HN user

pospischil

1,105 karma

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eng.amperity.com 6y ago

Beyond CLV: Modeling meaningful moments in the customer journey

pospischil
10pts0
medium.com 7y ago

Entering the New Era of Intelligent Retail with Custora (YC W11)

pospischil
3pts0
www.custora.com 12y ago

Ecommerce Holiday Trends and Benchmarks

pospischil
8pts0
blog.custora.com 13y ago

Sparse matrix formats: pros and cons (R stats)

pospischil
2pts0
blog.custora.com 13y ago

Introducing Member Lifetime Value

pospischil
4pts0
www.timeinc.com 13y ago

NYC Startups to Watch

pospischil
39pts17
venturebeat.com 13y ago

Custora's (YC W11) new platform lets retailers test any marketing strategy

pospischil
7pts0
blog.custora.com 13y ago

Why average revenue per user is a useless metric

pospischil
9pts0
www.custora.com 13y ago

Ecommerce Behavior Around the Holidays

pospischil
8pts0
www.custora.com 13y ago

The Cost of an Email Unsubscribe

pospischil
39pts33
blog.custora.com 13y ago

Don’t look at Average Time to Conversion

pospischil
20pts1
blog.custora.com 13y ago

Designing Marketing Experiments

pospischil
2pts0
blog.custora.com 13y ago

Evaluating Significance – Designing a Marketing Experiment

pospischil
7pts0
howtowriteabusinessplan.com 13y ago

Follow 3 startups through the SpringBoard Mobile accelerator

pospischil
4pts4
howtowriteabusinessplan.com 13y ago

Interview with Custora (YC W11) Co-Founder Jon Pospischil

pospischil
21pts0
blog.custora.com 14y ago

How I Predicted Pebble Backers with 98% Accuracy

pospischil
17pts2
betakit.com 14y ago

Custora (YC W11) Ecommerce Analytics Debuts Update, Analyzes $10B

pospischil
29pts0
gigaom.com 14y ago

Meet the startup helping sites like Fab and Etsy court their customers

pospischil
7pts0
www.nytimes.com 14y ago

Learning to Chase Online Word of Mouth

pospischil
7pts0
blog.custora.com 14y ago

A Bayesian Approach to A/B Testing

pospischil
99pts20
blog.custora.com 14y ago

Use Probability Models to Predict Pebble Sales (and win a Pebble)

pospischil
34pts10
blog.custora.com 14y ago

Infographic: How different are mobile customers?

pospischil
17pts0
www.kickstarter.com 14y ago

Pebble becomes most funded kickstarter project ever

pospischil
2pts1
blog.custora.com 14y ago

Objective C-like Null Object Pattern in Ruby

pospischil
5pts0
techcrunch.com 14y ago

Fab: In 2 Years, iPad Users Will Account For A Quarter Of Our Revenue

pospischil
8pts0
gigaom.com 14y ago

Fab.com’s iPad app users account for 25 percent of revenue

pospischil
6pts0
blog.custora.com 14y ago

Predicting Customer Pregnancy At Target (How We Would Do It)

pospischil
20pts5
blog.custora.com 14y ago

Customer Lifetime Value techniques: be careful with cohort analysis

pospischil
37pts3
blog.custora.com 14y ago

How ARPU can lead to a 120% error in Customer Lifetime Value

pospischil
38pts6
blog.custora.com 14y ago

Dispelling the myths of customer retention in retail

pospischil
18pts2

OP here -- the numbers are in no way bogus, all sourcing information and methodologies are listed on the page itself (see the bottom left * on each 'slide').

Would love to understand what gave you that impression, as we work hard to build content like this, and hate to see it shrugged off.

Why?

I've read that they offer few benefits, but I've never heard this explanation. I also don't see how it makes sense for a company in their position?

OK -- the data is definitely out of date for at least one company (ours, custora). I wonder how common this is? Perhaps the cache was not cleared before generating the output?

I forked the repo, ran it on custora.com, and eNom was (correctly) listed as the registrar.

I'm re-running the full ycombinator list now, and will update when finished.

Is the data collection methodology described somewhere? I'm questioning the accuracy given an error on our data (GoDaddy is not our registrar, namecheap is).

It's also a bit suspect that namecheap is not listed as anyone's registrar after so many fled GoDaddy for namecheap a few weeks back.

Whoops! Thanks for the feedback! That's an old page that was supposed to be replaced on our latest redesign.

The simplest explanation is pattern matching: we analyze customer and transactional data to understand how different customers behave. Using this understanding we can make predictions for how each user will behave in the future.

We use all of that analysis to power actions - take actions on the right user at the right time, optimizing for CLV.

Here's more: https://www.custora.com/home/customer_lifetime_value

[dead] 15 years ago

Having quite a bit of trouble down here in south jersey.

[dead] 15 years ago

Felt it in south jersey. Shook my house quite a bit, even knocked some things off the kitchen counter. Lasted quite a while (felt like close to a minute).

Sounds like you have some fantastic customers/a great product!

It's possible (and likely) that your CLV is changing over time as the mix of customers you are getting is changing - the key is to be able to calculate CLV as early as possible while still getting an accurate number.

If you are going to earn $1500 in profit from a customer, why wouldn't you be willing to spend $1200 to acquire more? The issue you may run into is that, if your $1500 customers found you organically, you can't necessarily expect customers you acquire via different means to be worth the same.

There are some other variables at play as well: are you cash constrained? How soon do you need your acquisition expense to be paid back?

Absolutely - the next step is to calculate the CLV of different acquisition channels. Maybe Organic search results in a favorable mix of good vs mediocre vs bad customers, whereas affiliate marketing results in a poor mix.

You can use this information to help inform a new channel decision (a new paid search channel will likely be more similar to another paid search channel then it will be to an affiliate program).

Behavioral triggers (which Custora uses) get more complicated -- but maybe we'll touch on that in a future post.

Disclaimer: I'm the co-founder of Custora (YC W11), and one of the keys to our product is accurate lifetime value estimation.

This is a great rundown of how to do a descriptive revenue per customer analysis.

As many have pointed out here, true CLV really needs to account for the expected value of customers as well -- not just what we have seen, but how we expect customers to behave into the future. This information can help us determine how much to spend on customer acquisition. Even better, performing the calculations across acquisition sources helps us decide where to spend our advertising dollars in future periods.

The single most important thing to recognize when building a survival model is that there isn't a constant retention rate. Instead, when customers join, some are good (slow churners) and others are bad (quick churners). The key to an accurate survival analysis (and thus, an accurate LTV number), is getting a sense of this distribution of customers.

Thanks!

Our models are calibrated first using transaction data, then by layering in other types of usage.

Acquisition channel is then looked at to see which sources drove the customers with the highest lifetime values.

As for data in/out: we integrate directly with a number of recurring billing and shopping cart platforms or we can take simple log file inputs.

From the bits and pieces that I have read, there are some very real patent questions still looming.

Jason Garett-Glaser put together a great comparison of h.264 vs VP8/WebM. Check it out here: http://x264dev.multimedia.cx/archives/377

His summary: the spec is really terrible, the performance leaves a lot to be desired (though, there is a lot of room for optimization), and it 'copies too much from H.264 for comfort'.

Im working on a service, currently in private beta, that I think you (and lots of others here on HN) would be interested in.

Shoot me an email and I'd love to tell you more about it: Pospischil at gmail

I definitely like the concept. My hang up is -- how is this different than mahalo answers? (more focused, sure, but the mahalo folks could answer these questions, no?) Doing something to verify the tutor's expertise might help with this (could be simple quizzes or something).

Another general note -- as a tutor, I'd like some assurance that I will get paid for answering the question. This may lead to less questions, but significantly more answers. This obviously introduces quite a bit of complexity for the poster, but I think its necessary. You could potentially start people with a few pounds in their account that you finance to get things rolling (or, give people a few pounds when they sign up and add a credit card).

Next -- visual design -- I was impressed with your design, there are some nit-picky things to tweak, but overall it is visually appealing. -In safari, the sign in/register links at the top have the descender part of the g gets cut off (probably because the containing div is too short). -The font color in the "Post My Question", "View All Questions", "Answer Question/Make Bid", etc is a bit difficult to read. This one nags at me quite a bit because it makes the buttons look pixelated or something -- i'd fix this up right away. -Really like the visual representation of description of service -> ask a question call to action. looks great/leads the eye the way you want it to!

As others mentioned -- the about us could use some copy. Don't want to spend too much time on it, but it adds a lot of credibility (or rather, it takes a lot a way to see 1 line of text there).

I have to run here in a second, but one last thing -- you might want to think about requiring signup AFTER someone has answered the question (as you do with the asking of a question). Once someone has spent time answering a question they are more likely to sign up.

Wish I had some more time, but the site looks good, keep up the great work!

Good luck!

No one has mentioned it, but sifter looks like a great app (www.sifterapp.com). I tried it for a project I was working on, mostly because I was curious about the interface. It was much more than we needed, but could be a great option for you.

So do we. The interface isn't the greatest, but it is configurable enough (on screen, no coding required) to cover just about anything. And if for some reason it doesn't do what you need, and you can't configure it to do so, it's written in rails so diving in is no trouble at all.

- Your design is a great start -- The guy holding the megaphone gets the point across very well.

- Trends are a great idea, and showing them by area makes it a lot more powerful (for example, i'd love to see what people are saying about the election right now, here in south jersey).

- My first question when visiting the site is -- How will the public people see my postcard?

- My next question is -- why should I use this instead of twitter, where I can do things like @reply the public person.

- The top message "send positive/negative postcards"... conflicts with the bullet list of the things I can use the service for...

- I'm not sure navigating between realtime and trends to set the geographic area of search is very clear to a user. Not quite obvious enough

- I think you can lean things out a bit -- do you really need a log in box taking up that much space on every screen?

- Real time: the map is a neat attention grabber, and gets me interested a bit the first time visiting, but I'm not sure it would be as enticing on later views. As mentioned above, I'd work on a more direct way to see trends in an area.

Great start, hope this was helpful!