Kumar's Blog

Today, I introduce you to a wonderful service - IFTTT (If this then that). Some of you may know about it and some of you may be using it as well, but if you're not, you should definitely give this a try.

The name says it all. Bringing together 77 channels like Facebok, Twitter, Linkedin, Blogger, Instagram, Reddit, Tumblr, Youtube, it allows users to create recipes for their digital activities. A recipe is nothing but an 'if this then that' statement defining what action (that) needs to be done on what trigger (if this).

In the age where every person is active on scores of digital services (I myself can be reached in eleven different ways for an immediate response on my phone alone) performing hundreds of digital transactions (liking a photo, tweeting a link, writing a blogpost) every day, a little automation will go a long way in making the whole ordeal easier.

You can create some interesting recipes like 'if I like a photo on Instagram, then download it', 'if there is a new job suggestion in LinkedIn, add a new row with details in a Google Drive spreadsheet'. You can even turn your recipes on and off at will. In fact, you can even write a recipe to automatically turn other recipes on or off.

Like most awesome services, this has its privacy concerns. Through your recipes, you are basically telling your thought process for many types of transactions.

While Uncle Sam might not give a rat's a** about your thought process (in most cases at least), marketers do. They practically drool on information that can be as rich and accurate as your IFTTT usage provides.

Then again, no awesome product is free.

I'm quick to admit that I have an algorithmic lifestyle. A lot of things I do follow a certain routine. This makes me quite an easy target to marketers because if they can't tell as to what I'm likely to be doing and where I'm likely to be at any given time, they are highly likely to lose their jobs.

Most advertising decisions and product decisions today are based on the understanding of customer behaviour patterns and routines. But how effective is this really?

I have come to realise that if I'm settled into a routine, it is for a reason. The reason is that I'm comfortable and happy with that routine. If I go to Costa Coffee every Sunday to read a book, showing me an ad or sending me an offer about Cafe Coffee Day won't make me go there. The time to show me an ad or send me an offer would be on a Sunday when I either don't go to Costa Coffee or leave earlier than usual (unusual behaviour). Because it is likely that there was a break in my routine because I had a bad experience there (either it was crowded, or the coffee was not good).

Understanding customer behaviour patterns is really helpful if the gathered data is made use of the right way. If the customer is following a certain routine, she is happy with it and unlikely to break it after viewing an ad for a competing product. She is far more likely to be persuaded by an ad when she breaks her routine. So identify breaks in routine rather than trying to induce breaks in routine. It is likely to fetch better returns.

And if your product is already part of customer routine, ensure you please the customer in every way possible, continue to exceed expectations. Do not give her a reason to break the routine.

Because most purchase decisions made by people are irrational.

Most organizations crave for diversity in their employee profiles because people with different backgrounds bring in different perspectives. When a team with a diverse set of people are presented with an open-ended problem (nearly all vital problems that an organization has to address to stay afloat and trudge forward are open-ended), it is highly likely that each one will bring her own perspective in addressing the problem.

Yet, while deciding on how to present advertisements, how to design product features, we still try to think in a rational way by understanding what need the product is solving or the advertisement is claiming that the product will solve and use that understanding to design the features that define the product or the advertisement.

Over the last one month, I have been involved in designing the User Experience (UX) for our product and that has been a very revealing experience. The traditional way to go about it is to put ourselves in the skin of the customer and decipher what she would like to see in the product. The actual design will reflect that understanding. But when putting ourselves in the customer's skin, the time has come to ask 'which' customer's skin?

While organizations understand and appreciate diversity in their own employees, they actively disregard diversity in the customer base for their products. Until recently, this was acceptable because it was not practical to understand the background and the expectations of the customer base. It was good enough to think rationally by entering an 'average' customer's skin and deciding product features. But no longer.

It is now possible to understand all the quirks and the seemingly irrational behaviour of our customer base. It is only rational that we go ahead and obtain this knowledge. And then make use of it to customize our offerings to exceed the expectations of every customer. Not just the average customer. 

Earlier this week, Facebook put an end to its EdgeRank algorithm that was used to determine what posts users would see on their newsfeeds. The posts that used to be shown were selected based on affinity, currency and engagement. This was using Big Data in the most primitive way. Identifying past behaviour and trends to determine future behaviour. Even the primitive use was pretty good is testimony to the potential of Big Data.

Now, Facebook has taken a step further in how it uses Big Data. The new algorithm has one simple addition to the way it worked previously. If Facebook knows that you haven't seen a post that you are statistically inclined to interact with, that post will be shown in your newsfeed even though it is not necessarily a 'current' update.

This is a very good feature that benefits not just users, but brands that advertise on Facebook as well. Facebook's mobile revenues have seen a big boost due to native advertising (advertisements showing up as one of the news items in the newsfeed) this year. With Facebook understanding the user's behaviour in different contexts, and then using it to determine what goes into the newsfeed, brands have an easier job of targeting their audience. They no longer have to post the same thing multiple times, once every few hours to reach more people. They just have to generate content that users are likely to engage with.

But there is one aspect of user experience that will be affected. I'm used to viewing newsfeed items in chronological order. If this algorithm alters that too much, it might take me some time to get adjusted to the new view. And whenever there is user adaptation needed, there is always the risk of making the user unhappy. But in order to innovate, you have to take these risks in your stride and that is exactly what Facebook is doing.

Advertising has always been about creativity. Advertising agencies have been flourishing because creativity is not in abundance. Nearly all brands end up going to an advertising agency to make their advertisements. Before an advertisement is made though, a key action lies in identifying who the target audience is, what their behaviour is, and where they are most likely to view an advertisement and act on it.

In the last few years, advertising agencies are growing increasingly dependent on the likes of Google and Facebook for answering those questions about the target audience. This growing dependency seems to have scared the likes of Omicon and Publicis.

What is their answer to it? Merge into one entity and combine their data expertise to take on the likes of Google and Facebook. At first look, this looks incredibly stupid. After a little reflection and thought, it still seems quite stupid. What does this advertising giant hope to achieve? Can it know the Facebook users better than Facebook does? Can it know the online behaviour of people better than the makers of the home page of hundreds of millions of people?

Their fear is understandable. Their evaluation of the role digital and Big Data will play in advertising is understandable. But their solution is not something I understand.

This is a situation that will leave anyone in a dilemma. Whether to compete with the ones having rising influence on the industry? Or to embrace the emerging powers and focus on improving the value we offer?
As often is the case, there isn't a right answer. We will just have to see how Publicis Omnicon will fare in the coming years.

I make the case for Big Data and the opportunities it offers quite often on this blog. It will make it possible for you to identify and map the usage and behaviour patterns of a lot of people with respect to the products, software services and several other things that they use. Many marketers and business developers have their own plans for using Big Data.

Marketing strategies are being formulated, SEO optimization techniques are being planned, new product ideas are being thought of, advertisements are being scripted, movies are being made, even as I write this. All looking to capitalize on the learnings from Big Data.

The opportunities on offer can be capitalized on only when there is an understanding of what all the data means. It is not at all enough to just know historic patterns and extrapolate them to predict future behaviour. It is unfortunate that many marketers tend to forget the first lesson in Statistics in the excitement of all the opportunities. They tend to forget that correlation doesn't necessarily mean causation.

Technologies are being disrupted in ever quicker cycles. If Apple had mined Big Data about phone usage patterns, they would never have disrupted and made the iPhone.

Big Data is not a replacement for disruptive innovation. You just have to make use of it to aid innovation. Not incremental innovation like adding a small extra feature. That is no good in the long term. But disruptive innovation. You need to understand usage and behaviour patterns not to make more products that will allow the users to continue using these products and services in the same way. All small companies that have become big, overshadowing the existing giants, have done it by disrupting user behaviour and hooking them on to a newer and better way of doing things.

How will you use Big Data?

"We see people and things not as they are, but as we are."
                                                                                         - Anthony De Mello

Every Marketing textbook, and every business book, must have a few pages dedicated to laying emphasis on this statement. Understanding this is a must to making a successful mass product. You can make successful products without understanding this. But that will only cater to an audience who are fairly similar to you, the creator. If you want a wider audience to accept and remark about your product, you have to understand that they see your product as they are, and not as you intend it to be.

I wrote a post a couple of months ago about the importance of choosing the right context to communicate with your audience. While the context is an important aspect to consider, the frame of mind, the behavioural traits and the personality of your target audience matters a lot as well. Understanding this is extremely hard. That is what makes Marketing hard. And that is what makes building successful global products hard.

Geographic traits, local cultural traits, demographic traits all aid in the process of understanding behavioural traits of your target audience. But this is only helpful as long as you cast a wide net (target thousands of people with the same advertisement). This will give you a reasonable success rate as a good number of the target audience will receive your communication the way you want them to.

But as precision targeting of advertisements increase (especially online), this strategy is no longer good enough. You need to understand your target audience a lot better than you do right now. And this is the challenge for digital marketing at the moment. Big Data is showing some promise in meeting this challenge, but there are still a lot of hurdles to cross.

It is true that digital marketing is not showing success rates as promised. It is true that very few brands have been built through digital marketing efforts alone while thousands have been built through traditional marketing efforts alone. But that is no reason to give up on the hope of realizing the promise. We just have to find ways to make it work. The first step is to gain credibility when making claims about overcoming privacy concerns of people.

This is the approach many marketers are taking with the advent of Big Data. With so much data available, the emphasis in marketing activities is shifting to number crunching. The brilliant new marketer who can transform the image of a product is now the one who can make sense of the data available to her about customer behaviour.

While mining of Big Data can provide wonderful insights, they provide just that, insights. The mined data will only enhance available information. The hard work of incorporating this information into product feature decisions, pricing decisions, distribution channel decisions, etc still remains to be done. No amount of number crunching will throw up these answers. If you make the mistake of thinking they will, you're ruling out the possibility of any innovation.

With numbers come metrics. With metrics come hard targets (hard targets are different from hard-to-achieve targets). And when the focus is on meeting these hard targets (like gather 2000 new customers from Mumbai area who have previously disliked a competitor's service in a month), there is little room for innovation.

Marketing efforts are not just responsible for boosting sales and brand image, they are equally responsible for boosting innovation. It is easy to be engulfed by the promise Big Data beholds. But it is essential to not get sucked into a world of metrics and hard targets. Innovation is paramount.