A Thought on Web Analytics and Big Digital Data

Kris
Kris

Table of Contents

I find more and more articles on Big Digital Data in major media outlets and also hearing it on radio. Since Google introduced its search engine to the world and came to known the existence of their algorithms behind their search data, I’ve always sensed that digital data, especially in the application and usage in businesses was going to take off.

It made clear to me that web analytics was the first outlet for people like me to be immersed into digital data. Google Analytics was a breakthrough which allowed people to track their website or blogs at no cost. At that time of introduction of Google Analytics to the public, websites or blogs were the primary digital property and avenue that was measurable other than the online ads.

We’re now in an era where every content are available in a digital form (books, music, videos, photos, what you like/share, etc.). Even historical archives that are in libraries or museums or even government records are digitized. When that data becomes available, a lot of cool stuff can be done from the data analytics standpoint, and many people around the world could benefit from it. That huge data is commonly referred to as ‘Big Data’.

I strongly believe that Web Analytics analysts need to look beyond websites. Even if the website is the primary channel for your consumer’s touch point within your business, still look beyond by thinking how to integrate and scale more data to best champion it.

There are many avenues of digital data outside of website analytics platform, and here is the list of major digital channels that are well measurable (not limited to…):

  • Social Media (shares, tweets, likes, social graph, sentiments, etc.)
  • Videos
  • Paid Media Ads
  • Market data
  • Consumer profile data
  • Voice of Consumers
  • Survey

So why am I referencing BIG Data? Well, the way I see it is, all these data sources are in silo. They’re all useful in its own way, but very hard to link to it as a causation, given that these data as a silo do great in correlation. The same goes with Big Data.

This is also mentioned in the NYT’s article on Big Data as…

Data is tamed and understood using computer and mathematical models. These models, like metaphors in literature, are explanatory simplifications. They are useful for understanding, but they have their limits. A model might spot a correlation and draw a statistical inference that is unfair or discriminatory, based on online searches, affecting the products, bank loans and health insurance a person is offered, privacy advocates warn.

 

So this is where I think web anlaytics is positioned really well in many ways. There is no need to be a statistician, if you put your stick in the ground and leverage Web Analytics integrated data to measure ROI, then your business folks will be happy and if business takes action on the data, you can make improvements in business results, and make more money.

Here are few examples that could help illustrate what I’m thinking…

You have a video on YouTube generating tons of views (like.. multi millions views) and likes. However, you don’t know the value of that video. You can use statistical models or correlate to sales and say, “yes!” it is influencing sales… Reason you can’t tie it directly to sales is because video’s data is within Youtube and not passed or integrated with other channels.

Another way to approach that analysis is, let’s say you find that Video on your website, perform segmentation analysis on Video viewed (or initiated as you can’t track video view completion) and Purchased a product Versus people who did not saw the Video and Purchased the product. Now you know exactly what the incremental sales it gives you online from dollar stand point. To me, that is much more tangible than some fuzzy correlation stuff.

Another one…
Social Gaming company is getting billions of record of data on what gamers are unlocking and buying within the game. A lot of them are using sales attribution or statistical models to look at what contributes to MAU or DAU (monthly/daily active users). They’re very happy because they got Big big data and they can do some complex/insane segmentations within their lovely database using SQL and modeling.

So what traffic acquisition channels drove that sales or even engaged audience?
How are they going to target that audience to make them a repeat user?
Macro eco system changes, so what’s happening our side of the gaming platform that is impacting the business?

These data attributes could come from Web Analytics platform as well as other external database, but just because you have a lot of data doesn’t mean you can make sense of it by itself, it helps to better perform analysis if you integrate with other external data as well.

It boils down to what you really want to understand and analyze, but the the point I want to make is that, Digital Analytics are being highlighted in a silo, but not in an integrated way. At least that is what I feel based on my subjective view…

For us, digital analysts, we have to recognize the point where rubber meets the road, or at a data point where we can do causal analysis after seeing correlation. That has nothing to do with Big Data Vs. traditional data or web analytics or blah blah… It comes to digital data is awesome, and both Big Data and non-Big data needs to co-exist to better make sense of it by good analysts.

I think that concept is mentioned lightly and a lot of people/businesses aren’t talking about that, which is truly the important part of the data business.

Marketing Strategy

Kris

As a data journalist, I enjoy curating and analyzing marketing trends, and data. The things that fascinate me the most are the transforming business landscape due to evolving marketing technologies.