I had blogged about getting traffic through bots leaving referral signatures, and it seemed as if the whole internet saw this happening on their sites. After I blogged this post, Moz.com came out with suggestions on putting filters on Google Analytics to clear our your analytics data.

I saw a spike in traffic after I published that post and over a period of time, my normal traffic returned. I still get a sliver of traffic on that post. Interestingly enough, 5% of that traffic is from Samara Oblast.

What is Samara Oblast?

The small city of Samara sends as much traffic to my website as the city of Mumbai (from which I hail from). For those of you who do not know what (or where) is Samara Oblast, Samara is a city in Russia. Technically, its an administrative division better known as an Oblast; hence the name.

Now, the Mumbai traffic I can easily explain. It’s most likely coming from my office and from friends and family. Perhaps, I get an occasional referral through the social sources (which is always great Smile). However, how can a remote district in the soviet generate so much traffic? The remote topic that might be liked by Russians on my blog is DOTA2! That still does not explain this high a number.

Clearly, this seems to be a concerted effort from someone who is generating bot traffic and looks like Samara Oblast is an intentional signature that the bot is leaving behind.

Just like the referral traffic signature.

Geographic Trolling?

To me, this stinks of someone trolling the entire internet into thinking that Samara Oblast locals are responsible for generating this traffic. In truth, its an agency which is targeting all up and coming websites into believing that they are getting referral traffic from Russia.

If its bothering you so much, just filter it out from your GA data. However, I am more interested in seeing what happens after this. I think there is a greater troll at work here and it’d be fun to see what are the next plans. One concern that I have is that if the website is deemed insecure by this bot, then there might be even more malicious bots attacking the site.

So the Samara Oblast bots could just be wolves in sheep’s clothing.

I wrote this note out for a discussion on Social Media sites and how their relationship with publishers has evolved over a period of time. It goes to show that too much of reliance on any one channel may not be such a good thing after all!

Can we as digital marketers and analysts create a measurement model that can reliably help us to identify whether our social media investments are justified?

Social Media and Creators

One of the problems that new Social Media websites face is generating enough content that users want to consume. This they do by welcoming publishers to come and register on their websites. This is the main fuel for their growth.

The social media site in question (including Facebook) does all it can to attract publishers and creators. The focus is on getting more creators and therefore more users. Users get to follow their favorite brands and celebrities on these sites. Brands and celebrities get a scalable way to engage with their fans. A win-win on paper.

A platform is born

As more users sign-up and start using the site, it soon starts being recognized as a platform. This platform now is independently known and now, creators are attracted to the platform not because its easy to publish their content or its easy to create their content … but because that platform already has their potential target audience.

So, from engagement at scale, the reason why the platform is being used shifts to reach and discovery. The very publisher who used to get throngs of crowds flocking around them now is looking at the platform as the source of that crowd. The shift of behavior due to the change in thinking is not amiss to platform owners.

From Win-Win to Monopoly

The platform owner now knows the dependence of the publisher upon the platform. E.g Facebook single-handedly crippled the stock prices of Zynga (famous for Farmville app on Facebook) by taking it off their Featured apps page.

Take the organic reach that Facebook now provides. Some years back (circa 2012), a single post on your Facebook page would be shown to 10-12% of your followers. This has slowly trickled down to 1% now (3%-4% if you have high engagement on the page). The reason behind this is because every brand out there is pushing out more and more content than what the platform was designed for, and every brand / celebrity out there wants to create content that goes viral.

Pursuit of Viral

Publishers in the pursuit of this holy grail tend to create a Sea of Crappy Content. This is loads and loads of content which does not drive engagement. Platform owners now are scared by the very publishers they used to chase. Not because they don’t need them … but because they are not clearly able to differentiate the good ones from the bad ones. The definition of quality becomes more blurred.

Zero Organic Reach

In the end, the platform owner plays the one card that they can control. Throttle the impressions and reach of the publishers. Quality is then replaced with budgets, with the underlying assumption – if you can create great content, most likely you have enough budgets to buy the impressions required to go viral.

Another example to highlight this is to look at any Facebook page which has over 10,000 likes, the last post of that page won’t even have an engagement rate of 1%. The problem may not with the page or the post in itself, it stems from the throttling down of organic reach.

So what can be done?

Do we pay the piper and buy our followers? Or do we dance to the tune of the platforms and keep pushing more content in the hopes of getting that one beautiful post that gets shared by the millions.

Can we instead, arrive at a scientific method of identifying what platform works and what doesn’t in furthering our objectives?

I have been talking about data and analytics for quite some time now. So much so that, I have shifted from doing development as a service (at 13 Llama Studio), to agency as a service (at 13 Llama Interactive). The reason behind this was to capitalise on my love for data analysis and build an organisation that works with data instead of opinions.

From Full Service to Data Analysis

One of the main things that I have been doing, is never say no to anything that lands on my work desk. This is a good thing, since you can pretty much get started as a service based business and do a variety of things.

This, however, is a bad thing since it takes you away from your chosen area of work. In my case, that’s analytics.

We started off as a Full Service Digital Agency and did everything under the sun. Websites, logos, app development … product development, incubation even. Whereas, it’s a fantastic way to keep busy, it did not sate my need to work with numbers.

Saying No

The year 2017 was the year of No. I have been steadfastly refusing to engage with anything which did not involve numbers. So much so that, the organisation that I had so loving built has become an empty shell, almost.

While, this lean attitude is good for companies where there is a lot of waste, taking this to near starvation levels also does not help. Unfortunately, I keep getting such insights only as hindsight :)

What 2017 did offer was a massive consolidation of business interests, which was a good sign. It also taught me the value of human engagement and how business engagements were closely related to the simple human interactions.

Focus on Measurements

I had been going on and on about measurements for some time. I realised that without getting into this completely in your system, you cannot really appreciate this thought. Here’s a quote from Swami Vivekananda –

Take up one idea. Make that one idea your life — think of it, dream of it, live on that idea. Let the brain, muscles, nerves, every part of your body, be full of that idea, and just leave every other idea alone. This is the way to success…

To fully understand and appreciate what this means, do go through this interpretation by Srinivas Venkatram.

It took me some time to fully get this, and for me that meant focusing on analytics. It did not really mean saying No to different engagements. It means applying my love for data and analysis in whichever engagement to drive value.

2018 for me, represents just this. A year where using measurements I would drive value. Be it in product development, be it in promotions.

It’s always a pleasure to use a product that keeps evolving. The possibility of discovering a new feature that’s been recently launched, and the happiness of seeing the applications of that new feature is what keeps me coming back to the product. Google Analytics is one such product for me. Slowly and steadily, they have evolved the product so as to give the free tier users a taste of what Google Analytics Premium (GAP) offers.

Intelligence reports have been around for quite some time now. However, what GA has done in the recent times, is give the user the ability to articulate their question in natural language, and use natural language parsing to understand the question and present meaningful answers back to the user.

Smart and Intelligent reports

Here’s an example of how these intelligent reports work. Suppose, I see a spike in traffic yesterday, and I want to know the reason why.

Normally, I would go to the Source/Medium report in the Acquisition section and see which of the sources have had an increase in traffic since yesterday. However, what intelligent reports does is this –

So what’s the big deal?

The big deal is this. If you are not comfortable with the analytics interface or are not savvy with using the right set of reports for fetching your data, then the intelligent reports are a rather user friendly way for getting access to perhaps the right data.

Notice, in my example, the segments that intelligent reports ended up reporting was a rather advanced segment (Organic traffic, Country-wise).

To reach there, I’d have to go through atleast two separate iterations. This was given to me rather quickly.

Cool, are there any disadvantages?

There is one huge disadvantage. The data given is prescriptive in nature.

You are relying on Google Analytics to give you the right data.

While, for most use cases, the data may not be that important, but for someone whose living runs on getting the right numbers, this may not be enough. It’s good enough to get you started in the right direction though.

Why do I still like it?

The nature of querying is also pretty great. Now, business teams can directly dive into Google Analytics instead of having to wait for an agency or an analyst to make sense of this data. That’s power to the people!

This means, a lot more people can now engage with analytics and take the right data driven steps for improvement.

Recently, I bought a Fitbit. It’s a fantastic tool. Now, I can rave more about the features and go on and on. However, a friend and a colleague asked me an interesting question.

Has it changed you?
No, it did not.

Before I go on, I have to tell you that I am on the heavier side of the weighing scale. Those of you who know me personally would be surprised at the sudden interest in all things health. Yeah, I roll like that.

It’s not about the Fitbit

Like any other measurement tool, the Fitbit is doing a marvelous job at letting me know certain metrics that I need to care about.

They have even gamified the steps by putting in cute little badges and built in peer support (and also peer pressure) to keep me motivated. All this is good as it should be.

At the core of it, it’s a measurement tool. Just like any of the billion other tools we use in Analytics.

Targets and Measurements

On very similar lines, we as marketers or as businessmen often deploy shiny new tools because we think they will help us do more.

Unfortunately, like me in this case, how many of us forget on defining the purpose?

I implicitly assumed that the Fitbit would automatically by some magic give me the purpose of losing weight and leading a more healthy life. Without this purpose, here’s what would happen —

I will wear it to work, and dutifully report the steps taken and life would go on as usual. Some of the badges would come in as time goes by, and it would not really matter to me if I took 2000 steps a day (which is a walk in the park) or 10000 steps a day (I haven’t achieved this yet).

How would I change, if let’s say I choose to give myself a target of say, 10000 steps a day.

Without Purpose, there’s no Change

I would for one have to make time to walk those 10000 steps. I could try walking in the office or doing a much more rigorous transit than an Uber. However, I would have to commit to making the time for those steps.

Thus, this choice of making a change in my routine should be addressed. At the heart of it, the shiny new tool is not at the center. Yes, you have bought Google Analytics Premium and all of that is great … but that’s not really at the center.

At the center, is the purpose. Has this been defined? Has this been clarified and articulated so that the team knows about this?

A tool doesn’t give us Purpose

It does give us a sense of progress towards our purpose. A Measure of Success, if you will. The shiny new tool that we just acquired is useful, but only as long as we keep the purpose at the center.

As people who know how to use a tool, if we do not understand the purpose, the tool will end up regurgitating meaningless data.

TL;DR — When setting up measures, don’t keep the tool at the center. Keep the purpose at the center. The rest should follow.