[Illustration by Stocksnap under Creative Commons]
In the previous article, I had shared how Little Data opened up a new path for us. It was based on the idea that incremental, data-driven insights, which do not require sophisticated data handling capabilities, can lead to fairly significant transformations.
In this article, I would like to continue that argument. My key contention here is that Little Data can help achieve any kind of major business outcome you might set out to achieve.
In our case, we have derived a range of benefits. Some have been transformative (how we see our customers); some have led to surprising gains. We have been able to come up with new revenue ideas and also transpose insights from one part of the business to another.
All this happened because we became data-genic.
A question for those who are running a digital business: Are your operations optimized more for weekend traffic than week days?
Online audiences tend to spike over weekends. Not only are the numbers higher, but they spend more time online as well.
And yet, if most users are coming on our sites on weekends, it begs the question why our operations are built any other way. I know we haven’t optimized for weekend operations as much as we should.
Customer-centricity, or the lack of it, is evident through the little things that we do or don’t do. Data is invaluable there—it shows us up.
At CarToq, our digital content product for car buyers and owners, we learnt how our resource allocation was not really based on what users wanted.
In the auto industry, there exists an age-old belief that test drives of cars are the most valuable piece of content to produce for car buyers. Reputations of auto journalists get built or marred by who gets to test-drive a car first.
Car companies tend to use this mindset to their advantage. They have made test drives a sought-after privilege. Drives are organized in exotic locations over two-three days; there’s lavish 5-star hospitality and the articles, videos and photo features get written.
While car companies get a lot of publicity from these articles, do the content sites gain as much?
We thought we did. Our test-drive content did get us a large number of users, but there was a problem.
With all that effort (from our senior content team) to produce this content, our traffic never grew beyond a point. On average, we did about 300,000 monthly visits, with occasional spikes taking us to 500,000 visits.
The data was even more damning on other counts. We were not increasing repeat users to our site. If test drives were indeed the most valuable piece of content users craved, they should be coming back for more of it regularly. They didn’t.
Then we started A/B testing with some other content types (photo features, single-parameter car comparisons). And we found that Facebook audiences were telling us something very different. On average, we got 3x more users from car comparisons alone, and photo features got us even more users.
Our users didn’t value content related to test drives anywhere as much as we thought they would. That was probably one of our earliest realizations about how far removed we were from our customer’s preferences.
Since then, we have increasingly experimented with new content formats, testing continuously against user responses. Today, on average, we get an organic reach of 300,000 people on CarToq’s Facebook page, and we are leaders in user engagement through content among auto sites.
Data set us on the right path.
In another instance, it set us off in a new business direction altogether.
Surprise: New revenue stream
Every now and then, we do content analytics across our projects. The goal is simple: track online content for insights that our customers might find useful. Often, we don’t even know what we are looking for.
In a project for a large IT company, for whom we do various content marketing tasks, we wanted to identify some new content trends for fresh ideas in thought leadership marketing.
Our research team studied over 650 content items from the top IT firms globally. We mapped this content to a framework we have developed to analyze content for B2B (business-to-business) marketing.
The analysis threw up a bunch of new content ideas for our client. But we also discovered something far more valuable for ourselves.
We discovered a new business opportunity.
We found a significant gap in thought leadership content from almost all IT majors. Everyone was doing enough content to build awareness and sell their solutions. But they were missing a crucial bit in the middle.
Customers also need to get educated about how to scope their solution requirements before they can move to solution assessment. Nobody was doing enough content here.
We shared these findings with companies and pitched the idea that we could help plug this gap. They were interested. We quickly set up a dedicated team to offer scalable thought leadership content solutions to IT and technology companies.
We have made decent headway. Three Fortune 500 companies have signed up as our clients so far.
Discovering revenue opportunities in this manner is perhaps the biggest validation for the data-driven approach. However, I must confess that the maximum satisfaction has come from another kind of opportunity elsewhere.
Smart: Transferring insights
It’s often easy to apply learning from one part of the business to another. But when it comes to data-led insights, the transposition is even more seamless and effortless.
It must be something about the nature of data and technology that makes it fungible and scalable—I am not sure what makes it possible. But I am convinced that this aspect of data-driven management can really be a source of endless benefits.
In early 2015, we had developed a tool that tracked content trends across auto websites globally. We were hunting for clues on how to make content a hit on social media. The tool would automatically collect content from across the globe, and arrange it by decreasing order of popularity in social media (likes, shares, tweets, etc).
It took us a while to fix the code that would collect the content feeds cleanly, but once we got there, the editors found it very useful to learn from the best social media content.
Then, in our content marketing business for IT and technology companies, we started seeing a recurring problem. Our client teams were often running out of ideas for their thought leadership marketing. Could we help them come up with new ideas? If yes, then how?
Someone in the team came up with the idea of having a similar tool. Collect content feeds from IT sites globally, and that might throw up some ideas, we thought. We took our CarToq content tool, tweaked its architecture to allow for content tagging by our domain experts, and made some changes to the user dashboard.
It worked. Beautifully.
We are now able to come up with topics for our client teams in very specialized niches such as medicine personalization and P2P (peer-to-peer) payments in retail banking. I am sure, at some stage, we will take back some of the learning from here to the original CarToq tool. And so on.
We have only just started out with our data focus about a year ago—and I am surprised at the variety of gains made, from sales to operations. With more time and commitment, use cases should increase rapidly.
In my next piece, let’s look at some easy ways to get started on the data-genic journey.