What’s the Worst that could Happen with Poorly Worded Menu Options?

Choices on mobile apps (also on any app) need to be worded appropriately so as not to cause any confusion in the user.
This menu option on a sleep tracking app seemed to be a clean way to do it. A simple line that explains each option when selected.

What’s the worst that could happen with poorly framed menu options?
Back in 2007, I got my first credit card. And the one I would default to even when I had more cards. Over the past 13 odd years, I suppose the card company and I benefited from the service.

Then sometime during the pandemic, RBI laid down new rules for debit and credit cards, making users manually opt-in for availability of different types of transactions (online, POS, international), and set limits for the same. I downloaded the mobile app this bank offered. However, I faced 4 challenges with it:

  • The way the choices were worded created some ambiguity (on whether we had opted in or out of a choice)
  • Touch selection was slightly glitchy, you sometimes had to click more than once to select/deselect
  • If you changed any card limits, you would receive an OTP to confirm the changes
  • There was a delay in receiving the OTP. Every time.

These four challenges together, created quite a frustrating experience. As you firstly wouldn’t be aware if the option read a choice you wanted to opt for, or the opposite. And to check it, you would have to go through the motions of generating an OTP, confirming changes, and then seeing if the change reflected what you wanted, or the exact opposite.

The result. I stopped using the card. For starters, simply because the choice options created a confusion in me, and verifying each one of those choices took a longer route of glitchy clicks, waiting for the OTP, and then waiting to see what change had occurred.

If you can’t phrase choices in an easily understandable manner, something simple like the explanatory sentence or two for each choice would go a long way in retaining former loyal customers.

Feature Suggestion for Todoist

In my last post, I recommended reading the book, To-do List Formula. I also shared my own key takeaways from the book.

The book highly recommended the Todoist app to create and track tasks. I started using it ever since, and compared to all the apps I have used so far, I have found it to be somehow designed to allow for more efficient days.

I did feel the computer and mobile apps could use a small feature improvement that could further improve the efficiency its users derive from it. And I wrote to them about it. A RattL ’em idea if you will.

Here’s what it is.

While any to-do app allows you to set deadlines for tasks, you can create them without specifying a deadline as well.

Image 1

 

Image 2

Now say you wanted to try and rearrange entries 7-15 so that they would be according to your measure of importance and urgency, after which you could enter achievable deadlines for each. This can become a challenge when it is many more than just 9 entries that you need to put into sequence.

Now if you are diligent in the easy bit of at least adding tasks to an app, you would notice that the number of entries could easily go up to a few dozens if not more. Now Todoist (and other apps like Trello) allow you to drag and drop to change the order of entries. But even then, since your view is only limited to about 6-7 entries (on the laptop or mobile app), that can require a lot more mental processing or note taking to sequence the entries so that it becomes easier to then assign due dates for them.

A solution to this, would be a simple ‘pop-up view’ option (grey below) that could be offered. This would accommodate all the entries on the list, on the pop-up view screen, in a grid (as opposed to a scrolling list). 

Image

Image 3

Here, the user could drag entries around into a better priority sequence, and then switch back to the scrolling list view and start assigning due dates for them (below).

Thoughts?

Struggling with To-Do Lists and Staying Productive?

A lot of us struggle with staying productive. Especially so in these times of lockdown and uncertainties. And also when you are focusing on larger goals that don’t really offer much daily satisfaction of accomplishment.
I have heard of some really brilliant people, especially from the behavioural science and behavioural economics communities, struggle with staying motivated and on top of their tasks. I guess that is enough to confirm that it is clearly a human challenge, and not one that those who understand behaviour better than the rest of us can easily solve.
It also does not mean it cannot be solved. Just probably not in the ideal, smooth-flowing way we expect it to.

Staying productive and to-do lists are something I do struggle with. And I have tried many apps to help me. Some have worked, to some extent. Some have worked well in combinations with other apps. In short, it has been a messy process at least for me.

I started creating Excel spreadsheets to keep track of my tasks during my venture capital days. And over time, I’d realize I am falling back, so I’d rework the layout, find some effectiveness, and the cycle would repeat.

I have since, used Google Keep, EverNote, more spreadsheets, Trello, and well over a dozen other apps that I didn’t seem to work for me.

Recently, I read the book, ‘To-Do List Formula‘ by Damon Zahariades. And, it is brilliant.
The book has been beautifully written. The author literally describes different approaches from the perspective of a newbie, and then tells you why that one doesn’t work or where it falls short. That way, by just reading the book, you quickly go through the process of discovery and progress that could otherwise sometimes take years. Ask me.

Anyway, I created a list of key points from the book to serve as a ready reference. Sharing the overview of key points I created from the book here, in case some of you find it useful.
Of course, this is simply to give you a flavour of the book itself, which I strongly recommend you read. For those of you who have a Kindle Unlimited plan or trial plan, it is available there as well!

Anyway, he highly recommended the Todoist app. I have been using it for almost a month now.
Of course, still too early to say, and obviously, it is not the tool itself that will compensate for shortfalls in our enthusiasms or anything, but so far, it has been a good tool.

I love Trello, that I have been using for over a year, and still do. But this one somehow edges it out when it comes to the layout and experience. Still haven’t figured exactly how though yet.

In the next post, I share a RattL ’em idea I suggested to Todoist recently.

Till then, here’s the overview of key points I created from the book.

What if the Comments Section on Social Media had a Search Feature?

Image: source

Say you create a post on social media, and friends or acquaintances comment on it over the next few days or weeks.
Now, sometimes it gets tricky if the comments function is basic.

If there are a few new comments before the next time you check that account, finding them could be a little tricky. Especially if someone comments in reply to your or someone else’s reply. Or if the platform takes you broadly to that section but not specifically to the new comment.

Facebook does a decent job of highlighting the region around a new comment, making it easier to spot.
And LinkedIn gives you the option of sorting comments by Most Relevant and Most Recent.

However, this still leaves a lot to desire.

What if social media platforms could include a search function as a feature on comments?

For instance, LinkedIn has a fairly good search function on messages. It allows a user to sort messages by Archived, from Connections, Unread, InMail, and Spam. However, commenting on posts can get messy really fast if you have a conversation in comments with multiple people, and each one replying to their respective sub-threads.

Facebook gets a bit tricky on birthdays, especially if you are someone who tries to respond to everyone who wished you, and then there are a few small interactions happening in those sub-threads.

Would be nice if the search feature in comments across social media platforms would let us sort by recency, maybe even filter by commenter, etc.

Social media platforms also collapse the comments section for appearance and probably speed, and show only a few comments at a time. With each ‘next’ click, Facebook (and probably LinkedIn) show the next 10 comments, Instagram shows the next 3 only!
Would be great for social media platforms to have a ‘See All Comments’ feature.

From a development perspective, I would imagine it would be similar to adding the Filter function to a spreadsheet.

Do you feel the need for a more effective comments section on social media?

Reading and Writing Smarter

While looking up an old blogging account of mine, I stumbled upon a #RattLem idea from many years ago.

I had made a suggestion to Google, sometime in Feb., 2013 regarding composing of emails.

People sometimes want to, or even unintentionally tend to write lengthy mails.
And people’s attention spans have become shorter [or unchanged, as per some reports, while number of distractions have increased]. Which means, most of us have lesser and lesser time and patience to read through any written matter. And since most of what we read is online, I felt there is scope for improvement.

My suggestion was that emails could have the option to group sections [remember the ‘Group’ option available in Microsoft Excel]. These sections would become collapsible. That way, the recipient of the email can quickly get a gist of the content, and could then expand any or all section if they want more details, and toggle back to birds-eye view whenever needed.

This would be better than overloading the reader with an endless sea of paragraphs that stand the risk of going partly unread.

Main points or key news headlines could be listed out, with  details kept hidden by a [+] sign, so that recipients could expand and read more.
Let me know what you think, and if you have any better suggestions.

Sindhutai Sapkal – The mai of over a 1000 children

 

 

Image: source

Sindhutai Sapkal passed away yesterday.
For those who haven’t heard of her, she was born in an extremely poor family in the state of Maharashtra, India in 1948.Married at the age of 12 to someone who was 32, her husband abandoned her when she was 9 months pregnant. Forced to give birth in a cow shelter, she then went to her parent’s place, but was not welcome there either.

She started begging at railway stations, where she realized there were many abandoned children begging too. So she adopted them as well, and begged to feed them.

Then, in an act perhaps only a higher being is capable of, to avoid partiality between her own child and her growing number of adopted children, she gave up her biological child to a trust.

She later fought against the government for the rehabilitation of 84 villages in forest areas, and for compensation for villagers killed by wild animals! And won!

Over her life, she nurtured well over 1000 orphans (1400 by some estimates!). And she used money from the 700+ awards she won during her life to buy land and build more homes for her children.

She was fondly addressed as ‘Mai’, meaning mother.

If I remember correctly, later on in life, her husband came back and asked for her forgiveness. She said she couldn’t take him back as a husband, but allowed him to live there as one of her children.

When we think about human potential, I hope Sindhutai Sapkal’s higher sense of purpose and selflessness will continue to be remembered.

14 November 1948 – 4 January 2022

Sample Size of One: Towards a Possible Solution

This post explores an alternative to fix the replication crisis (particularly in the behavioural science and economics fields, and if relevant, in other fields too). This post is in continuation to an earlier post titled Sample Size of One: The Rose Negotiations. It would help to read that one first before coming to this one.
 
What can we do to solve our human desire to create or find patterns and thumb rules to how we function? Or to find keys to getting humans to behave in a particular manner, be it to drive a more healthy culture, or improve finance sense among populations. Especially when few patterns exist. And when our desire might be overly simplifying a pattern which might be far broader than what we might want it to be.
 
Here is a broad suggestion towards what a possible solution looked like, at least in my head.
Consider a “hypothetical” scenario where a group of researchers wants to find the effects of an ‘opt-in/opt-out response’ for organ donation.
Up until now, behavioural economists or scientists would identify a large, diverse study group of volunteers, and conduct the experiment. Let’s suppose at the end of the study, they found that 70% of respondents opt for the organ donation program when the form requires them to physically opt-out of organ donation.
Now, a non-profit across the world tries this tactic on a local population, but perhaps has a less than encouraging (and far less than a 70% success rate) outcome. This leads to questioning the research findings, and the broader hue and cry around the reproducibility and replicability of such studies/ experiments.
 
For a moment, consider currencies. They are always fluctuating, and there is a definite exchange rate to convert between any two currencies at at a given point in time.
Or consider diverse marketplaces across the world. Any single product would be differently priced in these different marketplaces. And within a single market, the price variance might not be too much. But it might vary if you went to a market in the next village.
 
Coming back to trying to find an alternative to traditional experiments that try to find thumb rules to then apply to social or business causes.
 
The alternative I see, is where the economist or scientist creates a simple experiment or study around the hypothesis they would like to test. They would then put it on an online platform (and share it with their colleagues and counterparts across the world, who would then deploy it among local populations).
The experiment would be introduced via a website. Deployment could be done online with voluntary participants, or random people. The experiments would run in perpetuity (hence online), and results of the same would keep evolving over time and geographies.
 
The outcome for the same opt-in/ opt-out hypothesis with this alternate deployment might look something like this:
The experiment is designed to be unbiased, simple (easy to deploy without the original team of researchers being physically present), and yet robust enough to provide meaningful data.
The results of this experiment would not be captured as a single value (like 70% in the first hypothetical scenario), but rather as a function of (age/sex/location/study response/point in time).
As a result, what the outcome might look like, is diverse data points from across the world at diverse points in time.
It is possible that patterns will emerge in localized groups, or even at a nation-level for some experiments (since respondents or the general population might share a similar national history, current political and economic environment, and similar fears and concerns – whether it is about inflation, unemployment, or a multitude of other variables that were possibly getting ignored when a research study focused on finding a thumb rule.
With a global, perpetual study, for the same opt-in/ opt-out experiment, we might perhaps get results like an average of about 65% in Mumbai, India, but a 20% on the outskirts of Mangalore, India, and maybe even an 80% in Itanagar, India.
That way, researchers and anyone trying to use these research findings would be mindful that it isn’t a one-size-fits-all finding. But rather that perhaps (cautiously), one might expect to get a similar response to an organ donation campaign in a town in Country 1 and a city in Country 2, because their outcome values over a particular period of time have been similar.
 
And these values that emerge across individuals and locations are not fixed values. They are ever-evolving, to reflect the evolution of humans in a particular society, given the context of its changing sociopolitical and socioeconomic landscape, among other variables. So perhaps the same individuals too could participate in the same experiment multiple times over the years, with different results. In that sense, it would be similar to taking an IQ test or an MBTI test.
Which means, the same non-profit that is driving an organ donation exercise in a particular country in a particular year, would refer to the current result outcomes for different parts of that country, to determine what strategies they might have to employ (government intervention, financial incentives, etc.), towards driving a more successful change effort.
 
An obvious extension of this proposed solution will be coming to a post soon.
In the meantime, it was still challenging conveying the problem and my solution concept to people. So I started working on a simpler way to do that, and here it is.
 
#SampleSizeOfOne #BehaviouralScience #BehaviouralEconomics

The Behaviour Triangle

 

A humorous take on the paradox that exists between the views or tendencies of us common humans, versus that of therapists, who seem to take the more empathetic approach, versus some behavioural science practitioners who try to leverage behavioural knowledge to grow business without it necessarily being beneficial to customers themselves.

A related interesting read someone shared: Nudge Theory needs to take more external factors into account.

#Humour #BehaviouralScience #BehaviouralEconomics #Nudge #psychologist #Behaviour #Behavior

Sample Size of One: The Rose Negotiations

Image: source

The Replication Crisis is an ongoing crisis where it has been difficult or impossible to reproduce findings of scientific studies.

The field of behavioural science too, has had its challenges with replicating past research findings. Some years ago, peer-reviewed scientific journal, Nature Human Behaviour, attempted to replicate 21 social and behavioural science studies published in the top peer-reviewed journals, Nature and Science. It could replicate only 13. Other such studies conducted too, resulted in disappointing results.
 
Is it surprising if behavioural science and behavioural economics research findings are difficult to replicate? Till recent decades, many studies were undertaken by professors on captive university students; a long shot from representing world diversity. Findings from one country could throw up different results in another country based on many variables like the history of that nation, recent and current economic progress, poverty levels, trust levels, level of ethics in government, enforcement and business, among other factors. We see diversity even in our interactions with foreigners on social media.
 
And yet, we as humans, are always trying to find a simple common denominator. A thumb rule. A recipe or formula that we would like to think would apply to the world population.
 
Instead, what if we looked at behavioural science endeavours the other way around? Why struggle to have larger and more diverse sample sizes to represent world diversity and improve study accuracy? Instead, what if we started with a simpler sample size? One that we are more sure of, and that offers more accurate data points. What if we start with us as individuals? The observations, feelings, rationale or reactions of the individual (hence ‘Sample Size of One’)? And from there, cautiously see if and to what extent, it applies to other individuals or groups?
 
Whenever we experience a situation, we could try and assign values to various parameters. Then, similar situations created for others in other parts of that city, country or the world, would give us more data sets. We could then look for a single line passing through diverse cultures, or spot similarities in diverse groups. Similarities in similar groups from contrasting countries too? Or not.
 
What we will have, is readings across these situations or experiments across countries and cities. At present, if an experiment with a sample size of 10,000, finds 70% respondents behave a certain way in a scenario; we extrapolate it and believe 70% of world population might behave in a similar way.
 
Instead, what if we had that scenario, but had different data sets for different locations? That way we might find clearer patterns (there goes the human in me again) among groups in diverse cultures where a certain improvement intervention might respond similarly to another one which had similar outcomes from an experiment.

This thought occurred to me during a recent festival and an interaction with a flower woman in the market. Here’s the story.

Sample Size of One: The Rose Negotiation

My family is a bit religious. During Dussehra puja a few weeks ago, I was back at the market, buying flowers and fruit.

A woman in the market has a flower stall and sells bouquets. I always buy roses from her. On regular days, a rose costs INR 10. On festive days, she sells them for either INR 12 or 15.
I asked her how much for one.

“INR 15”, she smiled and replied, “but you can have them for INR 12. How many do you want?”

I asked for ten. Like always, I asked her to cut them to a particular length. I said I’ll pick up the other stuff on my list and come back for the roses.

Back at her stall 15 minutes later, she said the total was INR 150.

I said, “but didn’t you say you’d give them at INR 12 a piece?”

Now she seemed confused, like she had goofed up the prices.

In the past too, I have always paid her the full price, whether she offered a discount or not. After all, these vendors pay a premium to buy flowers during special occasions. And on that day too, I had intended to pay her the full INR 150 either way.

But there’s the funny thing.

When she first offered a discount and later forget about it, I felt a mild disappointment or something. And it is possible others might have felt the same way in that situation. It is odd, since I was ready to pay full price, right? A loss aversion of sorts.

Trying to quantify my feeling on a Disappointment-Delight scale [-10 to +10] (-10 being very disappointed, 10 being very delighted), I got:

  1. If I go to the stall on a regular day, and I am charged INR 10 for a rose: 0 (on the scale)
  2. When the woman first quoted the festival price of INR 15: -5
  3. When she said she’ll let me buy them at INR 12: 5
  4. When I made a mental note to still pay her INR 15 a piece: 9 (it is always priceless to expect and see smiles on the faces of those who work hard to make a living, when you pay them full price and not be the asshole who squeezes an extra buck out of them)
  5. Her later quoting the original rate of INR 15 a rose: -8
  6. Me then paying her the original rate of INR 15: 3

Despite my intended payment amount and her final quote being the same, my delight level dropped from a 9 (in pt. 4) to probably a 3 (pt. 6).

-End of story-
 

What do you think? Could experiments/ experiences like this one, experienced by a single person, be then gauged on a list of parameters for other people in the same city, country, and in other parts of the world? The objective not being to find a single global thumb rule or measure (like 70% or 8/10 on delight). But rather, to see how different groups of people fare on each such experiment/ experience. It need not be a labour-intensive effort. Data could be crowd-sourced.

Could this approach be a little less presumptive and a little more accurate than prevailing forms of research studies?

Read about a possible alternate solution that I propose, here: Sample Size of One: Towards a Possible Solution
 
#SampleSizeOfOne #BehaviouralScience #BehaviouralEconomics

Wonder Why so many Americans are wary of Vaccines

 
In the past, US Anti-vaxxer protests have not gone unnoticed by the world. And while it was surprising then, anyone who was curious enough to dig a bit deeper, also saw that the US had at least a few more vaccinations prescribed to newborns-through-18 than many other countries. So, at least to me, questioning the need for all the vaccines by some groups seemed understandable (though not justified, especially when one’s personal choice could put others’ health at risk too). But thanks to Covid-19, a good part of the world became keen to get vaccinated, so they could go back to a normal, pre-Covid kind of life.
 
Early on with the Covid-19 vaccines, it seemed a bit concerning that educated populations from developed countries, were trusting of the Covid vaccines. Especially considering that in the past, vaccines took years to develop, even for less rapidly mutating diseases. And yet, in a record time, a few pharma companies had created vaccines for a dangerous variant of the flu that the world had not seen before. And one that continued to mutate into concern-causing variants through the vaccination drives. So while a considerable population of the developed and developing world scrambled for vaccines, it was not surprising how part of the population in the US continued to resist getting vaccinated.
 
The media and propaganda played a big part no less. Readiness or resistance toward the vaccine getting influenced by one’s political stance or religious beliefs. It gave us a glimpse of what the combination of human bias, politics, religion and media, are capable of.
 
While most of us have lost at least a few friends or family to Covid, and seeing how the vaccines have been safe so far, it was surprising to see some people in the US stay put on their decision not to get vaccinated.
 
As per a BBC article from a few days ago, US President Joe Biden was insistent that employers ensure their staff gets vaccinated. And a number of US citizens across professions remained adamant about not taking the shot, even if it cost them their job. Many seemed to be from the healthcare sector.
 
I wondered if those from the healthcare sector, being closer to the problem and solution, knew something about the vaccines that the rest of us did not. Especially since the virus continues to kill about 1500 Americans daily.
 

A few months ago, I was reading the exceptional book, ‘The Signal and the Noise‘ by Nate Silver [get a copy of it, it is priceless!]. An incident detailed in the book from American history made me wonder if that could be one of the causes that sowed the seed of doubt about vaccines or strong government interventions among Americans, making them continue to resist it. Especially since the country is among the top in innovation, so we are talking about an intelligent people, not some isolated, small town population in an underdeveloped country, cut-off from world perspective.

In the 1970’s, there was a common belief at that a major flu epidemic struck roughly once in a decade, and by 1976, the world expected one to hit.

In January, 1976 at Fort Dix, David Lewis, a nineteen year old private who had returned from holiday, had the flu – a common occurrence at army bases, thanks to soldiers returning from holiday bringing back some variant of the flu from their hometowns, and into cramped up bases, where it would spread. However, it was almost always the common variants, causing no concern. However, private Lewis, while on a march, collapsed and was later declared dead. The cause was pneumonia.

Hundreds of soldiers suffered from the common A/Victoria flu that year. Blood samples sent to the Center for Disease Control (CDC) showed that some had the more disturbing H1N1, or swine flu; the one responsible for the 1918-20 Spanish flu. Around 200 soldiers at Fort Dix tested positive for swine flu, with private Lewis being the only casualty. While flu season had passed by then, scientists feared that by the next winter, there could be a severe outbreak of a more mutant strain of swine flu.

US President Gerald Ford’s secretary of health, F. David Mathews, estimated a potential death rate of a million. Fighting to repair his public image, President Ford thought that preparing his country for the epidemic would be the perfect way to do it. He rallied Congress to allow a USD 180 million plan to manufacture 200 million doses of vaccine, and ordered a mass vaccination program.

It was winter in the southern hemisphere, but to everyone’s surprise, there were no instances of H1N1. Criticism started to build. No other western country had called for such drastic measures.

Instead of admitting their mistake, the Ford administration went rogue. It created panic-causing public service announcements and telecast them at regular intervals. One TV message showed a healthy fifty-five year old mocking the vaccine, only to shown on his deathbed moments later.

The result was an American public that was fear-struck, by the disease and the vaccine. Under pressure from drug manufacturers, Congress indemnified them from legal liabilities that could arise from manufacturing defects. Vaccine production was rushed, without adequate testing. Compared to government estimates of 80%, polls found that only about 50% Americans intended to get vaccinated.

The vaccination program began in October. Three Pittsburgh citizens died shortly after receiving their shots. Similar news poured in from other cities, causing concern among those who had taken the shot.

By late fall, a bigger problem emerged. 500 of the 50 million vaccinated, began exhibiting symptoms of a rare neurological condition called Guillain-Barré syndrome, an autoimmune disorder that can cause paralysis. This occurrence among the vaccinated, was ten times its usual incidence in general population (one case per million). Manufacturing defects due to the rushed production seemed a possible cause. The vaccine program ended on December 16th.

Long story short, the outbreak at Fort Dix was an isolated one, with no other H1N1 cases across the country. The government faced USD 2.6 billion in pharma liability claims. Cities and towns saw upright citizens who had contracted Guillain-Barré. Within a couple of years, the number of Americans willing to take flu shots dwindled to about one million.

One cannot say for sure if a horrific experience like this is what might have left Americans so wary of Covid-19 related government assurances and the vaccinations themselves. But it did make me wonder.

 

 
%d bloggers like this: