Do You Have to Write 25 Headlines to Get an Awesome One?

Headlines hold special power.

They determine whether people tap on a blog post or a LinkedIn article to read more, or whether they swipe past it.

“One of the best ways to make your content shareable, get found on search engines and grow your traffic is to write great headlines,” says Nathan Ellering of the marketing calendar company called Co-Schedule.

How do you create irresistible headlines?

“Write 25 different headlines for every post,” advises Garrett Moon, the co-founder of CoSchedule.

This echoes career blogger Penelope Trunk‘s mantra in her course on reaching your goals through blogging.

“Your title [or headline] is extremely important,” she says. “It should tell people what’s there beyond the click, and how it relates to your reader and how their life will change.”

Realizing that I devote hours to each blog post, but only spend a few minutes on a headline when I’m getting ready to publish, I knew it was time to switch the focus.

Quick Hacks to Help You Come Up with Attractive Blog Post Headlines by Marko Saric led me to CoSchedule’s headline analyzer.

Type in any headline. You’ll get instant data on word balance, headline type, length analysis, first 3 and last 3 words, keywords, and sentiment (positive, neutral or negative).

Plus, you’ll see how your headline will appear in a Google search or as an email subject line. Those first few words really matter.

Headlines are scored on a scale from 0 to 100. The best headlines (green) score at 70 and above. Average headlines (yellow) are 55 to 69, and bad headlines (red) are 54 and below.

This made me wonder how all of my blog headlines would stack up. So I did a little experiment. I entered all 152 of them into the headline analyzer.

And what a humbling experience it was. Only 36 headlines were green, 55 were yellow and 61 were red. Ouch!

What went wrong?

Two things stand out.

First, I was writing short headlines that would fit better into my current WordPress theme. I tried to be too clever and too brief so the headline would fit on a single line. As a result, the headlines weren’t fully describing what the post was about.

Second, I suffered from “the curse of knowledge.” This is a trick our brains play on us. When we’re highly familiar with certain information, we tend to assume that others are similarly informed, even though that logically makes no sense.

Because of this, I wasn’t assessing my headlines from the point of view of someone who didn’t know as much about the subject as I did. My brain filled in details, but since they weren’t in the headline, not enough information was there to interest a reader.

Yet there was a silver lining. In the last 9 months my headlines have been all green and yellow, with 50% in each category. Why? I wrote longer, more descriptive headlines. And this showed up in the analyzer scores.

Looking beyond the scores, I could see what headline types I was using. According to Ellering, the most effective types of headlines are list posts, how to’s, and questions.

The sentiment scores also attracted my attention. Headlines with neutral sentiment get the least engagement. Positive headlines attract the most attention. This is consistent with other data I’ve found on people being more inclined to share positive stores.

Then there’s the emotional angle to consider. The Advanced Marketing Institute developed an Emotional Marketing Value (EMV) score. This tells you how much of an emotional chord you’re striking with your readers.

As I wrote 25 headlines for this post, I tried the top-scoring ones in the Emotional Marketing Value Headline Analyzer.

Disappointingly, the top-scoring headline with a 76 – “Will the 25th Headline You Write be the Best?” – only rated a 22.22% EMV. That’s not great when a target of 30-40% EMV words is desirable, and higher is even better.

I chose this particular headline because I wanted to prove a point in this post. Writing 25 headlines helps get your creativity flowing, and you start writing better headlines once you get to 10 or 12. However, diminishing returns can set in. Rarely will the 25th headline be the best one.

But in the process you’ll come up with an optimal headline. While your 25th headline won’t likely be your best, there’s tremendous value in training your brain to write that many headlines.

Unfortunately my top headline didn’t hit enough emotional notes. So I went to the next-highest-scoring headline and made a few tweaks. I came up with “Do You Really Have to Write 25 Headlines to Get an Awesome One?

This got an EMV score of 46.15%. That euphoric feeling only lasted until I entered it in the headline analyzer. Too many words, it said.

Is there a happy medium between the scientifically optimal headline and the emotionally appealing headline?

For this post, it turned out to be “Do You Have to Write 25 Headlines to Get an Awesome One?” Taking the “too wordy” feedback to heart, I eliminated the word “really.”

It was a balance between a 73 green score in the headline analyzer . . .

. . . and a 41.67% EMV score.

So what if the headline analyzer still said it was too wordy? Those words may just elicit more emotion – and more engagement with this post.

For now I’ll live with the cognitive dissonance of a headline analyzer that identifies 0% emotional words and an emotional marketing value analysis above 40%. Clearly the algorithms differ, so it’s something to explore in future posts.

And the most fun of all? The science of words is starting to turn me into a data geek after all.

What LinkedIn Content Gets the Most Engagement?

It’s almost the end of my month-long experiment of posting an update every weekday on LinkedIn.

There’s a growing spreadsheet of data ready to analyze for conclusions and implications. I’ll share them in an upcoming blog post.

In the meantime, I found an interesting data point in a book released this month.

It’s Everybody Lies: Big Data, New Data and What the Internet Can Tell Us About Who We Really Are by Seth Stephens-Davidowitz.

Seth got his Ph.D. in economics from Harvard, worked as a data scientist at Google, and writes for the New York Times.

He makes the case that “we no longer need to rely on what people tell us” in things like surveys or social media or casual conversations.

He  provides compelling data telling the story that big datasets of how people search for information online reveals what’s really on their minds.

Seth writes about “text as data” and how sentiment analysis can identify how happy or sad a piece of content is.

He shared the most positive 3 words in the English language: happy, love and awesome. The 3 most negative? Sad, death and depression.

And what content gets shared more often? Positive or negative stories?

If you agree that “news is about conflict” – summed up by the journalistic sentiment “if it bleeds, it leads” – you might conclude that negative content gets shared more often.

But it’s actually the reverse, according to a study by professors at the Wharton School, Jonah Berger and Katherine L. Milkman. They looked at the most shared articles for the New York Times.

And what was shared the most?

Positive stories.

As the professors said, “Content is more likely to become viral the more positive it is.”

My first reaction was happiness that my “positive comments only” philosophy for social media savvy had some data supporting it.

The second reaction was to turn to my own data from this month’s LinkedIn experiment to see if it held true.

Here I’m measuring engagement by the number of views, rather than by the number of shares.


I’m fairly new to this daily posting routine, so the first change I’ve seen over the past 4 weeks is an increase in views of my content, rather than any significant shares. And I’m finding shares more challenging to measure so far.

What were my most-viewed posts?

The first 2 posts make sense to me as highly positive content. The third made me pause. On the face of it, it seems like a negative that our brains are limited in the amount of focus they can handle.

But as I thought about it and revisited the comments on the post, I realized that many people might have found this information to be happy news. In other words, it’s okay and even desirable to NOT focus your brain all the time.

How about the least-viewed posts?

The first has to do with a fabulous new book by Sheryl Sandberg and Adam Grant on what the research and practice say about bouncing back from adversity.

But since it began from Sandberg’s husband’s death, one of the saddest words in the English language, that puts the topic in the negative zone. (I still recommend reading the book, because it’s full of uplifting advice about grit and resilience.)

The second was a special report in The Economist about how “data are to this century what oil was to the last one: a driver of growth and change.” Because “change” is not something many people eagerly embrace, perhaps this story was seen as more negative than positive.

The third was a Harvard Business Review article about what distinguishes goals we achieve from those we don’t. My takeaway here? Maybe thinking about goals we haven’t achieved brings up negative thoughts.

Could other factors have impacted which posts were the most and least viewed? Perhaps. Day of the week would have been the most likely. However, the top and bottom views were each for the most part posted on Mondays and Tuesdays.

Another factor could have been posts during the beginning of my daily posting experiment vs. those closer to the end. This certainly could be a factor. Posts later in the month are getting more views in general. From the first week of May to the last, views of my posts have increased more than 6 times.

One conclusion could be that the consistency of posting daily is increasing engagement with my content. Of course, it’s still a small dataset at this point. In the months to come, I’ll continue tracking it and adjusting my strategy. (Opinions expressed in this blog are my own.)

How are people engaging with your LinkedIn content? What’s attracting the most interaction?

Can Data Presentation be a Matter of Life or Death?

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To my surprise and delight, “communication” topped the list of key skills for data scientists in a CEB Market Insights blog post I read this week.

The post covered the top 10 skills for data scientists and 2 strategies for hiring them. Yet “communication” felt like a lone outlier among a list of highly quantitative skills, like managing structured data, mathematics, data mining and statistical modeling.

But indeed, the Business Broadway study the post cited showed that “communications” recurred the most frequently across a variety of data science roles.

When Thomas Davenport and D.J. Patil named “Data Scientist” the sexiest job of the 21st century in Harvard Business Review, they cited an enduring need “for data scientists to communicate in language that all their stakeholders understand – and to demonstrate the special skills involved in storytelling with data, whether verbally, visually, or – ideally – both.”

As a communicator who pivoted into marketing analytics, it’s heartening to to see data showing there’s a role and need for effective communication and storytelling skills.

And having led communications, the field is dramatically improved by data that demonstrates what works and what doesn’t, and helps predict how various audiences might respond to different communications strategies.

Beyond enabling data-driven decisions, clear communications about data can literally be a matter of life or death. Two fascinating examples crossed my path this morning in an article by Dr. Jenny Grant Rankin called Over-the-Counter Data: the heroics of well-displayed information.

The first example was an early use of data visualization in the summer of 1854. In London, 500 people died of mysterious causes in a 10-day period. A Dr. John Snow made his data user-friendly. He took a neighborhood map and noted the exact locations where people had died.

This pointed toward a local water pump that was the culprit in the spread of cholera. With this clearly displayed data, Dr. Snow was able to convince authorities to remove the pump’s handle in order to stop the outbreak.

Another example took a much more ominous turn. The night before the Space Shuttle Challenger launched in January 1986, NASA engineers and their supervisors looked at charts and data on the rocket’s O-ring function. This is what keeps hot gasses contained. Based on what they saw, the launch was cleared for takeoff.

But the available data was not displayed clearly. It showed failed launches, but not successful launches. And this led decision makers to overlook a critical piece of information – the O-rings worked properly only when the temperature was above 66 degrees. The day of the Challenger launch was 30 degrees below that. It was “so cold it does not even fit on the graph.” It’s still heart wrenching to recall the tragedy that occurred that day.

While thankfully the work of data scientists is rarely a life or death matter, these examples underscore the need for clarity in communicating data. For what cannot be understood cannot be implemented.

What’s the Future of Big Data?

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Data is the raw material of the information age.

So says Alec Ross in his book The Industries of the Future.

An expert on innovation, Ross draws parallels between land being the raw material of the agricultural age and iron being the raw material of the he industrial age.

Essentially, big data will touch every aspects of our lives. “Big data,” he says, “is transitioning from a tool primarily for targeted advertising to an instrument with profound applications for diverse corporate sectors and for addressing chronic societal problems.”

Here are a few of his predictions:

  1. During the next decade, big data will enable people to converse in not just one another language but dozens. While I won’t give up on my Spanish studies anytime soon, it’s good to know that data-based help is on the way.
  2. As the world’s population grows, so does the need for more food. “Precision agriculture” enabled by big data will help solve this problem.
  3. Smarter financial systems can be powered by big data. It was surprising, and even a little shocking, to read how antiquated many banking systems still are today.

An important caution is to understand the limits of big data and the critical interplay between machine and mind. This comes in the form of spurious correlations that may result from ever larger and bigger data sets. “Not all the trends it finds are rooted in reality,” he says.

The solution? Including error bars with data analysis predictions. Error bars are “visual representations of how likely a prediction is to be an error rooted in spurious correlation.”

In addition to peering into the future of big data, Ross gives two great tips for “the most important job you will ever have.” How does he define that? Parenting.

What can parents do to help their children be ready to embrace the future?

Ross frames it in terms of languages. The first language is globalism. “Ironically,” he writes, “in a world growing more virtual, it has never been more important to get as many ink stamps in your passport as possible.”

And even though big data may eventually make the need to learn other languages obsolete, it’s wise to learn another language beyond English. The most practical choices, not surprisingly, are Spanish and Mandarin.

The other language to learn is technology. “If big data, genomics, cyber, and robotics are among the high-growth industries of the future,” Ross says, “then the people who will make their livings in these industries need to be fluent in the coding languages behind them.”

Other benefits come with understanding technology. Ross cites fellow pundits who tout the ability to better see patterns and to think in new and different ways. Studying technology is a valuable way to sharpen your critical thinking skills.

One of Ross’ points that I was happiest to see came in the introduction. Because his book explores competitiveness, he delves into the driving force behind competitive countries and businesses being the development of people.

He takes it a critical step further. “And there is no greater indicator of an innovative culture than the empowerment of women. Fully integrating and empowering women economically and politically is the most important step that a country or company can take to strengthen its competitiveness.”

Well said, Alec Ross.

Great Blogs About Marketing Analytics and Big Data


Since small steps add up to big change, what are some blogs that accelerate learning about marketing analytics and big data?

A great place to start is with this post: Want to Learn Marketing Analytics? Start With These 9 Great Resources.

From that and other searches, these are 3 to check out regularly.

  • The KISSmetrics Blog. Here there’s daily content about marketing analytics, marketing and testing.
  • Alexandra Samuel’s blogHere this “technology researcher, writer and strategist” covers how the social web is changing every aspect of our lives.

Is this last one strictly about marketing analytics and big data? No, it’s bigger than that. It’s about life.

And isn’t the point of analytics and big data to enable better decisions and therefore better lives?


My post 6 Brilliant Blogs for Marketers covers more general marketing blogs, including FiveThirtyEight on “using statistical analysis to tell compelling stories.”

4 Key Questions About Data


When I started my learning project, the plan was to alternate posts between learning how to learn and learning more about data science.

A data review would show I’ve focused too much on the former and not enough on the latter. The data-driven conclusion? It’s time to shift the balance.

As I’ve worked in a new role the last 6 months focusing on marketing analytics, I’ve drawn heavily on my academic background. There’s  economics with its emphasis on statistics and communications management with its reliance on research.

My professional experience is key, too. Leading an employee engagement survey strategy for several years and conducting corporate communications surveys has helped tremendously.

It’s fascinating how many parallels exist between seemingly disparate areas. And problem solving and team leadership are often similar from function to function.

One of the skills I’ve needed to sharpen is thinking critically about data measurements. I’m learning to ask better questions. And I’m learning to anticipate questions from colleagues on how data was collected and analyzed.

Harvard Business Review is a valuable resource in generating good questions – from branding to market insights and from big data to the customer experience.

A March 2016 article by Thomas C. Redman – 4 Steps to Thinking Critically About Data Measurements – gives great tips on asking good questions about data. Here’s a short summary:

  • How does the actual measurement line up with what you want to know? Ask yourself if the measures are good surrogates for what you really want to know.  Redman advises to “distinguish ‘pretty close’ from ‘a good-enough indicator’ to ‘not what I had in mind.'” If you’re settling for something less than perfect, you should be aware of it.
  • What do you want to know? Clarify what you want to know. This is similar to asking, “what problem are we trying to solve?” It’s also important to make sure all stakeholders are aligned on the exact nature and outcomes of the measurement process.
  • What are weaknesses in the measurement process? Here Redman advises a thorough understanding of the entire data collection process. He suggests listening to customer calls if you’re measuring customer complaints or going to a factory if you’re measuring factory productivity. This helps to “develop a feel for the weak links.”
  • Have you subjected results to the “smell test”? If results don’t seem right to you, based on other knowledge you have, dig into them. If results come in much better or worse than expected, consider the possibility of bad measurement and investigate further.

Thank you, Thomas Redman, for a few simple litmus tests to think more critically about data.


Binge Watch Your Way To New Skills


Who doesn’t love binge watching a favorite show?

Whether it’s Game of Thrones or Billions, watching multiple episodes in a single sitting makes the experience more intense, rewarding and fun.

That’s a fun part of working for at the company that provides DIRECTV. Whether it’s the DIRECTV app or a programmer app with the subscription, it’s easy to stream great content on a mobile device.

It got me thinking about how binge watching might apply to online learning. Could it make learning more effective? More efficient? How about more fun?

And why was I pondering this question?

A Fortune 10 CEO was recently quoted in the New York Times on reskilling people for the future. “There is a need to retool yourself,” he said, “and you should not expect to stop. People who do not spend 5 to 10 hours a week in online learning will obsolete themselves with the technology.”

(Full disclosure: I work for this great company. Opinions in this blog are my own.)

While it’s true that small steps add up to big changes, it’s possible to accelerate learning by binge viewing great online courses.

As an example, for professional certifications that require ongoing education, binge viewing online courses is highly effective.


  • It eliminates the inefficiencies of starting and stopping courses.
  • It amplifies learning by increasing the ability to see patterns and make connections between seemingly disparate concepts and information.
  • And a significant amount of learning can be completed in a relatively short time, fueling more motivation to seek out further coursework.

As I rectify my accreditations in public relations and human resources every 3 years, this strategy has made ongoing learning more efficient and more fun.

And it’s worked well for a series of marketing essentials courses I co-created with colleagues in my new career role. And for several weeks my action-item list has included “complete this series of online courses.” But somehow it didn’t happen. Until today. And here’s why.

Schedule time. The 5 online courses I need to complete are 90 minutes each, totaling 7.5 hours. Have you ever found a full day without meetings that you could commit to online learning?

Earlier this week I looked at my schedule and saw I had a few open late afternoon hours on a Friday. So I booked it for 2 online courses. Which then became 3, as I was pulled into the reward of completing course after course.

It was much easier to click into that next course as long as I was already online, in a comfortable place, and with a few hours of time I’d blocked out.

Make yourself comfortable. Maybe there’s a comfortable chair in your workspace. Or a standing desk. Or even a treadmill desk. What would make the environment even better? Your favorite coffee beverage? A healthy snack?

Focus on the course. Find a quiet place. Close your door if you have one. Turn off email and text notifications and other sounds on mobile devices.

Enjoy the experience of focusing intently on only one thing. Research shows that humans can’t multitask anyway, as much as we delude ourselves into thinking that we can.

Write notes on key points. Listen for 3 key takeaways. There’s magic in the number 3. It focuses your thought processes and forces you to prioritize what you heard and saw.

Taking notes on those key points helps to solidify the learning, especially if you hand write them. And you have something you can quickly refer to when you want to refresh your learning.

Take one immediate action. Of those 3 key points, what’s one thing you can put into action right away?

As part of my PR recertification, I listened to an IABC webinar on the art of social media by Guy Kawasaki. That’s how I discovered Canva. It makes anyone, including me, into a graphic designer. Many of the images in this blog are from Canva.

Given the need for all of us to prepare for our next career, why not binge watch your way to a new skill?

What Does Kindness Have to Do with Learning?


Does what we say to ourselves influence how much, how fast and how well we can learn new things?

Absolutely, says Erika Andersen, the author of the forthcoming book Be Bad First.

She outlines 4 key mental tools in her Harvard Business Review article, Learning to Learn. They are aspiration, self-awareness, curiosity and vulnerability.

Aspiration. Andersen says “great learners can raise their aspiration level.” How? By focusing on the benefits of what you’ll learn, rather than on the challenges in the learning process. A good question to ask is “What would my future look like if I learned this?”

Self-awareness. This is about seeking feedback and taking action on it. Good questions to ask yourself about feedback are “Is this accurate?” “What facts do I have to support it?” and “How do I compare with my peers?”

Curiosity. Andersen writes that “curiosity is what makes us try something until we can do it it, or think about something until we understand it.”

If you’re not interested in a new subject, Anderson advocates changing your self-talk to ask why others find the subject so interesting.

As a person interested in words, ideas and influence, my curiosity is helping me find where those interests intersect with analytics and big data.

In starting to read Tom Davenport‘s Big Data @ Work, I became more curious about how organizations of the future will better focus on the collaboration and communications activities of their people.

This led me to a footnote that took me to another book called Social Physics. This is defined as “analyzing patterns of human experience and idea exchange within the digital bread crumbs we all leave behind us as we move through the world.”

Now I’m truly fascinated and thinking about the connections with another book I read last year, The Reputation Economy. This is about how individuals can shape their digital footprint at a time when your reputation can dictate the kind of life you’ll live and what opportunities may be available to you.

Vulnerability. This is about the scary prospect of “being bad at something for weeks or months; feeling awkward and slow; having to ask ‘dumb’ questions; and needing step-by-step guidance again and again.”

The cure? Changing what you say to yourself. Andersen suggests that instead of saying “I’m terrible at this,” replace it with, “I’m making beginner mistakes, but I’ll get better.”

As I’m pursuing my own learning project and getting up to speed in a new role, I reminded myself of trying out for a sports team in high school.

When I showed up for the first practice before tryouts, I almost didn’t come back the next day. I felt uncoordinated, self-conscious and silly. But I made myself come back the next day. And the next.

And happily, I made the team. But what if I’d given up that first day? What if I’d allowed myself to believe that I was terrible and had no hope of getting better?

There are very few things we can’t learn if we tell ourselves we can. And if we encourage ourselves with positive thoughts. And remind ourselves that others don’t notice our mistakes as much as we might think.

I have to tell myself that frequently as I walk into yet another figurative wall by mistake. Oops. That hurt. Did anyone notice my mistake?

But the important thing is the dust yourself off. To keep moving forward. And to avoid making the same mistake twice.

What’s a good way to do that? By being kind to yourself. Encourage yourself. Have faith that with grit and perseverance, you can do what you set out to do.

One day this month I came home and a friend from a community group had left a thank-you card and a book on my doorstep. The book is “The Power of Kindness.” It’s about “the unexpected benefits of leading a compassionate life.”

And while the main focus of the book is on being kind to others, there is power in being just as kind to ourselves.

That doesn’t mean we shouldn’t set aspirational goals and have high standards for ourselves. But it does mean encouraging ourselves and asking how we could do better next time.

In addition to my learning journey in data and analytics, I’ve written in this blog about learning stand-up paddle boarding and learning yoga. My goal this summer is to combine the two.

Today I went paddle boarding and tomorrow I’ll take a yoga class. The benefit to both is a kind of zen that helps me be kinder to myself and to others.

It pulls me out of the moment-to-moment frenzy of everyday life and puts me in a meditative state. A reflective state. A refreshed state.

All the better to keep learning.

Can Dream Headlines Focus Your Research?


Headlines are critical in corporate communications.

If someone reads nothing else but the headline, will they get the key message? And will the headline compel them to read the story?

A tweet can serve the same function. Can you get your key message across in under 140 characters? Will it engage your followers to click on the related link?

It turns out, there’s another powerful use for headlines and tweets. Alexandra Samuel outlines this in her HBR post How Content Marketers Can Tell Better Stories with Data.

“Start with your dream headline,” Samuel advises. She likes to start by “imagining my dream headlines or tweets: the discoveries that I would love my data to yield.”

Samuel gives the example of looking at child-related security risks. “I hoped to discover the security practices that led to the biggest reduction in online misdeeds,” she wrote, “something like ‘good passwords cut hacks perpetrated by kids by 50%’.”

This informs how she tackles the research. What’s less important is whether the discovery she wants to find is actually supported by the research. Because the method provides focus to the research.

This gives a better ability to discover “data that would yield the best-case outcome.” The headline and the story then evolve based on the most interesting and relevant insights from the data.

My first introduction to Alexandra Samuel was through her series of e-books, which ultimately become Work Smarter with Social Media. These helped me to work better with LinkedIn, Twitter and more.

That’s why I was drawn to Samuel’s articles during my Sunday morning reading of HBR posts on marketing, market research and data. It’s all part of my ongoing, online learning project.

And it speaks to the 5-plus hours of learning that everyone at my employer is encouraged to do to mobilize the future.

We’re all lifelong learners. It’s a gift to be part of a company that creates a learning culture to do just that.

What are you learning today?

Are Great Leaders Persuadable?


Are the hallmarks of great leaders confidence, certainty and decisiveness?

Or as our world grows ever more volatile and complex, are the best leaders open to influence? Are they persuadable?

That’s the premise of a great new book by Al Pittampalli called Persuadable: How Great Leaders Change Their Minds to Change the World.

How did I find it? By reading one of my favorite marketing blogs. Seth Godin had a great plug for it last week in his post “When I want your opinion…”. And if Seth is recommending a book, it’s going to be good.

With only slight sheepishness at being a marketer’s dream by buying the Kindle edition of the book after reading the post, I dove into it this week.

What did I learn? In a nutshell, I’m going to be much more comfortable evaluating new data and information as it comes to light. And I’ll be more willing to change my mind as a result.

Some of it harkens back to the classic principles in Robert Cialdini‘s Influence: The Psychology of Persuasion. The reciprocity principle in particular has stood the test of time as a key driver of social media.

John Maxwell‘s writings about Becoming a Person of Influence also made an impression. Maxwell says you have to be open to the influence of others, in order to have an influence on them. I’m still tickled that he was one of the first people who “followed” me back on Twitter.

Why is persuadability to important? “In a world that is unpredictable, ultra competitive and fast changing,” Pittampalli writes, “being persuadable is the ultimate competitive advantage.”

This gives key advantages, he explains — accuracy, agility and growth:

  • A better understanding of the world fuels more accurate decisions.
  • Quickly seeing and responding to changing conditions enables necessary pivots.
  • And honestly evaluating your performance and getting feedback creates growth.

How do you become persuadable? Pittampalli outlines 7 practices of persuadable leaders. Here are 3 that most resonated with me.

First is “considering the opposite.” It seems straightforward, yet we have to overcome our own cognitive biases to actively seek out information that conflicts with our current thinking.

A simple way to counter it is by asking yourself questions, starting with “what’s the opposite here and have I thought about it?”

Second is “update your beliefs incrementally.” What works in leading change in general also applies to being more persuadable.

As more evidence becomes available, we can update our beliefs along the way. That way, beliefs evolve naturally over time. It’s easier for your own brain as well as for others to embrace smaller changes in thinking.

Third is “avoiding becoming too persuadable.” Just because you choose to become more persuadable as a leader, there are still plenty of times when it’s appropriate to make decisions that may be unpopular and take action.

Like many things in life and leadership, there are tradeoffs to be made. It’s valuable to get input up to a point, but then there are diminishing returns over time of each additional piece of feedback.

Perhaps you’re embracing on a course of action and finding it difficult to decide whether or not to proceed. A good question Pittampalli puts forth is asking yourself, “Is it worth it?”

My experience in business reinforces for me that it’s more important than ever to be open to new evidence. The world is constantly changing, and information used previously to make decisions is likely to have changed.

By extension, it’s important to become ever more comfortable with changing you mind. Along with that, it’s critical to clearly articulate the reasons behind the changes in your thought process.

As Simon Sinek so compellingly outlined in his TED talk How great leaders inspire action, understanding “why” is the first thing people need to know in order to change the world.