Data is being used to showcase that value has been generated. In order to do this, the most beautiful reports have to be eked out. Now if you are a follower of Avinash Kaushik and don’t like data pukes, then you would be aghast at some of the reports that agencies in India tend to dish out.

I was, and 13 Llama Interactive was born out of that need to do better at both data driven marketing and reporting with transparency.

The road to hell is paved with good intentions

If you’ve been providing paid marketing services to clients for any extended period of time, you know that every person you work with has a different level of online marketing knowledge. Some people might be experienced account managers, others might know basics, while others still might not know the industry at all.

Apparently “agency reporting” is a thing. This is where every week or every month, the agency that is handling the brand account (or the performance account if you may) sends across reams of PDFs (or excel sheets) that’s meant to prove that whatever hair brained plan that they had cooked up the last period has worked.

The most common method to justify existence is to keep throwing boatloads of data reports from all tools and then talk about worthless metrics. Each of these tools mentioned in the article that I have shared helps agencies do this at scale, effortlessly.

Is too much data a bad thing?

It can be. If all that data is leading to Analysis Paralysis … or if it leads to falling in love with data analysis itself and forgetting real business outcomes (the reason why you got money for funding the collection of all that data).

If no one is using this mountain of data for solving problems, then it’s better that the data not be collected at all.

Yes, you are letting go of possibilities, but so be it. The damage to the business by wasting resources on gathering more liabilities instead of assets is much worse.

That’s what creates a paradox. Should we or shouldn’t we collect data?

Here’s a great video from Superweek that makes the case pretty well.

Any analysis team would work day and night to justify the reason for their being. There are enough articles being shared on the internet on arriving at a Return on Investment for Analytics (RoIA). However, the main service that any of these teams did was to crunch business data into A-has. This hasn’t changed over the years, and a lot of analysts derive job satisfaction through this very hunt for the A-ha! from their audiences.

The switch to being a core business

Data and business analysis was until now a support function, which needed business data in order to thrive and be effective. Aside from very few models (those that sold business critical data such as ratings, organizational data, etc), the data was never used as the primary product.

There was always a pre-activity and an analysis activity for that data to be useful. However, over the years I am seeing that has changed. Data is now being presented and sold as the main product.

Data as the product

Those of you who know Bloomberg, Hoovers, S&P or CRISIL, would know that data as a product business model works. Now that you know the pattern, let’s take a look at how this business model works.

Data collection as a ancillary service

There is one function of the business which works with the entire industry it is catering to, to collect data. This more often than not is made available as a freemium or free service.

Some examples of this would be – Alexa Certified metrics, Google Analytics, Walnut app, Swaggerhub, etc.

You get the general idea here. If a good product or service is offering you a free plan, more often than not the data you are entering on that platform would be mused for multiple usecases. Not just for your primary use case.

Data aggregation and visualization

This is akin to the marketing function, and most probably gets a lot of early adopters talking good things about the product.

E.g a blogger singing paeans about Google Analytics, an industry benchmark visualization being shared, data report about a competitor, etc.

This way, the inherent value in the data is presented.

Data access and pricing plans

This is how the business is monetizing the data. By selling access to it. Often on a pay per use basis, or a per data point basis. Note, there might be multiple reports given to the user, however the user has to do the analysis on their own.

E.g SEMRush, SimilarWeb, Alexa, etc.

Wait, these are all old products

Yes. They have been around for quite some time. However, I am seeing that other industry are also copying this model. I recently spoke to someone in the pharma industry who was selling aggregated prescription data to pharma companies.

The credit industry has already been doing this for so many years. TransUnion is a perfect example. In India, most working professionals are familiary with their CIBIL scores. What few people realize that CIBIL is a TransUnion company. Similarily, CRIF score (which is an alternative bureau) belongs to Experian.

What gets my goat in this scenario, is that the firm which is collecting data is based out of another country! This firm now claims to own and know the data of citizens belonging to another country.
Shut up and take my data

Let’s go back 300 years or so. The British killed the Indian textile industry by mutilating the weavers who used to make cloth. Then they bought the cotton and other crops at throwaway prices, that cotton is similar to the data that is being collected. The industry grade cotton which was then imported back in India is similar to the data aggregation and reports that are being sold.

The only difference is that 300 years back, we were scared of the East India Company. This time around, we are welcoming the data traders with open arms. Should we not be a bit more aware of who and how our data is being used?

One of the things that going digital does to any brand, is that it suddenly gives access to a lot of data. Data, that opens up a world of possibilities.

Possibilities which had not earlier been anticipated or even thought of. Somehow, it propels teams to start thinking in terms of achieving certain data metrics … and that seems to justify the sheer obsession with data.

However, in data lies a certain trap. Let me walk you through how a typical marketing team approaches data.

Measure & Monitor

At the start, the team starts collecting data and reporting this on a daily basis. The fact that data is being collected and monitored allows for these teams to make pretty graphs and bar charts which get discussed in weekly or monthly meetings.

Don’t get me wrong, I am all for #measurement. It’s just that what do you wish to measure is much more important than the fact that you are collecting data. I have already written about this in the past, having defined a simple Success-Failure framework for measurements.

However, when I see the work being done by most teams in India, it drives me up the wall. The sheer volume of data, and sometimes the lack of understanding the context can confuse the data analyst. What happens next is just Analysis Paralysis.

Analysis Paralysis

This is a state of over analysing data to such an extent that no action is taken and its being discussed to no end. The data ends up getting regurgitated from excel sheets to powerpoint to emails, but no real action is taken.

It’s not that everyone keeps an eye on the more important metrics. If you are looking at a list of smart and helpful series of insights, then do go through this list of analytics insights published on the SEMRush Blog. Keep these aside for a minute, and try and see how tracking each of them would really impact your business.

Most teams, don’t necessarily do that, and that’s what bugs me. Here are some of the metrics that really get my goat.

Bounce Rate

Yes. It’s something that you would look at and obsess over. Wouldn’t you? Think again. It’s a subjective metric. What would you say to a high bounce rate for a landing page that’s giving you a high conversion rate?

The metric if considered purely on a standalone basis tends to bias the analyst, and that’s why its something you need to avoid.

Traffic

This is my most hated metric. What is the point in running after loads of traffic or buying traffic that has zero business outcomes? However a lot of teams are made to run after traffic, and then instead of focusing on getting the right customers, teams start focusing on getting as many footfalls as possible.

Impressions

Yes, your brand got the most number of impressions and that’s a high number of eyeballs. However, if you are getting only one person to act out of every 100, then don’t you think there is a problem?

Brand building is always a good idea, but does brand building translate into driving higher number of impressions? The mental model associated with this approach is scary – because then as marketers and businessmen, we start focusing on running after the wrong metric.

Imagine showing a wrong message to a vast audience. Scary right?

Clicks

This is a metric for those of you who are are running paid promotions on digital. Since a lot of the work that is done on paid promotions is customer acquisition, there is an unhealthy focus on looking at clicks.

Clicks are good, but when it comes to paid promotions, who knows perhaps the person clicking is being incentivized to click your banners and has zero interest to engage with your business.

Social Likes

This again is a personal favourite. For a lot of content oriented brands, the number of social likes is somehow extremely paramount.

If we step back and examine why people likes things on social platforms, then we will see that most of the times it is to express an opinion about something (yes, we are opinionated, and we love it!). Some times it is to open a dialogue and have a conversation about a topic.

Yes, having more likes typically does translate into a greater reach and engagement. However, this number is also a very subjective metric. Perhaps the link being liked is so bad that it’s good (think Gunda, or the Friday-Friday song). Would you as the content creator be happy or sad that people are (dis)liking your content?

The next time you sit down to define which metrics to track, definitely think about how the metric is going to help your business. If you can generate a straight line visibility between that metric and revenues for instance, then that should be something you need to track.

I am in the middle of reading Shashi Tharoor’s An Era of Darkness: The British Empire in India. If you have been living under a rock like I was, then you may not have heard about his Oxford debate where he smashed his contemporaries on why Britain should do reparations to India.

At this time, I chanced on the movie Gold in Amazon Prime. What perfect timing! A movie about India’s first Olympic gold medal – as a free country. The movie stars Akshay Kumar as a sports manager of the British India National Hockey team, and their ability to keep winning the Olympic gold for British India. History buffs and hockey buffs (preferably both) would be quick to point out that during that time the team was led by the Wizard of Hockey, Dhyan Chand.

For the sake of preserving identities of the negative roles, the names have been changed, and Dhyan Chand is portrayed by Kunal Kapoor as the legendary captain Pritam. If you do not know who is Dhyan Chand, please stop reading and head on to the wiki link. India was well known in the history of hockey largely due to this chap. We owned the international circuit from 1928 (pre-independence) up till as late as 1980. Pretty much the time cricket took over as the national craze and the national sport lost its crowds. Ironically, in 2014 when Dhyan Chand’s name was being considered for Bharat Ratna (the highest civilian award in India), it was never nominated and the award winner was none other than apna Sachin!

But I digress, this is about the movie and not a diatribe about hockey losing out to cricket!

The movie is about getting India’s first Olympic gold, and how the main character in the story (a Bengali team manager played by Akshay Kumar) helps the team get its gold. This under the backdrop of the partition and post-independence struggles that the new country faces make for a riveting story.

Bollywood has oft taken an anti-Pakistan stance in the past, and it’s very easy to take this stance. However, you should see how this movie has spun the entire India-Pakistan tale. It’s heart-rending and one might wonder … a magnificent what-if … our national leaders back then were brave and foolhardy to take such a decision then. What stops from doing something equally foolish now?

History tells us the outcome of this story … India dominated the hockey scene for a long time. However, the story also talks about the role of administration in ensuring that the sport has enough backing. In the chaos of IPL and slogans like fan banna padega … I ask you this … what about our national sport? I wish this movie had done much better on the box office, it deserves to be seen, not only for the acting – but also for the narrative.

This blog is a modest small-tier blog. It does not get too much traffic (much to my chagrin) and therefore expecting the blog to monetize is too much. However, I have steadily written my thoughts and opinions on this … for the past 7-8 years now.

Looking at such a long time range allows me to study how blogging and blog monhersetization has changed over the years. Especially now with mobile form factors being the main devices that users tend to consume content with.

What mobiles really mean for publishers?

It means that the website design and user experience needs to be re-thought for the mobile. It also means that most traffic channels (Search, Social) for bloggers are now suddenly very sensitive about how users consume their content on their platforms.

It’s a race to retain the user on their platform. That’s the only way the platform can retain control over the publishers. Let me explain this a bit.

People do not come to my site to read about analytics or technology. They go to Google. Or they see this in their Facebook feed. All this on the mobile device, being on the move. Now, I’d like to embrace this and sing hallelujah for the technology gods, however, anyone with a 3G connection in India would know that 3G in India is the same as 2G (or worse) in any developed country. Data is scarce and consuming data on mobile devices is a pain. Despite of 4G and the Jio revolution.

AMP and Facebook Articles

In comes this feature. Where now the publisher had to just create content, now for users on mobile devices across different platforms, the publisher had to now create content in various formats.

I have already written about this at length, and am not at all impressed with how publishers are being arm twisted in following the platform rules. Having said that, I did embrace AMP and have implemented AMP on my blog (since it’s relatively easy to do so).

Drop in traffic

Since then, I have observed a steady drop in traffic. The AMP traffic (and I have AMP analytics implemented) does not register. The numbers do not match or tie-up.

This, I have pretty much noticed across all publisher blogs who have embraced AMP. Funnily enough, I would not have come to this realization until and unless I had embraced another AMP component … AMP Ads!

AMP Ads

Google AdSense have very recently rolled out Auto Ads for AMP. This is something that I wanted to try, and I did. The number of impressions that I received whooshed up to twice the number on the desktop! The negligible earnings that I had from AdSense has turned into a minor trickle and that’s largely due to AMP based ads.

The traffic that the AdSense report indicates is much more than what Analytics shows up. Now I know at some point I have said that do not measure the same metric with two tools and worry about the difference. However, when I see such a huge difference, it only means one thing … my Analytics code may not be firing on my AMP pages … even after doing exactly what the AMP analytiics specs were. If a trained programmer cannot do this on his blog, how many content creators can do this effectively?

There lies the seed of doubt, gently working its way and making me re-think this entire AMP implementation. I will leave this article here, in doubt and am starting a thread on this to watch how this evolves over a period of time.