ASX Sharemarket Game

Product awareness and training is an uphill battle for complex products - product walkthroughs, demos, knowledge centre aid to an extent but it doesn't build user confidence or trust especially where financial investment is required from the user at the outset. The stakes are pretty high and poor initial performance/financial loss could negatively impact the user -  feeling incompetent with the product/domain leading to higher barriers of entry for future use.

ASX has been a shining example of resolving such issues with ease via their ASX Sharemarket Game. The game provides its participants with seed money of $ 50,000 which can be invested in the live stocks at ASX. Here are some noteworthy aspects : 

* The game is not run in a separate simulated environment but in the same stock trading environment - so the price of the stocks is live, trading is live, portfolio standing/impact is live

* Since it is mock money, the participants can try out various strategies, take higher amounts of risks and explore different stocks available

* Over a period of time, the participants get better understanding of how a stock exchange works, what affects the price of stocks and overall how the global economy is interrelated - all without going through laborious hours of videos and expert talks

* By playing the game, the participants become familiar with all the features of buying/ selling at ASX and gain confidence with trading - making conversion post the game a breeze

* There are few gamification aspects like leaderboard, prizes etc.  added to give it a competitive sense

* There is a social element to it - the game can be played individually or as a group

Loved the fact that it has been offered to high schools too which gives early exposure to children to build their financial muscle.

While I have enjoyed exploring the world of stock trading via the game, there are some great product takeaways in there !

More about the game can be found here : https://game.asx.com.au/game/info/public/about-the-game

Biomimicry & Design Thinking

Humans are considered the most evolved species due to our ability to think (or so we think). However there is so much to learn from nature and other species that there is an entire stream dedicated to the same called Biomimicry. Biomimicry understands how species adapt and function in certain conditions which has been emulated to solve complex problems for us. 

Image credit : Roche, 2016

The head of a bullet train is shaped like a beak to eliminate a tunnel boom and be more efficient, delivery pods/advanced logistic maps are inspired by honeybees, velcro was designed from Budrock plant and so on. There is a golden/divine ratio of 1.618 which governs balance in structures to the frequency of a galaxy !!

So how does biomimicry relate to design thinking ? Let's break down the basic elements of design thinking - Empathise, Ideate & Iterate. To empathise is to understand the users, their pain points, alternatives used etc. This in the biomimicry world is expanded to all species - understand how the species function and what their challenges are. A biomimicry ideate would then be to brainstorm how the species' over come their challenges, extract learnings from those and map how we could apply them to solve similar problems.

It's not just physical products that have benefited from this, but even advance computing algorithms too. Here are some fascinating complex systems/alogrithms which were designed from biomimicry:

• Data driven behavioural model derived from bacteria
• Search engine optimization inspired by Arboreal Ant trails
• Machine learning inspired by insects' nervous system

Upon reading about so many facets of biomimicry and its direct applications to product/design thinking, couldn't agree more to the following quote:

Nature will teach us many lessons if we take the time to visit her classroom.
— Donald L. Hicks

Library visit - a multi sensory experience

Our local library underwent a major revamp and reopened last week. A recent visit has been surprisingly a multi sensory experience and surely worth the wait.

* The categorisation of the books is done so well by genre instead of just the standard alphabetically stacking. However each section has a recommended shelf of the latest/ frequent borrows. It even has a BookTok shelf (books made popular on TikTok) !

* The checkout stations have been turned into sophisticated kiosks which can scan multiple books (like a shopping basket scan)

* The return chute has been replaced with sensors that automatically scan the returned book codes

But more than anything, it is the spacious layout and structural design that really stands out. The address is 5 Parramatta Square and so the library has been aptly named as PHIVE with the building designed to resemble a bee hive !

The smarts have been incorporated in everything - the name, look to the ambience providing a great CX. 

First principles thinking

 

Often we are given problem statements with constraints and we get boxed into it. So the solutions are also sought within these boundaries i.e. we inherently can't think 'outside the box'. Although the following is more than a decade old, it's a great example of how not putting blinders on can expand the solution horizon.

In 2009, a batch at Stanford was divided into 14 groups - each group was given $ 5 in an envelope ✉️and tasked to generate maximum ROI. They had a few days to plan but once they opened the envelope and took the money, they had 2 hours. Each group was then to present the findings in 3 minutes the following Monday.

🚲 One group built a stand and offered to fill air pressure in cycles for the uni students (pay for convenience). Since they charged $ 1, the expected returns were also low.
🍔 Another group made reservations at sought after restaurants and then sold these reservations to those waiting in long queues with a low chance of getting one on the spot. Many paid for upto $ 20 for such timely reservations (pay for scarcity). The team raked up a decent profit.
💸However the winning team exhibited business acumen like no other group, generating record profit without spending a dime of the $ 5 given to them - they didn't open the envelope ! They clawed back to fundamentals of 'how can we maximise value' without getting constrained by the $ 5 or the 2 hours. While the other teams focused on the physical realm around them, this team thought of the most opportune moment to catch everyone's attention - the Monday presentation and sold ad space on their slide to a student recruiting firm for a whooping $ 600.

This is one of the finest examples of first principles thinking and also reflects on how valuable every inch of digital real estate is. The above was in 2009 at a micro level, imagine the potential of Adtech in 2022. Advertising in general gets a bad notion since it gets aggressive and intrusive but done with the right control measures, is the most effective medium for business reach and growth.

Framing - how words can change $ perceptions

Ever wondered why it is called tax returns and not tax declaration? A simple choice of a positive word 'return' can frame the perspective better. A tax return reminds us of a favourable outcome we can expect provided we file one (so serves a dual purpose of reminder too). It's also the anticipation of money refunded which provides the motivation to complete the activity. If we look at it very objectively, the fact that we overpaid taxes is a lost income opportunity (if that same amount was invested elsewhere). But the frame is set up so well that we don't realise / overlook this aspect.

Similarly use of negative words frames a non favourable impression - something the credit card companies have been trying to lobby for a while without success. So is credit card fee a surcharge or is paying by cash a discount ? The fact that it's called a surcharge implies the base value is lower and we are being charged additionally for the card processing. If however payment by cash is called a discount then the base value changes. The surcharge frame is penalty based and hurts the image of credit cards.

Also this difference of projections between fine and fee is what changes our perceptions drastically. A fine is a penalty for what is considered to be wrong (socially in most cases ) and comes with a guilt associated to it. A fee on the other hand is a monetary charge for getting away with something or getting access to additional benefits that is not the norm. So a $ 100 fine for speeding indicates that speeding wasn't the right act and hence has been penalised. But if that is converted to a $ 100 fee for speeding, it changes the context althogether. Now, people would be more open to speeding and would do it more often as they just consider it as a monetary transaction. Such frames do hold a delicate balance between social and monetary norms.

"What counts isn't the frame, it's what you put in it."  - Otto Preminger

Voter biases to watch out

Australia has one of the highest turnouts for voting 👏 across the globe (power of penalties perhaps ?). It is such an important right, yet voting has been predominantly a subconscious activity/gut decision. Over and apart from 'in-your-face' propagandas there is a ton of subliminal persuasion at play. Here's top 3 voting lapses we should steer away from, to make a conscious well thought about decision:

🖼️ 𝐅𝐫𝐚𝐦𝐢𝐧𝐠: Media plays a big role in framing and while in an ideal world the media should be unbiased, it rarely is. Selective statistics or partial information frames the context in a very different vein.
🤝 𝐂𝐨𝐧𝐟𝐢𝐫𝐦𝐚𝐭𝐢𝐨𝐧 𝐛𝐢𝐚𝐬: This is such a common one and applies to a wide range of decisions we make. We seek information that validates our views. It mutually impacts the bandwagon effect - we get surrounded by like minded people and in the process create an echo chamber.
😇 𝐇𝐚𝐥𝐨 𝐞𝐟𝐟𝐞𝐜𝐭: We form connections between unrelated attributes especially based on looks. Ever wondered why politicians use family photos while campaigning ? Being a good parent has nothing to do with political leadership.

"𝘔𝘢𝘺 𝘺𝘰𝘶𝘳 𝘤𝘩𝘰𝘪𝘤𝘦𝘴 𝘳𝘦𝘧𝘭𝘦𝘤𝘵 𝘺𝘰𝘶𝘳 𝘩𝘰𝘱𝘦𝘴, 𝘯𝘰𝘵 𝘺𝘰𝘶𝘳 𝘧𝘦𝘢𝘳𝘴." ~ 𝘕𝘦𝘭𝘴𝘰𝘯 𝘔𝘢𝘯𝘥𝘦𝘭𝘢

Wordle Hurdles

Wordle has taken the world by storm with it's simple game play, great UX and an addictive mechanism (without any lock ins). Over the past few days with NYT taking over, the words have gotten harder and there is quite a lot of backlash.

Here's a few reasons that come to mind :

* It's Social : The social share of Wordle let to it virality - who wants to share an unsuccessful attempt ?

* It's Emotional : Dopamine is the hormone released when we complete a task or accomplish something (no matter how small it is). With an unsuccessful task, the lack of dopamine hits you harder. As the task gets difficult, the resistance increases - after all this is played for leisure while travelling, multi tasking etc.

* It's Personal : You don't want to be reminded of your English competency time and again. Plus many of the players use this as a bonding activity - playing /sharing with kids, parents etc. The Oxford level English is beyond their scope altogether. Who uses CAULK and SWILL in their daily conversations ?

Hope NYT is able to add a novel easy spin and revive it to the enjoyable level it was - else like many one time wonder products, this one too might fizzle out.

Here are some hilaroius tweets :

Big data vs Small data

Human decision making is truly irrational. While we strive to get conversions by using linear algorithms or banking on tons of data to understand consumer behaviour, it's the small things that truly matter - in this case, small data.

Two recent experiences reaffirmed the same :

🎤 At a recent product talk, the presenter talked about how Google's flu program failed when a simple heuristic approach worked wonders

Google Flu Trends (GFT) which used big data analytics and a black-box algorithm tried for years to predict flu outbreaks without any success (was wrong for 100 out of 108 weeks) and the program was finally terminated in 2015. However a surprisingly simple recency heuristic forecasted the flu outbreaks more accurately - based on psychological theory of how people deal with rapidly changing situations.

📖 Read a book on Small Data by a renowned branding consultant who has transformed major brands like Lego, Lowes etc using ethnography and understanding the entire ecosystem the users interact with.

Excerpt from the book :What helped turn around Lowes wasn't a local or regional solution. It didn't come out of a Harvard Business School or Wharton case study. "Big data never told us to build SausageWorks" a member of Lowes' executive team told me later. "In fact, the opposite is true." In every single Lowes, we hired a store manager whose only task was to determine whether or not shoppers were happy. They did, too. When people shopped at Lowes, they told me afterward, they felt 'at home'.

Small data involved Lowes Foods representatives actually going out and meeting with customers in their homes and speaking with them to learn more about what they want, need, and expect from the brands they choose to shop with.

Big data is important for decision making, reporting and assessing the overall health of the systems - it's effective in rational domains (what is already known). Small data has outperformed big data models in predicting outcomes, such as U.S. presidential elections, or other uncertain events, such as consumer purchases, patient hospitalizations etc.

A combination of both would be a powerful toolkit to have.

Product Thinking - Kidpreneur edition

The Smithsonian Spark!lab kits are great.

The inventor kit instruction manual (even though for kids) is product thinking 101 itself! All that's missing is customer validation (just like some real life projects 😉)

I was tasked with the Think It phase and constructing a problem statement.

Following were the questions I had to answer (no kidding) :

* What problem could your robot solve ?

* How could life be improved by having a robot ?

* How does your robot move ?

* What does it look like ?

Here's my attempt at racking up a problem statement 🙈

More often than not, we lay emphasis on these questions in reverse order or sometimes are so solution bound (how do we implement it and what does it look like) that we lose sight of the problem we are solving (and if the benefits are worth the effort) altogether.

I was blown away at the prototype created by my 9 year old though - was so aligned to the brief !

He added a few customer service elements : the robot says "Hi, how can I help you?"

The face tilts from side to side to give it a more humanly touch.

There's a brad pin added so the receipt doesn't fall off.

And a 10% discount just for today - launch offer thought about by a Gen A !!!

We didn't add the motorised component to it yet- but are calling this one our MVP 😀

All we need to do now is Sell It - any buyers ? 

Humor in products and services

Humor is a great leverage for both products and services - it breaks the monotony, boredom; relaxes the audience making them more receptive to the product/service.

However humor needs to have the right balance, overdo it or use it at the wrong time and it can cause an irrepairable damage. One of the most pathetic uses of dark humor has been by Specsavers lately when Dr. Kerry Chant's glasses broke while delivering a public message - the marketing team had no sense of respect for the NSW Chief Health Officer or the pademic we are in.

But there are so many products and services out there who are leveraging humor so well, here's some of my favourites:

[Call on hold] Waiting for the call to be transferred to an agent could be time consuming. Plus the fact that a customer is on hold means a risk of losing the customer if aid is not provided in the right amount of time. And what better way that humor to keep the customer engaged ? I recently moved houses and needed the Aussie Broadband agent to check the account set up details for me. While I was on hold, I was delighted to hear one liner jokes rather than the monotonous wait message! Aussie Broadband is definately raising the bar in terms of exceptional customer service.

[Release notes] Release notes are boring and nobody reads them but its one of those mandatory stuff to provide. However Slack has put an amazing twist to them with their witty and different approach to writing the release notes - on dull and boring days, I literally read all of them for some smiles :)

[Error 404] Who thought error especially the notorious 404 error page can be a great way to showcase some wit and branding. Here's Pixar's 404 page using one of their iconic characters from Inside Out (hats off to the creative genius behind it) : 

Top 3 impressive products

The benefit of the working in the startup world or contracting is that you get a wide exposure to products and can easily get hands on experience before it gets mainstream. Also you start looking at products differently - track the feature progress, release notes and make mental notes of key UX aspects (good, bad,ugly) to draw inspiration from in your work domain.

Here's my list of the top 3 really good tools/products I would happy advocate :

Loom

I have loved Loom since my first interaction and with quite a lot of changes made in terms of features and pricing too lately, it seems to be a very promising option - especially the video in video capture and ability to add time markers is a great aid to capture session notes. Have used Loom for recording customer interviews, explaining concepts or even to share thoughts in a very easy way.

Beautiful.ai

How much time do we spend in adjusting sections and layouts for presentations (be it Google slides or ppts) only to realise we now have more content to accomodate and rework ? The hours might add up to light years! Which is why Beautiful.ai has been a breeze of change for the better - layouts that adjust effortlessly and templates to create glossy presentations in literally minutes.I am not looking back to Powerpoint ppts / Mac Keynotes / Google Slides anytime soon.

Wise (formerly TrasnferWise)

Even though Wise is not a start up but a scale up now, it's still a mention worthy product. I have been a loyal user since two+ years now and have loved every interaction with it. It has got brownie points from get go - the ease of creating an account in a matter of minutes, the simplicity of transfers and of late the ability to hold multi curreny accounts accompanied by a sleek UI makes it a real winner. Bye bye big4 banks, hello neobanks !

I also had Miro and Otter.ai as close contenders - gaining quite a lot of traction and on my radar.

Slack, Canva, Trello are no doubt great products but they have been around for a while now and well on their path of becoming soonicorns.

Talking about soonicorns and minicorns, the Australian startup space is shaping up really well : Take a look ... Aussie, Aussie , Aussie oi oi oi !

Survey Statistics - it's all a numbers game

The double edged sword of surveys : if done right, they provide a wealth of information to take a data informed decision but come with the downside of going down a rabbit hole if not executed correctly.

If you are looking for quantitative research, relying on a collective inputs of mass to arrive at informed decisions, look no further. The benefits of surveys far outweigh the drawbacks (which can be easily averted following a systematic and unbiased approach).

There are a lot of aspects of surveys which need to be considered at design stage - from inherent biases to overcome to type of questions to consider. Survey tools have evolved drastically and provide a plethora of question formats to select. So what's the best type of question to select ? 

• Objective : What hypothesis is the question trying to validate ? Every question has to have a motive on why it's being asked. If there isn't any direct linkage to objectives, it's probably not worth asking the question (a compact survey has more chances of completion)
• Analysis : The question format depends on how the answers are going to be analysed. Are the answers going to be used in correlation analysis ? Or are they aiding in structured text analysis ?
• Spectrum : For polarity related questions it is always suggested to provide bipolar ordinal scale with equally spaced response options.

Let's consider this question : 'To what extent do you agree with moderation process?'  

Options on a ranking scale start from 1 (Agree) to 5 (Strongly Agree)

This is a biased unipolar nominal question - there is an underlying false assumption that all users agrees with the process and the gauge it to what extent.

Instead, the question should be : 'To what extent do you agree/disagree with our moderation process ?'

Options on a ranking scale start from 1(Strongly Disagree) 3(Neutral) to 5(Strongly Agree)

Now its an unbiased bipolar nominal question - a much better alternative.

Majority of the survey tools do provide basic chart/graphs related to the responses. However to get the most of the responses, a little bit of statistical analysis provides loads of valuable insights.

• Contrary to what the survey tools display, median is a better gauge for ordinal data than mean
• Of course mode is the only way to measure nominal data
• Correlation analysis between questions (scatter graphs for visuals) yields valuable insights on interdependences in the data set
• Last but not the least, almost types of research data aids in identifying clusters which then translates to segmentation

Clustering is a very powerful method to segmenting target audience or even identifying different personas. It takes correlation to the next level by grouping data sets which exhibit common functionality within the cluster but distinct from the other clusters.

In a nutshell, an innocuous looking survey question holds the potential to provide a wealth of information - if only we can see the magic in the numbers.

Voice of the Customer

This is an exhaustive subject in itself - to determine the elusive customer and then figure their voice. In many B2C cases where we have ourselves been customers of a similar product its easy to relate to and determine ways and means to identify their needs. In a lot of B2B cases, this gets tricky as access to customer base or knowledge of it is limited. Plus competitor analysis becomes hard as the data on other products is guarded.
So how do we determine the VoC ?
Holistically there are two approaches - Qualitative and Quantitative
Quantitative is relatively easier - metrics and numbers speak for themselves.
Qualitative analysis is challenging but interesting at the same time. It relies on our ability to elicit and interpret the data to then frame and cluster it.
Right from field study to focus groups to surveys there are various approaches which are non obtrusive and each suitable for a different desired outcome.
Having created surveys on numerous projects, here's some key information on the same. Surveys provide great metrics as well as key quantitative insights we are looking for however the genre plays a vital role. With constant mobile distractions and a fast paced life, surveys need persuasion from the word go. In one of the surveys sent, we experimented with an alluring subject line ( in the email invite ) and the response went up 80 %. Then there needs to be enough of a motivation ( in majority of cases a financial benefit ) to complete the survey. The survey itself needs to be short and sweet, after all who has the time to tell us their entire life story. So a survey has to have one or two distinct objectives and about 10 questions ( the less the better ) around the same. Then comes the format of the questions - do we keep it open ended or multiple choice, your guess is as good as mine. Open ended questions do gather lot of valuable information but need to be used sparsely so as not to scare the user away, they don't have anything to lose if the survey is abandoned.

Here's an apt but hilarious way to illustrate how important it is to frame the question right. At times the question is so long and complicated or ambiguous that even the options don't make sense. But survey insights do provide a lot of critical mass data which enables to take data driven decisions.

However surveys as with all other forms of customer research have the risk of being proven false. This is because the customers are quirky, they say one thing and often end up doing another. That's the gap being stated intent and actual behaviour. Hence constant experimentation and refinement is the key, this has to be an ongoing activity to always be on the top of our game and enable value add from this activity.

Roles & Responsibilities

Every project team goes through the standard team stages - forming , storming, norming, performing and adjourning stages and each stage has its significance. However the foundations are laid by the forming stage and it is this stage that has the maximum ambiguity in terms of who is going to do what. If the stage is set up well , it saves all the confusion and hurdles later on like "we assumed you would be doing this ... " or " we thought this is your responsibility .. " etc.

Conducting stakeholder analysis and RACI documentation is indeed helpful in getting everyone onboard with what the project roles and expectations are. And its not just helpful with the core project team but even the support team ( or external entities ) which might be consulted on the project and be required as and when needed. 

Its not only the executing team that faces this issue, its even in the project / product being worked on. Business Process Modeling is not given as much importance as it should. After all the product / project success depends on the seamless flow of data from one entity ( role ) to another and identifying the roles and actions is crucial to understanding which teams are impacted or need to be communicated. Swim lanes seem pretty simple but as far more effective if done right. They ensure we haven't missed any stakeholders and the data handshakes are understood by all.

The fall out of not including the right roles and their tasks at the outset, could vary from very serious to moderate consequences but in all cases it pushes the project into a fire fighting mode during / after completion with people running against the clock and budget to fix the misses. The last minute surprises not only dislodge the project, it also could lead to reduced output quality as hasty fixes / band aid solutions are strapped on without rigorous testing. 

A miss could also be as simple as not keeping the impacted role in the loop which means they don't understand what needs to be done , when , where and why. Communications plays a vital role - a successful project always has open channels of communication, a visible dashboard to track progress and clear release plans , release notes as well as defined post implementation support.

Post implementation plan is most often the most neglected part of any project undertaking. Everyone is so focused on getting the product / project out of the door that they forget to consider what needs to happen when its actually out of the door. Admin / support staff is identified at the last minute and given little to no training which means they scramble around to provide customer support. Which is why the project was undertaken in the first place - to enhance the customer experience or add value to existing processes / features.

So in the end the project is as successful as the team behind its steering wheel and if the right people are involved in it from the start its highly unlikely to go offtrack.

Product complexity

The last blog on scope creep  naturally lead to this one. One of the primary reasons we have scope creep is that more and more features are thrusted onto the product with an expectation to deliver in a very short span of time. There are completely valid reasons why certain enhancements or changes need to be done asap, gaining a competitive edge being one of them. But then there are some unreasonable justifications like the team has bandwidth or we need more engagement.

A product needs to certainly grow in terms of its offerings with time, but the basic question is : are the new features being added, relevant to the core of the product ? In other terms, are they in any ways enhancing the customer experience ? The following graph explains it so well, I'll let it do the talking : 

Graph credit : Kathy Sierra

The product team always has an inside out perspective, we know too much and hence we assume too much. We know how the data flows and its very obvious what actions the users should take. But with more features, comes more choices for the user or 'decision overload'. It could very well be that the users are very satisfied with the current state of working and are using the product for its simplicity, making it more complicated than it needs to be could be counter productive.

Then there is also inter system complexity that needs to be taken into account. With data aggregation and a single consolidated view for the user, the product would be integrating with n systems in the back end. Without thorough systems analysis & integration done, we end up in a soup of non synced or inaccurate data and then spend a lot more effort and budget fixing those leaking taps. The advantage of having smaller multiple systems is that each performs a specific function standalone and it makes it easier to plug into another similar system down the road. It also reduces the reliance on one particular system. But they are need to work like a well oiled machine for the product to run smoothly.

Also with hundreds of products being released into the market every single day, the only way a product can sustain the competition is to meet the complex user needs in a simple way. If the needs are simple enough, the user could do it manually / semi-manually or use existing products to do so. So the need / problem needs to be complex enough to be worth solving but the solution can't be complex else the users would need be trained to use it ( like aviation pilots ) and that would limit the reach. Also if we follow the lean principles, it should be just minimal features to test the waters. Business Owners get excited from day 1 and have an elaborate list of features they want to incorporate which makes it a shaky start. It's great to have a product vision, but implement in manageable chunks.

 So to summarize, product complexity is very much required for the product to be of value however the challenge lies in shielding the complexity from the users ( end users as well as back end users ).