This 20 minutes talk has been summarised into one template [3] of 10 slides released under creative commons license.

PS: Watch the movies before you fill the slides!

[1] http://bit.ly/hhrodk The Art of Raising Venture Capital

[2] http://bit.ly/dVB5pI Guy Kawasaki blog named “how to change the world”

[3] Guy Kawasaki, The Art of Raising Venture Capital Presentation’ template

Template from “The Art of Raising Venture Capital” by Abdelkrim BOUJRAF is licensed under a Creative Commons Attribution-ShareAlike 3.0 Unported License.

One of the main concerns for a firm is when, how and to whom they should market their products. Firms make marketing decisions based on how much data they know about their customers and potential customers.

They may choose for mass market when they do not know much about their customers or they may market directly the consumer based on some observed characteristics.

Depending on the needs, the firm will use one of the two methods (primary and secondary) to collect its data.

Primary data collection is more expensive to produce as “they have to be observed and recorded or collected directly from respondents” (William M. Pride, 2008).

They are four main techniques (Baker, 2000):

1. Obtrusive: the interviewee is directly observed while realising an act (e.g. movement of an individual in a kitchen). Disadvantage: its impact on the behaviour of the interviewee as he/she knows he/she is observed; the observer shouldn’t intervene during the experimentation (Hamer, 2003)
2. Non-obtrusive: the interviewee is observed quietly by using “invisible” devices like electronic devices (e.g. camera, internet browser). Advantage: Nominal impact on the behaviour of the interviewee
3. 3. Experiment: the interviewee is requested to test a variable (e.g. a drug, flight simulator). Its difficulty: to establish the results keeping certain variables constant so that the effects of the experimental variables can be measured
4. Survey: the data are collected through mail, telephone, personal interviews that can be structured or unstructured (Amir Azarpazhooh, Winter 2008).  Its difficulty: the “physical” collection of the result is not guaranteed (e.g. the interviewee is too lazy to send the answer by post mail) (Ibeh, 2004)

Secondary data collection is less expensive to produce as they are normally compiled inside or outside the firm. They include: Firm’s records (e.g. Customers sales figures), Trade associations (e.g. chambers of commerce), Government statistics (e.g. Census) or Syndicated research reports (e.g. Gartner) (Baker, 2000) .

Today, the amount of data collected is so huge that computers, spreadsheet applications or more commonly “data mining” are tools used to give value to the data collected (Montgomery, 2001).

Clickstream data, defined as “the electronic record of Internet usage collected by Web servers or third-parties services” (Randolph E. Bucklin, 2008) tracks the navigation patterns of the Internet users in order to display advertising based on the observed interest of the consumer with a high degree of precision:

• Keywords collected from pages the consumer has loaded in its browser
• Data the consumer has entered onto the web pages (e.g. Facebook profile)
• Network-based marketing take advantage of links between consumers to increase sales (Montgomery, 2001); (e.g. Friends of Facebook)

Works Cited

unknown, A. (YYYY, MM DD). Critically analyse the effectiveness of primary and secondary research applied to product development (looking at qualitative and quantitative research). Retrieved December 05, 2010 from UK Essays: http://www.ukessays.com/essays/marketing/primary-secondary-research.php

William M. Pride, O. C. (2008). Marketing, 2010 Edition. Mason: South-Western College Pub.

Amir Azarpazhooh, W. H. (Winter 2008). Structured or unstructured personnel interviews? Healthcare Management Forum , 21 (4), 33-43.

Baker, M. J. (2000). Marketing strategy and management (Palgrave Macmillan; 3rd Revised edition edition ed.). Unknown: Palgrave Macmillan.

Edward H. Ip, P. L. (2004). Interactive Profiler: An Intuitive, Web-Based Statistical Application in Visualizing Educational and Marketing Databases. Journal of Educational and Behavioral Statistics , 29 (2), 157-175.

Ibeh, J. K.-U. (2004). Conducting survey research among organisational populations in developing countries: can the drop and collect technique make a difference? International Journal of Market Research , 46 (3), 375-383.

Hamer, B. (Director). (2003). Kitchen stories [Motion Picture].

M. Kataria, K. L. (2009). Effects of social marketing on battery collection. Conservation and Recycling (53), 429–433.

Montgomery, A. L. (2001). Applying Quantitative Marketing Techniques to the Internet. Interfaces , 31 (2), 90-108.

Randolph E. Bucklin, C. S. (2008, March). Advances in clickstream data analysis in marketing. Journal of Interactice marketing , unknown pages.

Easily described: Dabble DB provides common functionalities of a database: CRUD of records.

But, they provide many features that I’ve seen only in Filemaker many years ago (Filemaker had fewer functionalities, I must admit) : easy database normalisation, data restucturing, grouping, filtering, generation of charts including “world maps“, automatic recognition of patterns allowing Dabble DB to automatically generates calendar, and many other features.
A 7 minutes demo is available and will give you a good idea of what could be achieved.

Now only one question comes to my mind, what is their business model?

1. Inviting people to save their private data like many other web 2.0 companies (Zoho, Signals37, name them…)?
2. Invite CIOs to save their “added value” data?

I’ll never believe in this kind of business model at least because here, in Europe, data privacy means something. A simple calculation decreases their market by 500 millions EU customers and hundrerd of thousands EU companies too!

Even they claim to take care of our privacy, history proves that US government cannot be trusted and our data could be compromised too easily.

Dabble DB cannot be hosted at home, I hope that competitors will align their user interface based on Dabble DB!

Maybe the answer comes already from Ismael Ghalimin, the Intalio co-founder: “…As long as it does not matter that the data stored into Dabble DB can be seen by anyone once you publish it [you can select Dabble DB to host your data]…“.

Off course this post can be applied to all Web 2.0 companies relying on the craziness of people to store their private data on a remote server. I will be glad to see the figures of the kind of customers those Web2.0 have after 2 years……