Thursday, April 10, 2014

How to become more C (client) oriented in B2B?

It is obvious that B2C businesses priority is Client. Now, if you are in a B2B, how could you become more C oriented?

Find/get C metrics that B use and show improvements with A/B testing. 

How to improve C metric?
Increase Good patterns and/or Decrease BAD patterns.
How do you find pattern?
Do advance analytics/data mining.   

B2B business usually don't invest much in C but if they were, they will get more business:
  • Better clients experience lead to more business (more clients + more happy business clients)
  • Better clients experience lead to more inbound marketing as oppose to outbound (cost saving)
B2B great companies know they are B2B2C and are client data driven. 

You might have seen this inspiring Jobs 45 sec video but it worth looking at it again (B2C vs B2B):

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Monday, November 25, 2013

Visualizing High Dimensional Data (PCA, LLE, t-SNE)

Here is a Great talk about data visualization: Visualizing Data Using t-SNE - YouTube

Here is the PCA 2 dimension reduction of mnist data (digit 28x28). 

Now with a better transformation to keep distance function.


LLE (collapse many points to one)

So now, what is better in the context of unlabeled data?

You can now use t-SNE to visualize millions of objects. Very exciting!

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Monday, November 18, 2013

Simplicity's impact on conversion

What drives online business is conversion. What is the biggest driver of increase in conversions?
  • More users landing (PPC)
  • Payment simplicity
What is the point of increasing the number of users landing to your site if you don't start by optimizing your biggest show stopper: the payment funnel.

Digital currency such as bitcoin can simplify this funnel by making it one step, not 4. 
So which currency is less friction?

Does simplicity really increase conversion:

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Sunday, November 10, 2013

Why MBA aren't design for startup?

Why standard MBA don't bring any value to startup is quite simple, they are trained to be successful in a big corporation not in a struggling startup in the early stage.

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Thursday, November 7, 2013

Information theory applied to business

If you want to validate a business need, you have to master information theory. 

#1 Evaluating people feedback
        - Indifference = Nice to Have = No value
        - Hate or Desire = High Information = High potential

Potential is proportional to reaction, good or bad. Normal reaction is a sign of nice to have which means no value.

#2 Value
    - Ask = Little value (nice to have)
    - Pain = High Value
    - Observe = a business opportunity

Never ask people want the want, observe them and focus on their pain.

#3 Don't forget: Benefits >>Cost  

Last, there is no business if the benefits aren't significantly higher then the cost.
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Saturday, October 19, 2013

Machine Learning API challenges ahead

Here is a summary of the ML challenges to reach mass market with APIs:
  1. Simplify the preprocessing (data cleaning, features extraction & selection-> 90% work) & integration into a mining or ML (10%) & (opensource project supported by google &  INRIA research group)
  2. Simplification of data visualization
  3. Simplification of semi supervised tagging (reduce the tagging/labelling effort) 
  4. Simplification of parameter selection (model included): Hyperopt: A Python library for optimizing machine learning algorithms; SciPy 2013 - YouTube
  5. For services in the cloud, the biggest show stopper is data transfer (way to slow) & confidentiality

Players to watch: 
PredictionIO : open source machine learning server 
Apache Mahout: Scalable Machine Learning and data-mining
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