Hoe we onze op gebruikers gebaseerde groeimotor hebben veranderd in een revolutionaire beweging  💥

Een inzichtelijke kijk op mijn eigen diepte-interview op de coole blog van Canva 👐

We laten onze snelgroeiende community van professionals de controle over ons platform overnemen .

Nu maken we van al deze waanzin een beweging die de manier waarop professionals kennis ontdekken en consumeren, verandert in het tijdperk van informatie-overload en content-shock.

- - -

Eerst afhaalrestaurants

Bottom-lines vanaf ons eerste jaar als startup

We increased the Network Effect “density" on our platform in the past few weeks and the impact on the amount of Weekly Active Users is MASSIVE =)

Stats

• •We will cross the 16,000 Weekly Active Users mark in a few weeks from now
• •We launched one revenue channel pilot last month. By the end of this month it will generate $7,500 MRR

Thoughts

1. 1Who would have thought that two founders and a team of seven volunteer workers could pick up such an initiative? Without any funding.
2. 2Such initiative that it’s making the biggest companies in the fields of EdTech, Content, Media, and Product reach out to us to understand “how we do it".
3. 3Such initiative that causes a large number of angels and funds to proactively contact us and explore funding opportunities. 
   We’ll talk about investments and strategic partnerships more in my next post.

— — —

Let’s try something different this time, alright?

Instead of writing an article in a storytelling style, I’ll just write down what’s going on here in bullet-points.

That will help me convey the messages in a more sharp and interesting manner.

Shall we? Let’s go!

— — —

Chapter One

Huge mistake: Putting people in the center of your startup’s technology.

Not a huge mistake: Putting people ahead of your startup technology.

• •There is no reliable and effective solution for professionals to discover and consume content that provides added value.
• •Reliability is dimmed as there is more reliance on algorithms to provide us with the content they “think" is relevant to us.
• •Algorithms in centralized platforms (e.g. Facebook, Twitter, LinkedIn) are serving us with content we want, NOT the content we need.
• •The most important part of the content we consume is not how relevant this content is to us (that’s a given), it’s whether or not it holds an added value for us as professionals who consume it
• •OK, so algorithms which serve us content are a great idea to discover and consume content for amateurs (it’s fun to see a cat playing a piano, no?)
• •But when it comes to a professional who wants to consume professional content, it can be hazardous.
• •The big platforms that help us discover and consume content are just adding fuel to the fire. They use relevancy instead of added value to show you their “Recommended for you" content. They put the publishers they work with before the end users who actually want to consume content and that’s a broken mindset.

— — —

Chapter Two

Decision paralysis, content shock and tribes of lemons

When I was CMO at Webydo and met Idan Yalovich, we were both managing large teams of professionals and we both felt that as professionals and managers we sometimes experienced decision paralysis, where due to the surplus of information, you no longer know what is right for you and for your team.

• •But every time someone sent us an article to read, we would read it.
• •It meant that if a person “approved" the content, then it was worth our time.
• •We then discovered two theories: One of of them beautifully described the problem we had, and the other described the solution we chose to solve this problem.
• •The problem was described in Mark Schaefer’s Content Shock theory: The amount of content produced increases exponentially as it becomes cheaper and more accessible to produce it. But our ability to consume content reaches a certain limit.

Taken from Mark’s blog — https://www.businessesgrow.com/2014/01/06/content-shock/

• •The pain of this reality is clearly demonstrated on Fred Wilson’s (Managing Partner at Union Square Ventures) recent artilce: Prioritizing Content Consumption:

Screenshot from Fred’s artilce. Can you relate? We do. And we think that we’ve find the right sollution for this so-well explained pain

• •But the inspiration for the solution came from Seth Godin‘s Tribes theory:

“It turns out that it’s tribes, not money, not factories, that can change our world, that can change politics, that can align large numbers of people … What we do for a living now, all of us, I think, is finding something worth changing, and then assemble tribes that assemble tribes that spread the idea that spread the idea. And it becomes something far bigger than ourselves. It takes a movement. “- Seth Godin, TED," The Tribes we Lead “

Seth’s lecture- The Tibes we Lead. Watch, people. Just watch it.

— — —

Chapter Three

Display window, distilleries and a product which is based on the Network Effect but with a twist of lemon

• •What you see as Zest.is is “only" the display window of the real product. It is in fact the final product of human refining, backed up by machine learning that studies consumers, content, and use of the product.
• •The final product is “individualized professional knowledge". On the one hand, the distillery is filled with content and information overload, and on the other hand, professional knowledge is presented in a tailored and individualized form to each user.
• •The distillery itself is a super-machine (Idan is now writing a mega cool article about it, from the technical PoV) in which hundreds of volunteers go over the content that has been submitted by the rest of the community.
• •The distillery is built in a hierarchical way and the distilling space is like a digital collaborative Wework, where everyone is content contentious, holding discussions about whether “this article is Zest-worthy or not," commenting on each other’s decision making and offer immediate improvements.
• •The more distillers (members) there are, the better the refining process is.
• •The more distillers there are, the better machine learning process will be, and we will be able to serve added value content in an individualized way to the end users.
• •To sum up this chapter: Zest is a Multilevel Network Effect product (See NFX’s blog for more Network Effects gems).There may be another two or three products in this style that solve other problems: like Waze and Wikipedia.

— — —

Ok, let’s stop here and leave Chapters 4 and 5 for the next article.

— — —

And for the yellow Zesteam: Nichole Elizabeth DeMeré, Katarina Andrejević, Tal Atzmon, Karolis Vanagas, Omer Buzo:

Without you, I’m sure that this lemon would not have been that juicy. Hack that, I’m quite sure that it would have not even been yellow at all. ;)

— — —

But above all, there is our highly engaged and oh-so helpful members who just keep pushing us to the moon and beyond.

We are so thankful to have you with us.