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.

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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.

I attended SXSW 2019 with my employer Sprinklr, and one of the sessions I got a lot out of was titled How Data is Revolutionizing the NFL.  I took notes on paper and now that I’m back in the office, I transcribed some of the most interesting notes from the session and thought I’d share them here.

I’m not a football fan, but I love data analysis, and this session was a lot of fun.  I think there’s a lot here that can be a source of inspiration for work in just about any sector, especially work that involves data.

* Each player has an individual game plan for each game (I didn’t realize that but of course it makes sense.  When I put my work to-do list on my calendar, that makes me feel a little like I’ve got an individual game plan in support of my team’s plan.)
* LA Rams analytics team has 3 people: a forecaster, a data architect, and a front end developer for internal systems.
* Whether it’s today or the 90’s before there were analytics teams, there have always been people looking at data, looking at probabilities, and trying to help teams make good decisions
* When you see players who are successful, you look to see if you can discover any new traits they have. Then you can look to find other people who have those traits as well but who may have missed other benchmarks and thus not been discovered.
* One person can’t do analysis of all the data available, but if the work is documented and reproducible, then you can come back later and repeat it, or pick it up again to iterate with new data and knowledge. As long as you’re iterating in your analysis, that’s good.
* These analysts are working with R, Python, SQL databases, and spreadsheets are often the final product that’s sent to someone
* You’re not going to be 100% correct in your forecasts, in fact your failure rate is going to be very high – and you just have to get used to that
* Much of the analytics are used for tracking player workload for optimization (makes me think about capacity management in an information worker’s worklife)
* The NFL is using data to try to make fans smarter, so they can hang out with their friends and say “you should look out for this when the game is being played.”  When you put the names of receivers and who’s covering them up on the screen, people love that. (cool validation of this as a commercially viable value add)
* For QBs air yards is a key stat. Everything these days is a quick, controlled game. We’re asking QBs to throw shorter passes and they should have about 60% pass completion rate
* Data science is a great place for people from diverse backgrounds to showcase your abilities by analyzing public data and find new perspectives. You can showcase your abilities, get attention for it, demonstrate, show your work, share your code
* Communication is super important. As an analytics person, you should be able to translate your work to anyone who could use it. That’s just as important as the ability to do the work itself.  (I’m pretty sure it was Namita Nandakumar who said that.)
* People think stats are going to tell you something dramatically different than what you think – but they often don’t. They often tell you something smaller, like who on your team has the potential to play a larger role.
* You can support people moving toward more statistical thinking in an incremental fashion: show one success first, then move toward more grey areas
* Having discipline in this job is key because there are so many interesting things you could be analyzing, you must constantly assess and reassess projects

Those were my notes, I hope you find them useful as well!

Let’s say you’re working on something that would benefit from the perspective of a really knowledgeable person in addition to yourself.  In fact, you probably are.

I think people, especially smart ones focused on particular fields, are the ultimate source of knowledge and insight because they are dynamic.  They just keep going.  Books and articles and such are great – but there’s nothing like finding a really great person for taking your understanding of the work you’re doing to the next level.

I’ve been in the people-finding business for almost a decade now, but today online a friend asked me how to find people who aren’t on social media.

I came up with this list of 5 ways.  What am I missing?

Ask people who are on social media

Social media is the easiest way to discover relevant people, either based on what they’ve published or based on who is connected to them.  The easiest way to find people is on the internet, and one of the best ways to find people who aren’t on the internet is to ask the people you find who are, who else you should talk to.

Search news

It would be great to extract this automatically, but just for a fresh test: I searched for “artificial intelligence” and “social justice” on Google News and the first result that wasn’t a TED Talk was an article about a conference and the first name in it was of an important college professor who has no Twitter account, 9 contacts on LinkedIn, and a blank avatar on Facebook.  He’s got a big CV though.

Search books (try Google Talk to Books)

Google’s new semantic search engine of books, called Talk to Books, is a pretty great way to explore around any topic.

Go to events

You know who the king of going to events and finding incredible people is? Kent Bye, host of Voices of VR and Voices of AI.  Thats where he gets his interviews.  And he has done hundreds, if not thousands, of interviews.

Leade.rs

Loic Le Meur’s new startup Leade.rs is a great looking way to find public speakers on hot topics.  It’s a directory. Is it social media?  Maybe.

 

Also: From the remarkable new Pew study titled “The Future of Well-Being in a Tech-Saturated World,” based on responses of more than 1,000 experts, some perspective:  Stephen Downes, a senior research officer at the National Research Council Canada, commented, “The internet will help rather than harm people’s well-being because it breaks down barriers and supports them in their ambitions and objectives. We see a lot of disruption today caused by this feature, as individuals and companies act out a number of their less desirable ambitions and objectives. Racism, intolerance, greed and criminality have always lurked beneath the surface, and it is no surprise to see them surface. But the vast majority of human ambitions and objectives are far more noble: people desire to educate themselves, people desire to communicate with others, people desire to share their experiences, people desire to create networks of enterprise, commerce and culture. All these are supported by digital technologies, and while they may not be as visible and disruptive as the less-desirable objectives, they are just as real and far more massive.”

Power pools at the points of intersection. That’s a clear theme in several of the most moving things I’ve read in the past few days.

Here are four items I recommend highly. Were we to do a multi-variate regression analysis of a few different dynamics in the world, these here might be explorations of independent factors that drive dependent factors like social cohesion, business productivity, justice and injustice.

• In the relationship between mind and machine, product and platform, core and crowd – the latter of each pair has grown so much stronger now that the relationship between each of these must be re-examined…The business world is always changing but in transitions as profound as this one, things are even more unsettled than usual.
  –Machine, Platform, Crowd: Harnessing Our Digital Future, Andrew McAfee and Erik Brynjolfsson, 2017
• “#changemanagement is often done with far too little communication, when it should be carried out more in the open with #WOL [Work Out Loud]+ #ESN [Enterprise Social Networks]+ network #leadership.”
  – Dion Hinchcliffe, quoted in Change management needs more, different and modern communication to be successful (which I wrote)
• A heartbreaking story of British imperialists collecting the dreams of their colonial subjects, in order to inform their control. Frustrated, they found – and resisted – evidence that we’re all equally human & that colonial rule is a nightmare.
  -Erik Linstrum, The empire dreamt back To help rule its empire, Britain turned to psychoanalysis. But they weren’t willing to hear the truth it told (Aeon)
• And finally, tonight I listened to the most powerful speech I’ve heard in my life. If it doesn’t change your perspective on race and gender, then you’re not paying attention. If you already know all this stuff then you’re paying far more attention than I am – and chances are you’re not. Incredibly effective talk. Kimberlé Crenshaw – On Intersectionality – keynote – WOW 2016 Professor Kimberlé Crenshaw, – the academic who coined the term ‘intersectionality’ and co-founder of the African American Policy Forum – gives a keynote on the unique challenges facing women and girls of colour when it comes to the struggle for gender equality, racial justice and wellbeing.

Back in January I did some fun hacking together of a Twitter list and some stats about corporate social strategists on Twitter, based on a great list of people in charge of social technology strategy at companies around the world compiled by Jeremiah Owyang.

Jeremiah kept adding to his list, though, and I quickly fell behind in trying to find each new addition to his list on Twitter and adding them to my Twitter list. Last month I finally figured out a way to get myself caught up and a list that was 141 members strong is now up to 277!

Here’s that list, if you haven’t started following it already. And here are a bunch of metrics and insights into the first half of the list. (If you’re interested in this kind of research about any other business sector, but better, you should contact me, by the way.)

Here’s how I caught up on list updates, if you’re interested. I copied all the names on Jeremiah’s updated list into a Google Doc, then I copied all the names on my Twitter List into another Google Doc. Then I emailed my favorite virtual assistant service Fancyhands and asked them to send me a list of the people on Jeremiah’s list but not on mine. They did that promptly. Then I sent the resulting list back into Fancyhands on another work request and asked for everyone’s Twitter username on that list.

Then I turned the resulting list into a bunch of links to those Twitter profiles. Then I changed my Twitter password. Oooooh, scary! Then I gave my new Twitter password to my fabulous new friend Steve Malloy and he did me the favor of adding all the new people to the official list! Thank you so much, Steven, for helping all of us keep track of the Tweets of social strategy leaders around the world!

I wrote a post this evening about Google’s forthcoming announcement that all Google Apps for Your Domain customers would be enabled with OpenID provider functionality within the next few weeks. It was emailed to a public list and it seems pretty clear that it wasn’t meant to be.

I think this is very important. Writing the article was an opportunity to address the tension between small innovators and big vendors in the digital freedom space.  (Hey, new phrase for me, but isn’t that what this is?)  That’s something I’ve been thinking about peripherally for awhile.  Both are needed, people say.   Innovators on the edge to come up with crazy ideas and be authentic – big vendors like Google and Facebook to deliver the ideas to the people, validate them and grant the functionality only possible with scale.  It’s not always pretty, though.

I ran with this story just as fast as I could, but I think I will revisit it because it’s a big deal.  For what it’s worth, I sure didn’t start my RWW headline with “EXCLUSIVE” or anything like that – because that’s so crudely self-aggrandizing that it’s embarrassing to read.
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