moorwald

21/06/2021

Ich stolpere noch viel zu oft über Webseiten, die beim Datenschutz Federn lassen. Dabei ist es gar nicht so schwer die gröbsten Fehler zu vermeiden.
Ich bin kein Jurist, doch aufgrund meiner langjährigen Erfahrung unterstütze ich immer wieder Unternehmen dabei die groben Schnitzer auf der eigenen Webseite zu vermeiden.

Hier habe ich einmal einige Hinweise und Checklisten zusammengefasst für den Umgang mit , , , und all diesen „leidigen Themen“.

Ich hoffe die Präsentation hilft dem einen oder der anderen.

Liebe Grüße und einen tollen Abend Euch allen.

03/05/2020

It is still necessary to . So stay at home if you can to protect those who need protection.



Made with . First try of the tool. Starting to love it.

16/12/2019

Working on my website⁣
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I am in the process of designing my website. It is still a long way, but I am in good spirits.⁣
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As a data analyst, I’m a little outside my comfort zone here, but challenging myself is always a good thing.⁣
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I’m curious to see if I’ll get any helpful feedback from the dear people in the community. And I’m looking forward to it.⁣
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08/12/2019

Authentic Data⁣
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As an analyst, it’s not our job to look good. Nor do we have to be popular.⁣
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However, our customers must be able to trust us. We are obliged to report correct data. Our analyses must be authentic and credible. They must help our clients to make the right decisions based on the data.⁣
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Of course, we have to make our customer contacts look good. Especially in front of their boss. Our customers’ superiors must be able to trust them. They must be able to trust the data. Real managers don’t want “fake news”, but “real facts”.⁣
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We have to say goodbye to the hype-cycle and leave the bu****it bingo at home. I plead for more honesty and credibility.⁣
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29/11/2019

ATTRIBUTION MODELLING

Desciding whom to credit for success and how to calculate ROI of a marketing channel can be a quite political minefiled. Especially as there is no one true way to do so. Attribution modelling tries to identify the moment a user makes a buying decision.

But how to identify such a moment. Simple models (that go a good way already) either take the first contact or the last contact before an order as a signal. Or they do a linear attribution to all involved channels.

But what about and ? How to calculate and attribute their part of the conversion? Not so easy. You might want to take a look at my last post for an idea, though.

Whatever model you decide on - never forget it is just a model. You need to take a look at the whole experience your user encounters.

Thanks for inspiration goes to these lovely people



tags

27/11/2019

What is the value of innovation? What is the value of design? What of UX?

There are ways to attach a number to questions like these.

I want to show you one way to report on the ROIn - the Return On Innovation. Just like the Return on Invest this KPI shows the value added by innovative features. But it could just as easily be used to calculate the value of a new design. So for everybody doing or asking your friendly might provide some added arguments for innovation, design and good ux.

If you like my content - please share the love.

If you have any questions, feel free to ask. I will try to answer any question.

Every day I get inspired by great folks like:

.branding .patricia .mars .helen

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24/11/2019

On the weekend my partner (who always inspires me) and I processed some pumpkins. Ok some very many pumpkins. All were historical varieties and as we want to grow them again next year the seeds had to be cleaned.

While I removed the seeds from the pumpkins by hand and cleaned them bit by bit I started to ponder.

Basically, cleaning the seeds is a very appropriate metaphor for cleaning data.

In both cases you first have to get to the data/seeds. You have to dig your way through all kinds of fattening. Once you have the data/seeds in front of you, you have to clean them, sort out those that are broken and thus ensure that you create a valuable substance from a contaminated raw material.

Only in this way can a good fruit/knowledge emerge and grow from the seeds/data.

21/11/2019

Histogram I

A histogram accurately representats the distribution of numerical data.

It’s an estimate of the probability distribution of a continuous variable. It was first introduced by Karl Pearson.

To construct a histogram, first you bin the range of values. Meaning you divide the range of values into a series of intervals.

Then you count how many values fall into each interval. Bins are (usually) non-overlapping intervals of a variable. The bins are often (but not required to be) of equal size.

Histograms give a rough sense of the density of the underlying distribution of the data.

Histograms differs from bar graphs: \

A bar graph relates two variables. \

A histogram relates only one variable.

Also a histogram is used for continuous data, where the bins represent ranges of data, while a bar chart is a plot of categorical variables.

Some recommend that bar charts have gaps between the rectangles to clarify the distinction.

20/11/2019

PageView

A pageview or page view (occasionally page impression), is a request to load a single HTML file (web page).

Nowadays with SPAs it is also measured when the view changes significantly, even without loading a new HTML file.

This being sent to the tracking server is one of the most used metrics.

18/11/2019

Visit

A visit (or often called session) is a unit of measurement of a user’s actions taken within a period of time.

In some cases sessions are defined in regard to completion of a specific task.

Most often a session is the time between the first measured interaction of a user on a website and the last measured interaction that is followed by an interval of inactivity that lasts at least 30 minutes.

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17/11/2019

Definitions

Unique User

According to IFABC Global Web Standards, a unique user is

"An IP address plus a further identifier.

The term “unique visitor” may be used instead of “unique user”. Both have essentially the same meaning.

In Web Analytics (unique) visitors usually are identified by an ID stored in a cookie.

15/11/2019

I love using slopegraphs to compare two points in time.

In addition to the absolute values (the points), the lines give a visual inclination of the increase or decrease in rate of change (via the slope).

No need to explain specifically, as that’s what they are doing. It’s intuitive.

In conclusion, Slopegraphs are great if you find yourself comparing two groups across the same dimensions. Also if you are plotting two points in time.

Use them to visualize your data in a way that would be intuitive for your audience. Make what you want to highlight as easy as possible to see.

13/11/2019

13/11/2019

13/11/2019

Wie schon auf Instagram geteilt möchte ich natürlich den Begin meiner Reihe auch hier posten.

Ich erkläre hier Stück für Stück verschiedene Graphen und für welche Zwecke (oder Daten) man sie gut einsetzen kann.