Tuesday, 31 January 2017

Online Content: Is Longer Really Better?

Writing online content is something of a balancing act. For years, SEO experts have pointed out that Google loves longer content.

Your readers? Not necessarily.

As a writer, that means you’re kind of stuck in the middle. Write too little, and your content won’t rank. Write too much, and most people won’t read your content.

‘Tis a conundrum, no?

The good news is, Google has realized that word count and keyword density aren’t always the best predictors of relevance. People care about their on-page experience—not the keyword count.

As a result, Google has placed an increasing focus on user experience. In Moz’s 2015 report on non-keyword ranking factors, 4 of their top 10 factors relate to user experience:


Given this trend, the odds are that as Google gets better at discerning great on-page experiences from the ho-hum ones, many pages with a lot of text but little value will start dropping through the ranks.

As a result, it’s not enough any more to write in-depth, keyword rich content—you have to optimize your content length for user experience. And, to do that, you need to know how much content your audience really wants on a page.

Fortunately, figuring that out isn’t nearly as difficult as you might think. To help you out, let’s take a look at how users interact with content and how you can test your content to maximize its effectiveness.

Is Longer Better?

Since Google has historically prioritized longer content, most companies and blogs have spent years producing long-form content. Often, this content is good, high-quality writing that delivers a lot of value (case in point, the Kissmetrics blog).

But the question is, is longer better?

For some sites, it probably is. But, to tell you the truth, I rarely read through everything on a page, even if I care a lot about the content. As it turns out, most people act the same way online.

In fact, Chartbeat ran a study to see just how far people make it through a typical blog post. Turns out, your average user only reads about half of a blog post:

So, while you may have written an epic, 8,000-word blog post about the psychology behind the Chewbacca Mask Lady’s viral video, most people aren’t going to read the whole thing. They’re going to bail long before your oh-so-compelling conclusion.

Sure, your article might rank well, but if people don’t finish reading it, will your article help your business? That’s debatable.

This idea holds especially true for site pages and landing pages. The internet is littered with enormous pages like this one (I rearranged the page into 3 side-by-side columns to improve your reading experience—see what I did there?):


Pages like this have a lot of good content, but all of that good content gets lost in the length of the page. Yes, the information a potential customer needs is probably on the page, but if they can’t find it, they’re not going to have a very good experience.

The point here is that crafting a compelling user experience doesn’t mean writing a lot of content. In fact, depending on your audience, writing more may mean people read less and therefore convert less.

But how can you know what sort of content length your audience prefers? To answer that, you’ll need to run a simple test.

Testing Out Different Content Lengths

When it comes to conversion rate optimization, a lot of companies focus on major page elements like headlines, hero shots, form fields, CTA buttons, etc. Content length often sits at the bottom of the list.

This is a shame, because content length is a major part of your user experience—especially if you run an active blog.

For example, at Disruptive, we were recently helping OURrescue optimize their site. Now, OURrescue is an amazing group. They travel the world saving kids from sex traffickers. It’s pretty hard to top that.

To fund their rescues, OURrescue runs a regular blog that discusses the (often heart-wrenching) details of their “missions.” Each blog post ends with a call for donations to help fund further rescue efforts.

In keeping with most blogs, OURrescue’s articles were usually a minimum of 1,500 words long and very detailed. The blog was generating decent donations, but my VP of Conversion Rate Optimization, Chris Dayley, started to wonder about the length of their content.

Were they writing too much? Too little? Would OURrescue get more donations if they changed the length of their content?

To answer these questions, Chris asked OURrescue to write short, medium and long versions of a few articles. We then used Optimizely to send traffic to each of the post variants. Similar to Chartbeat, we tracked how far users scrolled through each post (using Hotjar), time on page and the donations generated from each version of the article.

On desktop, the results were about what you’d expect (note, we tested multiple articles, but for simplicity’s sake, we’re only showing the variants for one article):


The longer the posts, the longer people spent on the page. That makes sense, since longer posts take more time to read. However, the mid-length articles actually had the highest completion rate.

So, while readers spent more time on the longest version of the posts, more people actually finished the articles and saw the donation CTA on the medium-length versions.

Things got even more interesting when we looked at our mobile users:


On mobile (which is where most online time is spent these days), the longest post variants had the lowest time on page. The middle-length page variants had the highest time on page.

The shortest version of the posts, however, had the highest completion rate—nearly double the completion rate of the longest variants.

Now, these stats were all very interesting, but none of them really answered the most important question: which length of content provided the best user experience?

Or, to put things in more concrete business terms, which version of the articles produced the most donations?

As it turned out, the “winning length” varied between desktop and mobile:


Compared with the longest version of the articles, the shortest versions drove over 80% more donations on mobile and the medium-length versions drove almost 30% more donations on desktop.

So, was longer content better for OURrescue? Not by a long shot!

What makes this data particularly interesting is the fact that time on page wasn’t a particularly good predictor of donations. Page completion rate, however, was.

If you think about it, this makes sense. After all, with a CTA at the bottom of the article, if people weren’t finishing the article, they weren’t seeing the CTA, which meant they weren’t donating.

Now, it’s possible that adding a floating CTA users could see throughout their reading experience could help improve donations further, but that’s hardly the point of this test. Since the CTA was at the bottom of the article, that meant that people who saw the CTA were having a good enough experience to get to the bottom of the article.

So, what drove donations for OURrescue? It wasn’t the articles with the most words—it was the articles with the best user experience.

All this being said, these were OURrescue’s results. Your audience will be different. It’s very possible that you could run this same sort of test and get completely different results.

But, if you don’t test the length of your content, can you really be sure that you’re providing the optimum user experience?


So, is longer content really better? For years, long content has been a great way to get ranked on Google, but that’s beginning to change.

These days, both Google and your readers are looking for content that provides a great experience. That means your online content needs to be the right length for your audience.

As Google continues to focus their algorithms on providing ever better user experiences, it’s time for online marketers to do the same.

Have you ever tried a test like this one? What were your results? Do you agree that online content should be optimized for user experience, rather than word count or keyword density?

About the Author: Jacob Baadsgaard is the CEO and fearless leader of Disruptive Advertising, an online marketing agency dedicated to using PPC advertising and website optimization to drive sales. His face is as big as his heart and he loves to help businesses achieve their online potential. Connect with him on LinkedIn or Twitter.

from The Kissmetrics Marketing Blog https://blog.kissmetrics.com/content-is-longer-really-better/

Where Are You on the Marketing Maturity Curve? [Report]

marketing benchmark report

Author: Adrienne Whitten

I love data. As a marketer today, you can’t really function without it, and as far as I’m concerned, the more you have, the better. 

When I started at Marketo last fall, I was excited to see how data-driven this company is. We are awash in reports, analytics, spreadsheets, charts, and graphs…which is great! So, I was particularly happy when I learned that we were fielding a benchmark survey to gather insights on how our customers from different company sizes, functional areas, and industries are moving along their own paths to digital transformation.

2017 Marketing Benchmark Report–North America 

As our own CMO, Chandar Pattabhirim says: “The future of marketing relies on our ability to engage with people in a personal and authentic way.” But, the question is–how exactly are marketers doing this today? So, we asked them, and we are proud to offer you the first of what will be an annual survey to give you marketing benchmarks from some of the best marketers in the world.

The report is rich with useful data, so I won’t try to capture it all here, but as a preview, there are six sections to the report:

  1. Marketing Organization & Technology
  2. Usage & Effectiveness
  3. Multi-Channel Strategy
  4. Lifecycle Marketing
  5. Metrics & ROI
  6. Opportunities

How Marketing Technology Is Making an Impact

My favorite section of the report is the one on marketing technology since I’ve been marketing various kinds of software throughout my entire career, and I’m fascinated by how technology continues to both improve and disrupt business processes across the organization, particularly in marketing.

The question I had on my mind, that I now have an answer to is:

How many types of marketing technology does it take to make an impact?

Based on our survey of over 1,300 marketers, the most common answer was 6-10 different technologies. And more than 60% of marketers surveyed have that or more. What’s even more interesting to me is that larger companies don’t necessarily use more technologies. In fact, it was the mid-sized companies (by a hair) that were using more technology. Perhaps they have more pressure to grow, or to be efficient? 

What we do know is that size doesn’t seem to matter when it comes to building a marketing technology stack. Even with small businesses, the majority had more than six technologies. And I actually wonder whether the marketers who said they had five or less were just leaving out pieces that they hadn’t integrated yet.

One thing’s for certain: if you’re using more than six technologies for marketing, you’ll definitely need a hub for a 360-degree view to bring it all together. We, of course, use the Marketo Engagement Platform as ours, and many of our customers also have Marketo at the center of some very impressive marketing stacks.

The great thing about benchmark data is that you can draw your own conclusions and sometimes justify new investments or shifts in strategy.  If you’re in the minority that’s using one or even (gasp!) zero marketing technology, perhaps this survey will help you start a discussion with your manager. There are more than 3,800 companies offering marketing software, according to Scott Brinker at Chief Marketing Technologist–at least until he updates his Marketing Technology Landscape Supergraphic for 2017!

So, dig into our 2017 Marketing Benchmark Report–North America and let us know what you think and what questions you still have about marketing organizations, technology, strategy, channels, metrics, or anything else. 

marketing benchmark report

Where Are You on the Marketing Maturity Curve? [Report] was posted at Marketo Marketing Blog - Best Practices and Thought Leadership. | http://blog.marketo.com

The post Where Are You on the Marketing Maturity Curve? [Report] appeared first on Marketo Marketing Blog - Best Practices and Thought Leadership.

from Marketo Marketing Blog http://blog.marketo.com/2017/01/where-are-you-on-the-marketing-maturity-curve-report.html

The Essential Artificial Intelligence Glossary for Marketers

ai featured image.png

Thank goodness for live chat. If you’re anything like me, you look back at the days of corded phones and 1-800 numbers with anything but fondness.

But as you’re chatting with a customer service agent on Facebook Messenger to see if you can change the shipping address on your recent order, sometimes it’s tempting to ask, am I really talking to a human? Or is this kind, speedy agent really just a robot in disguise?

Believe it or not, this question is older than you might think. The game of trying to decipher between human and machine goes all the way back to 1950 and a computer scientist named Alan Turing.

In his famous paper, Turing proposed a test (now referred to as the Turing Test) to see if a machine’s ability to exhibit intelligent behavior is indistinguishable from that of a human. An interrogator would ask text-based questions to subject A (a computer) and subject B (a person), in hopes of trying to figure out which was which. If the computer successfully fooled the interrogator into thinking it was a human, the computer was said to successfully have artificial intelligence.

turing test.png

Since the days of Alan Turing, there’s been decades and decades of debate on if his test really is an accurate method for identifying artificial intelligence. However, the sentiment behind the idea remains: As AI gains traction, will we be able to tell the difference between human and machine? And if AI is already transforming the way we want customer service, how else could it change our jobs as marketers?

Why Artificial Intelligence Matters for Marketers

As Turing predicted, the concepts behind AI are often hard to grasp, and sometimes even more difficult recognize in our daily lives. By its very nature, AI is designed to flow seamlessly into the tools you already use to make the tasks you do more accurate or efficient. For example, if you’ve enjoyed Netflix movie suggestions or Spotify’s personalized playlists, you’re already encountering AI.

In fact, in our recent HubSpot Research Report on the adoption of artificial intelligence, we found that 63% of respondents are already using AI without realizing it.

When it comes to marketing, AI is positioned to change nearly every part of marketing -- from our personal productivity to our business’s operations -- over the next few years. Imagine having a to-do list automatically prioritized based on your work habits, or your content personalized based on your target customer writes on social media. These examples are just the beginning of how AI will affect the way marketers work.

No matter how much AI changes our job, we’re not all called to be expert computer scientists. However, it’s still crucial to have a basic understanding how AI works, if only to get a glimpse of the possibilities with this type of technology and to see how it could make you a more efficient, more data-driven marketer.


Below we’ll break down the key terms you’ll need to know to be a successful marketer in an AI world. But first, a disclaimer ...

This isn’t meant to be the ultimate resource of artificial intelligence by any means, nor should any 1,500-word blog post. There remains a lot of disagreement around what people consider AI to be and what it’s not. But we do hope these basic definitions will make AI and its related concepts a little easier to grasp and excite you to learn more about the future of marketing.

13 Artificial Intelligence Terms Marketers Need to Know


An algorithm is a formula that represents the relationship between variables. Social media marketers are likely familiar, as Facebook, Twitter, and Instagram all use algorithms to determine what posts you see in a news feed. SEO marketers focus specifically on search engine algorithms to get their content ranking on the first page of search results. Even your Netflix home page uses an algorithm to suggest new shows based on past behavior.

When you’re talking about artificial intelligence, algorithms are what machine learning programs use to make predictions from the data sets they analyze. For example, if a machine learning program were to analyze the performance of a bunch of Facebook posts, it could create an algorithm to determine which blog titles get the most clicks for future posts.

Artificial Intelligence

In the most general of terms, artificial intelligence refers to an area of computer science that makes machines do things that would require intelligence if done by a human. This includes tasks such as learning, seeing, talking, socializing, reasoning, or problem solving.

However, it’s not as simple as copying the way the human brain works, neuron by neuron. It’s building flexible computers that can take creative actions that maximize their chances of success to a specific goal.


Bots (also known as “chatbots” or “chatterbots”) are text-based programs that humans communicate with to automate specific actions or seek information. Generally, they “live” inside of another messaging application, such as Slack, Facebook Messenger, WhatsApp, or Line.

Bots often have a narrow use case because they are programmed to pull from a specific data source, such as a bot that tells you the weather or helps you register to vote. In some cases, they are able to integrate with systems you already use to increase productivity. For example, GrowthBot -- a bot for marketing and sales professionals -- connects with HubSpot, Google Analytics, and more to deliver information on a company’s top-viewed blog post or the PPC keywords a competitor is buying.


Some argue that chatbots don’t qualify as AI because they rely heavily on pre-loaded responses or actions and can’t “think” for themselves. However, others see bots’ ability to understand human language as a basic application of AI.

Cognitive Science

Zoom out from artificial intelligence and you’ve got cognitive science. It’s the interdisciplinary study of the mind and its processes, pulling from the foundations of philosophy, psychology, linguistics, anthropology, and neuroscience.

Artificial intelligence is just one application of cognitive science that looks at how the systems of the mind can be simulated in machines.

Computer Vision

Computer vision is an application of deep learning (see below) that can “understand” digital images.

For humans, of course, understanding images is one of our more basic functions. You see a ball thrown at you and you catch it. But for a computer to see an image and then describe it makes simulating the way the human eye and brain work together pretty complicated. For example, imagine how a self-driving car would need to recognize and respond to stop lights, pedestrians, and other obstructions to be allowed on the road.

However, you don’t have to own a Tesla to experience computer vision. You can put Google’s Quick Draw to the test and see if it recognizes your doodles. Because computer vision uses machine learning that improves over time, you’ll actually help teach the program just by playing.

Data Mining

Data mining is the process of computers discovering patterns within large data sets. For example, an ecommerce company like Amazon could use data mining to analyze customer data and give product suggestions through the “customers who bought this item also bought” box. 

data mining.png

Deep Learning

On the far end of the AI spectrum, deep learning is a highly advanced subset of machine learning. It’s unlikely you’ll need to understand the inner workings of deep learning, but know this: Deep learning can find super complex patterns in data sets by using multiple layers of correlations. In the simplest of terms, it does this by mimicking the way neurons are layered in your own brain. That’s why computer scientists refer to this type of machine learning as a “neural network.”


Machine Learning

Of all the subdisciplines of AI, some of the most exciting advances have been made within machine learning. In short, machine learning is the ability for a program to absorb huge amounts of data and create predictive algorithms.

If you’ve ever heard that AI allows computers to learn over time, you were likely learning about machine learning. Programs with machine learning discover patterns in data sets that help them achieve a goal. As they analyze more data, they adjust their behavior to reach their goal more efficiently.

That data could be anything: a marketing software full of email open rates or a database of baseball batting averages. Because machine learning gives computers to learn without being explicitly programmed (like most bots), they are often described as being able to learn like a young child does: by experience.

Natural Language Processing

Natural language processing (NLS) can make bots a bit more sophisticated by enabling them to understand text or voice commands. For example, when you talk to Siri, she’s transposing your voice into text, conducting the query via a search engine, and responding back in human syntax.

On a basic level, spell check in a Word document or translation services on Google are both examples of NLS. More advanced applications of NLS can learn to pick up on humor or emotion.

natural language processing.png

Semantic Analysis

Semantic analysis is, first and foremost, a linguistics term that deals with process of stringing together phrases, clauses, sentences, and paragraphs into coherent writing. But it also refers to building language in the context of culture.

So, if a machine that has natural language processing capabilities can also use semantic analysis, that likely means it can understand human language and pick up on the contextual cues needed to understand idioms, metaphors, and other figures of speech. As AI-powered marketing applications advance in areas like content automation, you can imagine the usefulness of semantic analysis to craft blog posts and ebooks that are indistinguishable than that of a content marketer.

Supervised Learning

Supervised learning is a type of machine learning in which humans input specific data sets and supervise much of the process, hence the name. In supervised learning, the sample data is labeled and the machine learning program is given a clear outcome to work toward.

Training Data

In machine learning, the training data is the data initially given to the program to “learn” and identify patterns. Afterwards, more test data sets are given to the machine learning program to check the patterns for accuracy. 

Unsupervised Learning

Unsupervised learning is another type of machine learning that uses very little to no human involvement. The machine learning program is left to find patterns and draw conclusions on its own.

Have an artificial intelligence definition to add? Let us know in the comment below.

AI YouTube Live

from HubSpot Marketing Blog https://blog.hubspot.com/marketing/artificial-intelligence-glossary-marketers

Why Design and Coding Academies Need to Get in on Inbound Marketing

Computer on Table -2.png

Supermodels may have ruled the world in the 1990s, but today it's the creatives. Everyone wants in on disruptive, viral, [insert your own buzz word here] intersecting worlds of design and technology. Especially the savvy students who are looking for challenging, fun, and economically rewarding professions.

Design and coding academies are rising to meet these opportunities, but there's a lot of noise swirling around. If you want your academy's message to shout out and reach your prospective students, you need to be using inbound and content marketing.

Fortunately, your creative natures and enterprises are great fits to achieve great results with content marketing and inbound.

You're Already Flush with Content

For a lot of marketing teams, creating quality content on a consistent basis is a big challenge. Not so for design and coding academies. Your faculty and students already create amazing content daily. Student projects, faculty lectures, and documented curricula are all content sources ready to be tapped.

You can video individual lectures from different courses and post clips online. You're naturals for developing some of the best visual content out there. Take some screenshots of the design or coding tools you teach students to use and add some eye-popping captions as a mini-tutorial. Share your faculty's expertise by publishing their work paired with a short back story or interview with that teacher.

Getting creative is your jam. Review the wealth of content your community is already creating through the lens of your content strategy to attract new students. You'll see your opportunities.

Improve Your SEO by Repurposing Your Content

The first step with the inbound methodology is attracting your target audience. This requires an SEO strategy based on relevant keywords and topics. A blog talking about things your personas don't care about isn't going to help your academy get found.

After you've done some SEO research, freshen up blog posts, newsletter articles, and other content you already have. Let's say your research tells you that prospective students are curious about mobile UX design best practices. Now you can add new a summary, keywords and tags to a lecture video or presentation you've posted on this topic that are more relevant. Instead of captioning it "Introductory Lecture on Mobile Design," you can change it to "Mobile UX Design: Learning Best Practices for Mobile Apps" (or whatever your research indicates).

Understanding what your SEO research is telling you will also help you select the most useful and on-point content to repurpose. Your academy does have a wealth of content, but that doesn't mean you want to throw all of it up to see what sticks. You want to make strategic selections of what content to look for, what to create, and how to optimize it for SEO so you make best use of your resources.

Your Content Will Build Your Reputation

The linchpin of finding success with inbound marketing is using your content to build trust with your target personas. Academies and bootcamps don't have the brand recognition that traditional schools enjoy. The waters are also muddied by the explosion in your direct competition.

The number of coding academies grew by nearly 50% in 2016 and is projected to continue growing rapidly. If you want to carve out a spot on the leader board, then you need to boost your brand recognition and make sure your brand connotes credibility and authority.

Prospective students won't trust putting their professional training in your hands if they don't see you as a go-to source on topics related to coding or design. Use your content to build up their confidence that your academy is at the front edge of your field and has the chops to make them employer-magnets after you graduate them.

You can share recent alumni stories that show how easily your graduates transition from students into lucrative careers. Quintupling your salary post-graduation? That's not a bad haul.

Build your reputation as masters of your field by regularly publishing content that addresses its most pressing issues and trends. Publish your academy's own insights on everything from your field's fundamentals to controversial issues. The phrase is cliché, but you need to become a thought leader, not just as an academic institution, but within the professions you're training students to enter.

Your prospective students are out there, dying for clear guidance and answers to their most pressing questions. If you can be resource that answers them, you'll be the academy they choose. 

Efficient Education Marketing Machine - Free Ebook

from HubSpot Marketing Blog https://blog.hubspot.com/marketing/why-design-and-coding-academies-need-to-get-in-on-inbound-marketing

Why 2017 Is the Year to Take Snapchat Seriously [Infographic]


Here at HubSpot, we're not shy about our fondness of Snapchat. Heck, we even devoted an entire day to recruiting via Snapchat. But maybe not everyone is as crazy about the app as we are. Personal feelings aside, it's time to start taking it seriously.

If nothing else, there's something to be said for Snapchat's off-the-charts growth. It's shown a 12% average year-over-year increase in revenue since 2014, and is estimated to earn just short of $1 billion is 2017. Why is it worth so much? Because people are listening and watching. In fact, content posted to the app gets, in total, 10 million views every dayDownload our free Snapchat guide to learn how to use it for your business. 

So, are you ready to start listening and watching, too? If you're not on board with Snapchat yet, have a look at this helpful infographic from our friends at WebpageFX. Think about what these figures might mean to your own organization -- and start snapping.

why-snapchat-matters-to-marketing-final.png free guide: how to use snapchat for business

from HubSpot Marketing Blog https://blog.hubspot.com/marketing/2017-year-to-take-snapchat-seriously

104 Email Marketing Myths, Experiments & Inspiring Tips [Free Guide]

Email Ebook.jpg

As the number of email senders fighting for recipients’ attention continues to climb, many marketers are seeing their engagement rates steadily decrease -- even if they're using an approach that worked well a year or two ago. But that’s the problem: If you haven’t shaken up your email program in over a year, your emails are probably getting stale.

Whether you’re an email marketing veteran or are just getting started, you may be operating under certain common misconceptions about email that have been disproved by research. Even worse, your email may be getting dull due to a lack of experimentation or inspiration. Maybe you’re aware that it’s time to switch up your email marketing, but it can still be hard to know where to begin.

HubSpot and SendGrid are here to help. We’ve joined forces to jumpstart your effort to redefine your email program. In doing so, we created a guide with over 100 rigorously-researched tips on how to avoid common misconceptions, figure out what works for your audience, and bring new inspiration to your email program. Inside, you’ll find:

  • Facts to help you push past the newest and most stubborn email marketing myths
  • Test and experiment ideas you can use to optimize your email campaigns
  • Tips and inspiration to help you identify ways to keep your emails fresh and engaging
  • Extra juicy pro tips you can share with your network with one click

Click here to download 104 Email Marketing Myths, Experiments, and Inspiration

104 email marketing myths, experiments, and inspiration  

from HubSpot Marketing Blog https://blog.hubspot.com/marketing/email-marketing-myths-experiments-tips

How Your Agency Can Use Social Media to Attract New Talent

In 2015, GE ran an amusing ad campaign featuring Owen, a newly hired programmer trying to explain to family and friends why they should be excited about his new job. They were baffled that a programmer would work at what they believed was just a manufacturing company, offering only condolences as he tried to outline the innovative nature of a more modern GE.

The spot was a clever way for GE to spread the word about its position as a digital industrial company, and not just a manufacturing one. Simultaneously, it helped boost the recruiting of young, tech-savvy developers into the fold. After the ad campaign aired, GE’s online recruitment site received 66 percent more visits month after month.

With the exception of GE -- whose goal was to let people know that it does more than manufacture -- the top agencies often offer similar services with little or no variation. Beyond that, what separates the greats is their personalities: their people, their values, their approach to business, and their interactions with their communities.

In today's culture, who you work with is becoming more important than who you work for, and digital marketing is the best way to show prospective employees who you are as an agency, from the bottom up. By aligning digital marketing with HR, marketing agencies have the potential to create a sense of community that draws potential employees, clients, and market influencers closer than ever before.

Blurring the Lines Between HR and Marketing

Before the "Owen" ads brought more attention to GE, recent trends among other companies were already blurring the lines between HR and digital marketing. For instance, leaders are recognizing that employees are the best influencers, and have started leveraging them on social media channels, where employees can share company posts with their networks.

Certain corporate campuses even have designated areas for Instagram moments, allowing people to take photos with specific corporate campus attributes in the backdrop. The trend has spread all the way to the top, with CEOs like Meg Whitman posting pictures of their workspaces to promote more transparency.

By aligning HR's and marketing's methods and goals, you place your agency's HR personnel in a more strategic position to achieve their recruiting goals. It also forces the creation of a single, consistent brand that accurately portrays your agency's values and community.

Using Social Media to Attract New Employees

Most consumers today wouldn't make a large purchase without first researching the brand. Likewise, practical job candidates will likely research multiple agencies’ brands before applying or accepting a job at any of them. In fact, company websites are a top resource for candidates on the job hunt. Keep your agency's online representation consistent -- and therefore more attractive to interested parties -- with these five tips:

1) Highlight your agency's culture on social media.

Every social media platform caters to a different need, and understanding the gains of each will help you use social media to its utmost potential. For instance, use Snapchat to tell quick visual stories that showcase the agency's inner culture. Use Instagram to share photos of daily office life, and Twitter to showcase your agency's unique personality and content.

If your agency doesn't have a strong social media presence in 2017, you not only limit your chances of getting discovered by potential job seekers, you also risk turning off candidates in the process of researching your agency. Job seekers want to be able to get a good sense of what working for your agency is like on a daily basis. Without sharing content on social media that highlights this, they could get the impression that you don't value transparency.

2) Build employee advocacy.

In addition to using your agency's social media presence to showcase your teams's culture, it's important to build up employee advocacy. Social media isn't going away, and empowering employees to use it to the agency's advantage isn't difficult.

Encourage employees to share their own insights about working for your agency on LinkedIn, Facebook, Twitter, Instagram, and other relevant social media platforms. Their extended networks will see their posts and spread awareness of your agency's brand. By leveraging your employee's personal and professional networks, your agency has the potential to reach people you wouldn't have otherwise been able to with your business presence alone.

3) Connect with influencers in your agency's niche.

Digital marketing also allows your recruiting team to more easily interact with potential candidates, as well as the most influential individuals and companies in your market. Like them on Facebook, interact with their tweets, and follow the trends that research shows are proving the most successful.

4) Network freely.

Networking is at the heart of social media and digital marketing, so use media extensively to connect and network with potential candidates, clients, and companies that you work with. Capital One, for example, offers another idea of how increased networking boosted HR performance. Just this year, Capital One’s CIO attended the Grace Hopper Celebration of Women in Technology, specifically promoting Capital One’s digital products and, most importantly, its company culture.

5) Aim to amplify your message.

Connecting and networking with the right influencers also gives you the opportunity to amplify your message to a significantly larger audience. If you build employee advocacy, utilize social platforms to your advantage, and master the art of networking, you’ll see your brand spread exponentially every time someone posts, tweets, or Snapchats something about you. Others will see it, too, including the hundreds of thousands of followers your connections will be able to reach.

When employees share content about their company, those shares receive up to eight times more engagement and are reshared up to 25 times more frequently than the content on the brand’s page. Research shows that such strong engagement and company culture helps companies outperform their peers in "profitability, productivity, customer satisfaction, employee turnover,”"and more.

And by participating in social media and mobile apps, companies like Target have been able to attract and retain top talent while demonstrating its success with digital marketing. Because its digital marketing efforts are so extensive, those seeking new jobs already have an idea of what Target’s initiatives are.

GE’s engagement campaign, along with those of many other companies, offer a glimpse into how focusing more on value and results can boost an agency's image, performance, and recruitment efforts across the board. Follow their example, introduce your agency's personality to the world, and let top-level talent know who you are and how well they would fit into your agency's culture.


from HubSpot Marketing Blog https://blog.hubspot.com/marketing/agency-social-media-new-talent

Monday, 30 January 2017

Your Customers Don’t Care About Your Product: They Care About Progress

It’s true. Your customers don’t care about your product. Don’t worry, they don’t care about your competitor’s products either. Your customers don’t care about any products. Thankfully, your customers do care about something, which is why they buy your product.

Your customers care about the progress they will make as a result of using your product.

As Growth Marketers and Product Builders, it’s our job to make sure customers understand how our product will change them for the better. Then we can create an efficient customer funnel that turns potential customers into loyal, repeat customers. We use data to optimize each stage of the user lifecycle. However, it’s easy to get bogged down in user data and product features. When we lose sight of whether or not our customers have realized the better life we’ve promised, the customer becomes stuck in our funnel and we lose our customer.

By understanding the progress our customers are hoping to make, we can increase conversions at any stage of the user lifecycle: Acquisition, Activation, Retention, Revenue, and Referral.

Customers Buy Progress

Customers actually don’t buy your product. They aspire to be more awesome, and they believe your product will help them get there. They buy the vision of themselves being more awesome. This visual from Samuel Hulick explains why customers buy products.


Customer progress is a key concept of Jobs To Be Done (JTBD). I was first introduced to the above Super Mario graphic by Alan Klement’s book on JTBD, When Coffee & Kale Compete. The JTBD helps us focus on the customer’s desire to make life better and the progress they are hoping to achieve. With this focus, we can grow faster and build better products.

Alan lists 10 JTBD principles in his book. We’ll focus on two.

  1. Customers don’t want your product or what it does; they want help making their lives better.
  2. Solutions and Jobs should be thought of as parts of system that work together to deliver progress to customers.

The rest of this article will show how growth and product teams at B2B and B2C orgs have used these two principles to create better top of funnel marketing messages and increase LTV and retention through progress-centric product updates.


  • Create ads and content that focus on progress. Progress is overcoming an emotional struggle to make one’s life better.
  • Make sure you have the right understanding of progress for your audience.

Case Study

TownHound was a dual-sided marketplace that was picked up by Google just 8 months after launch. It was a mobile app that brought restaurants more patrons during off-peak hours by offering discounts to its users. In just 3 months, TownHound was able to sign on 6x more restaurant partners in the San Jose, CA region than it’s behemoth competitor Groupon.

This is a huge accomplishment because two-sided marketplaces are tricky. You need a high volume of Demand (customers redeeming TownHound deals) in order to build up Supply (restaurant partners that offer deals). Bryan Solar, Co-Founder of TownHound, understood the progress that his customers were hoping to achieve, which he used to guide his paid acquisition strategy.

Early on, his Facebook and Instagram ads were just doing okay. TownHound was bringing on new users, but they weren’t sticky. Users would download the app, redeem a single deal, and then poof, they were gone. He wasn’t acquiring the right users.

He needed more quality users in order to satisfy the balance of his two-sided marketplace. He decided to interview customers that had redeemed more than one deal.

Bryan’s interviews led to a huge discovery. He learned that his best users were dating app users. His repeat customers were using TownHound while on first, second, or third dates.

  • TownHound’s Restaurant partners want more patrons during slow hours: Monday – Thursday nights.
  • Dating app users typically meet for dinner during the week because weekends are too precious to waste on a potentially traumatic first Tinder date experience.
  • It’s a match!

Bryan learned that his best customers didn’t use TownHound to get discounts on meals. They use TownHound in order to find the right person for a relationship. He also understood that his customers didn’t necessarily love to go on dates. Dates are exciting, but they’re also stressful and expensive. For many, dates are a necessary evil.

When TownHound’s ad content changed, quality user growth and restaurant partner growth rapidly increased.

  • Before: Ads focused on saving money on dinner.
  • After: Ads focused on relieving the pain of going on expensive dates.

Bryan found his core audience and tailored acquisition efforts to focus on their progress, rather than the function of his product.


  • Re-highlight the progress that was promised in acquisition.
  • Link onboarding process to progress or overcoming a struggling moment.

Samuel Hulick, the creator of the Super Mario graphic above, runs UserOnboard.com – a site dedicated to onboarding and activating users. He sat down with Ryan Singer of Basecamp and discussed how JTBD can be applied to the onboarding process. Ryan noticed a change in the way he approaches onboarding when customer progress is his goal.

“That’s really interesting to look through a Jobs-to-Be-Done lens, because then the question becomes ‘what can we do to help this person decide that this is the right tool for them?’ That’s a very different task for the designer than ‘how can I thoroughly explain the mechanisms of my products?’”

Case Study

Le Tote is an e-commerce subscription service for women that delivers a personalized box of clothes directly to their customer’s doorstep. Le Tote’s monthly subscription lets customers wear the clothes they receive as long as they want, and then receive a new box in exchange for sending back their previously worn garments. Le Tote is old-school Netflix for women’s clothes.

Le Tote uses style preferences, ratings of previously shipped garments, and sizing info to curate a box of clothes for each customer. In theory, the more you use Le Tote, the better the service is at matching you with clothes you’ll love.

However, Le Tote doesn’t have a history of customer feedback to leverage when shipping a box to a first time user. It’s critical that Le Tote gets the first box right because it’s essentially a “test drive.” Send a bad box to a first time user and the likelihood of them sticking around for a second box is slim.

If the first box is critical to a new user adopting Le Tote, then the onboarding process incredibly important. Le Tote needs to gather as much info about their customer’s style preferences during onboarding as possible in order to make a great first impression, without bombarding users with tedious onboarding tasks. So how does Le Tote get users through a lengthy onboarding process without seeing a drop in conversion?

Here are two steps in the process. The user is met with easy to answer questions about occasions that are hard to dress for and weather, which is uncontrollable.


Now, think about the progress that Le Tote’s customers are hoping to achieve. They want access to new, trendy clothes in order to feel confident in situations that matter. Buying a new garment from a traditional e-commerce site for every special occasion can get expensive. Plus, ‘that perfect new shirt’ tends to lose it’s magic after a few wears and a couple months in the closet. A Le Tote customer wants to feel confident in new clothes while maintaining wallet-friendly peace of mind.

Le Tote communicates progress by highlighting a few occasions that customers have struggled to get ready for in the past. This reminds the user why she’s jumping through onboarding hoops — to overcome these struggling moments and make progress. This is easily forgotten when onboarding focuses too much on the product and not the user, and we activate fewer users as a result.


  • Use data to track changes in usage behavior.
  • Interview customers when behaviors change to understand if customers are making progress.
  • Make product changes when features are standing in the way of progress.

Your marketing and sales efforts have promised the solution to a struggling moment, and your customer has chosen your product to take them from ‘Normal Mario’ to ‘Awesome Fireball Throwing Mario’.

If you don’t deliver progress, your customers will churn. How do we know that we’re delivering progress?

Behavioral data helps us understand which features are being used and how often customers are coming back. This data is incredibly actionable, but it doesn’t tell us if our customers are actually making progress.

Customer interviews are key to improving retention. Data will help uncover behavior changes of our customers, but interviews will reveal the why behind those changes. Alan Klement gives us examples of behavior changes to investigate through customer interviews: “When someone purchases a product, begins to use a new product, stops using a product, suddenly uses a product more, and suddenly uses a product less.” (p. 190).

Case Study

Wade Warren, Co-Founder of Resource, is using JTBD to guide the product roadmap of his candidate sourcing platform. Resource finds candidates and then writes personalized, custom outreach that comes from an internal recruiter’s identity. It’s a platform that helps recruiters with limited hiring bandwidth to build teams faster.

Resource has a feature where new candidates are automatically screened in – which means that they are contacted without explicit recruiter approval.

Wade noticed a decline in usage in the product. People were signing up for Resource, adding a number of roles and using it for a few weeks, before suddenly pausing their roles and stopping usage. His team interviewed customers to understand the root of the issue. One of his interviewees was a user that had stopped using Resource, but then began to use it again.

She got responses from a few candidates who had been automatically screened and was forced to speak with candidates that weren’t a good fit, which caused anxiety. She paused her Resource roles and went back to contacting candidates through Linkedin.

Then, she saw a recruiter on her team using a buried feature that allowed her to individually pick the candidates to be contacted: “I saw Sarah clicking approve and asked, ‘what is that’. She explained to me that you can screen each individual candidate in Resource if you change this setting.” She immediately went back to Resource.

Wade heard this same story from a few different customers, so his team made a product change. Automated screening was switched from a default feature to a feature that must be toggled on by the user. Once this switch was made, he saw usage go up and churn decrease across all of his customers.

Although the original feature performed its intended function of reducing work for his customers, it caused anxiety. Wade’s interviews helped him better understand the progress his customers wanted to achieve: “We didn’t think that giving our customers more work in the product would mean them making more progress, but counterintuitively did.”


  • You’ve already delivered some progress. Find ways to deliver more progress.
  • Add features that make progress easier to achieve.

Case Study

When Bryan’s team at TownHound focused their acquisition strategy on dating app users, he started acquiring quality users. He noticed an increase in quality feedback as a result. The feedback he got informed a product update that increased both retention and revenue because it helped to deliver more progress for his users.

TownHound rolled out a new feature that is similar to a feature in the expense reporting app, Expensify. The new feature allowed users to redeem their discounts by snapping a photo of the paper receipt in the app after the meal was over. Before this feature, the user could only redeem a discount by showing a waiter or waitress a confirmation page in the app during the meal.

At its surface, this new feature provides TownHound users more flexibility when redeeming their discounts while at dinner. It could even allow a user to redeem a discount after leaving the restaurant if they forgot to show their waiter the in app coupon.

The new snap-a-photo feature does offer flexibility, but more importantly, it contributes to progress for users who are on dates. Dates are stressful because first, second, and third impressions matter. We want to impress the person sitting across the table. Although most would agree that living frugally where we can is an admirable characteristic, a first date typically isn’t the place to tout this trait. The new snap-a-photo feature allows a TownHound user to redeem their discount without their date knowing. They don’t have to worry about being perceived as cheap!

TownHound is used to help create a meaningful dining experience for users that are looking for a new relationship. Bryan’s team at TownHound had a deep understanding of the progress his customers were hoping to make and the role that TownHound played in delivering that progress. If he had viewed his product simply as a “deals app”, he wouldn’t have been able to make a key product update that brought in more revenue as more users redeemed second, third, and fourth deals.


  • Use incentives that align with progress to influence referrals.
  • Don’t assume increased credits, storage, or currency equals progress.

If you help your customers make progress, it’s likely that their friends will hear about your product. Unfortunately, word of mouth alone won’t raise our K Factor above 1, so we must encourage referrals. Social networks like Linkedin and Twitter have had huge wins through productized referrals. Josh Elman explains how his teams at Twitter and Linkedin created winning referral programs in this video called 3 Growth Hacks: The Secrets To Driving Massive User Growth:

Linkedin and Twitter are social networks, so the “better with friends” referral play works incredibly well. What about products that aren’t social? How do we build an effective referral program for customers?

The common referral incentive we see looks like this: “If you use my referral code when you sign up, we each get $10 off our purchase.” Sometimes the reward for the referrer is delayed until the new user makes a purchase, but there is usually a give and a get incentive. In other words, “I give you $10, I get $10.”

Case Study

Le Tote used the standard give/get strategy early on, but couldn’t find the right mix of give/get secret sauce in order for their referral program to take off. Le Tote is not a social product.

Before working as Director of Growth at Le Tote, Luke Langon implemented referral programs at Lyft and two other mobile apps that he co-founded. Luke interviewed his customers in order to find out what give/get incentive would work best. His goal was to increase the percentage of users participating in referrals.

He learned that many of his customers weren’t referring friends because their give of $25 only covered half the cost of their friend’s Le Tote box. This means that their friend would still have to pay in order to test drive Le Tote. His customers didn’t like the idea of recommending a new product that forced their friends to pay. The get of $15 was intended to incentivize a referral, but not all customers were motivated by saving money on their next Le Tote box.

Le Tote’s referral program became a top acquisition channel when it shifted from ‘Give $25/Get $15’, to ‘Give a free box, Get nothing.’ Referrals achieved the lowest Cost Per Acquisition compared to all other acquisition channels and ranked second in volume of new subscribers.

Le Tote’s subscription does help customers save money on new clothes, but this isn’t how they make progress. Le Tote’s customers make progress by feeling confident during important occasions involving people they want to maintain or create a healthy relationship with. This progress is more important than saving money, which is why the old referral program didn’t work for many customers.

How to start using progress to benefit you and your customers

Customer interviews will help you discover what progress means to your customers. Remember, progress is overcoming an emotional struggle to make one’s life better. You need to uncover an emotional hurdle that has nothing to do with your product. When you use progress as your guide, you will create more wins throughout the entire customer lifecycle.

If you’re interested in learning more about Jobs To Be Done, JTBD.info is a great place to start. It’s run by Alan Klement, who’s book I linked at the beginning of this article.

If you have any questions or thoughts, please comment below or feel free to reach out!

About the Author: Chris Brophy likes to drive growth for consumer-focused startups. He’s currently consulting startups on growth strategy at Tradecraft and exploring his next adventure. If you’d like to chat about growth, JTBD, or live music, reach him at cabrophy89[at]gmail[dot]com.

from The Kissmetrics Marketing Blog https://blog.kissmetrics.com/customers-dont-care-about-your-product/

3 Ways to Make Controversial Content Work for Your Brand

how to make controversial content work

Author: Andrea Lehr

Most brands avoid controversy like the plague, in large part because on the surface it does seem ill-advised. Who would want to associate their name with something Merriam-Webster defines as an “argument that involves many people who strongly disagree about something?”

However, there are some who choose to stir the pot because they know something others might not fully understand yet. Controversy attracts attention because it triggers an emotional response, which is essential in generating massive engagement. It encourages audiences to click, read, and share the content.

One of the most difficult parts of controversial content, though, is execution. In this post, I’ll introduce three ways you can approach controversial content and how to determine which one is right for your brand:

3 Types of Controversial Content

The first thing you need to understand is that controversy for the sake of controversy is not going to provide value to your brand or target audience. To get big results, your content needs to get people talking in a way that can still benefit both your brand and consumers. Below are a few different approaches to controversial content along with examples that show how each type can positively relate back to a brand:

1. Disprove an easily held assumption by offering surprising or unexpected content. 

These ideas typically force audiences to rethink a common belief or rely heavily on a shocking visual. Consider “Hotel Hygiene Exposed,” which we created for our client Travelmath. A few members of our team went visited 9 different hotels in order to gather 36 samples from various surfaces. We sent the results to a third-party lab and found out that the nicest hotels are actually the dirtiest–driving more than 700 media pickups and 24,000 social shares.

controversial content about hotel hygiene

What made this campaign work is that although the results are controversial, the content still relates back to the services offered by the brand–specifically any visitors using Travelmath to find hotels for a future trip.

2. Take advantage of our innate interest in taboo subjects. 

These ideas center around topics that aren’t often discussed, which is why this type of content typically does incredibly well. A great example is the Ad Council’s incredibly successful “Love Has No Labels” video. The idea was quite simple: Using an X-ray machine, passersby saw different sets of skeletons showing various signs of affection to one another before revealing their sexuality–forcing viewers to rethink any unconscious biases they might have.

The video worked because it connected directly to the organization’s mission, which is to “produce, distribute, and promote campaigns that improve everyday lives.” And the ability to take a closer look at someone else’s differences–an often taboo subject–helped the video generate more than 57 million views on YouTube, becoming the second most-viewed community and activism campaign of all time.

3. Stir up a debate. 

Most controversial ideas would fall under this umbrella, with a majority of these campaigns presenting data from both sides of the fence so that readers can drive the discussion. A great example is real estate research site Adobo’s “America’s Most P.C. and Prejudiced Places” analysis, which revealed which areas have the most politically and non-politically correct tweets. The idea was controversial, but it worked because it answered one question everyone has when looking for a new place to live: Will I get along with my neighbors? This helped ignite a discussion that drove more than 620 placements and over 67,000 social shares.

How to Make Controversy Work for Your Brand

Although it sounds counterintuitive, most brands would be foolish to rule out controversy entirely. However, the examples above prove that these types of campaigns walk a very fine line. To maximize results, you want to stir the pot without having everything boil over since research has shown that too much controversy actually discourages engagement.

In one of their earlier studies together, researchers Jonah Berger and Zoey Chen analyzed more than 200 articles to see how controversy impacts engagement levels. Their results revealed that while low-level controversy encourages discussion among audiences, anything beyond a moderate level of controversy actually decreases the likelihood of high engagement.

So how do you determine which type of controversy is right for your brand?

Remember that all of your marketing efforts support a consistent image, and controversial content is no exception. Not every brand is edgy, so you’ll want to figure out what your audience wants before moving forward with any polarizing idea. Below are a few questions you’ll want to answer pre-production:

  • Does your audience expect controversy from you? This isn’t necessarily a yes or no question; instead, you want to figure out whether or not your audience is looking for something different. Have you seen a dip in traffic, for instance, on your blog? This could be an indicator that your content is becoming too predictable.
  • Have your competitors done anything controversial before, and if so, did it work for them? If you’re not ready to take the plunge into controversial waters, see what your competitors have put out there. Tying back in the Abodo campaign, although some brands within the real estate vertical might think they’re only limited to conservative content, the massive amount of engagement from the P.C. campaign prove otherwise.  
  • Is the proposed content authentic? Your brand shouldn’t produce something to play devil’s advocate simply for shock value–if you voice opinions you don’t hold, for instance, understand that you will be held accountable to them later. To avoid this mess later on, you should simply let the content speak for itself.

With so much information readily available to audiences across the web, some brands don’t have the luxury to take a conservative approach to content marketing for every campaign–particularly if their goal is to generate high levels of awareness. By offering authentic, balanced, and somewhat surprising content through a controversial campaign, your brand can invite engagement from both familiar faces as well as new audiences–a strategic move that will bring you a whole new level of exposure.

Have you ventured into the world of controversial content? Share what other tips and tricks would you recommend in the comments below!


3 Ways to Make Controversial Content Work for Your Brand was posted at Marketo Marketing Blog - Best Practices and Thought Leadership. | http://blog.marketo.com

The post 3 Ways to Make Controversial Content Work for Your Brand appeared first on Marketo Marketing Blog - Best Practices and Thought Leadership.

from Marketo Marketing Blog http://blog.marketo.com/2017/01/3-ways-to-make-controversial-content-work-for-your-brand.html

A Brief History of Productivity: How Getting Stuff Done Became an Industry


Anyone who’s ever been a teenager is likely familiar with the question, "Why aren’t you doing something productive?” If only I knew, as an angsty 15-year-old, what I know after conducting the research for this article. If only I could respond to my parents with the brilliant retort, "You know, the idea of productivity actually dates back to before the 1800s." If only I could ask, "Do you mean 'productive' in an economic or modern context?"

Back then, I would have been sent to my room for "acting smart." But today, I'm a nerdy adult who is curious to know where today's widespread fascination with productivity comes from. There are endless tools and apps that help us get more done -- but where did they begin?  Download our complete guide here for more tips on improving your productivity.

If you ask me, productivity has become a booming business. And it's not just my not-so-humble opinion -- numbers and history support it. Let's step back in time, and find out how we got here, and how getting stuff done became an industry.

What Is Productivity?

The Economic Context

Dictionary.com defines productivity as “the quality, state, or fact of being able to generate, create, enhance, or bring forth goods and services.” In an economic context, the meaning is similar -- it’s essentially a measure of the output of goods and services available for monetary exchange.

How we tend to view productivity today is a bit different. While it remains a measure of getting stuff done, it seems like it’s gone a bit off the rails. It’s not just a measure of output anymore -- it’s the idea of squeezing every bit of output that we can from a single day. It’s about getting more done in shrinking amounts of time.

It’s a fundamental concept that seems to exist at every level, including a federal one -- the Brookings Institution reports that even the U.S. government, for its part, “is doing more with less” by trying to implement more programs with a decreasing number of experts on the payroll.

The Modern Context

And it’s not just the government. Many employers -- and employees -- are trying to emulate this approach. For example, CBRE Americas CEO Jim Wilson told Forbes, “Our clients are focused on doing more and producing more with less. Everybody's focused on what they can do to boost productivity within the context of the workplace.”

It makes sense that someone would view that widespread perspective as an opportunity. There was an unmet need for tools and resources that would solve the omnipresent never-enough-hours-in-the-day problem. And so it was monetized to the point where, today, we have things like $25 notebooks -- the Bullet Journal, to be precise -- and countless apps that promise to help us accomplish something at any time of day.

But how did we get here? How did the idea of getting stuff done become an industry?

A Brief History of Productivity


Productivity and Agriculture

In his article “The Wealth Of Nations Part 2 -- The History Of Productivity,” investment strategist Bill Greiner does an excellent job of examining this concept on a purely economic level. In its earliest days, productivity was largely limited to agriculture -- that is, the production and consumption of food. Throughout the world around that time, rural populations vastly outnumbered those in urban areas, suggesting that fewer people were dedicated to non-agricultural industry.

Screen Shot 2017-01-12 at 10.29.31 AM.png Source: United Nations Department of International Economic and Social Affairs

On top of that, prior to the 1800s, food preservation was, at most, archaic. After all, refrigeration wasn’t really available until 1834, which meant that crops had to be consumed fast, before they spoiled. There was little room for surplus, and the focus was mainly on survival. The idea of “getting stuff done” didn’t really exist yet, suppressing the idea of productivity.

The Birth of the To-Do List

It was shortly before the 19th century that to-do lists began to surface, as well. In 1791, Benjamin Franklin recorded what was one of the earliest-known forms of it, mostly with the intention of contributing something of value to society each day -- the list opened with the question, “What good shall I do this day?”

Screen Shot 2017-01-12 at 10.29.31 AM.png Source: Daily Dot

The items on Franklin’s list seemed to indicate a shift in focus from survival to completing daily tasks -- things like “dine,” “overlook my accounts,” and “work.” It was almost a precursor to the U.S. Industrial Revolution, which is estimated to have begun within the first two decades of the nineteenth century. The New York Stock & Exchange Board was officially established in 1817, for example, signaling big changes to the idea of trade -- society was drifting away from the singular goal of survival, to broader aspirations of monetization, convenience, and scale.

1790 - 1914

The Industrial Revolution actually began in Great Britain in the mid-1700s, and began to show signs of existence in the U.S. in 1794, with the invention of the cotton gin -- which mechanically removed the seeds from cotton plants. It increased the rate of production so much that cotton eventually became a leading U.S. export and “vastly increased the wealth of this country," writes Joseph Wickham Roe.

Screen Shot 2017-01-12 at 1.55.09 PM.png Source: Gregory Clark

It was one of the first steps in a societal step toward automation -- to require less human labor, which often slowed down production and resulted in smaller output. Notice in the table below that, beginning in 1880, machinery added the greatest value to the U.S. economy. So from the invention of the cotton gin to the 1913 unveiling of Ford’s inaugural assembly line (note that “automotive” was added to the table below in 1920), there was a common goal among the many advances of the Industrial Revolution: To produce more in -- you guessed it -- less time.

Screen Shot 2017-01-12 at 2.19.12 PM.png Source: Joel Mokyr

1914 - 1970s

Pre-War Production

Screen Shot 2017-01-12 at 2.25.52 PM.png Source: Joel Mokyr

Advances in technology -- and the resulting higher rate of production -- meant more employment was becoming available in industrial sectors, reducing the agricultural workforce. But people may have also become busier, leading to the invention and sale of consumable scheduling tools, like paper day planners.

According to the Boston Globe, the rising popularity of daily diaries coincided with industrial progression, with one of the earliest known to-do lists available for purchase -- the Wanamaker Diary -- debuting in the 1900s. Created by department store owner John Wanamaker, the planner’s pages were interspersed with print ads for the store’s catalogue, achieving two newly commercial goals: Helping an increasingly busier population plan its days, as well as advertising the goods that would help to make life easier.

Wanamaker_Diary_TP2 (1).jpg Source: Boston Globe

World War I

But there was a disruption to productivity in the 1900s, when the U.S. entered World War I, from April 1917 to the war’s end in November 1918. Between 1918 and at least 1920 both industrial production and the labor force shrank, setting the tone for several years of economic instability. The stock market grew quickly after the war, only to crash in 1929 and lead to the 10-year Great Depression. Suddenly, the focus was on survival again, especially with the U.S. entrance into World War II in 1941.

GDP_depression.svg Source: William D. O'Neil

But look closely at the above chart. After 1939, the U.S. GDP actually grew. That’s because there was a revitalized need for production, mostly of war materials. On top of that, the World War II era saw the introduction of women into the workforce in large numbers -- in some nations, women comprised 80% of the total addition to the workforce during the war.

World War II and the Evolving Workforce

The growing presence of women in the workforce had major implications for the way productivity is thought of today. Starting no later than 1948 -- three years after World War II’s end -- the number of women in the workforce only continued to grow, according to the U.S. Department of Labor.

That suggests larger numbers of women were stepping away from full-time domestic roles, but many still had certain demands at home -- by 1975, for example, mothers of children under 18 made up nearly half of the workforce. That created a newly unmet need for convenience -- a way to fulfill these demands at work and at home.

Once again, a growing percentage of the population was strapped for time, but had increasing responsibilities. That created a new opportunity for certain industries to present new solutions to what was a nearly 200-year-old problem, but had been reframed for a modern context. And it began with food production.

1970s - 1990s

The 1970s and the Food Industry

With more people -- men and women -- spending less time at home, there was a greater need for convenience. More time was spent commuting and working, and less time was spent preparing meals, for example.

The food industry, therefore, was one of the first to respond in kind. It recognized that the time available to everyone for certain household chores was beginning to diminish, and began to offer solutions that helped people -- say it with us -- accomplish more in fewer hours.

Those solutions actually began with packaged foods like cake mixes and canned goods that dated back to the 1950s, when TV dinners also hit the market -- 17 years later, microwave ovens became available for about $500 each.

But the 1970s saw an uptick in fast food consumption, with Americans spending roughly $6 billion on it at the start of the decade. As Eric Schlosser writes in Fast Food Nation, “A nation’s diet can be more revealing than its art or literature.” This growing availability and consumption of prepared food revealed that we were becoming obsessed with maximizing our time -- and with, in a word, productivity.

The Growth of Time-Saving Technology

Technology became a bigger part of the picture, too. With the invention of the personal computer in the 1970s and the World Wide Web in the 1980s, productivity solutions were becoming more digital. Microsoft, founded in 1975, was one of the first to offer them, with a suite of programs released in the late 1990s to help people stay organized, and integrate their to-do lists with an increasingly online presence.

Screen Shot 2017-01-13 at 9.58.58 AM.png Source: Wayback Machine

It was preceded by a 1992 version of a smartphone called Simon, which included portable scheduling features. That introduced the idea of being able to remotely book meetings and manage a calendar, saving time that would have been spent on such tasks after returning to one’s desk. It paved the way for calendar-ready PDAs, or personal digital assistants, which became available in the late 1990s.

By then, the idea of productivity was no longer on the brink of becoming an industry -- it was an industry. It would simply become a bigger one in the decades to follow.

The Early 2000s

The Modern To-Do List

Once digital productivity tools became available in the 1990s, the release of new and improved technologies came at a remarkable rate -- especially when compared to the pace of developments in preceding centuries.

In addition to Microsoft, Google is credited as becoming a leader in this space. By the end of 2000, it won two Webby Awards and was cited by PC Magazine for its “uncanny knack for returning extremely relevant results." It was yet another form of time-saving technology, by helping people find the information they were seeking in a way that was more seamless than, say, using a library card catalog.

In April 2006, Google Calendar was unveiled, becoming one of the first technologies that allowed users to share their schedules with others, helping to mitigate the time-consuming exchanges often required of setting up meetings. It wasn’t long before Google also released Google Apps for Your Domain that summer, providing businesses with an all-in-one solution -- email, voicemail, calendars, and web development tools, among others.

Screen Shot 2017-01-13 at 6.35.20 AM.png Source: Wayback Machine

During the first 10 years of the century, Apple was experiencing a brand revitalization. The first iPod was released in 2001, followed by the MacBook Pro in 2006 and the iPhone in January 2007 -- all of which would have huge implications for the widespread idea of productivity.

2008 - Present

Search Engines That Talk -- and Listen

When the iPhone 4S was released in 2011, it came equipped with Siri, “an intelligent assistant that helps you get things done just by asking.” Google had already implemented voice search technology in 2008, but it didn’t garner quite as much public attention -- most likely because it required a separate app download. Siri, conversely, was already installed in the Apple mobile hardware, and users only had to push the iPhone’s home button and ask a question conversationally.

But both offered further time-saving solutions. To hear weather and sports scores, for examples, users no longer had to open a separate app, wait for a televised report, or type in searches. All they had to do was ask.

By 2014, voice search had become commonplace, with multiple brands -- including Microsoft and Amazon -- offering their own technologies. Here’s how its major pillars look today:


The Latest Generation of Personal Digital Assistants

With the 2014 debut of Amazon Echo, voice activation wasn’t just about searching anymore. It was about full-blown artificial intelligence that could integrate with our day-to-day lives. It was starting to converge with the Internet of Things -- the technology that allowed things in the home, for example, to be controlled digitally and remotely -- and continued to replace manual, human steps with intelligent machine operation. We were busier than ever, with some reporting 18-hour workdays and, therefore, diminishing time to get anything done outside of our employment.

Here was the latest solution, at least for those who could afford the technology. Users didn’t have to manually look things up, turn on the news, or write down to-do and shopping lists. They could ask a machine to do it with a command as simple as, “Alexa, order more dog food.”

Of course, competition would eventually enter the picture and Amazon would no longer stand alone in the personal assistant technology space. It made sense that Google -- who had long since established itself as a leader in the productivity industry -- would enter the market with Google Home, released in 2016, and offering much of the same convenience as the Echo.

Of course, neither one has the same exact capabilities as the other -- yet. But let’s pause here, and reflect on how far we’ve come.

Where We Are Now...and Beyond

We started this journey in the 1700s with Benjamin Franklin’s to-do list. Now, here we are, over two centuries later, with intelligent machines making those lists and managing our lives for us.

Have a look at the total assets of some leaders in this space (as of the writing of this post, in USD):

Over time -- hundreds of years, in fact -- technology has made things more convenient for us. But as the above list shows, it’s also earned a lot of money for a lot of people. And those figures leave little doubt that, today, productivity is an industry, and a booming one at that.

How do you view productivity today, and what’s your approach to it? Let us know in the comments.

Productivity Guide

from HubSpot Marketing Blog https://blog.hubspot.com/marketing/a-brief-history-of-productivity