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April 16, 2018

14 Signals for LinkedIn Best Practices in Content Optimization

By reading the article “Serving Top Comments in Professional Social Networks” on the LinkedIn engineering blog I stumbled upon the signals that the LinkedIn machine-learning model looks at to rank top comments on the platform. While this seems to be limited to comments – I argue – those signals can teach us how LinkedIn‘s team think about the relevance of content. Thus, in a way, it makes you better at communicating on LinkedIn.

In short, my argument is this: if the LinkedIn team decided to use the following signals for its machine-learning model to rank top comments, those signals might actually be relevant also for other kinds of contents on the platform.

However, I want to repeat – here I must use the conditional – those “might” be the signals LinkedIn algorithms look at in general when ranking content.

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The 14 Signals to take into account when publishing content over LinkedIn

In its machine-learning model LinkedIn ranks 14 signals to allow top comments to be shown:

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Source: engineering.linkedin.com

The content in the comment is judged by using four parameters:

Commenter (is this someone I care about?)

connected / following
edge affinity / connections strength
Influencer
profile views
locale & industry
likes & replies received in the past

We have commenter features that characterize each commenter’s reputation and popularity (i.e., their profile view counts, influencer status, etc.). We also match the commenter and the viewers on the basis of industry, location, and other shared attributes. At LinkedIn, we have access to various mature machine-learned signals to represent the engagement affinity between two members. We take into account their connection/follow relationships, their profile similarity, and past interactions on the feed. These signals are crucial inputs that help us select high quality comments that are personalized to each viewer.

Content (is this about something I’m interested about?)

length of comment
language of comment
mentions & #hashtags
mentions me, my connections, an influencer

As far as the actual comment content is concerned, we leverage our in-house Natural Language Processing (NLP) library to characterize the language, the comment length, the grammatical structure, the presence/absence of hashtags, and other content features. We also attempt to infer whether the comment includes mentions of LinkedIn members or other entities.

Popularity (does the community think this is valuable?)

likes & replies overall
likes & replies from people in the industry, by influencers, by author
unique repliers in the thread

Social engagement features generated on the feed are segmented by industries for the machine learning model to capture when a particular comment might only be popular for a segment of members.

Time (is it fresh?)

Comment freshness features capture recent actions on the comment. We capture the timestamp of comment creation, the last reply, and the last like. Viewers have a tendency to read fresh comments or recently discussed topics.

LinkedIn looks at over 100 features for online ranking

We’ve only scratched the surface here. There are close to 100 features that we capture and use in online ranking.

Those features might turn into thousands of signals. In fact, as soon as you access to your LinkedIn feed, a machine learning algorithm identifies in a fraction of a second the posts that are most relevant to you. This means the algorithm has to be able to rank tens of thousands of posts in that fraction of a second.

As specified by LinkedIn engineering team:

Flowing into this algorithm are thousands of signals that help us understand a member’s preferences and enable us to personalize the feed for a specific member. These signals fall into three broad categories:

Identity: Who are you? Where do you work? What are your skills? Who are you connected with?
Content: How many times was the update viewed? How many times was it “liked”? What is the update about? How old is it? What language is it written in? What companies, people, or topics are mentioned in the update?
Behavior: What have you liked and shared in the past? Who do you interact with most frequently? Where do you spend the most time in your news feed?

Thus, based on three major/broad categories, related to your identity (company, skills, connections), content (likes, comments, share for that update), and behavior (for instance, who you interact with more frequently) that is how LinkedIn builds your feed.

What are other signals?

These range from well-known metrics, like time spent reading, to insights from your social graph. We also incorporate a variety of findings from other sources in our models, such as user experience research.

One indication is given by the LinkedIn engineering team regarding what’s next for LinkedIn feed and that in some ways answers to those who assert that LinkedIn is becoming way more like Facebook is this:

Creator-side optimization: Many recommendation systems focus on optimizing for discreet, short-term gains in member activities (click, like, share) as a proxy for member engagement and value. In the future, we’re investing in models that specifically optimize for members who create high-quality content on LinkedIn over time.

Source: engineering.linkedin.com

If high-quality content remains the long-term focus of LinkedIn, then you can expect a high ROI from investing time and resources on this platform.

Key takeaway

In this article, we’ve looked at some of the signals used by LinkedIn machine-learning model to rank top comments. If those signals are applied to classify top comments they might also be used to rank online content on LinkedIn – I argue.

Of course, as LinkedIn AI-powered algorithm built on top of a vast knowledge graph, becomes smarter the more signals it might take into account. In fact, as pointed out by the LinkedIn engineering team, as of now there are thousands of signals taken into account to personalize the feed and a hundred features used for online ranking.

Looking at the signals, LinkedIn engineering team takes into account for ranking top comments also help you understand the aim of the platform, thus making you more effective at communicating on LinkedIn.

Some of the interesting aspects and questions to ask when posting on LinkedIn are related to content quality. In fact, as LinkedIn will invest more resources at looking for quality of content rather than traditional signals used on social media (likes and shares), it becomes critical to assess whether you are publishing quality content.

How can that be defined according to what we’ve seen in this article?

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Published on April 16, 2018 13:07

April 14, 2018

How to Create Your LinkedIn Background Plus Five Free Canva Linkedin Backgrounds

With over 500 million members LinkedIn is the most powerful platform for business development. If you’re building your own business or you’re running the sales and marketing department of another company it is critical to optimize your profile to improve your social selling ability.

One of the aspects to optimize for your LinkedIn profile is the background. This is the picture people can see on the back of your LinkedIn profile picture. I personally like to keep it simple, while giving immediate information about my business and professional life.

Let me show you how to create a LinkedIn profile background in a few minutes with Canva.

Find next five free LinkedIn backgrounds. After that, you will also find the instructions to create a LinkedIn background in a few minutes and for free by using Canva.

Create your own LinkedIn background with Canva

Canva is a tool that allows you to design anything, from ebooks cover to logos or web banners, mostly for free. I want to show you how to create your own LinkedIn background for free.

Create a Canva account for free from here.

Once logged in, pick the LinkedIn banner:

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From there you can choose one of the free design that Canva makes available:

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Once you drag and drop one of these designs you can start customizing them to create your own background:

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For instance, I got LinkedIn colors guidelines and used a LinkedIn palette to create my own background with LinkedIn blue, which is #0077b5.

If you have more complicated tastes and want to play out with colors. Get the colors available on w3schools.com.

Once done that you can also select free images from the left side of Canva editor:

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Look for free photos and drag and drop within your LinkedIn background:

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Once done you only need to save and download the file.

As simple as that!

Now it is time to set that up.

Set up your LinkedIn Background

Go within your profile and click on the small icon on the top right of the screen: [image error]

Crom the pocture and apply the changes:

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That’s it!

If you don’t have time to create your own LinkedIn Background I created a few for you below.

Free LinkedIn Backgrounds to use for your LinkedIn profile:

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Handpicked related articles:

Top Four Communities to Join to Be a Successful Digital Marketer

How to Grow Your Business with Growth Hacking

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Published on April 14, 2018 13:11

April 12, 2018

LinkedIn Features That Can Impact The Growth of your Company Quickly

In the last few years I’ve been using LinkedIn for meeting key people that helped me out in finding jobs, I’ve used it to bring traffic to my blog and to bring revenues to my online businesses. Now LinkedIn has become also a powerful tool to build your community and true fans. No matter how you look at it, investing some of your time to understand this platform has become a must. I invested the last two years of my professional life using LinkedIn on a daily basis. There are a few features you need to know about in order to make the most out of LinkedIn. I’ve listed them all.

Do you need a LinkedIn consultancy?

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LinkedIn Social Selling Index (SSI)

The LinkedIn Social Selling Index (SSI) is a useful metric to look at to understand how the LinkedIn algorithm perceives you from time to time.

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This metric will not only allow you to see how you’re doing in four areas of your profile but also how you rank respectively in your industry and your network.

You might want to align those two metrics (how you rank in your industry and network). In fact, the more you grow your profile compared to the industry, the more you want to make sure your network SSI is growing.

A strong network is also what makes your communication effort over LinkedIn more effective. In addition, you can track how the Social Selling Index is progressing over time:

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This feature, of course, is the starting point. Indeed, if on the one hand understanding how the LinkedIn algorithm is perceiving you is critical. On the other hand, understanding how people in your network are perceiving you is even more important. How can you track that?There is another critical feature for that.

LinkedIn People Also Viewed Feature

The People Also Viewed Feature allows you to understand how people perceive you on LinkedIn based on three main things:

the keywords you have in your profile: in fact, people find you on LinkedIn thanks to the keywords you use within your profile
the things that you post and publish: on LinkedIn you can use the self-publishing platform to publish or re-purpose your content. You can also publish posts and video which are native. Those can reach thousands of people over LinkedIn
what you like and share: LinkedIn Feed Algorithm is quite powerful. In fact, everything you do becomes part of your activity graph. Thus when you like or share something on LinkedIn you’re literally putting the face on that. Thus make sure to be aware when you like or share something

That is why based mostly on those activities, that is how your network will perceive you. For instance, if look at Neil Patel profile, which is public, you will see a few interesting things:

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As of now, when you look for Neil Patel and dive into the People Also Viewed feature you will mostly notice profiles of people that work in the SEO industry (like Rand Fishkin and Brian Dean) or other entrepreneurs profile (like Brian Chesky from Airbnb).

This makes sense as Neil Patel is one of the most knowledgeable entrepreneurs, focused on SEO. Thus, this means that Neil Patel is pretty good in communicating over LinkedIn. Besides, this also tells you that he has a strong brand (which he has built over the years).

Thus, you might want to make sure when people visit your profile, they also view profiles that are related to your industry or in any case to sectors tied to your bottom line.

LinkedIn Search Appearances

When you go to your LinkedIn page, click on your image to access your dashboard. On that dashboard, there are interesting information and data. Some data is pretty important to understand whether your business effort over LinkedIn is paying back. You need to look at search appearances:

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When you click on those search appearances you will notice the breakdown of companies that have been looking at your profile each week:

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You can also find out where the people that looked at your profile which industry they belong to:

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In my specific case, this information is critical. Because when I communicate over LinkedIn I want to connect to people that have specific roles within the organizations. In most cases, as I handle a complex sale, the more I get closer to the spending decision center, the more I improve my chances to close a deal.

Thus, when I talk to founders, executive directors and website managers, that informs me whether my communication effort is working. Thus, try to have in mind who’s the ideal person within the organization you might want to talk to and mold your communication on that. What role does that person have? How senior the profile needs to be? Do you want to target small organizations or a more structured company?

There is also another part of the LinkedIn Search Appearances that is critical: the keywords through which people are finding you on LinkedIn. Thus, this leads us to the next point.

LinkedIn Keywords Optimization

Within the LinkedIn Search Appearances you can also look through the keywords that are allowing you to be found on LiknedIn:

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For instance, of those keywords, I realized that just the last one was relevant to me. The others seemed to be out of place. What to do when you get found for the wrong keywords? Simple: you have to update your profile to reflect the keywords you want to be found.

Where to focus your effort?

reorganize your skills
include relevant keywords in your headline and summary
complete the information on your profile by keeping in mind who’s your target

LinkedIn Who’s Viewed Your Profile Feature

LinkedIn offers plenty of analytic data from your profile, that can help you adjust the target by time to time. This includes how your profile is getting viewed over time. To access this feature go on your LinkedIn homepage and click on “who’s viewed your profile”:

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You will get access to the Linkedin analytical dashboard:

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Although LinkedIn doesn’t show you all the profile viewers unless you have the premium version. This feature is useful to track whether you’re getting more visibility over time.

LinkedIn Views of Your Post

As posts on LinkedIn have become quite important LinkedIn also allows you to track how those posts are performing. You can access the analytics of your post from the LinkedIn homepage:

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Posts that are well drafted and in target with your audience, you can reach easily a few thousand people on LinkedIn:

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This allows you to monitor how many views, shares you’re getting; and from which companies, roles, and cities those views are coming from:

[image error]Monitoring which posts work best and which ones generate business conversations is critical to growing your influence over LinkedIn.

However, it’s important to strike a balance. For instance, posting inspirational phrases might get you tons of likes. Yet I wonder from the business perspective if that adds any value.

It’s easy to get likes, less to generate business conversations.

People You May Know Feature

Growing your network is critical to improving your reach. Thus the business conversations you can generate over LinkedIn. LinkedIn‘s algorithm can help you out in building your network more quickly and efficiently. In fact, from the homepage, if you click on “My network,” you will access a page, that shows you the pending invitations you might have.

It will also show the people you may know:

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Use this feature wisely, don’t just add anyone. Keep in mind that from the selection you’re doing you’re also training the LinkedIn algorithm to work for you. So the better you’ll select the people you might want to have in your network the more the algorithm might give you better suggestions.

Withdraw LinkedIn Pending Invitations

When you click on “My network” on the home page you will access the page where you can see the pending invitation and the people you may know. From there, click on manage all:

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It will open up a page where you can see all the invitations you’ve sent:

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Why do you want to withdraw contacts request? If you added someone because it represented a good fit for a business conversation, if after a week or so you didn’t get accepted it makes sense to withdraw the invitation for a few reasons. Frist, the other person simply doesn’t see you as a good fit. Second, you might have used the wrong message, thus by withdrawing you can retry with a more personalized message. Third, that person might be not that active on LinkedIn so it makes sense to find other channels to talk to her/him.

LinkedIn Native Video

I’m not an expert on LinkedIn videos, not because they don’t work or because they’re not effective. Quite the opposite. If you master videos you can reach a large audience. However, this is not my strength.

Yet people like Allen Gannet reach thousands of people with each video published on LinkedIn:

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I admire Allen’s work because he’s pretty effective at personal branding. This is clear by the engagements each of his videos has. But he is also able to grow his business. How do I know? I bought his book, The Creative Curve, thanks to his videos on LinkedIn.

The above video is an example of a forty seconds video getting viewed by over sixty thousand people. Of course, Allen Gannet didn’t reach those numbers overnight. Yet if you become comfortable with publishing short video interviews, tips and in any case find the format the suits you best you might be able to reach thousands of people with a little effort.

LinkedIn Self-Publishing

A few years back the LinkedIn self-publishing platform was the most powerful tool to get noticed over LinkedIn. However, as you can imagine that also lead people outside the feed. This makes the publishing platform less interesting for LinkedIn from the monetization standpoint. In fact, in the feed, LinkedIn learns many things about us. That data we give it allows the company to monetize in several ways.

For instance, by showing sponsored ads. Or prompting us to buy a subscription plan or an online course part of the LinkedIn learning platform. Thus, over time the publishing platform has been taken over by posts and videos that instead are featured on the LinkedIn feed. Therefore, more valuable for the company from the financial standpoint.

Having said that I still believe the self-publishing platform is a powerful syndication tool. In short, if you use a company blog as a way to generate leads. Then from time to time it makes sense to republish that content over LinkedIn. Just like I did below:

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This article that was previously published on my blog got re-published on LinkedIn. Over a thousand people looked/read it. That means that over ten thousand people might have seen it in their feed. This is not bad for a republished article, that only took a few minutes to set up. In addition, since at the end of the article I included a link that says “originally published on my blog” which points toward the article on my blog, this also brings traffic back to your website.

You could alternatively also include a call to action, such as “subscribe to my newsletter.”

LinkedIn Advanced Search

When prospecting to find the key people that can help you grow your business LinkedIn advanced search is a great tool. You can filter people based on locations, a degree of connections (1st, 2nd, 3rd) and current companies they work for:

[image error] Besides people, you can use the same advanced search to look for jobs, content, companies, groups, and schools.

LinkedIn Career Advice

This is a feature implemented in November 2017. As explained by the LinkedIn team:

That’s why we’re launching Career Advice, a new feature that helps connect members across the LinkedIn network with one another for lightweight mentorship opportunities. Whether you need advice on your career path, switching to a new industry or best practices for a project you’re working on, Career Advice can help you find and connect with the right person who can help.

You can get started from here:

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Click on get started:
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You can specify from whom you want to get a career advice based on the job function and industry:
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Eventually, you can specify what kind of advice you’re looking for:
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Why and how can this feature affect your business bottom line? LinkedIn is a powerful tool to generate conversations that lead to business deals. What is great about that is the fact that LinkedIn puts its members in a business-friendly mindset. Thus, if tools like career advice can help you out to learn from people in your industry and create a potential partnership, why not take advantage of it?
LinkedIn Groups Revival

LinkedIn as any other platform has a digital marketing community that from time to time spreads new trends, buzzwords, and myth. One of those potential myths developing lately is the revival of LinkedIn groups. In short, LinkedIn groups seemed to be dead, yet many digital marketers say they are again an effective way to improve your reach.

I’m honestly not able to tell you whether this is true or only marketing buzz. In fact, in the last period, which I’m been posting in some of the groups I didn’t get any useful result. However, there is one thing for which groups might be useful. Once you joined a group you automatically have access to an incredible database of contact.

In fact, even though you’re not connected with a person on LinkedIn you can still reach her/him directly if that person is in the group:

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This is going to open up the database of members, which you can contact, even though you’re not connected with them directly:

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Wih this feature it gets easier to know people that are outside your network, yet share the same interests.

LinkedIn Slideshare

Slideshare is another section of LinkedIn entirely dedicated to presentations. If you work in the corporate world or participated as a speaker at various conferences for sure you’ll have a few presentations that might be interesting to an audience. Create an account and upload some of those presentations. The effort required is minimal. Yet if you get featured in the daily top slide shares you might get hundreds of thousands of views:

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LinkedIn Recuirter Toggle On

If you go inside your privacy settings you can let privately know to recruiters on LinkedIn that you’re open to job opportunities:

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Within that you can specify things like:

What job titles are you considering?
What locations would you work in?
What types of jobs are you open to?
Which industries do you prefer?
What size company would you like to work for?

Once activated you can also create a 300 characters note for recruiters:

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Why would you use this feature if you’re an entrepreneur or not really looking for a job? The answer is simple. Recruiters know a lot of people. It’s their job. So getting to know recruiters can also open up conversations with other companies, which might lead to business deals or partnerships. So why not give it a try?

Handpicked related articles:

Everything You Need to Know About LinkedIn Feed Algorithm and How to Grow Your LinkedIn Network for Your Personal and Business Branding
LinkedIn Multi-Sided Platform Business Model Explained
Advanced Social Selling: How to Use LinkedIn to Hack the Growth of Your Business

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Published on April 12, 2018 16:14

April 11, 2018

Model After The Strategies Used By Amazon To Get Traction Over Your Own Store

Whether you love, hate or feel indifferent towards Amazon, you cannot deny the sheer scale of its success. At this stage, it likely accounts for over the 43.5% of US e-commerce sales it reportedly gathered in 2017, and for many people it’s the default e-commerce destination.

And when you see a business dominate like that, you must learn from its methods. You don’t win points for originality, and it isn’t the ideas that matter anyway— it’s the execution.

Let’s take a look at how Amazon is leading the pack, and identify some takeaways that you can use to get your own store moving in the right direction.

Focus On Meeting Customer Needs

Amazon is phenomenal at giving customers what they want. It collates information from its massive pool of users, analyzes the data, and comes up with simple solutions that seem obvious in hindsight but could easily have been missed. Before they essentially forced the entire e-commerce industry to provide free shipping, was it viewed as a prospective game-changer?

And did anyone else understand, as they do, that users will gladly accept recommendations? We like to know what combinations of items others are buying because it takes some of the work away from us. When you don’t feel like rummaging around the web for in-depth guides, a simple “Item X works well with Item Y” is incredibly convenient.

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Bundles like this are powerful sales tools.

This system is a win-win of monumental magnitude. The user saves time and easily gets a bundle they know will function, and Amazon makes a huge sale in one fell swoop. Now, your store won’t have the resources and sophisticated infrastructure that Amazon wields, so you probably won’t be doing anything too complex— but you can absolutely optimize it to give people what they want.

You can provide manual recommendations of good combinations, and generally put yourself in their shoes to consider what elements of your store might discourage them from buying. How can you best give them what they want while also getting what you want?

If you get everything polished to a shine, plenty of your customers won’t even think twice before buying. That’s the kind of value proposition you’re aiming for.

Use Testimonials to Full Effect

Amazon is packed with reviews. Some are short, some are long, and some are incredibly detailed with photos and illustrations, but the main thing is that the numbers are there and the prominence is absolute. And though it barely needs confirming (they wouldn’t put so much time into something that had no impact on revenue), the stats confirm that testimonials are hugely important for making sales.

So it isn’t enough to simply throw in the occasional review through manual uploading. Ideally, you need a full system for automating and presenting them as effectively as possible.

If your website is fully bespoke, you can embed a solution like Trustpilot. If you built it through one of the main online store builders, you should be able to find a free (or very cheap) review app or plugin to handle most of the work for you.

Here are just some of the free review apps you can get for a Shopify store, for instance:

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Whatever route you take, you should ensure that every product has a good array of reviews that make sense and cover the basics. And whatever you do, don’t hide all the negative ones— it harms far more than it helps. People want to read believable comments, not filtered praise.

Expand Your Revenue Stream

The Amazon Marketplace was a masterstroke, and it has given Amazon the kind of leverage that feels insurmountable. The idea was simple enough: build a strong retail platform with plenty of traffic, then tempt other retailers to share it instead of just trying to compete with it. They get more exposure, and Amazon gets a vast ecosystem that allows customers to buy pretty much anything they need from one e-commerce site.

Just think about how they get the best of both worlds. eBay, their chief rival as far as the scope goes, sells only third-party items. Most retailers sell only their own items. Amazon does it all. And there’s no reason at all why you can’t expand what you offer on your site too.

Think about your local community; all the small, niche retailers, and the entrepreneurs with quality products but ad-hoc distribution systems. You can give them a larger platform and provide value for your customers at the same time, making your store more appealing.

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How Amazon draws sellers in.

If you’re e-commerce only, you can engage in some affiliate marketing, endorsing specific products that you don’t sell but know will be useful for your customers. If you set up your site through a store builder (as we previously touched upon), you’ll likely have the option of using an app or a plugin to add to your inventory through dropshipping. This is a hands-off practice that allows you to sell an item but play no part in fulfilling the order once it has been placed.

If you have a retail location, though, you have even more options. You can find great local products and strike a deal to sell them at the checkout, rent out a corner to an aspiring magician, or charge a fee to play a band’s music in your building. And as long as you do it tastefully, and strive to be selective about the partnerships you form, your customers will appreciate the added variety.

Be Willing to Adapt

One of the reasons Amazon has become so staggeringly effective is that it is entirely willing to let its creative team innovate and back them against mountains of precedent if necessary. In many cases, businesses get stuck in ruts where they just want to carry on with tactics that have worked before and fear that any change will be counterproductive. Not so with Amazon.

That’s how they’ve been able to move from retail to books, ereaders, operating systems, tablets, phones, drone deliveries, and now grocery stores. They’re willing to give new things a shot.

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Source: https://www.flickr.com/photos/atalaya...

And yes, their astronomical piles of money allow them to do that but consider that as recently as 2013 they were widely questioned for not being all that profitable. The truth? They were taking that profit and investing it in the future— and now it’s paying off hugely.

So how can you apply this lesson to your store? It’s simple, though not easy: be creative, be fearless, believe in your ideas, handle your cash flow efficiently, and be ready to turn your business on a dime if the right opportunity comes along. The slower you are to take advantage of opportunities, the less you’ll get out of them.

Amazon is on top of the e-commerce world for a lot of really good reasons, so why not learn from the best? Model your retail approach on theirs, and you’ll be able to take advantage of the disruptions they’ve brought to the industry.

[image error]Victoria Greene is an e-commerce marketing expert and freelance writer who finds Amazon’s Lightning Deals hard to resist. You can read more of her work at her blog Victoria Ecommerce.

Connect with Victoria on Twitter

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Published on April 11, 2018 15:43

April 8, 2018

How Does Mark Zuckerberg Make Money? Facebook Hidden Revenue Business Model Explained

As of the time of this writing, the social network created by Mark Zuckerberg in 2004 in his Harvard dorm room is worth more than five hundred billion dollars. If Facebook were a country that would be the most populous on earth!

Facebook’s business model is quite simple and based on advertising. Yet the company has been able to unlock so much business value from its operations that has become one of the most profitable tech giants, competing with Google and Microsoft:

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In this article, I’m going to show you all you need to know about Facebook’s business model.

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The five pillars of Facebook’s business model

The overall company is based on five pillars; as reported in its annual report for 2017:

Facebook enables people to connect, share, discover, and communicate with each other on mobile devices and personal computers. There are a number of different ways to engage with people on Facebook, the most important of which is News Feed which displays an algorithmically ranked series of stories and advertisements individualized for each person.

As highlighted here the News Feed is the crucial component of Facebook. In fact, that is where the company can engage its users. That is also the place where the company manages to monetize its users.

Instagram is a community for sharing visual stories through photos, videos, and direct messages. Instagram is also a place for people to stay connected with the interests and communities that they care about.

Messenger is a messaging application that makes it easy for people to connect with other people, groups and businesses across a variety of platforms and devices.

WhatsApp is a fast, simple, and reliable messaging application that is used by people around the world to connect securely and privately.

Oculus virtual reality technology and content platform power products that allow people to enter a completely immersive and interactive environment to train, learn, play games, consume content, and connect with others.

As we’re going to see the News Feed is the real cash cow.

How much money does Facebook make?

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From the annual report for 2017: Facebook reported over $40 bln of revenues in 2017.

A 47% growth compared to 2016. The income from operations has grown to over $20 bln. An over 62% growth compared to 2016.

What does it mean? Shortly, not only Facebook has been able to accelerate its growth. However, it has also managed to reduce the growth pace of its expenses. That had a positive impact on the operating income.

When it comes to cost of revenue (the money spent by Facebook to incur an income) the company specifies:

Our cost of revenue consists primarily of expenses associated with the delivery and distribution of our products. These include expenses related to the operation of our data centers, such as facility and server equipment depreciation, salaries, benefits, and share-based compensation for employees on our operations teams, and energy and bandwidth costs. Cost of revenue also includes costs associated with partner arrangements, including content acquisition costs, credit card and other transaction fees related to processing customer transactions, cost of virtual reality platform device inventory sold, and amortization of intangible assets.

When a company manages to become efficient in its spending while increasing its revenues that is a good sign for the financial health of the organization.

Also, for tech companies, it’s also important to keep a pile of cash to acquire competitors or to face hard times. That is why on the Facebook balance sheet are sitting more than forty billion dollars in easily convertible assets (called cash, cash equivalents, and marketable securities):

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The advertising business model

The business model is quite simple: advertising. In fact, even though there are two sources of income, most of the revenue comes from ads:

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1. Advertising (over 98% of revenues): it consists of displaying ad products on Facebook, Instagram, Messenger, and third-party

2. Payments and other fees (almost 2% of total revenues): it consists of net fee received from developers using Payments infrastructure or revenue from the delivery of virtual reality platform devices and others

I wouldn’t be surprised to see the other sources of income, other than advertising, grow in the next years. That is good to diversify the revenue stream.

However, as of now, the company growth is tied to its ability to engage its daily active users. According to Facebook as of December 2017, there were 1.4 billion daily active users. Also, not all users are born equal.

In fact, some users (for instance, North America and Europe) are worth more on Facebook because those areas are monetized differently. In addition, there is one key metric that tells us if the value of Facebook will keep growing in the long-run: ARPU.

It’s all about ARPU: How much are you worth to Facebook?

ARPU stands for average revenue per user. In short, how much money a company can get on average from each user. In Facebook case, we can take into account the monthly active users.

For a company like Facebook, for which over 98% of its revenues come from advertising the amount of time people spend on the so-called news feed is crucial to increase the profitability metrics of the company.

That isn’t only because Facebook is an advertising company, but also the way its business model was built. In fact, if you think about Google, what makes the company able to monetize its users is not necessarily how much time they spend on the search results pages. Instead, that is based on how fast users can find what they need. In fact, once they click through that is how Google makes money.

Of course, things are changing fast both on Google and within Facebook. Yet as of now the more time you spend on Facebook and the more you’re active on it, the more you allow it to make money. What else? Not all users are born equal. In fact, according to the geography and the ad market of each country, the monetization strategy changes:

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That is how much each user is bringing on Facebook’s pockets based on three main geographical areas:

US and Canada: $26.76
Europe: $8.86
Asia Pacific: $2.26

Therefore, a user from the US or Canada is making as much as 12 times more than a user from the Asia Pacific region!

Summary and Conclusions

Facebook was founded in 2004 by Mark Zuckerberg in his dorm room at Harvard. Since then the company has never stopped growing. In fact, if it were a country Facebook would probably be the most populous on earth. However, the ability of the company to increase its value over time is based on how much money on average can make for each user.

In fact, over 98% of Facebook’s revenues come from advertising. Therefore, unless things will change; the news feed is still the main driver for monetizing Facebook’s content. A simple change in its algorithm can influence the mood for billions of people. Also, it can affect the value of the company for billions of dollars.

So far though, Facebook had made sure to have a pile of cash sitting on its balance sheet (more than forty billion dollars) which give the company enough space to buy its potential competitors or to face hard times in the next future!

Handpicked related content:

Everything You Need to Know About Snapchat Business Model [Financial Infographic Inside]
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How Amazon Makes Money: Amazon Business Model in a Nutshell
The Power of Google Business Model in a Nutshell

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Published on April 08, 2018 16:29

April 2, 2018

Everything You Need to Know About LinkedIn Feed Algorithm and How to Grow Your LinkedIn Network for Your Personal and Business Branding

Many gurus will tell you that as soon as you write for humans you will be fine. This is in part true. In fact, although the LinkedIn algorithm will pick up content based on quality and relevance. I believe it is important to know how LinkedIn defines “quality and relevance”

Indeed, the algorithm assesses the content of the platform based on the guidelines it receives from humans. Thus knowing how the algorithm works – I argue – is critical to be successful on LinkedIn. Why? By understanding the algorithm in reality you understand what’s the aim of the platform and also how it is evolving.

In addition, even if you don’t plan to build a strategy on LinkedIn but you’re a user and you’re curious about what’s behind a platform that recently has crossed half a billion members this article is for you.

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Everything you need to know about LinkedIn Feed Algorithm

As explained by Rushi Bhatt, director of Engineering at LinkedIn:

Keeping the LinkedIn feed relevant by identifying unprofessional and spammy content is critical to maintaining the quality our members’ content consumption experiences. In this post, we describe the various processes and algorithms that keep our feed cleared of spam and relevant to our members.

Thus, the relevance of the content is assessed via negativa. In short, the LinkedIn algorithm is at each time trying to understand whether a piece of content is spammy or not:

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The LinkedIn spam-fighting strategy, Source: engineering.linkedin.com

It does that by performing small tests. In other words, instead of pushing out the post update to most of your network, the LinkedIn algorithm starts with a small number of people; if those people find the content engaging. The selection begins to expand. Therefore, when you post content on LinkedIn it goes through three main players:

users
algorithm
human editors

The users give their vote with Likes, Comments, and Shares. The algorithm acts as a sort of middleman between the users and the human editors to keep the flow going. When the content gets a low content quality score (which tries to answer “is content good?”), it triggers the check of a human editor to see whether it’s spammy. If instead, the content passes the content quality score it’s cleared and displayed to a small number of users that can give their vote.

After the vote (with likes, comments, and shares) quality classifiers and virality predictors algorithms keep performing an assessment, which triggers a check from human editors again. If it passes the test (is content good?), then it gets cleared and displayed back to users.

That is why in some way posting stuff that is interesting to people, rather than focusing on the algorithm is critical. In fact, if your post is going viral yet it might be spammy, it will still be checked by human editors that might demote it! That is because assessing whether the content is low quality or not also depends on factors that are not easy to weight.

In short, as of now, it might be easier to fool algorithms, than human editors. However, the algorithms do play a critical role in filtering out content. In fact, using humans to do that, for a platform with over half a billion users might be impossible.

What are the steps the LinkedIn feed algorithm takes to make a post or article go viral?

Pass the content quality assessment

As LinkedIn specifies:

The role of the LinkedIn feed is to provide timely, professional content. What may pass as acceptable content on a general social network may not be a pleasing experience for a professional social network like LinkedIn. We would like to eliminate as much low-quality content from the site as possible. At the same time, we do not want to be overzealous about filtering content from the site, because that could lead to more false positives and user dissatisfaction. In other words, we need to strive for high precision and recall for our classification and labeling.

The LinkedIn main aim is to provide “timely, professional content.” This definition is critical. In fact, as LinkedIn gets closer and closer to Facebook, it is worth understanding that LinkedIn Business Model is quite different from it.

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As of 2015 (before LinkedIn got merged into Microsoft), more than 50% of LinkedIn Revenues came from Hiring and premium subscriptions. Instead, if we look at Facebook revenues stream as of 2017, you can see that it mostly come from advertising. Why is this important at all to understand the LinkedIn feed algorithm?

Willingly or not, companies’ decisions are influenced by the way they monetize. Where Facebook is highly dependent on its feed for monetization. LinkedIn is less so. That means LinkedIn has also more freedom to choose how to shape its feed in a way that is more in line with its subscriptions based users and HR professionals part of the platform.

Thus, the LinkedIn algorithm is focused on avoiding low-quality content on the feed, while making sure not to filter content that might lead to false positives (cases in which something seems spammy but in fact, it’s not). How does it do that?

Precision and Recall mechanism to select relevant content

As specified on Wikipedia:

In pattern recognition, information retrieval and binary classification, precision (also called positive predictive value) is the fraction of relevant instances among the retrieved instances, while recall (also known as sensitivity) is the fraction of relevant instances that have been retrieved over the total amount of relevant instances. Both precision and recall are therefore based on an understanding and measure of relevance.

In short, this is a sort of balancing mechanism. On the one hand, precision focuses on finding relevant instances. While recall focuses on completeness. So imagine, there are ten posts showing up on your feed, of which only five seem to be relevant to you. This means that the precision is 5/10. In short, you get half the time what you’re looking for.

However, imagine that in your network of one hundred connections at that given time were posted thirty posts that might have been relevant to you. Yet you only got five. This means the recall is 5/30. As you missed other twenty-five potentially relevant posts.

In other words, this mechanism tries to answer two specific questions:

how useful is the content shown?
and how much relevant information is shown to each user?

The FollowFeed mechanism of virality

Back in 2012 LinkedIn introduced a feed infrastructure called Sensei. This was a distributed data system that also supported the LinkedIn feed. As explained by LinkedIn, Sensei was both a search engine and a database. However, in 2014 LinkedIn set out to build FollowFeed which was launched in March 2016 and today powers up LinkedIn feed experience. Why does it matter at all?

First, with FollowFeed LinkedIn has been able to improve its feed performance while scaling up the number of users (back in 2016 LinkedIn grew to over 400 million members). Second, even though LinkedIn was scaling up in terms of users base, it also improved the relevance of its feed by introducing algorithms able to offer better content recommendations to users in real-time.

The FollowFeed uses the concept of a timeline (shares an article, member is mentioned in an article, etc) to compose the feed for each member. To compose the feed LinkedIn uses a model called “Fan-out-on-write” which as explained:

Feed for each viewer is pre-computed, materialized and kept ready for retrieval using a simple lookup query. This is made possible by fanning out a content record to pre-materialized feeds of multiple entities.

How LinkedIn created the Activity Graph from a bug to emphasize organic content

LinkedIn’s strategy is based on users engagement. The strength of LinkedIn – I believe – is based on its business model. In fact – as advertising is one of the revenue streams LinkedIn relies on – the company can focus on engagement without affecting too much its bottom line.

This is highlighted by LinkedIn in June 2017:

The story of the almost year-long project behind LinkedIn’s Activity Graph begins with a bug report, as things usually go. We noticed that sometimes, sponsored content (i.e., an ad) would show up in the first position in a member’s feed. This is against our internal best practices and something we actively try to avoid; we want the most interesting organic content to be the first thing a member sees, not an ad.

In other words, once the LinkedIn team has figured out that with a sponsored post you could hijack its feed algorithm. They worked out a way to avoid this happening so that organic content could be emphasized over sponsored content.

What is an organic content?

it consists of the pieces of member-generated content in the feed, which we call “Activities.” An Activity is defined by three main components: Actor, Verb, and Object. An example in prose would be “Val shared a text post,” or “Vivek liked a comment.” We present these Activities as cards in the feed UI.

Thus, each time you’re liking, sharing, or writing a text post, this can be defined as an activity, which will be labeled by LinkedIn as organic content.

In short, apparently, as LinkedIn algorithm had come up with a process called “decoration” a spammy organic content, was removed before it could be shown to the users. Thus, allowing a sponsored content (an ad) to get the first slot, which instead was reserved for the organic content.

Before moving on, keep this in mind, not all Likes are born equal.

Beware, LinkedIn isn’t Facebook

When you like, share or post something this enters your activity graph. Thus, each of those activities should be done strategically if you’re using LinkedIn for business. For instance, if you’re liking something, you might want to avoid to like a video of cats (unless of course, you sell accessories or food for cats).

Why? First, this will enter your activity graph, thus influence the feed algorithm and what you will see next in your LinkedIn feed. Second, when you like something this acts as a vote/recommendation that you offer to your network. In short, a Like on LinkedIn weights much more than a like on Facebook.

Thus, before liking the next funny cats’ video (assuming the LinkedIn feed algorithm doesn’t demote it), beware of that!

LinkedIn also introduced the concept of low-quality content (called LQ).

Avoid low-quality content to go hyper-viral

If the precision and recall mechanism allows the LinkedIn algorithm to filter relevant content by trying to keep out content that is spammy or low-quality. There is an issue of scalability. In fact, as LinkedIn put it:

Having a few low-quality shares go hyper-viral can cause dissatisfaction for a very large number of members.

Thus, since the risk of having low-quality content go hyper-viral is too high the algorithm would rather stop something “suspicious” rather than allow it to go viral.

LinkedIn feed content syndication summarized

As explained by the LinkedIn engineering team the mechanism is the following:

At creation

There are a set of classifiers that label the content in three ways:

spam
low-quality
clear

It is important to understand that this process happens in near real time. Thus, as soon as you hit the publish button before the content gets shown to your network it has already been labeled by the LinkedIn algorithm.

If the content gets classified as spam or low quality it might get either demoted or passed to a human editor. It is important to understand that as professional network LinkedIn gets most of its value from keeping its feed as clean from spam as possible. Thus, when a content can be deemed as spam or low quality it would get demoted rather than risk to have it go viral.

If the content passes the quality score assessment it gets cleared to gather some audience data.

As it gathers audience

At this stage, the LinkedIn algorithm needs to gather data from the audience in one person network to assess whether the content is worth. However, to avoid the risk of having low-quality content go viral the LinkedIn feed algorithm keeps monitoring a few aspects:

reach of the original poster,
members interacting with the content,
and the temporal signals like the velocity of likes, shares, and comments,
the computed content quality scores

This sort of recipe allows the algorithm to understand two main things. First, if the content is likely to go viral. Second, if the content that is likely to go viral is also potentially low-quality content. Those analyses run every few hours to keep the feed as clean as possible.

There is an aspect that is highlighted by the LinkedIn engineering team:

Most of the easy to catch content is filtered out at creation time, leaving behind hard to classify instances in the feed.

Thus, once again when you hit the publish button on LinkedIn at creation time your content might already be checked for quality insurance before it even gets shown to anyone. As the feedback from LinkedIn members grows so the LinkedIn feed algorithm gathers data to push the content through the network.

Members also play a key role in assessing content quality

When members report low quality or spammy content those are taken into account for two reasons. First, to reassess and bring down content that the feed algorithm or human editors were not able to detect. Second, this data gets fed to the LinkedIn algorithm so it can learn what the LinkedIn members find valuable and what not.

Now that we know how the algorithm works, how can you leverage the LinkedIn network effect?

Leverage the network effect to grow your LinkedIn audience

Start by analyzing your LinkedIn network with http://socilab.com/#home.

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Making sure you widen your network is important. Yet, size matters relatively. Knowing whom you need to talk; to building your brand/business is crucial. For instance, I used socilab to understand how my network is clustered.

There are a few metrics you might want to monitor to leverage the “network effect” (although the tool I used only analyzes 499 connections max):

The effective size of your LinkedIn network

That tells you that not all contacts are born equal as some overlap with your network. Those overlapping might add less value in terms of reach. However, they might also be important to build a strong brand. Thus, if you’re trying to build a brand with social media it might make sense to have a clustered network initially. Then as you get known in that cluster it makes sense to expand that network to contacts that don’t overlap to have a greater reach.

LinkedIn Network constraints

That is an index that measures how distributed is your network. While a widespread network might be good for virality. That might be less so to build a reliable brand. Thus, you need to balance those two aspects

LinkedIn Network Density

It shows how close is your network in terms of actual ties compared to possible ties. The denser your network the more your contacts know each other. Once again, while this might be good initially to take over a niche, once you’ve become known in that niche you might want to lower the density of our network.

LinkedIn Network Hierarchy

Hierarchy assesses how dependent you are on a few focal contacts (imagine most of your contacts know you through your boss!). In general, you want your network to be distributed to avoid the dependence on a few contacts. In short, also in terms of networking, you might want to avoid to have your eggs all in one basket.

LinkedIn Network Betweenness

That tells you the bridging opportunities (for instance, which of your contacts might get you closer to a cluster or a contact that can widen your network quickly). For instance, I noticed that there are two contacts in my network which bridge me with an industry I’m weaker. I connect back to those two contacts to widen my network.

LinkedIn feed algorithm explained

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Published on April 02, 2018 09:51

April 1, 2018

Four Patterns for Technological Adoption That Any Tech Startup Founder Should Be Aware of from Anthropologist Jared Diamond

One of my favorite authors is Jared Diamond, a polymath which knowledge goes beyond books, education or instruction. In fact, Jared Diamond is an ecologist, geographer, biologist, anthropologist.

Whatever you want to label him, the truth is Jared Diamond is just one of the most curious people on earth. As we love to put a label on anything, we get impressed by as many labels one person has. However, Jared Diamond has been just a curious person looking for answers to compelling and hard questions about our civilization. The search for those answers has brought him to become an expert in many disciplines.

In fact, even though he might not know what’s the latest news about Google‘s algorithm update, Apple’s latest product launch or what features the new iPhone has, I believe Jared Diamond is the most equipped person to understand how the technological landscape evolves. Reason being Jared Diamond has been looking at historical trends in thousands of years and dozens of cultures and civilizations.

He’s also lived for short periods throughout his life with small populations, like New Guineans. In his book Guns, Germs & Steel there is an excerpt that tries to explain why western civilizations were so technologically successful and advanced compared to any other population in the world, say New Guinea.

For many in the modern, hyper-technological world, the answer seems trivial. With the advent of the digital world, even more. We love to read and get inspired every day by the incredible stories of geniuses and successful entrepreneurs that are changing the world.

Jared Diamond has a different explanation for how technology evolves and what influences its adoption throughout history, and it has only in part to do with the ability to make something that works better than what existed before.

Why the heroic theory of invention is flawed

If you read the accounts of many entrepreneurs that have influenced our modern society, those seem to resemble the stories of heroes, geniuses, and original thinkers. In short, if we didn’t have Edison, Watt, Ford, and Carnegie the western world wouldn’t have been so wildly successful. For how much we love this theory, that doesn’t seem to resemble history.

True, those people were in a way ahead of their times. They were geniuses, risk takers and in some cases mavericks. However, were they the only ones able to advance our society? That is not the case.

Assuming those people were isolated geniuses able to come up with the unimaginable; if the culture around wouldn’t have been able to acknowledge those inventions we wouldn’t have traces as of now of those discoveries. So what really influenced technological adoption?

The four patterns of technological adoption

According to Jared Diamond, there are four patterns to look at when looking for technological adoption:

a relative economical advantage with existing technology
social value and prestige
compatibility with vested interests
the ease with which those advantages can be observed

Relative economic advantage with existing technology

The first point seems obvious. In fact, for one technology to win over the other doesn’t have just to be better; but way more effective. To think of a recent example, when Google took off the search industry. When Google got into the search industry, it was not the first player. It was a latecomer. Yet its algorithm, PageRank, was so superior to its competition that it quickly took off.

What’s next?

Social value and prestige

This is less intuitive. In fact, for how much we love to think of ourselves as rational creatures, in reality, we might be way more social than we’re rational. Thus, social value and prestige of a technological innovation play as much a key role in its adoption as its innovative aspects.

Think about Apple’s products. Apple follows a business model which can be defined as razor and blade business model. In short, the company attracts users on its platform, iTunes or Apple Store by selling music or apps for a convenient price, while selling its iPhones at very high margins.

However, it is undeniable that what makes Apple able to sell its computers and phones at a higher price compared to competitors is the brand the company was able to build over the years. In short, as of the time of this writing, Apple still represents a status quo that makes the company highly profitable.

Compatibility with vested interests

In Jared Diamond‘s book, Germs, Guns & Steel to prove this point he uses the story of the QWERTY keyboard. This is the keyboard most probably you’re using right now on your mobile device or computer. It is called in this way because its first left-most six letters form the name “QWERTY.”

Have you ever wondered why do you use this standard? You might think this has to do with efficiency. But instead, that is the opposite. This standard has been invented at the end of the 1800s when typewriters became the standard.

When typists were typing too fast those (page 248 of Germs, Guns & Steel) typewriters jammed. In short, they came up with a system that was thought to slow down typists so that typewriters wouldn’t get jammed anymore. Yet as the more than a century went by and we started to use computers, and mobile devices instead of switching to a more efficient system we kept the old one. Why?

According to Jared Diamond, the most compelling reason for not being able to switch to a new standard was the vested interests of small lobbies of typists, typing teachers, typewriter and computer salespeople.

The ease with which those advantages can be observed

When a technological advancement can be easily recognized as the fruit of the success of an organization, country or enterprise, it will be adopted by anyone that wants to keep up with it. Think for instance, about two countries going to war. One of them has a secret weapon that makes them win the war.

As soon as the enemy that lost the battle finds that out, next time that weapon will also be adopted by the losing side. Think also of another more recent example. As big data has become a secret technological weapon used by Obama to win his electoral campaign. So Trump has used it to take over his competitors during the last US political campaign.

Now that we know what are the four patterns of technological adoption, one might wonder: do we still need to believe in heroic entrepreneurs?

Do we still need to believe in heroic entrepreneurs?

I’ve recently read Skin in the Game by Nassim Nicholas Taleb. He has an interesting point about beliefs. They need to be judged at epistemological level. In short, those don’t have to be taken literally. For instance, when we read a story about Edison, Lincoln or Rockefeller, chances are those story are apocryphal.

However, that story might make you believe something that makes you take action. If anyone was “rational” and calculating the probability of success of a startup, none would become an entrepreneur.

In fact, some of what we call “irrational beliefs” make us take actions that might lead to certain results that are good for the collective. Thus, if you do take actions that benefit the collective, you cannot be called irrational.

Because what matters is not the belief itself but the positive result it leads to. Thus, if you want to believe that we would still be in the dark; had Edison not invented the light bulb; so be it!

Yet don’t ask anyone to believe that story, instead, use that belief to do something great! You also know now what are the factors to take into account for technological adoption.

Key takeaway

As technology advances, most of the times they are the result of tinkering and trial and errors. Also, the adoption of those technology depends upon the ability of a society to accept those technologies.

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Published on April 01, 2018 13:57

March 30, 2018

How Does ConvertKit Make Money? CovertKit Business Development Model Explained

ConvertKit is an email marketing tool that monetizes with three main subscription plans based on the list size. For instance, an email list with 0-1k subscribers goes for $29; 1k-3k subscribers cost $49, and 3k-5k cost $79. ConvertKit reached a milestone of over $1 million in monthly recurring revenues, in March 2018.

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ConvertKit recently announced a significant milestone, $1m in MRR. Not bad for a startup which was bootstrapped by its solo-founder, Nathan Berry. In fact, Nathan Berry set out a challenge, which he called Web App Challenge, back in 2012. He didn’t know what to launch; he only had one objective: make $5k in MRR.

That is how ConvertKit started out, and here you can read the whole story:

ConvertKit Startup Story: How CovertKit grew from $0 to $1M in MRR with direct sales, word-of-mouth, and affiliate marketing

What are the main distribution channels ConvertKit used to grow?

Along the way ConvertKit mastered three main channels:

direct sales
word-of-mouth
affiliate marketing

Direct sales

It all starts with direct sales. If you don’t have customers, there will be none referring you.

When Nathan Berry launched ConvertKit, after almost two years into the project, growth wasn’t picking up. Instead, it was slowing down at the point that he was advised to shut down the company. Yet he decided to double down, invest part of his savings from previous online businesses and started to dedicate to the project full-time (in fact, he was only devoting part of his time to ConvertKit).

Among the initial strategies he was using, there was content marketing, blogging, and social media. However, those strategies didn’t bring ConvertKit far in terms of growth

What direct sales tactics did Nathan Berry use?

It can be broken down into three main parts:

cold email
Skype demos
super-organized follow-up

Cold email template Nathan Berry used for ConvertKit

Sarah,

Is anything frustrating you with MailChimp?

The reason I ask is I run ConvertKit, which is an email marketing platform for professional bloggers. We’ve got a lot of great bloggers using us like Katie and Seth from Wellness Mama, Pat Flynn from Smart Passive Income, and Chris Guillebeau.

I’d love to hear more about how we can build it to better serve bloggers like you.

Talk soon,

Nathan

Source: nathanbarry.com/sales

This is how Nathan Berry reached out to potential ConvertKit users. The next step was the Skype demo.

Skype demo to remove the biggest objection

At the time jumping on a Skype call was a way to understand what was the main point of friction ConvertKit potential users had. In fact, as Nathan Berry describes:

Most early sales conversations ended with the lead saying, “ConvertKit sounds great and I love what you’re about, but… switching email providers is so much work. Sorry, it’s just not going to happen.”

Ouch. Just when I thought the conversation was going so well.

Then out of a moment of desperation I said, “It’s not that much work. I’ll prove it to you and do it all for you. For free.”

A little startled, they agreed. Then I realized that’s the silver bullet. The prospect placed all their possible objections on a single thing: the cost of switching. So with one offer I could remove that and make them so much more likely to switch.

This turned into a service that we now offer many times a day: concierge migrations.

Basically on any account over $79/month (5,000 subscribers) we will move them from their old email tool over to ConvertKit for free. That includes FTPing into their site and switching all their opt-in forms, signing into MailChimp (or another tool) and copying and pasting over all their automated emails, and finally exporting and importing all subscribers to keep any tags or segments.

It’s a decent amount of work, but we can do it pretty quickly. More importantly, the churn on accounts that go through a migration is around 1.5% rather than the more typical 5.5%. So it’s definitely worth the initial work up front.

In short, conversations are instrumental in understanding what is the main point of resistance and acting on it. When Nathan Berry realized there was one central point of friction (too much work in changing email provider) he set up a “concierge migration” that allowed his potential customers to switch to CovertKit for free!

Follow-up system used by Nathan Berry when growing ConvertKit

When you follow-up you will often say over and over again the same thing. Don’t do that. Instead, find something useful for the person you’re following up with. As Nathan Berry explains:

If your follow-up emails are just, “Hey, I haven’t heard from you, can we talk?” You’ll probably never get a response. Instead find some way to help them. It could be an intro, feedback on a recent project, a tip to fix something, or a tactic that’s recently worked for you. But don’t just keep sending them the same “Hi, hi, hi let’s be friends” emails.

Also, initially he didn’t use any complicated or expensive software. Instead, he used a Trello board to track all his conversations and make sure he wouldn’t lose a contact anymore:

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Source: nathanbarry.com/sales
Word-of-mouth

Once you have is mainly about customer success. Once you managed to get into a small niche, most people will know each other. Therefore, you will have to make sure those people are happy enough to refer your service to more people in their community. This is the power of word of mouth, which of course starts from a consistent direct sales strategy.

Affiliate marketing to amplify growth

Once growth picked up for CovertKit, Nathan Berry started to experiment with affiliate programs. As most of his initial customers were professional bloggers making money with affiliate earning, he thought it made sense to amplify growth by offering them a 30% recurring commission. People like Pat Flynn contributed a lot to ConvertKit growth. Of course, affiliate programs don’t always make sense. In any case what makes sense is to understand whether your customers can also become your distributors.

ConvertKit Business Model Explained

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Published on March 30, 2018 09:21

March 20, 2018

Five Tech Startups Business Models Explained

A business model is a crucial part of the life of any business. In fact, although there are many ways of monetizing. A business model isn’t only about monetization. Instead, that is more about the overall value unlocked by the business and how it affects several stakeholders. In fact, if we look at most of the companies that have been wildly successful in the last decades (Microsoft, Apple, Google, and Facebook), those companies were able to involve several players before being able to scale up.

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For instance, Google before becoming wildly profitable it spent some time tinkering with several monetizations strategy before coming up with its advertising networks which involved three main players as explained here.

Quora and the content value matrix

Quora recently started to monetize the platform by testing an advertising program that allows publisher and businesses to add their product or service to the Quora’s feed with a text ad. The company has been very successful in building a trusted platform where users post any question, asked by committed non-professional writers. Besides, on Quora often famous writers and authors host Q&A sessions that make the platform even more engaging.

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Wolfram Alpha: the smartest engine around (so far)

Wolfram Alpha is the search engine created by a former physicist turned a successful entrepreneur: Stephen Wolfram. Today, Wolfram Alpha, a computational engine is the smartest engine around. Its business model is based on subscriptions, APIs, and applications. As Google is getting smarter and smarter from the computational standpoint, one might wonder whether Wolfram Alpha will lose competitiveness over time. And by the way, if you thought you didn’t know Wolfram Alpha, most probably you’re wrong. In fact, Wolfram Alpha powers some queries of the iPhone’s voice assistant, Siri.

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Airbnb: disrupt modern hospitality to go back to old days

When Airbnb came in the hospitality industry a few years back. Few players realized how disruptive it was until it was too late for stopping its growth. Today Airbnb is one of the wildest tech success of the last decade, based on a simple business model, which relies on the trust between guests and hosts. Also, over the year as quality pictures have become an essential aspect for Airbnb growth, the company started to work regularly with freelance that would take photos of hosts’ accommodations for free so that the listing could be more appealing for guests.

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DuckDuckGo: where Google loses DuckDuckGo wins

DuckDuckGo is a search engine that doesn’t track its users. In short, it gathers the data that might be useful to offer a localized search, but it throws it away on the fly. Thus, if Google mainly monetizes thanks to the information, it gathered from users. DuckDuckGo does the opposite. It allows its users to rely on a private navigation experience; while it monetizes mainly through localized keywords and affiliate earnings.

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LinkedIn: the multi-sided platform where hunters and hunted grow together

LinkedIn is the most significant professional network on earth and also one of the most engaging social networks as of the time of this writing. The value of the platform comes from its multi-sided customer focus. In fact, LinkedIn, on the one hand, offers services to HR professionals that allow them to find the right fit for the open positions. At the same time, LinkedIn offers its users a learning platform useful to bridge the gap with the professional world. Thus, making the platform more valuable for those HR professionals.

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More business models?

Tell us in the comments below which business models you’re curious to hear about!

The post Five Tech Startups Business Models Explained appeared first on FourWeekMBA.

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Published on March 20, 2018 14:57

ConvertKit Startup Story: How CovertKit grew from $0 to $1M in MRR with direct sales, word-of-mouth, and affiliate marketing

Yesterday @ConvertKit hit $1m MRR. Thank you so much to everyone who has helped along this journey! We’ve now got an incredible team of 34 supporting 18,872 customers.

— Nathan Barry (@nathanbarry) March 19, 2018

On March 19 Nathan Barry, Founder, and CEO at ConvertKit announced in a tweet that the company had reached $1m in monthly recurring revenues (MRR)! How did they get there?

The story of ConvertKit is quite compelling for anyone that is trying to build up a business from scratch, bootstrapping it while sharing the financial results with its users. This is one of the most compelling business cases of the last years in the digital marketing world.

In fact, as ConvertKit is part of the Open Startups Project from Baremetrics, the company has been sharing its revenues and metrics transparently. Thus, there are a few critical lessons to learn here.

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The Web App Challenge: too ambitious?

It was December 31st, 2012; this might sound a year-end resolution yet on that day Nathan Barry started out its web app challenge:

I could just start a new web app and work on it quietly for a year before launching, but where is the fun in that? Writing and launching Designing Web Applications in only three months taught me that if I compress the deadlines I can meet a goal much more quickly. So here is the challenge:

Within six months build a web application to $5,000 in recurring revenue each month. A friend just referred to that timeline as “aggressive” so let’s add some more restrictions to make it more difficult:

I am starting without an idea. So I don’t know what the application will be, what it will do, or who it is targeted towards.
I can only spend $5,000 of my own money in this entire process. Meaning all other funds necessary have to come from paying customers. Since I will be hiring out the development, getting paying customers right away is mandatory.
I cannot spend more than 20 hours a week on this project. If allowed, I waste tons of time on projects. This limit is partially because there are other things that need my time (contract projects, writing, etc) and to help keep me focused.

The best part of this is that I am going to be completely transparent about every step of the process. Follow along on this blog to hear how things are going, what I’m learning, and the mistakes you shouldn’t repeat. The deadline is July 1st, 2013 to have $5,000 a month worth of paying customers. That could be 50 customers paying $100 a month, 10 customers paying $500 a month, or somewhere in the middle (most likely) Think I can do it? Good. Me too.

Thus, with no idea of what he was going to build next, and a deadline on July 1st, 2013 Nathan Barry was setting up an ambitious goal of hitting $5,000 MRR per month.

Entrepreneurship is not only about ideas but practical solutions to existing needs

As Nathan Berry put it back in January 2013:

Sorry to burst your bubble, but an idea you come up with is a terrible place to start a new business. The reason is that businesses need to make money if they are to be sustainable. To make money a business needs customers. Customers don’t pay for ideas; they pay for their problems to be solved. So rather than looking for an idea for what to build, you should be looking for a painful problem that you can solve. People will pay to make pain go away. The more painful and frustrating the problem is, the more they will pay.

So rather than sitting around dreaming up ideas, we want to find a painful problem to solve. That solution will become the idea for our business.

The birth of CovertKit: The Idea Extraction framework

At the time Nathan Berry was listening to an episode from Pat Flynn’s Smart Passive Income, which also focused on the idea extraction process to come up with business ideas. What is the business idea extraction process?

As Nathan Berry put it back then:

Idea Extraction is really pretty simple. Talk to potential customers to find their pain. Once you come across a painful problem, validate it with other companies in the same industry. Then find out how much these companies are willing to pay for this problem to be solved. This is the most accurate way to determine how painful the problem really is.

The process consists of a few steps:

Pick up a Market
Get your potential customers on the phone
Start conversations focused on understanding their painful problems
Uncover those problems
Understand whether they would pay to get that problem solved

That is how Nathan Berry came up with the idea of ConvertKit

Not a promising start!

In June 2013, after the launch of ConvertKit revenues seemed to pick up slowly as Nathan Berry remarked at that time:

Currently ConvertKit makes $1,888 per month, which means I am 37% of the way towards my $5,000 per month goal. Growth has been quite slow after the preorders, averaging a new trial account every other day. That needs to increase considerably in order to meet my goal.

Also, many of those trials are not converting into paid accounts, which means I need to do more work with the on-boarding process to increase that conversion rate.

With only 27 days left until July 1st (the deadline), I really need to step up my game. More on that later.

What to do?

Nathan Berry came up with a few ideas. He leveraged on his already existing audience. In fact, as he had launched his book recently, he thought to reach out to his audience and offer a deal on ConvertKit. So far Nathan Berry had been using a passive approach, solely based on content marketing. As he was coming back from BaconBizConf, where he had listened to Ryan Delk from Gumroad, which at the time was using a direct sales approach. Nathan Berry realized he could use the same strategy. That is how he set up to reach out authors, founders, and anyone else who could be a good fit for ConvertKit.

Nathan Berry also planned a guest post and podcast campaign that would allow him to leverage on other people’s networks to bring sales back to ConvertKit.

He also launched a new course about email marketing, which would be used as a lead generation tool for ConvertKit.

Last but not least Nathan Berry decided to contact anyone from its 750 people list personally to see if they were interested in activating a ConvertKit account.

ConvertKit challenge? Half a failure

Just six months before on July 1st, 2013 Nathan Berry had set out an ambitious objective: reach $5k in MRR for a project he didn’t even know yet. Yet after using the idea extraction process, he came up with ConvertKit. However, at the end of the challenge, CovertKit was only at $2,480/month.

In fact, at the end of the challenge ConvertKit had generated a small loss for Nathan Berry:

Expenses:

Rackspace: $997.00
Development:

Sam: $6,344.40
Ben: $3,471.00

Domain & Certificates: $37.30
Amazon EC2: $29.42

Total expenses: $10,879

Revenue:

Preorders: $4,541
Stripe payments: $1,093

Total revenue: $5,634

Profit: -$5,244.29

Initial Investment: $5,000

Cash on hand: -$244.49

At hindsight success always makes sense. However, by looking at those numbers, it’s hard to realize that ConvertKit would later become a company generating over $1M in MRR.

ConvertKit and the slow ramp of death

CovenrtKit is part of the Baremetrics open startup program. In short, Baremetrics is a tool that allows monitoring the primary metrics that drive the growth of a startup. For a company like CovertKit, which business model is based on a subscription plan, the MRR is one of those essential metrics to monitor on a monthly basis.

There are a few interesting things to notice. In fact, when Nathan Berry had set out to grow ConvertKit, at a certain point, it hit a plateau. In short, it seemed like growth wasn’t picking up!

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Source: convertkit.baremetrics.com

In the start-up jargon, this kind of pattern is sadly called the “slow ramp of death.” In fact, when you stop growing, there might be a structural issue related to the business model, a problem in the product or just a lack of strategy.

What was going on with ConvertKit?

Man, you better shut down ConvertKit!

A year and a half after starting out ConvertKit Nathan Barry was facing a decline in sales. In part, this was due to his loss of interest in the project. Nathan was returning from a conference with Hiten Shah. Just to give you some context Hiten Shah is a serial entrepreneur. He founded companies like CrazyEgg, KISSmetrics, Quick Sprout. When Hiten Shat met Nathan Berry he told him plainly:

I think it’s time you shut down ConvertKit.

and he continued,

You’ll be successful at whatever you do, but you’re well over a year into ConvertKit, it’s not growing, and it’s time to shut it down.

This seems madness now. Yet there was a profound truth in those words. Nathan Berry didn’t believe enough in that project. In fact, he was working on it part-time. Those words made him think about ConvertKit with a different perspective, for the first time since its inception! In fact, when they caught up again Hiten Shah added:

Or, you take ConvertKit seriously and give it the time, money, and attention it deserves. But whatever you’re doing, it’s not working.

Traction is not an easy game. Yet as months went by ConvertKit kept slowing down until it reached its lowest point in September 2014, when it generated $1,233 in monthly recurring revenues.

Either shut it down or double down!

Instead of shutting down ConvertKit, Nathan Berry doubled down. How? He hired a full-time developer and invested $50k from his other business and went all in with ConvertKit!

As Nathan put it at the time:

The biggest mistake I see authors, bloggers, and entrepreneurs making is they quit too early.

The blogger writes a dozen posts and no one cares. The author tries to get a book deal but can’t even get an agent to sign them.—let alone a publisher. And the entrepreneur throws up a sales page and starts promoting their software, but no one bites.

and he continued:

If this is your full-time thing you need to grind it out. You have to make it work, because you’ve staked everything on this project to provide for you and your family…

…But before you decide, ask yourself these two questions:

Do you still want it as much as you did when you started?
Have you given this company or product your best possible effort to make it succeed?

Ok, Nathan doubled it down, but what to do next?

Time for some direct sales

Many believe that growing a startup is a matter of automation and optimization. If that is true for a particular stage of growth; the initial traction needs a lot of human interactions to understand what it takes to grow the business. How your users are feeling about your product. And what you can do to improve that.

In fact, Nathan Berry realized it was time to reach out. He cold emailed professional bloggers to set up Skype demos. He realized there was a significant obstacle to ConvertKit growth: it was too hard and too much work for those bloggers to switch to a new email provider.

Thus, for how much they loved the idea behind CovertKit they would not switch to it because it was too burdening!

What to do?

First traction phase: Concierge migration and word of mouth (up to $20k MRR)

Nathan Berry said one thing to those professional bloggers that found it too hard to switch to ConvertKit: I’ll do it for you, for free!

This is how growth started to pick up with what they called at the time “concierge migration.” After six months, on March 2015 ConvertKit grew at $5,020 in MRR:

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Source: indiehackers.com

This strategy allowed ConvertKit to focus on higher quality customers, with more extended lifetime value. This kind of growth, fueled by direct sales and word-of-mouth made ConvertKit reach over $20k in MRR:

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Source: convertkit.baremetrics.com

Second traction phase: affiliate marketing at the smart passive income way

ConvertKit had attracted a niche of professional bloggers which made most of their income through affiliate marketing. At that stage, Nathan Berry thought to test an affiliate marketing program based on recurring revenues for the affiliates, rather than an upfront payment. That turned out to be a powerful weapon. In fact, as those professional bloggers liked a stable income over-time, a 30% recurring commission seemed quite attractive to them.

Just to give you an idea of how effective the affiliate marketing distribution channel was for ConvertKit, I looked at Pat Flynn’s Smart Passive Income report for October 2015. That is what he said:

Amongst the email marketing content that I published in October, I also used that opportunity to talk about the new email service provider that I’ve been using. In a highly viewed post titled Why I Switched from AWeber to Infusionsoft to ConvertKit, I revealed some of my struggles with other email service providers that I’ve used, and why I landed on ConvertKit as my ultimate solution.

Can you guess how much revenues Pat Flynn made to CovertKit on that month alone?

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Pat Flynn that month generated $1,463 in affiliate revenues. If those represented 30% of the total revenue, it means that Pat Flynn alone allowed ConvertKit to grow by almost $5k in MRR in October 2015. Not surprisingly the growth rate grew exponentially. By November 2015, CovertKit reached $68k in MRR.

This was one of the most successful articles from Pat Flynn which brought new customers to ConvertKit:

Why I Switched from AWeber to Infusionsoft to ConvertKit

In December 2017 Pat Flynn generated $36,956 in affiliate earnings from ConvertKit. If those still represents 30% of revenues, this means Pat Flynn alone contributes to more than $100K MRR for ConvertKit!

Note: The assumption here is simple. ConvertKit paid 30% in recurring commissions to its affiliates. Although today it pays 10%, we can assume that for large and long-time affiliates like Pat Flynn they kept the agreement as it was back then. Thus by dividing up 100%/30%, we get 3,33. By multiplying the affiliate earnings of Pat Flynn by that ratio (3,33), we get the actual revenues he generated for ConvertKit.

Third traction phase: there is no scale without profitability (FROM LOSING MONEY TO A 51% PROFIT MARGIN IN 5 MONTHS)

On his blog Nathan Berry showed a quick timeline of the growth from 2013-2016:

JAN 2013 — Started on the idea for ConvertKit

JUN 2013 — Reached $2,000 a month in recurring revenue (MRR).

SEP 2014 — Revenue declines to $1,330 per month.

OCT 2014 — Make the decision to double down on ConvertKit. Focus full-time, hire a team, and invest $50,000.

JAN 2015 — $3,000 MRR

JUN 2015 — $10,000 MRR

OCT 2015 — $25,000 MRR

DEC 2015 — $97,000 MRR

FEB 2016 — Growing quickly, but just barely profitable with only $30,000 in the bank. Make the decision to get profitable as quickly as possible. Goal of 3 months of expenses in the bank by July 1, 2016.

A company that grows fast but is not able to achieve profitability is fragile. I recently covered Snapchat Business Model and Tesla Business Model.

When you focus on profitability growth will slow down. However, you’re also allowing the company to become structurally more robust.

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Source: nathanbarry.com/profit

Where is ConvertKit today?

The growth of CovertKit has been an incredible ride:

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What lessons there are to learn here? I believe quite a few.

Accountability: there is no better judge than your audience

One interesting aspect of Nathan Berry project since the beginning has been to make them public. This I believe is also what contributed to ConvertKit growth. In fact, by taking part in the Open Startup program from Baremetrics, ConvertKit was accountable. This is a great incentive to focus on growth and avoid to get distracted.

When Failure goes beyond yourself, it becomes purpose

It’s also interesting the perspective of Nathan Berry on failure when he first took the Web App Challenge:

I don’t think it is likely that I will fail completely. A more likely failure is that I reach only a couple thousand in revenue, but that’s still a partial success. If it does completely fail, then it will be public. At least I, and everyone reading my posts, will have learned something to apply to future projects.

Thus failure becomes not only a way to learn from your own mistakes, but also to allow your community to learn along the way. This makes failure better digested – I argue – because you give it a meaning that goes beyond yourself. Now, you’re not doing something for your own. You’re doing it so that others can learn from it and get inspired. That is a significant paradigm shift.

Transparency is what makes you real

By sharing his story and numbers, Nathan Berry showed to be real. Transparency isn’t something you find easily in today’s marketing world. In fact, social media have contributed to creating fake influencers and social media gurus, that don’t make a dime but by advising others on how to make money. Instead, when you’re transparent, you allow people to know that you’re real. You’re not faking it, and that is why they can relate to you. Which brings us to the next point:

Community-building is a matter of trust

When people can connect with you because they know you’re real; as you’re not faking it and you’re sharing with them your failures, building up, a community becomes way more natural. That community will be what will help you out build a sustainable business.

Scalability isn’t linear yet requires focus

We like to think linearly about things. I do this, and I get that. Yet as ConvertKit story shows, scalability follows weird paths. You’ve been working for two years on a project just to find it on the slow ramp of death. Then, you start doing something right, and growth picks up exponentially. In short, in a matter of two months, growth accelerates by 10-20 folds. For how much we like to believe in self-help stuff that teaches us to grow every day, just like we were a computer program, that is BS. Real life often follows power laws.

Does it mean you need to stop doing things that “don’t matter”?

Rebalancing the 80/20 principle: can you really focus only on what seems to matter?

Few things will make a huge difference in your life. While the rest will matter not much in terms of results, happiness and so on. This fueled a myth that you can give up those things altogether, and your life and business will take off. That is wrong. Why?

Those things that apparently aren’t giving you any results are still significant. For instance, when Nathan Berry was focusing on his blog, that wasn’t making any money for him. Yet, his influence was growing; and as his influence was growing, his direct sales were more efficient.

Why? People contacted by Natan Berry were honored that he was taking the time to get in touch. Thus, if before he was perceived as a sales guy. After growing his influence, he got seen as a mentor.

Of course, if you take an approach based on optimizing things you might leave out things that at subtle level might seem unimportant. Most times the overall strategy works when you work on several aspects of your business and life. So what it looks useless might turn out to be quite remarkable after all.

Rebalancing Automation: when is it too early to automate?

In the start-up world automation has become a must! However, automation doesn’t work initially. As we saw in the ConvertKit’s case, Nathan Berry had to jump on hundreds of Skype calls with people before his business would take off. Of course, only after you’ve mastered the process you can automate. In fact, today if you go on ConvertKit request a demo page, you now get a recorded video. Yet this was possible after years of tinkering and talking to customers. Without that process that recorded demo would have been meaningless.

Today marketers stress out too much automation, with the risk of automating too early and too badly. Automation starts with tinkering and talking to people. After you’ve mastered that process, you can automate.

Summary and conclusions

Started as a challenge on his blog, CovertKit eventually managed to grow at $1M MRR in March 2018. This is a significant milestone for the company but also an interesting story for those that are thinking about starting, are trying to grow or are facing trouble with scaling up an online business.

Nathan Berry managed to turn around his business with focus, and dedication. Counterintuitively to what you think today, he didn’t use automation. He used direct sales. He didn’t do scalable things. He invested his own time in migrating mail list to ConvertKit for free. Anyone would think this is crazy as it doesn’t scale. Yet without it, it would have been impossible to grow the business.

Also, Nathan Berry at a certain stage of the process understood that profitability was critical to take the next step in building his startup, even though this meant slowing down the revenue growth.

The post ConvertKit Startup Story: How CovertKit grew from $0 to $1M in MRR with direct sales, word-of-mouth, and affiliate marketing appeared first on FourWeekMBA.

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Published on March 20, 2018 14:17

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