 5+ years at Sprinklr?  Quick context: You may or may not know that I started my career as a journalist, the first writer hired at TechCrunch back in 2006, then co-editor of NYT-syndicated ReadWriteWeb for much longer, then after six years as a journalist, a team and I productized my data journalism and influencer marketing practices in the form of a startup called Little Bird.   We sold it to Sprinklr in 2016. I’ve met so many inspiring people online and offline along the way, thank you. I’ve been a lot more heads-down over the past 5 years than I was the prior 10+ so I appreciate you still caring enough to read this.

Here are ten things I learned while at Sprinklr that I hope you’ll find useful.

Analyst Relations

While this was my responsibility, we won 6 straight Forrester & Gartner reports as a leader or the only leader in various markets, from content marketing to sales social engagement to the entire social suite category. (If you’re unfamiliar with those firms, they do a combined $5B in annual revenue from companies subscribing to their research and advice.) AR was always a team effort, of course, with as many as 20 or more teammates working for 3 to 6 months preparing to compete in each report. (Wow!) And working with an experienced AR leader like Drew Tambling on the team was one of the biggest keys to our success.

Analysts may be less accessible to many readers here than some of the other learnings I’ll share below, but I have set up a public Google Custom Search Engine anyone can use to search across the free published work of the 7 leading tech analyst firms. Don’t start a new strategic initiative without scanning the prior art analyzed there.  I use it almost daily.

Key learnings:

  • Analysts have tons of great advice to share. There’s so much I want to remember that I learned from Forrester and Gartner over the last few years.  A few things that stick out:
    • (1) I loved Rick Parrish’s model of how to do something (anything) with discipline: he says you do it with
      • Rigor (following a documented practice),
      • Cadence (regularly scheduled activities),
      • Co-ordination (among people and other practices),
      • and Accountability (making sure there’s a senior person accountable for the work.)  You put those four qualities together and you’re doing work with discipline.How delightfully well-abstracted that is. What a great model!
    • (2) I loved Forrester’s advice that every change initiative can increase its odds of success if you understand that the first cohort of participants will include just a subset that are willing and able to put in the time to find success in the initiative; and then those people will be your case studies you use to market to the next cohort.  Forrester says successful change management initiatives often take five years to change a company’s culture and they’ve got tons of great tools for doing that work.
    • (3) And perhaps most of all, I loved Kristina LaRocca-Cerrone of Gartner’s model for democratizing data synthesis skills in organizations:
      • (a) make the implicit knowledge of your most-skilled people explicit, in well-documented toolsets
      • (b) tell stories of the most successful data synthesis practitioners scoring wins in their work, and
      • (c) map out the network of good synthesizers and their favorite sources of data, so that anyone can tap into those sources and the network.
  • (4) The biggest value the analyst firms offer is not in their market leadership reports, but in their advisory services.  If your company has a subscription with one of these firms, you can schedule advisory and document reviews with them any time. The analysts are measured by how many advisory calls their customers sign up for, so they love it. And their knowledge of the industry, of best practices, of what b.s. smells like, and of customer needs is a great contribution to any strategy. The biggest, smartest companies in the world do inquiries with analyst firms all the time. When I was running AR at Sprinklr, we did more than 100 inquiry calls a year: we told everyone we could that this was an option – then we retold every happy story that resulted, to build interest in the next month’s calls. I’m really proud of that.

I will be forever grateful for the things I learned from Forrester and Gartner regarding maturity models, future-ready work skills, and so much more. What an amazing gift it was to get to lead the analyst relations team. Initially I said I didn’t want to do it; I’m glad I changed my mind.

Competitive Intelligence

Sprinklr’s competitive intelligence function, which I had the honor to be a leader in as well, was an incredible inspiration. Davin Galbraith, Elizabeth Closmore, and Asha Aravindakshan were other key leaders in that work. The breadth of their knowledge and the closeness of their collaboration with sales and product teams enabled us to win tens of millions of dollars every year in deals where competitive insights helped unseat incumbent software providers.  It was awesome.

My contributions to CI varied widely, but I’ll share two fun, simple little experiments I did that worked and I recommend to anyone else willing to do the work.

  • (5) Watch YouTube subscription playlists of your competitive set; they are a simple but powerful way to learn about features and market positioning relatively early. I subscribed to 10 or 15 competitors, and I booked an hour each Friday to watch any videos they’d uploaded that week. Sometimes I was the first person to watch some of them, and I was then (as was my job) one of the most knowledgable people at the company regarding what our competitors were up to. I suspect in B2B this is an underutilized avenue for market intelligence.
  • (6) Internet Archive comparisons of competitive product pages offered my team and I a great view into what new tactics a competitor was trying with a product now (things they hadn’t been doing 3 months ago), or what they tried a year ago that didn’t seem to work (so they removed it from their website.) Looking at the changes over time put me in a really good position to offer strategic advice on our own initiatives based on those market signals. (“Yeah, competitor X tried an idea a lot like that 2 years ago, but it didn’t seem to work for them so they took it off their website.”) I loved being able to see things like that.

Data analysis

I managed Sprinklr’s data analysis team for some time, which helps produce amazing industry reports for partners like Twitter, LinkedIn, Forbes, and more.

Two cool things I learned about data analysis that you might find useful:

  • (7) Counting things is cool, but counting their percent change period-over-period is even cooler. I loved being able to say, for example, “when people on Reddit talk about your company, these are the 10 things say about you most often. You may not be surprised by the top 3, but let me flip this chart around and sort by which of these is rising the most month-over-month.  Turns out the 7th most-popular topic is rising very fast. That’s something you want to take a look at.“
  • (8) Segmentation is magic.  My friend Justin Garrity used to say “at Sprinklr, we can tell you not only whether fans of the TV show The Walking Dead prefer eating popcorn or ice cream while they watch the show, but even more specifically, whether the ones who like ice cream like chocolate, vanilla, or Neapolitan ice cream the best!”  That’s cool, but the general principle is cooler: multi-layered boolean search queries are a non-intuitive and powerful way to learn about the dynamic constituent parts of any data set.

My favorite dashboards to build were ones that said “here are the top 10 things people talk about online when they talk about your brand, ranked first in sum total and second in percent change month over month.  Then for the top 3 topics, here are the top 10 sub-topics (eg when people talk about your toy brand, they talk about “learning” a lot, and when they do, that’s made up of conversation about mentorship, school, emotional intelligence, and more, in this ranked order), and here are some samples of the most-engaged content about learning and your brand over the last 90 days.” You can pull in a ton of useful intelligence that way and I loved when I could spend an afternoon using Sprinklr to do that.

But the general principle is universally available: multi-layered boolean search queries are a non-intuitive and powerful way to learn about the dynamic constituent parts of any data set.

For example, and this is just an example of the coolness of slicing data into parts to tell a story: did you know that despite its history-making industry leadership (it’s the fastest-growing social network in history), the tech press has only written about TikTok 1.2% as much as it has the rest of the FAANG companies? And when the tech press does write about TikTok, 68% of the time they’re writing about it in the context of privacy, China, kids, or Trump.  Much more often China (40% of coverage) or Trump (28%), less often privacy (23%) or children (21%).  That’s just a bunch of boolean search queries with AND and OR in them, searching inside a bounded set of data (the Techmeme archives).   But it’s cool. Make a few bar charts out of it and spend the ten minutes it took me to do those queries, write down those numbers, and do a little division…and you’ve got some interesting data to share.  The hard part is thinking to do it in the first place.

Influencer marketing

  • (9) Big companies will finally listen to and learn from influencers. I am happy to say that a decade after I got into the influencer relations game, at least some companies are now willing to relate to industry influencers as more than just a marketing channel or PR crisis protection. That’s the base level of the maturity curve, that way of looking at it.  Social media influencers are market intelligence gold mines!

For example, I was really proud when one of the biggest, most famous tech companies in history turned, at the onset of COVID, to our technology to find the most credible influencers across many different topics and bring them into an internal conversation about how that company should strategize around pandemic disruption.  That’s the way to do it!  The people we call “influencers” are often people at the center of highly connected networks, with incredible visibility into what the market is doing and lots of lessons learned on their way to the top. Treating them like nothing more than a distribution channel is absurd, and thankfully no longer universal.

At Sprinklr, we’d do things like hire an influencer to do a three part project with us: a webinar on a well-distributed channel like AdWeek, an e-book of our shared thoughts on the topic of the webinar, and an internal advisory video call where anyone on our team could join in and privately ask this external influential thought leader their questions about the market.  It was awesome!  It was also a fun way to share access with junior team members to the industry leaders whose work they read and admire.

Not everyone looks at it this way, but I was proud to be named one of the world’s top 20 B2B influencer marketing pros in 2020 while flying this flag.

A great boss makes all the difference

The tenth lesson I learned from my time at Sprinklr is that it’s amazing to work for a great boss. Sprinklr’s Chief Experience Grad Conn taught me so much, and brought so much kindness to the hard drive through an IPO.

Grad prompted me to start the Sprinklr Coffee Club video podcast, which we did almost 100 episodes of, with truly amazing guests, from Rachel Happe on community to John Hagel on innovation and many more. Someday I want to just make a list of notes from the wise things the guests on that show said. There’s so much there!

I took tons of notes from things Grad said over the years, like:

  • “every B2B sale is someone buying a chance of career success.”
  • “People lean back when they see powerpoint, lean forward when they see white boards.”
  • “You can improve the inputs of a measurement all the time, but you don’t change the outputs – you keep them consistent.”
  • P&G’s three parts of a good recommendation: Why it’s strategically justified, why it’s proven, why it’s cost effective.
  • Any data you show must have a recommendation to go with it.
  • “Don’t trash the past, there was nothing wrong with the past, we’re just adding more stuff.”

That last one’s one of my favorites. And there was so much more.

All in all, when I look back at my time at Sprinklr, I like to use my favorite model for a debrief:

  • What did you hope would happen?
  • What actually happened?
  • What does that gap suggest you should:
    • Do differently next time?
    • Keep on doing in the future?

And when I look back over the last five years at Sprinklr, I am satisfied.

Forward we go, together, internet friends.  I’ll let you know what I’m up to next in a few weeks.  I’m really excited about it.  Let’s connect as nodes on the networks of Twitter or LinkedIn if you want to stay in communication.  Thanks for your interest and support. Let’s do this internet thing together, for ourselves, each other, and where possible, for the rest of the planet.

New project: Exponential View climate future

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I’ve started contributing to a new collaboration that I couldn’t be more excited about. Azeem Ahzar and Marija Gavrilov have asked me to curate and summarize each week’s stories of climate change mitigation success and momentum for the amazing email newsletter Exponential View. It’s an amazing opportunity to work with information (as I like to do), in support of the sacred earth, in such a setting. If you’re unfamiliar with EV, and you can handle some heady big picture information about the fast-changing world, you should really check it out. The newsletter, podcast, and surrounding community includes some of the most impactful and interesting people in the world at the intersection of technology and society. Climate change has long been a focus there and it’s an honor to be curating that section of the newsletter as it shifts into a focus on opportunity, good news, and momentum. My discovery of the content featured there is made possible by research systems built with friends in volunteer efforts focused on climate issues. I’ll share more information about those in a later post. But I will tell you, they include all my favorites: Twitter lists, Custom Search Engines, and collections of RSS feeds! And more. I’m excited to use those tools in service of highlighting where we can find inspiration and put our collective energy toward the massively important challenge of climate change mitigation. I hope you’ll join the conversation about that and so much more over at Exponential View. And feel free to send me news about good climate work you are doing or leaning about. As John Hagel says of building communities, one great strategy is to seed, feed, and weed: let’s plant the seeds of what we want to see, feed what we want to see more of so that it can grow, and weed the things we want to get rid of. Not hard to see how that model applies to climate change mitigation!

My 5-minute productivity method

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I am always struggling with the relationship between aspirations and capacity, something I’ve really only grown aware of in recent years.  In part by blowing far beyond even my substantial capacity for too long with some family crises, and in part by reading the really smart book On Grand Strategy, which is largely focused on the singular point that aspirations must not exceed capacity.

One of the ways I try to get more done inside the time, space, and energy I do have is to try to spend 5 minutes doing a lot of things.  Can I do that thing in five minutes?  Could a five minute version of that thing be good enough?  Very often the answer is yes.

I also turn it around and imagine my future self saying to my present self, “you couldn’t even spend 5 minutes on that??”  I don’t want that to happen.

One of the most productive things I do almost every day is sit and think through a single topic for five minutes, usually with pen and paper.  I will also read a book for 5 minutes if that’s all I can do.

You know the GTD advice that if something can be done in 2 minutes, then you should do it right away? I think this is a related concept.

And that’s five minutes of blogging on that.

David Gurteen talks about truncated “Knowledge Cafes” with five minute talks.  That reminds me that I learned how much could be done in five minutes when I was in high school and won many speech and debate tournaments in Impromptu Speaking.  In that event, you’d be given three philosophical quotes, pick one, take 30 seconds to prep, and then give a 5 minute speech about it.  I would apply the perspectives of 3 different interesting thinkers or other people in history to the quote I’d picked, analyzing it from 3 different perspectives.  That was probably where I learned too about Symphonic Thinking, Daniel Pink’s term for the ability to generate connections between seemingly disconnected things.

And that’s five more minutes.  Cheating? Maybe.  Now if you’ll excuse me, I’m off to spend 5 minutes thinking through an important life matter.

7 steps I take to get value from what I read: Notes on note taking & review

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A friend asked me recently what some of the core principles are in my note taking and review system. I get a whole lot of value out of my note system and I love talking to notes nerds.  But not notes for notes’ sake! For making an impact on the world, for the better.

When I read Dan Pink’s book A Whole New Mind and learned about what he calls Symphonic Thinking, or the ability to find connections between seemingly disparate entities, as a key thinking pattern for the future of work, I thought “wow, that’s what I’ve been doing already! I’m going to do it more deliberately!”  And so I regularly cite research, reading, things I’ve heard on podcasts and more in my day job and my work outside of work.  It’s one of my superpowers, but I really believe it’s something far more people could help the world with. I recently changed my Twitter bio to read: “Sharing thoughts for growth-oriented people about how information can be synthesized to build power to make the world a better place.”

My notes come from a wide variety of sources, but most commonly from things I’ve stopped and typed up into Roam Research after I’ve heard them read aloud to me either by Pocket, which I feed with links from Twitter using an IFTT applet that sends the links in any tweets I favorite to pocket, as well as a few key RSS feeds. I also read a lot of PDFs by text to speech using hte Voice Aloud PDF to speech iOS app on my phone. I “read” with my ears and clean my kitchen a lot, or jog. I’ve also been experimenting lately with spending 5 minutes scanning through Feedly RSS reader to find things to toss into Pocket and listen to read aloud.

So I read a lot (I also miss a lot, it’s ok) and then I stop when I hear something really good and I write it down in Roam. (Or if I’m jogging, I associate each thing I want to remember with one of my limbs, then I go through them one at a time “left arm, left leg…” when I’m done running and I write them down.)

These are some of the things that came to mind when my friend asked about my note taking and review system.

  • Make it easy to take notes when you can. The Roam unofficial mobile interface has been essential for me.
  • Failure to cite your sources can be a real pain – finding an easy and repeatable way to cite where a note came from can make a big difference. I have notes from years ago where the insight is good but I didn’t record the source and it’s a real bummer.
  • Make it easy to review your notes, Anki flashcards are super helpful. Anki tells me I’ve been adding the equivalent of one card per day to my “lessons being learned” deck since late 2015.
  • Make it easy to recall half-remembered flashcards, Roam’s search or my personal wiki control-F have been really helpful. I search in Anki sometimes too.  I regularly have a hazy memory of something but search can bring it up in the background while I’m on a call for work.
  • Review as much as you can, as often as you can. It’s just like an athlete practicing. I try to spend 10 or 15 minutes on my flashcards each day. I wish I spent more time, I’d love to double that. Or more.  That’s something I’m actively working on right now.  You can see my scorecard there on the right. Lots of room for improvement, but that’s better than a poke in the eye. If I could consistently review 20 flashcards a day and really integrate the acquired wisdom with my life…that would be amazing.
  • As I review the flashcards, I try to think about a real life scenario I could apply that concept to. That makes it far more real and stick in my mind.
  • After each review session, there’s often one flashcard in particular that I really dig into. I might spend 5 minutes writing about it. I might just think about it while going about my day.

Those are some of the things I’ve been doing for the past few years. I’d love to hear anyone else’s tips and tricks you use as well. Ultimately, I think a lot of it is just about showing up. Being imperfect, coming back to the path, and applying what you’ve learned and reviewed in the real world.

Below, some examples of 3 of my most recently added flashcards.  These ones Anki is going to show me again in a couple of days, but in time it will space them out over years.  Good luck to you in your studies and their application!

Collaboration opportunity: Internet research for climate impact

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Data apprentice sought.

I’m going to try an experiment, but I can’t do it alone. I believe this is a chance to have a horizon-expanding experience that makes a meaningful impact on climate change.  Maybe this is of interest to you – or maybe you know someone it would be a good fit for.

Goal: to help increase the capacity & impact of people working on climate change by building, sharing, and teaching how to use a collection of online research tools for ongoing learning and topic tracking. I believe that access to great streams of knowledge can help people make a bigger impact on the world. We’re going to build and share some streams regarding climate work.

What I’m looking for:

You:

  • Want to make an impact on climate change
  • Can do 5-10 hours of work per week, for the next 3 months. Update: Originally I said this was unpaid, but I’m going to find a way to offer some payment for help with this. I got some good feedback that more people would be available to help if this wasn’t unpaid work. Let’s talk about it.
  • Want to expand your exposure to what people around the world are doing about climate change now
  • Want to learn how to use leading-edge systems for online research by helping assemble them for others
  • Love to learn how to do new things
  • Feel comfortable making judgement calls on the quality of information sources
  • Can help with organizing an online workshop

Work includes:

  • Source discovery: Validate, clean up, and expand lists of the best sources of information (blogs, news sites, Twitter accounts) regarding greenhouse gas emission reduction, using a combination of automated tools, existing research practices, your creativity, and patience
  • Information organization: Organize those sources of information inside of tools to maximize their usefulness (RSS feeds, Google Custom Search, Twitter Lists)
  • Story capture: help build a collection of short stories of successful projects that made a big impact on greenhouse gas emissions reduction.
  • Event planning: Assist with planning, promotion, and production of a series of 3 weekend workshops introducing people to the climate knowledge tools we create and showing how to use them. (I’ll lead the workshops but I need your help making them happen.)

About Me:

  • I’m a longtime, self-educated, professional online researcher
  • I used to be a NYTimes-syndicated journalist. The tools we’ll be building together are rooted in my journalism experience.
  • I have also been an investor-backed startup founder, political organizer, tofu manufacturer, and convenience store clerk. Today I am a VP at the world’s leading software provider for customer experience management and social media listening.
  • I have become a good manager and mentor. It was hard.
  • I have a strong commitment to social justice, including and beyond climate issues.
  • I love my day job and don’t have much time outside it. That’s why I need your help.

When: Starting ASAP, target date for first workshop is early January, second in early February. There’s no time like the present! Let’s get started!

How:

  • How we’ll collaborate: Outside of 8:00-5:00 PST (before and after my work day), we’ll use chat, video calls, and project management by spreadsheet
  • How to get in contact with me: Please email me at marshall@marshallk.com with the subject line: climate research volunteer. Tell me about yourself and your interest in the project.

I look forward to hearing from you!

10 good articles I read this week

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In a time of information overload, careful curation is a way any of us can add value to the the lives and minds of our peers. In that spirit, and on the encouragement of my friend Mike Mathews, I thought I’d experiment with a link-blog type post, which will then be delivered to email newsletter subscribers, and see if that’s something I can do regularly.

Here are 10 things I read, watched, or listened to this week that I found so valuable I wanted to share them.  I cut out the political ones, this time.

Tech

  • Humans in the Loop collective intelligence (Video) “Superminds: The Surprising Power of People and Computers Thinking Together with MIT’s Thomas Malone“

This 45 minute talk suggests that we move from the AI concept of “humans in the loop” to a paradigm of humans working together, augmented by machines, or “computers in the group.”

  • Roam Research raises a round of funding, at a $200 million valuation. Roam has already changed the lives of so many of its users, including mine. It’s not only where I do all my digital note taking, it also facilitates entirely new thoughts every time I allow it to. No wonder investors were able to support its ongoing development at such a dramatically high price.

Woop woop, that’s where I work! I’m having a great time and am excited about the future. This got lots of press, but the TechCrunch post was particularly good.

Foresight & Strategy

Futurist Amy Webb offers multiple tools for foresight on her company’s home page. This “Axes of Uncertainty” is a simple and powerful one.

Great conversation about AI but I’m putting it in Foresight because one of the strongest points is that AI’s pattern recognition powers makes it particularly well suited to the Observe and Orient stages of the OODA loop, supporting humans as they take responsibility for the Decide and Act stages.

Climate

  • OPML of Green Energy Sources (there’s a download link in this Tweet about it)

If you know how to import an OPML file into an RSS feed reader, here is an algorithmically created collection of the top sources on green energy that others in the green energy field pay attention to. I built it on Sunday because I’m really trying to dig into climate matters.  You might also like this Twitter List of 1K peer-validated climate change thought leaders.. There are almost 10K people following it!

If you don’t know how to import an OPML file into an RSS reader, you’re really missing out. My wife often teases me that I told her about RSS on our first date, and now 17 years later we’re very happily married!

Guess what % of the world’s new energy production capacity installed last year was from renewable energy? Guess what % of global energy used is now from renewable? Great informed discussion here. Happily, the answers to those questions are 80 and 27. I was surprised by both of those.

Even people who find this podcast annoying agree it’s chock full of some very good information and some reason for optimism.

6 minute interview with two indigenous people about the use of fire. I’ve watched this and shared it many times. I encourage you to watch it too.

Beautiful. Tired of the view out your window? Try someone else’s. Not tired of the view out your window? You may appreciate this even more, then.

A good alert can have many false positives

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I’ve set up thousands of alerts over my career as a journalist, entrepreneur, and now marketer. SMS alerts about every new blog post on a long list of company blogs were how I beat everyone to the punch almost 15 years ago and became the first writer hired at TechCrunch. Today I monitor for AI-benchmarked anomalous numbers of mentions in a short period of time of a long list of companies related to the firm I work for, Sprinklr.

(Above: the first Sprinklr Smart Alert hit I ever got was a good one. I took action on it; I amplified some good news and congratulated a business partner on an innovation of theirs I would have missed without this alert.)

I believe Alerts of various types are going to grow all the more important in the coming years – and I think we should talk about our expectations for them.

A lot of people get frustrated when they get a non-actionable alert. That’s the price of a good alert, I believe. Any good alert system will weed out 99.9% of potential events, send the .1% of events it thinks you may want to take action on. But you may only find that 50%, 30%, 10% or less are in fact actionable. Depending on how you’ve trained the system. Any way you do it, there’s more work to be done.

An Alert never tells a whole story, it only suggests where there me be a story to find. I love some alerts that are “false alarms” (non-actionable) the vast majority of times they sound. Because I’m willing to sift through noise to find quiet signals.

Furthermore, alerts are great for delivering news of an anomaly and maybe a little context – but the whole story is going to require manual skilled discovery of context, testing of a thesis, and will require decisions to be made.

That’s because almost no full set of circumstances for everything that could be actionable can be described by mortal humans ahead of time. Any Alert that doesn’t surface Unknown Unknowns is something else, something very narrow.

Below: this is not how or where I work.