Minimizing leakage in a marketplace for offline services 

"How do you deal with offline transactions?"
If I had a dollar for every time someone asked me that question...

Leakage is a problem that exists in any marketplace that deals with face to face services. It’s just like in fairy tails: when a charming customer meets a handsome service provider and they like each other - they want to stay in touch and might end up doing it outside of the platform.
Incredible customer satisfaction, amazing retention, except they all happen outside of your product, which is kind of a bummer…

Before I talk about how we deal with this phenomenon, let me start by saying this:

There’s no hermetic way to solve a marketplace leakage. Anyone who claims differently is either lying or simply too blind to see it. 
There are, however, many ways to mitigate this risk and minimize the leakage.

Evaluate your Product/Marketplace Fit:  Before diving into the tactical actions to minimize leakage, it’s important to understand the WHY.
Why would any of the suppliers …

Cohort analysis - 4 ways to analyze your product retention rate

We all know the importance of retention for the long term success of our products.
Retention is the key to creating a sustainable business. It shows long term engagement of your most loyal users - and that’s a strong sign of a product/market fit. It influences how much revenue will each cohort produce over time and therefore what would be the lifetime value.
Higher retention = more recurring paying users.

Retention is the key for creating a sustainable business. 
And while tweaking your onboarding process and funnels may drive immediate improvements in conversion rates (and produce instant gratification) - retention is a long term process, it often requires some heavy lifting, deeper analysis, but once it pays off - it can dramatically change the business results of your product.

In this post, I would like to share 4 useful variations of retention reports that can become very handy when analyzing the performance of a product across time.

So let's begin:

4 practical methods to an…

Your boss is obsessed with terminology? You probably deserve it!

My first boss was fanatical about using the right terminology and industry jargon. 
He was right.
I recently came across an interesting post by a product manager, complaining that her CEO freaks out whenever a wrong term is used in a document, a meeting, or even worse, in the product.

It reminded me of my first CEO who repeatedly urged all of us (sales, PMs, developers, QA engineers) to use the terminology and jargon used by the industry our products operated in.

He used to argue with us, correct us, waste time on explaining that words are more important than features, and he even fired someone for using Disney-style terms in a product demo (true story!). He was fanatical about terminology, and while it felt like madness 20 years ago, today I know he was right and we were all wrong.

Reading that young PM question (and some of the answers), convinced me to write this post and emphasize why product leaders should MUST be fanatic about terminology. 
It all comes down to communication, aut…

20 Dark Patterns to avoid when designing products

2 months ago I collected a crazy list of 84 cognitive biases that can be used to design better products.

The post received a lot of positive feedback, tons of backlinks, and was featured in numerous UX newsletters, but there were some readers who didn’t like the provocative title (using the term “exploit”) and thought that some of the examples (heck, I made over 40 design snippets that night!) were too manipulative and got into the gray zone of design, acting as dark patterns.

While I agree that some of the examples I used (especially the ones related to scarcity effect, loss aversion, and negativity bias) were a little bit manipulative, most for them were perfectly legit, and demonstrated how good design should take advantage of the human brain (with all of its' malfunctions) to convey a better message, emphasize the value of the product, improve conversion rates and establish trust with the users.

Since the term 'Dark Patterns' was brought up in those discussions, I dec…

10 shades of MVP (or: how to develop a product without developing a product...)

A minimum viable product (MVP) is often perceived as a subset of the real product: a minimized version, lacking some features or missing some UI fine-tunes, but in fact, an MVP is more of a tool to test the core idea of what’s intended to be a product someday.

While the name MVP suggests that it has to be both a product and a viable thing - the software industry has proven it doesn’t have to be the case. 
In fact, an MVP doesn’t have to be a product at all: it can be an email, a Facebook group, a service, or a bunch of processes performed manually.

An MVP is there to help you test your business riskiest assumptions, see if your product can provide enough value to attract customers, and collect some feedback that can guide you through the product development.
And last, people should be willing to pay for it (with real money or some level of commitment) - otherwise, it’s just theoretical exercise that cannot prove that the idea is commercially viable.

An incomplete list of MVP types:  …

11 lessons learned while trying to become a data-driven company

4 years ago we founded Missbeez: a mobile marketplace for lifestyle and beauty services on-demand.  For me, it was a significant change from leading a large B2B product to co-founding a small B2C startup. 
From the very beginning, it was clear that data will play a significant role in our decision-making process. We moved fast, made a lot of experimental changes, and didn't have those large customer representatives to talk to when making our decisions. I had to change my habits and replace humans with numbers.

We've embedded Mixpanel, Google Analytics, AppsFlyer, Facebook SDKs, Crashlytics, and a bunch of other tools, we created our own dashboard as well as a unique and addictive mobile dashboard, and deployed a set of real-time logs. It was fun!
Over the first 2 years of our startup, we've learned the hard way that being a data-driven company is harder than it seems.
I would like to share with you some of the lessons learned while working with data. I believe our insight…