The Digital Analytics Association defines Digital Analytics as the measurement, collection, analysis and reporting of internet data for purposes of understanding and optimising digital usage.
It’s not a minor thing that analysis and reporting are separated. Analysis and reporting are two really different things.
1. Analysis: Is the process of breaking a complex topic or substance into smaller parts to gain a better understanding of it. The technique has been applied in the study of mathematics and logic since before Aristotle (384–322 B.C.), though analysis as a formal concept is a relatively recent development.
The word comes from the Ancient Greek ἀνάλυσις (analusis, “a breaking up”, from ana- “up, throughout” and lysis “a loosening”).
As a formal concept, the method has variously been ascribed to Alhazen, René Descartes (and the contemporary philosopher René Dechamps 🙂 ), and Galileo Galilei. It has also been ascribed to Isaac Newton, in the form of a practical method of physical discovery (which he did not name or formally describe). Analysis definition here.
2. Reporting: A report or account is any informational work (usually of writing, speech, television, or film) made with the specific intention of relaying information or recounting certain events in a widely presentable form. Written reports are documents which present focused, salient content to a specific audience. Reports are often used to display the result of an experiment, investigation, or inquiry. The audience may be public or private, an individual or the public in general. Reports are used in government, business, education, science, and other fields.
Reports use features such as graphics, images, voice, or specialized vocabulary in order to persuade that specific audience to undertake an action. One of the most common formats for presenting reports is IMRAD: Introduction, Methods, Results and Discussion. This structure is standard for the genre because it mirrors the traditional publication of scientific research and summons the ethos and credibility of that discipline. Reports are not required to follow this pattern, and may use alternative patterns like the problem-solution format. Report definition here.
As you can see, in the above definitions there are to important points.
The analysis definition says that in the Analysis process it’s one person breaking up the information in smaller parts trying to identify insights, with his mental model. In that process the person generates constants questions and answers that defines the final the context in which some identified insight make sense. I call that the P.I.S. or personal information sense. The biggest challenge that an Analyst have is to transfer the P.I.S. to the reported person through the report. In the Report definition it says that you have to present the report with the method, however the P.I.S. is not the method. We can identify the P.I.S. like the mental process than with methodology.
Why is this important? I witness many times the presentation of a report by, in the best case, the analyst or, in the worst case, by another person (the cool person that presents reports to the client, because the “nerd” should not be in touch with clients (???)). Most of the cases I was not able to understand what was that slide trying to say or how the person was relating that “insight” with the shown information. The answer is that the context is given by the P.I.S. that in most cases is not transferred from the analyst to the reported person.
To do this you can use a simple method. Analytics is part of the logic (from the Ancient Greek: λογική, logike) which describes the use of valid reasoning. So the P.I.S. can be transfer using the Logic methods in each slide (that should transfer one clear and useful insight). One of those methods is the syllogism (Greek: συλλογισμός – syllogismos – “conclusion,” “inference”) is a kind of logical argument in which deductive reasoning is used to arrive at a conclusion based on two or more propositions that are asserted or assumed to be true.
There are infinitely many possible syllogisms, but only a finite number of logically distinct types, which we classify and enumerate below. Note that the syllogism above has the abstract form:
Major premise: All M are P.
Minor premise: All S are M.
Conclusion: All S are P.
The premises and conclusion of a syllogism can be any of four types, which are labeled by letters as follows. The meaning of the letters is given by the table:
|a||All||S||are||P||universal affirmatives||All humans are mortal.|
|e||No||S||are||P||universal negatives||No humans are perfect.|
|i||Some||S||are||P||particular affirmatives||Some humans are healthy.|
|o||Some||S||are not||P||particular negatives||Some humans are not clever.|
In Analytics, Aristotle mostly uses the letters A, B and C (actually, the Greek letters alpha, beta and gamma) as term place holders, rather than giving concrete examples, an innovation at the time. It is traditional to use is rather than are as the copula, hence All A is B rather than All As are Bs. It is traditional and convenient practice to use a, e, i, o as infix operators so the categorical statements can be written succinctly:
|All A is B||AaB|
|No A is B||AeB|
|Some A is B||AiB|
|Some A is not B||AoB|
So each slide can transfer the P.I.S. by using, for instance, syllogisms that explains the valid reasoning that we are transferring in each slide and which will help the reported person understand why you are saying that.
The valid reasoning should be supported by valid statistical models. So you can say, every time we show product B in the conversion funnel of product A the ticket value increases 20% (Square R 0.8, anova model), so if we increases the product B x% more in the same process, we will get a X% higher average ticket value with a confidence level of 95%. In this example, we are using a valid reasoning in parallel with a valid statistical method and we know the risk we are assuming by making that decision (increasing X% the appearance of product B).