Triangle marketing

This blog post is based more on how I have bought rather than how I have sold. The basic concept is that when you hear about a product or service from two or more independent sources, you are more likely to buy it.

The threshold varies by the kind of product you are looking at. When it is a low touch item like a book, two independent recommendations are enough. When it involves higher cost and has higher impact, like a phone, it might be five recommendations. For something life changing like a keto diet, it might be ten (I must mention I tried keto for half a day and gave up, not least because I figured I don’t really need it – I’m barely 3-4 kg overweight).

The important point to note is that the recommendations need to come from independent sources – if two people who you didn’t expect to have a similar taste in books were to recommend the same book, the second of these recommendations is likely to create an “aha moment” (ok I’m getting into consultant-speak now), and that is likely to drive a purchase (or at least trying a Kindle sample).

In some ways, exposure to the same product through independent sources is likely to create a feeling of a self-fulfilling prophecy. “Alice is also using this. Bob is also using this” will soon go into “everybody seems to be using it. I should also use it”.

So what does this mean to you if you are a seller? Basically you need to hit your target audience through various channels. I had mentioned in my post earlier this week about how branding creates a “position of strength“, and how direct sales is normally hard because it is done through a position of weakness.

The idea is that before you hit your audience with a direct sale, you need to “warm them up” with your brand, and you need to do this through various channels. Your brand needs to impact on your audience through multiple independent channels, so that it has become a self-fulfilling prophecy before you approach to make the sale.

What these precise channels are depends on your business and the product that you’re trying to sell, but the important thing is that they are independent. So for example, putting advertisements in various places won’t help since the target will treat all of them as coming from the same source.

Finally, where is the “triangle” in this marketing? It is in the idea that you complete the branding and sales by means of “triangulation”. You send out vectors in seemingly random directions trying to build your brand, and they will get reflected till a time when they intersect, or “triangulate”. Ok I know my maths here is messy ant not up to my usual standard, but I guess you know what I’m getting at!

 

The advantage of recurring payments

One of the best things about payments in the UK is the ubiquity of the direct debit system. From gym memberships to contact lenses to television licenses, all sorts of subscriptions are sold on a direct debit based model.

The mechanism is simple – the merchant, with the consent of the customer, sets up a direct debit system with the customer’s account such that a specified amount is debited periodically. This direct debit system can be cancelled at the customer’s discretion, resulting in automatic annulment of the subscription.

This is a great business model because it allows businesses to acquire customers for a repeated transaction, without the latter having to commit for too long a period.

The key feature of the direct debit system is the customer opt out. That the account will be continued by default means that it takes explicit action by the user to terminate the subscription, which helps the business acquire customers with the cost amortised over several time periods. The any time opt-out feature (which the user can do at her bank’s website or app, without consent of the merchant) means that the commitment at any time for the customer is for one period only, making the product an easier sell.

In the absence of the recurring payment based model, the business will either have to offer short term “subscriptions”, which implies a customer acquisition cost at each period, or long term contracts, which takes a higher upfront commitment from the customer making it a much harder sell.

In that sense, a recurring payment model offers a nice middle ground, resulting in value being unlocked for both the business and the customer, resulting in enhanced welfare all around.

In that sense, the lack of a recurring payments system is a key shortcoming of the payments scene in India. While it was possible to do this earlier, current rules by the Reserve Bank of India require authorisation by the customer (in the form of two factor authentication) for every transaction, making them opt-in rather than opt-out (the opt-out feature is key to amortise customer acquisition cost).

The updated version of the unified payments interface (UPI 2.0) was supposed to offer this recurring feature, but media reports say that the update is being rolled out without this feature. That is surely an opportunity missed for India’s businesses to grow.

Branding and positions of strength

I had an invitation to attend a data science networking event today. I had accepted the free pass for option value, but decided today to not exercise the option. Given I was not going to speak at the event, I realised that the value of the conversations at the event for me would be limited.

One of the internet gurus (it might be Naval Ravikant, but I’m unable to locate the source) has this principle that you shouldn’t go to networking events unless you’re speaking. Now, if everyone applied this principle events would look very different, with speakers speaking to one another (like in NED Talks!).

Thinking about it, though, I see clear value in this maxim. Basically when you go to a networking event and speak, you can network from a position of strength, especially after you’ve spoken. This is assuming you’ve done a good job of your speech, of course, but apart from elevating your status as a “speaker”, speaking at the event allows potential counterparties in conversations to have prior information about you before they talk to you.

So there is context in the conversation, and since you know they know something about you, you can speak from a position of strength, and hopefully make a greater impact.

It is not just about speaking and events. For a long time, a lot of my consulting business came from readers of this blog (yes, really!). This was because these people had been reading me, and knew me, and so when I spoke to them, there was already a “prior” on which I could base my sale. Of late, I’ve been putting out a lot of work-related content here and on LinkedIn, and that has sparked several conversations, which I have been able to navigate from a position of strength.

A possibly simpler word to describe this is “branding”. By speaking at an event or putting out content or indulging in other activities that let people know about you and what you do, you are building a brand. And then when the conversation happens, the brand you have thus built puts you in a position of strength which makes the sale far easier than if you didn’t have the brand.

You need to remember that position of strength as I’ve described here is not relative. It is not always necessary for the brand to elevate you to a level higher than the counterparty. All that is necessary is for it to put you at a high enough level that you don’t need to talk from a position of weakness. And if you think about it, cold calling and door to door sales is basically selling from a position of weakness – while it might have worked occasionally (which makes for fantastic stories), it is on the most part not successful.

And in some way, this concept of branding and positions of strength is well correlated to what I recently described as “the secret of my happiness“. By being really good at what you are good at, you are essentially putting yourself in a position of strength, so that people have no choice but to tolerate your inadequacies in other areas. Putting it another way, being really good at what you are good at is another exercise in brand building!

Brand building efforts can sometimes fail. There are times when I have given talks and got few questions – clearly indicating it was a wasted talk (either I didn’t talk well, or the audience didn’t get it). I have put out content that has just sank without a trace or any feedback. The important thing to know is that somewhere it all adds up – that these small efforts in branding can come together at some point in time, and make it work for you.

 

Analytics for general managers

While good managers have always been required to be analytical, the level of analytical ability being asked of managers has been going up over the years, with the increase in availability of data.

Now, this post is once again based on that one single and familiar data point – my wife. In fact, if you want me to include more data in my posts, you should talk to me more.

Leaving that aside, my wife works as a mid-level manager for an extremely large global firm. She was recruited straight out of business school for a “MBA track” program. And from our discussions about her work in the first few months, one thing she did lots of was writing SQL queries. And she still spends a lot of her time writing queries and building Excel models.

This isn’t something she was trained for, or was tested on while being recruited. She did her MBA in a famously diverse global business school, the diversity of its student bodies implying the level of maths and quantitative methods being kept rather low. She was recruited as a “general manager”. Yet, in a famously data-driven company, she spends a considerable amount of time on quantitative stuff.

It wasn’t always like this. While analytical ability has what (in my opinion) set apart graduates of elite MBA programs from those of middling MBA programs, the level of quantitative ability expected out of MBAs (apart from maybe those in finance) wasn’t too high. You were expected to know to use spreadsheets. You were expected to know some rudimentary statistics- means and standard deviations and some basic hypothesis testing, maybe. And you were expected to be able to make managerial decisions based on numbers. That’s about it.

Over the years, though, as the corpus of data within (and outside) organisations has grown, and making decisions based on data has become fashionable (a brilliant thing as far as I’m concerned), the requirement from managers has grown as well. Now they are expected to do more with data, and aren’t always trained for that.

Some organisations have responded to this problem by supplying “data analysts” who are attached to mid level managers, so that the latter can outsource the analytical work to the former and spend most of their time on “managerial” stuff. The problem with this is twofold – it is hard to guarantee a good career path to this data analyst (which makes recruitment hard), and this introduces “friction” – the manager needs to tell the analyst what precise data and analysis she needs, and iterating on this can lead to a lot of time lost.

Moreover, as the size of the data has grown, the complexity of the analysis that can be done and the insights that can be produced has become greater as well. And in that sense, managers who have been able to adapt to the volume and complexity of data have a significant competitive advantage over their peers who are less comfortable with data.

So what does all this mean for general managers and their education? First, I would expect the smarter managers to know that data analysis ability is a competitive advantage, and so invest time in building that skill. Second, I know of some business schools that are making their MBA programs less quantitative, as their student body becomes more diverse and the recruitment body becomes less diverse (banks are recruiting far less nowadays). This is a bad move. In fact, business schools need to realise that a quantitative MBA program is more of a competitive advantage nowadays, and tune their programs accordingly, while not compromising on the diversity of the student intake.

Then, there is a generation of managers that got along quite well without getting its hands dirty with data. These managers will now get challenged by younger managers who are more conversant with data. It will be interesting to see how organisations deal with this dynamic.

Finally, organisations need to invest in training programs, to make sure that their general managers are comfortable with data, and analysis, and making use of internal and external data science resources. Interestingly enough (I promise I hadn’t thought of this when I started writing this post), my company offers precisely one such workshop. Get in touch if you’re interested!

The missing middle in data science

Over a year back, when I had just moved to London and was job-hunting, I was getting frustrated by the fact that potential employers didn’t recognise my combination of skills of wrangling data and analysing businesses. A few saw me purely as a business guy, and most saw me purely as a data guy, trying to slot me into machine learning roles I was thoroughly unsuited for.

Around this time, I happened to mention to my wife about this lack of fit, and she had then remarked that the reason companies either want pure business people or pure data people is that you can’t scale a business with people with a unique combination of skills. “There are possibly very few people with your combination of skills”, she had said, and hence companies had gotten around the problem by getting some very good business people and some very good data people, and hope that they can add value together.

More recently, I was talking to her about some of the problems that she was dealing with at work, and recognised one of them as being similar to what I had solved for a client a few years ago. I quickly took her through the fundamentals of K-means clustering, and showed her how to implement it in R (and in the process, taught her the basics of R). As it had with my client many years ago, clustering did its magic, and the results were literally there to see, the business problem solved. My wife, however, was unimpressed. “This requires too much analytical work on my part”, she said, adding that “If I have to do with this level of analytical work, I won’t have enough time to execute my managerial duties”.

This made me think about the (yet unanswered) question of who should be solving this kind of a problem – to take a business problem, recognise it can be solved using data, figuring out the right technique to apply to it, and then communicating the results in a way that the business can easily understand. And this was a one-time problem, not something you would need to solve repeatedly, and so without the requirement to set up a pipeline and data engineering and IT infrastructure around it.

I admit this is just one data point (my wife), but based on observations from elsewhere, managers are usually loathe to get their hands dirty with data, beyond perhaps doing some basic MS Excel work. Data science specialists, on the other hand, will find it hard to quickly get intuition for a one-time problem, get data in a “dirty” manner, and then apply the right technique to solving it, and communicate the results in a business-friendly manner. Moreover, data scientists are highly likely to be involved in regular repeatable activities, making it an organisational nightmare to “lease” them for such one-time efforts.

This is what I call as the “missing middle problem” in data science. Problems whose solutions will without doubt add value to the business, but which most businesses are unable to address because of a lack of adequate skillset in solving the issue; and whose one-time nature makes it difficult for businesses to dedicate permanent resources to solve.

I guess so far this post has all the makings of a sales pitch, so let me turn it into one – this is precisely the kind of problem that my company Bespoke Data Insights is geared to solving. We specialise in solving problems that lie at the cusp of business and data. We provide end-to-end quantitative solutions for typically one-time business problems.

We come in, understand your business needs, and use a hypothesis-driven approach to model the problem in data terms. We select methods that in our opinion are best suited for the precise problem, not hesitating to build our own models if necessary (hence the Bespoke in the name). And finally, we synthesise the analysis in the form of recommendations that any business person can easily digest and action on.

So – if you’re facing a business problem where you think data might help, but don’t know how to proceed; or if you are curious about all this talk about AI and ML and data science and all that, and want to include it in your business; or you want your business managers to figure out how to use the data ┬áteams better, hire us.

Vacation Shopping

This is yet another of those questions whose answer seems rather obvious to everyone, and to me in full hindsight, but which has taken me a long time to appreciate

For a long time I never understood why people shop during vacations, when both time and luggage space are precious commodities. With global trade, I reasoned that most clothes should be available at reasonably comparable prices worldwide, and barring some special needs (such as a certain kind of shoes, for example), there was no real need to shop on vacations.

The last day of our trip to Munich in June convinced me otherwise. That was the only day on the trip that the wife was free from work, and we could go out together before our afternoon flight. The only place we ended up going out to turned out to be a clothing store, where the wife freaked out shopping.

It didn’t make sense to me – she was shopping at a chain store which I was pretty certain that I had seen in London as well. So why did she shop while travelling? And she shopped far more than she does in a normal shopping trip in London.

In hindsight, the answer is rather simple – diversity. While the same stores might exist in various countries or cities, each is adapted to local tastes and prevailing fashions. And while everyone watches the same “runways” in Milan and Los Angeles, there is always a subtle difference in prevailing styles in different places. And clothes in the stores in the respective places are tailored (no pun intended) to these styles.

And it can happen that the local prevailing styles are not something that you particularly agree with. For example, for years together in Bangalore I struggled to find plain “non-faded” jeans – most people there seemed to demand faced or torn jeans, and stores responded to serve that demand (interestingly, jeans shopping in my last Bangalore trip was brilliantly simple, so I guess things have changed).

Similarly, the wife finds it hard to appreciate most dresses in the shops in London (and I appreciate why she doesn’t appreciate them – most of the dresses are a bit weird to put it mildly), and as a result hasn’t been able to shop as much in recent times. She had taken to claim that “they don’t seem to be making normal clothes any more”.

But the styles in London aren’t correlated with the styles in Munich (or elsewhere), with the result that in that one chain store in Munich, she found more nice dresses than she had in some 20 shopping trips over a year in London.

Fashion suffers from the “tyranny of the majority“. It makes eminent sense for retailers to only stock those styles and models that have a reasonably high demand (or be compensated for stocking low-demand items with a high enough margin – I have a chapter on this in my book). So if your styles don’t match with those of people around you, you are out of luck. ┬áBut when you travel, you have the chance to align yourself to another majority. And if that alignment happens, you’re in luck!

PS: On a separate note, I’m quite disappointed with the quality of clothes in London. Across brands, they seem to wear much faster than those bought in continental Europe or even in India.

Linearity of loyalty rewards

So I’ve taken to working a lot in cafes nowadays. This is driven by both demand and supply. On the one hand I’ve gotten so used to working for my current primary client from home that I’m unable to think about other work when I’m at home – so stepping away helps.

Also on the demand side is the fact that this summer has been incredibly hot in London – houses here are built to trap in the heat, and any temperature greater than 25 degrees can become intolerable indoors. And given that cafes are largely air-conditioned, that’s an additional reason to step away from home to work.

On the supply side, there are three excellent hipster cafes within 200 meters of my house. Yes, I live in a suburb, though my house is very close to the suburb’s “town centre”. And all all these cafes make brilliant coffee, and provide a really nice ambience to work.

So far I’ve discovered that two of these cafes offer loyalty cards, and given my usage, neither makes a compelling reason to be loyal enough. The “problem” (in terms of retaining my loyalty) is that the loyalty card at both these places offer “linear rewards”.

Harris+Hoole has an app, which offers me a free drink for every six drinks purchased. Electric Coffee has a physical card, which offers me a free drink for every ten drinks I purchase. Now, the rate of reward here (I’m writing this sitting in Electric) is lower, which suggests that I’m better off patronising Harris+Hoole, but some variety doesn’t hurt – also I’m queasy about ending up and parking in the same cafe more than once in a day.

Even when I was writing my book in Barcelona two years ago, I would never go to the same cafe more than once a day, alternating between Sandwichez, Desitjos and this bar whose name I could never figure out.

Ordinarily, if I were a low intensity user, one drink for every N drinks ($math 6 \le N \le 10 $) would have been a sufficient reason to be loyal. Given my rate of consumption, though, and the fact that I go to both these cafes rather often, the incremental benefit in staying loyal to one of these cafes is fairly low. I can peacefully alternate knowing that sooner or later the accumulated ticks on my card or app are going to provide their reward.

It wasn’t like this last year, when I was briefly working for a company in London. Being extremely strapped for time then, I hardly patronised the cafes near home, and so the fact that I had an Electric card meant that I stayed loyal to it for an extended period of time. At my higher level of usage, though, the card simply is not enough!

In other words, rewards to a loyalty program need to be super-linear in order to retain a customer beyond a point. The current linear design can help drive loyalty among irregular customers, but regulars get indifferent. Making the regulars really loyal will require a higher degree (no pun intended ) of rewards.

PS: Given the amount of real estate hours I occupy for every coffee I buy, I’m not sure these cafes have that much of an incentive in keeping me loyal. That said, I occasionally reward them by buying lunch/snacks or even a second coffee on some visits.

PS2: As a consumer, loyalty card versus app doesn’t make that much of a difference – one clutters the wallet while the other clutters the phone (I don’t like to have that many apps). A business, though, should prefer the app, since that will allow them to know customers better. But there’s a higher fixed cost involved in that!