Naravno da je knjiga daleko kompleksnija i da se bavi dubljim idejama o ovih par crtica.

Kako sam pisao dugo i iscrpno o poslovanju, razvoju biznisa, svim mogućim i nemogućim uglovima preduzetništva, tome je nekako došao, pa… kraj.

Sredinom 2018-te sam se pomerio van granica Srbije i otišao u Švajcarsku i prestao da se bavim preduzetništvom. Ako mogu da dam konačnu misao o čitavom poduhvatu — bilo je divno i bolno. Uglavnom uspešno i uglavom na granici isplativosti.

Birajte tržište na kome ćete se boriti. Ono koje ima novca i ljude kojima treba to šta prodajete.

I to je to o preduzetništvu.

Ali da se vratim ideji knjige.

Sada kada živim van svoje zemlje, kada učim, prihvatam i razumem novo okruženje, veoma mi sve liči na drugu planetu o kojoj sam sanjao da ću nekada moći da nazovem prebivalištem.

A dom je tamo gde je porodica.

Pre mnogo godina započeo sam poslovni blog, podstaknut tadašnjim Biznis Blogom.

Tokom 10+ godina, mnogo tema o životu, smislu, poslovanju i nekom novom standardu u kvalitetu posla je prošlo kroz tu virtuelnu beležnicu.

Dalji zapisi su podstaknuti onim šta dolazi posle privatnog biznisa na Balkanu.

Putevi

Onda kada prestanete da budete preduzetnik, možete ili biti penzioner (probao, nisam imao dovoljno hobija / hobiji moraju da se pripreme unapred) ili se zaposliti negde (ili jednostavno biti nezaposlen).

Onda kada odaberete da radite za drugog, veliki kamen pada sa vrata (obaveze prema državi, samom sebi, zaposlenima…). Sa druge strane, neke druge obaveze i stege (ako ih tako možete nazvati) padaju na vaša pleća.

Korporativna kultura, politička korektnost, politički razgovori koji nemaju konkretnu informaciju, obavezni treninzi koji postoje da bi potvrdili da ste svesni posledica i načina na koje možete da loše utičete na kompaniju.

Novi kolega, koji je upoznat sa mojom istorijom me je pitao “kako izgleda korporacija”. Odgovor je bio veoma jednostavan “kao i svaka druga”. Promenile su se tehnologije ali je suština ostala ista.

Sistemi koji se polako i teško menjaju.

Jedini način napredovanja je autentičnost. Dobra ili loša — autentičnost.

Biti prosečan ili dobar radnik koji završava poslove je u redu. Napredovanje je rezervisano za autentične ljude.

I one koji žele da preuzmu odgovornost i umeju da vode ljude.

Ako preuzmete takav put stići ćete daleko. Ali budite sigurni da će deo autentičnosti polako bledeti kako idete dalje.

Start of romance

I like to start with business. Business drives demand for certain tools, proven shortcuts and more business. In world of online business, being blind on how business is going, without reports or performance metrics, it’s just not acceptable. Once ads started showing up on websites, ad space became property for sale and money started flowing through online channels, someone started asking questions: how do we measure this, are we better than yesterday, who is buying our stuff?

Eventually, some poor tech guys tried to answer business questions by analyzing what was available to them i.e. website’s log files. Put it simply, they were parsing (drill down) log files trying to answer business questions.

Side note: log file is plain text file sitting on web server with daily diary of web server’s activities. It consist of IP address from where request originated from, timestamp (date and time), requested resource (web page, image, styles…), what was referral (previous step if exist), status code (how web server responded), transferred amount of bytes (internet traffic was expensive long time ago) with identification of browser and operating system.

Tech people tried to answer business questions, producing summaries of parsed log files. With more traffic coming to web server, files grew, along with processing time required for file parsing. This became a bit of a pickle. You could easily end up providing data to business owners, one day after business day was finished. Speed was crucial.

In 1997, team from Urchin (Brief history of Urchin and Google Analytics to become, comes from one of the founders — Scott Crosby) managed to parse these files at fantastic rate, cutting processing from day’s worth time to minutes. This was the birth of modern web analytics. (Yes, there were others doing similar thing and yes, this is a romanticized story. Hate the writer. )

Business love

Believe it or not, people paid for tools that make sense of data. Yes, people pay for using analysis tools extracting data from log files. If these tools could explain business value to higher-up’s without tech supporting extraction, transformation and analysis, even better.

Urchin became really popular (and profitable — this is personal feeling) once it showed business value. Usage of UTM (or Urchin Tracking Monitor) which enabled marketing to measure performance (and do all other magic things) only made nice crust to excellent meat.

The most important thing, for business value, Urchin did, was augmentation of log files (beside fast processing). Where is a business value in augmented data?

Problem with too few bits of data

What can you do with 6 pieces of information? Now, imagine what can you do with 6 columns in Excel.

IP address origin| timestamp of request | request | origin of request | server status | data transferred | web browser that requested information

With these information you could do limited set of reports, understanding how much traffic comes from certain part of country, most popular browser, errors server produced, internet traffic spent. Very, very basic reports and insights.

Once first ISP’s came into existence sharing pool of IP addresses with thousands of users, even IP address was not unique identification of person accessing the web.

Augmentation

What if we could somehow, add more columns to that log file? You know, push more data into table? Like, having much more details. Augmentation is just a fancy word.

By using cookies (and information stored on users computers), running JS code within users browsers and sending this data to servers for processing, growing log files with new columns, carrying important information with business value — Urchin did it.

Why is augmentation important for business?

At one point in time, data coming from processed log files started to be unreliable. Level of detail present in log files was not deep enough. Business required more detailed information.

Log files could be expanded as they were textual in nature. Once moved to database structure, even faster and expandable.

In order to bring business value, user level i.e. browser level information was required. Each person or his/her’s browser must be unique and leave unique trail within expanded log files.

Cookies

In order to have some kind of unique information identifying browser (not yet particular user) cookies came into picture, storing unique first party cookie information tied to visited domain. That’s how analytics JS code could detect if user ever before visited web site and what was his/her unique identification (clientId).

With few key pieces of information, GA engine could stitch collected data from JS with behavior on particular domain and present information neatly tied together.

Data model

In order to understand how analytics engine groups information received from browser we should dig a little deeper into technology (nothing hard).

Every hit is actually new row in a log file, placed in specific sheet of enormous Excel which can represent your GA property. Hits are different and separated by type (pageviews, events, transactions…).

Rules and regulations

Like any system, web analytics is ruled by certain scope of expectations, what is possible, how data is interpreted, etc… But the basic one is: what is not recorded or pushed toward analytic servers will not be analyzed and processed.

Implication of this is — quality of data. You can not expect to have efficient and certain (up to some degree) analysis if data stored in your big tables is not on certain level of quality.

In order to properly understand what is session or hit — I suggest you dig deeper into documentation.

Didn’t you mentioned a little way back Excel?

This is very controversial thing to say and compare system like Google Analytics (or any other analytics) with software like Excel. Totally different breed of software but the function is comparable.

Analytic platform deals with vast amount of data stored in rows and columns (rows = hits, columns = data associated with particular hit). Each user, or session information is analyzed based on some key information that actually filters the data, groups the information, summarize it, makes average and repeats the function endlessly. Any spreadsheet program does it with pivots, right?

Excel is universal tool, which helps people live a bit easier in their jobs analyzing data. It is empty shell ready to be filled with information and drilled down.

On the other side, analytic platform creates data needed for analysis.

Once we (as users) or analytic platform, starts augmenting data based on business needs, everyone’s analytic tool starts to be very personal. Functionalities built into tools are for every day’s purpose — how’s business doing. But the key point is — how you configure your data, how you make data richer and how you use this data to make business better. This is the moment when (almost) no one else can understand you dataset and information stored within dataset, except you.

At the end, you end up looking after graphs and summarized (or averaged) information, based on crunched data.

Your analytics tool will provide you will all kinds of graphs and figures, and you will find value in information.

Why would you care about quality?

Imagine you have to make decision, on how much you should invest in advertising (display or search) or SEO activities. You must have data within your analytics tool which will provide you with precise enough (collected data is never collected 100% as internet is not 100% reliable, along with people behavior) information to make decision. If you don’t have enough details on you advertising efforts, you can not compare and make decision.

Quality of data allows you to make better decision.

Added value of analytic systems

We mentioned augmentation, as key moment in creation of business value with analytic systems.

Google grew Analytics system built on top of log file analyzer with stitching capabilities, enriched with additional columns, adding throughout the years new services built in-house or through acquisition.

Growth of Google Analytics from date of acquisition to present day by Head of Web Analytics for Google EMEA — Brian Clifton (period 2005–2008).

This is not bad. This is the way how to add value to (somewhere) free product. Allowing Google to reach into vast amount of data website visitors generate, while offering to website owners understanding how these people behave.

Off course, there are numerous issues, from ad-blockers, browsers, web servers, proper tagging, quality of data… but at the end — you receive product giving its users glimpse who are people and how people behave during their customer journey.

And yes, it depends on quality of data, that analytics platform receives and crunches.

More better romance

Once you notice that information you receive is sampled, figures strangely change between days, key dimension in analysis is required — you start blaming that damn tool behavior. Next question you ask is: how can I get better quality and what is going on?

The answer comes with premium product (paid). More storage space, processing power, tools, support staff — cost money.

Once you notice value in information, provided by analytic platform, you are ready to think about paying premium solution.

It’s complicated…

The moment you go into paying zone, more people come onboard. Not necessarily to make you life and engagement with data “complex”, but to provide you with higher quality of acquired data. To make your workflows efficient.

Complexity comes from the world we live in. Nothing is really simple anymore. Deep thinking about collection, and how processing will occur in order to have high quality analysis, became new norm.

Probably everything you collected and analyzed before is not good enough. But you made it and used data to grow relationship and trust data.

Cheaters

In every romance there is a cheat moment. We would like to game the system, get more than possible, overcome obstacles with some smart hack — and not get noticed or found out. Someone would not get caught a some will. Play by the rules and don’t put yourself in risk.

Is it worth hacking the system and abusing machines?

Marriage

At the end — best stories end with marriage. Holy union between data and business that produces result. You already have this kind of union on the side of Business Intelligence (BI) and business itself.

However, BI deals with people who are customers, where web analysis (or web intelligence) deals with people who will become customers.

In this moment we are entering strange place where there we see three actors working toward the same goal, from different sides, crying for attention.

Future

We will see new form of union of businesses, business data and world (web/apps/offline) data. In order for business to grow, analysis would need to go deeper, considering wide range of elements coming from different directions.

And that’s how romantic story became business.

Second World is between First and Third World countries. You know — the ones not really “there”. I will take literal freedom to describe all World countries and what they represent.

You see, when you live either in US or Canada, Japan, European union (+some more) you belong to First World country. Meaning you can travel most of the other countries in the world without much problem. Start a business, have laws protecting you or your investment/property, access to cheaper money, having options. You know — the regular.

Third World countries and their living population, on contrary, have serious problems. Not that they are problems you are facing but different kind of problems. Failed economies, oppressive regimes, messed up property rights, laws of stronger bully… You know — everything you’ve seen on TV with title “Shocking” or “Disturbing”.

One of the problem is moving to First World country. Limited to their environment and borders, they watch the world through TV sets, imagining their future somewhere else. You both see reality presented to you — first looking at it with pity and hidden fear of that reality coming to them, and other wanting security and peace.

Which brings us to Second World, vast number of countries between poverty/oppressive regimes/failed economies — and freedom to choose, social security nets (or not), legal systems run by some form of democracy, and opportunity to live long and prosperous.

Second World managed to survive most of the problems that happened to Third World, pushing toward First World ranks … and yet — still not getting “there”. Everyone would like to get to the First league but very few gets there. The rules are constantly changing and standards rise as we speak. Human rights, laws, standards change constantly. Just as you think you “got there” something changes.

For a short period of time last year as SWC citizen I had opportunity to have my passport filled with visas for different FW countries — meaning that I did not have any kind of problem arriving and being there.

And you know what I figured out? It is the same all over the world.

Yes — there are very different aspects of life (and quality of life) but people are more or less the same. Bullies are the same, they just take different forms. Sometimes it is the gang from the block, sometimes it is government — which preserves the way of life and food chain. But people are always the same — with same fears and needs. Somewhere with more variety and options and somewhere without one.

And all referencing to ones setting the standard, which we all desire.

Hello from Second World (and Third) wanting to make our country nicer to live.