Specstra: My Experiments in UI Automation to Extract CSS, Assets from Design Files

This is a proof-of-concept /experimental exploratory project I was spending my weekends during 2013-15 to come up with a cloud based tool that allows designers & developers in quickly getting assets, CSS and element details like position, dimension, shapes, raster, text formatting info etc. from the design file/screen mockups easily without them required to have installed Adobe Software suits like Photoshop.

The major challenges I faced were in reading the Adobe proprietary file formats like PSD to extract separate information on design elements specially the fonts and getting formatting information without using any of the Adobe technology available. Invented many workarounds and implemented them in an assembly line kind of architecture (i.e. chain of responsibility design pattern) to ensure that multiple design file uploads (each one having file sizes from few hundred MBs to 1 GB ) are processed successfully without crashing or over burdening the cloud system. Also the implementation required the necessary image processing tasks to achieve certain goals like creation and export of assets in specific resolution and rendering the red-lines on the fly.

The technologies used were: PHP, MySQL, Python, Perl, Ruby, Shell Scripting, HTML5, CSS3, JavaScript, Canvas & Node.

FEATURES:

Extract design info from a PSD comp to use with HTML & Native App projects like mobile and desktop designs, with Specstra.

Cloud based – Single dashboard to manage all design files.

Export design elements / assets e.g Raster (PNG,JPG) , Vectors (SVG), CSS

Dynamic selection of design elements/assets from the file.

Detects nested vector shapes, text objects, images/raster from the design file.

Detects color palette from the design file.

Specstra

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What the failure of Google Glass teaches about UX?

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In mid of January I saw the headlines making official announcement of the detah of Google Glass. I was not surprised. I knew lot of issues ave to be addressed before Gass could make it to the expectations. Many of them are issues related to UX. All of them related to an grey area of UX space, which was never given the prime consideration when designing a seminal product like Glass and many other legends.
Back in 2013, I had wrote a few posts on the usability in context to the social aspect of Google Glass that was being ignored. When I read now the article saying “privacy concerns” is one of many reasons of failure, it certainly louds the many of the design approach concerns I had raised.

Google Glass is not evil product, everyone agrees. Even all agree that it has immense potential. However, it certainly needs a facelift from product design point of view — and there by from UX point of view.

We saw, the raise and fall of Google Glass carrying it’s pattern where we can notice how with the emergence of Google Glass, the topics related to devices infringing with personal privacy became hot cakes for tech-debates. Many social scientists, human rights activists had started to see the ‘Glass’ as the evil that reminds them with George Orwell’s ‘1984’. The fear of a ‘Google Big Brother’ controlling the major shares of the information world is seen as the intruder to private aspects of ‘the public’. The “Glass Hole” incarnation of the Glass is equally seminal as the product “Glass” it self, due to bring out the topics like “user privacy”, “social context” and certainly what I believe as the “Context of the Other”.

It is not the case that Google has not spent money on user research and usability aspects before going ahead with the concept of persons using glass that may change the way we interact with systems in our daily life. Usability wise, it is definitely a super gadget that has the potential to catapult the device industry into next century. But the new features and interaction methods implemented in the device in a manner that is actually a decade old approach that is only fit for human-computer-interaction (HCI) in case of smart phones and tablets which have less tendency to hurt sentiments of those who do not directly interact with the device when the user might be performing some actions in a certain socio-cultural context. These sentiments could result in the fear of losing privacy , cultural distrust and humiliation among the second-hand users of the device who are impacted indirectly in some way by the device actions in the context.

Historically, the product design process while following the check and balances with heuristics and usability models, has never given prime importance to the user’s relationship to the ‘Other’ in his environment. And this is the missing piece that needs to be re-discovered and fit into standard usability matrix when Google might give “Glass” a face-lift to bring it back with a new incarnation that is more friendly and less intruder to user’s privacy and is compatible with SX model (Socio-cultural Usability Model) which I had proposed earlier.

Socio-Cultural User Experience (SX) – the missing piece in UX


‘Socio-Cultural User Experience to represent the aspect of Usability Design or User Experience (UX) that deals with usability aspect of products/ software in a social context. This is the same “Context of Other”

Considering the ‘Others’ in the User’s Social circle:

The existing UX model does not analyze the need beyond the current user and his ‘type’ to do a usability test — it never considers how it is impacting the other members of the society while the target user set is using the app/system.
For example, using car horn is a safety measure, but using it near a hospital or school is considered as unsocial and disturbing. There are many social check points that bar users of any system from using it in special socio logical context.

Criteria of a Good ‘SX’ Compatible System

Criteria of a sound usability design of an app on socio-cultural context:

1. Universal—has design elements that are universal.
2. Ethical – follows principles and approach that has positive ethical value
3. Non-racial – non biased and non-provocative attitude to user’s race and beliefs.
Socio-cultural User Experience (SX) and Social Interaction Design (SxD)
4. Respectful – towards user’s culture, social beliefs and ethnicity
5. Safety – has it’s social impact that is safe for the User.
6. Non-abusive – must not exploit the user and the environment he is in .
7. Common Sense – has geared towards common sense – behaves and reacts to the user in a sensible way
8. Protect Privacy – App’s feature and interaction must protect user’s privacy and other humans in the social circle.

Let’s take the case of Google Glass.

Google Glass is designed in a way that can act as more personal than a mobile handset, as it is a spectacle and can be indispensable accessory for the user once he gets addicted to it by replacing his conventional glass with it.
But the support for camera to take picture can pose a problem for the user to enter private areas, industrial areas, secure zones and offices where cameras are not allowed. In some places of earth, the cultural restrictions are in practice to ban cameras in certain places — most of the temples in India do not allow cameras inside. Now imagine, if the user has replaced his traditional spectacle for it , then he may find it difficult to manage without it in these scenarios.
So by following SX approach in usability design, the glass will require to have a “detachable set of camera” used in the glass so that the user can detach the camera and which would power it off and at the same time allow the user to keep on using the glass as a conventional spectacle.
This example may be just one of many features that Google glass might have, but it is enough to illustrate the approach in thought.

Points to Focus on while designing a SxD Compatible System

1. Provide multiple alternatives to the interaction methods to control the same functionalities in different socio-cultural context.
2. User should have total control over enable/disable of interaction methods for different scenarios.
3. The default interaction method must follow ‘SX’ approach.
4. Provide options to the user to switch between interaction methods with the system as and when needed.
5. Alternative mechanisms should be provided for physically challenged users. Rethink on the use of gestures and other interaction methods in the Article 508 context as everyday the new devices with unpredictable (not necessarily negative!) interaction methods and features.

Gesture and other Interaction Medium of SxD:

The ‘Social Interaction Design’ approach has the following major facets in the system interaction towards the user in socio-usability context:
1. Facial Gestures—The selection of Human triggered facial gestures (e.g. wink, smile etc.) to activate the system or trigger any action in the system must be judged based on the canonical meaning of those gestures in social and cultural context of the user where he is going to use it. For example, in case of Google Glass , the feature of “winking” (the gesture developed by Google Glass developer Mike DiGiovanni http://news.cnet.com/8301-1023_3-57582500-93/google-glass-code-lets-you-snap-a-photo-with-a-wink/ ) at someone to take a photo can pose a problem if the user is in India or Middle East countries. Even in western world winking at a lady or group of ladies (even though it is unintentional for any kind of abasement) can be taken as a negative action (e.g. weakness in character) and evoke anger and misunderstanding. So even if the winking to take a feature is a ‘cool feature’, in social context SxD will suggest the usability/interaction engineer to rethink on it to implement some options to ‘keep it disabled by default and allow the user the total freedom to use his judgment to enable and use the feature in any given socio-cultural context. Fig5: The ‘wink’ gesture developed by Google Glass developer Mike DiGiovann allows user to take a snap of the surrounding with just a wink of an eye.

2. Sound Gestures — The selection of sound gestures – the use of voice or sound pattern to control the system should be examined for different user environments. For example blowing a whistle to activate a play functionality on a portable music player, or to open an SMS on the cell phone can be an interesting feature, but on the other hand if it becomes useless in a busy street or in a meeting room where a discussion is going on.
3. Touch based Gestures – Touch, swipe and pinch are popular now a days as most of the tablets and smartphones offer this as a user friendly interaction method for the user. More devices are coming up which do not have any physical button rather a few multi-touch gestures are enough to fully control them. However ‘SxD’ stresses that the devices must be designed and developed with the interaction method that can allow alternative to the available touch triggered interaction mechanism. For example , while developing a digital medical instrument with touch sensitive display, the interaction methods should be carefully planned so that the surgeon can use the system without touching to avoid infections through contact with it while conducting any mission critical surgery.
4. Hand/Finger based 3D gestures – ‘SxD’ approach encourages to conduct a social analysis of the hand/finger based gestures that are planned to be used in a system – the gestures should selected / innovated by carefully studying the cultural context avoiding common gestures used in daily life that are considered abusive to others. In addition to this practical usage resulting out of user’s environment and work culture must be given consideration. For example the middle finger gesture commonly used by youths to represent the crack humiliating pun on the other should not be used for any app that is expected to be popular among the users from the similar demography. But note that only considering the demography is not enough to decide the gestures.
5. Mouse /Keyboard Control – Similar to the gesture , voice and the related interaction method with system, mouse, keyboard, joystick and other typical input device based methods should be considered with in the context in which they are going to be used. As this group of interaction method are very old, many standard guidelines are already in there in practice. They However we need to rethink on them and make sure they are upto date with the ever changing human –computer-interaction domain.

Our world needs products that are not only usable but also safe to use socially . It is high time, we need to consider the “Other” in our social context to improve the products and there by our future.

This is a rediscovery of "Accessibility" in the world of touch-screens and other natural interfaces. With new technology innovation the lines between accessibility technology and Technology for Mass are getting blurred. What used to be a special need is becoming a general need for mass use.Situational Disabilities Use-cases are defining the new age devices, wearable & smart interfaces. High time we need to rediscover on "accessibility" what we think we have already discovered!

Rediscovering Accessibility for Future Tech!

This is a rediscovery of “Accessibility” in the world of touch-screens and other natural interfaces. With new technology innovation the lines between accessibility technology and Technology for Mass are getting blurred. What used to be a special need is becoming a general need for mass use.Situational Disabilities Use-cases are defining the new age devices, wearable & smart interfaces.

High time we need to rediscover on “accessibility” what we think we have already discovered!

Linearity matters in ecommerce UI

Linearity Matters: Rethinking eCommerce UI

“Linearity” plays a strong role when it comes to usability of any e-commerce checkout. Many theories supporting this concept have been proved by numerous statistics. UX sites which talks about the best practices to follow while designing the checkout process, always advocate maintaining linearity. It’s make sense when we see multiple principles in human factors indicate that in most of the time when users are “walking on the path” in a multi-step process they want to move forward. But only designing the checkout process is not enough, as from the views of typical goal oriented design, the whole experience of shopping starts with user’s objective to “find something that might influence him enough to buy”where the whole experience is a flow-state which maps to the mental model of the user where “finding” and “buying” are the major component of buying. The former being the “cause” and the latter being the “effect”, the design of the experience should always be linear in order to avoid the situation where the user is distracted by something else to break that state.

If users think of your multi-step process as a straight path, then the sequence of your views must be linear else you will break people’s expectations that will result into a bad experience and usability.

Traversing from user needs the towards the task flow

“I need” –> “I buy”–> checkout

is equivalent to

“I need” –> “I find it ” –> “I buy”–> checkout

is equivalent to

“I need” –> “I browse for it ” –> “I search for it ” –> “I buy” –> checkout

is equivalent to

“I need” –> “I browse for it ” –> “I search for it ” –> I compare –> “I buy” –> checkout

There are two major task clusters now:

1. “I need” –> “I browse for it ” –> “I search for it ” –> I compare –> “I buy”

2. “checkout”

Note the goal stating “I buy”, is the logical point that is represented by the behaviour of the user through the act of “adding to basket/cart”

Meanwhile the act of comparison of the products can be spanned from what is in the browsable and searchable views and what is already existing in the cart (which the user has added to the card already through a previous loop in this category of task). It is similar to the way that you might have added a deodorant “Old Spice” to the cart and suddenly decided to go for an “Axe” that offers 10% extra in the same price (Note that the user’s mind wanders 30% of time). So it helps to allow the user to be in the loop with in the first task group and then jump to the checkout while making the transition to checkout seamless. In order to achieve, the more the mental model matches to the conceptual one and indicate the user’s state in the flow and encouraging him through “progression” in the linearity path.

Here is a sample flow that takes the benefit of the linearity as a part of the process for the experience that covers the pre-checkout and checkout process to complete the flow state.

The target of the solution is primarily a tablet, which is acting as a catalyst as being a touch enabled swipe gesture controlled device it provides the user the effortless approach to move between the “browse/Search” <–> Cart <–> Checkout , once he has reached the entry point to the system.

Explore the complete project at
https://www.behance.net/gallery/19044315/Flip-the-Cart-Reimagining-Social-Commerce

(c) 2014, Samir Dash. All rights reserved.

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Flip the Cart! : Reimagining Next in eCommerce

eCommerce has one of the strongest buzz that we come across now a days. Specially after the success of Amazon and Flipkart, the domain is seen as a goldmine that can help in bringing the disruptive business models to increase profit and business. So what is the next in eCommerce? I tried to conceptualise and re-imagine it from a socio-integrated experience. Following are some insights and sample sides that present those attempts:

 

Find the complete idea here:

https://www.behance.net/gallery/19044315/Flip-the-Cart-Reimagining-Social-Commerce

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

MakingSense: Reimagining the Next-generation Retails and e-Commerce Analytics platform

journey-consumerbenefits

 

 

In today’s ever changing world if we need to reimagine the next generation analytics platform for retail and e-commerce market, what it will look like? Well I gave it a go . Following is a conceptual framework (I call it  “MakingSense”) and a business case for an IoT based real time analytics framework for retail and FMCG market. The following post is presented as a real life business case:

 

 

 

 

Overview:

MakingSense” is IoT based market analytics platform to connect all goods and products (specially non-digital goods) that behave as fast moving goods to the cloud-analytics to get real-time market insights to make the required course correction for the market strategy and business decisions for the product manufacturers and retail chains. This enables a direct feedback model between the consumers with the producers and sellers.

 

The problem it solves:

As per current market trends, even high-tech goods like mobiles, digital accessories are behaving like FMCG in market. Rapid change is evident in consumer behaviour due to influence from technology, economy and changing buying power of the consumer . Speedy ‘go-to-market’ approach in the market from players in the market has increased the competition. Many local and niche competitors are giving tough challenges to bigger players in all segments, specially in emerging markets. For globl players the typical market strategy is not working in expected way. Traditional approach of market insights collection is not sufficient to apply the necessary check and balance for market plans in real time.

 

The 4 core needs that Making Sense will address are:

1.The manufacturers need market insights in real time

2.The consumer behaviour towards tech-goods is also needs to be tracked in real time to ensure how close they are behaving to the FMCG market behaviour.

3.In retail and non-tech sector the real time insights are needed for goods that are not digitally connected to analytics eco-system

4.Need to look beyond the traditional field immersions, surveys to get micro-insights for course corrections in strategy.

 

The solution and the business model:

The “MakingSense” platform will help product manufactures and retailers in gathering real time customer insights even for non-digital goods and helps adjust the customer retention dynamics . In retail and non-tech sector the real time insights are needed for goods that are not digitally connected to analytics eco-system. Need to look beyond the traditional field immersions, surveys to get micro-insights for course corrections in strategy.

The platform has self sustainable business model that will make it grow though benefiting the product manufacturers, retailers and the consumers. The final envisioned eco-system will have a big-data enabled management module in cloud, a super easy to use dashboard system for product manufacturers, retailers and consumers and mobile apps and easy integration public APIs along with one SMS enabled gateway.
The producers and sellers can register their products to generate specific code to their products category and if required can use the APIs to map their existing bar-code systems. The normal consumer can register themselves to generate the reward points and to be used directly in the registered retail chains or can redeem for some gifts from their dashboard itself.

The eco-system will allow the product companies and sellers to get real time analytics through creating data points directly.

 

 

Triple advantage benefits for consumers:
The incentivise/rewarding consumers for their feedback is what will make it more successful.
Whether the product the consumer gives feedback on is purchased from the registered retailer or not, he is definitely getting the reward points or freebies from the site.
If he purchases the product from the registered retailers, then he is getting additional discounts or reward points.
On top of it if the product manufacturer registers, then the customer is getting more discounts!

It’s a triple advantage for the customer.

Now, this is a new strategy where the customer is prompted to buy the product from specific manufacturer, from a specific retailers toget advantage of this.
While the whole aim is to get feedback and analytics running, this model also induces a new competition on product manufacturers to provide discounts to bring down the final competitive price to retain customers at the same time the customer is also getting benefitted.

This model is disruptive in nature where every one is getting benefited :

Manufacturer and Retailers – reduction in market research spending , getting real time-analytics — the mood of the segment- customer retention strategy formulation , attract customer to their outlets and
Consumer — reduction in home budget, get incentive, rewards for their feedback.

 

 

 

::Idea::

 

The “MakingSense” platform will help product manufactures and retailers in gathering real time customer insights in real time even for non-digital goods. In retail and non-tech sector the real time insights are needed for goods that are not digitally connected to analytics eco-system. Need to look beyond the traditional field immersions, surveys to get micro-insights for course corrections in strategy.

The platform has self sustainable business model that will make it grow though benefiting the product manufacturers, retailers and the consumers. The final envisioned eco-system will have a big-data enabled management module in cloud, a super easy to use dashboard system for product manufacturers, retailers and consumers and mobile apps and easy integration public APIs along with one SMS enabled gateway.

The producers and sellers can register their products to generate specific code to their products category and if required can use the APIs to map their existing bar-code systems. The normal consumer can register themselves to generate the reward points and to be used directly in the registered retail chains or can redeem for some gifts from their dashboard itself.

The eco-system will allow the product companies and sellers to get real time analytics through creating data points directly

:: Architecture:

The idea is about building an eco-system in multiple-phases that will have three components:

1. “MakingSense SmartCloud” — Cloud based server to store the data related to the consumers and host the analytic platform. This will have the following major components :
i. BigData analytic-engine that can do the necessary data mining to understand trends and formulate recommendations .

ii. Open REST APIs providing easy way to integrate third-party systems such as retail-management systems, third-party analytic and business process tools/apps.

iii. user management modules with different levels of access to different roles.

iv. Reward points management and coupon code management system.

v. Payment gateway and subscription and vendor management.

2.”MakingSense Portal” — Web-based portal/ thin-client solution that will allow consumers and product sellers/retailers who can register and access their respective dashboards

3. “Making-Sense client” — This is primarily mobile/device client and consumer facing service gateways (and optionally hardware) that can be used by the consumers to submit their feedback.
In the multi-phased development roadmap, initially the mobile apps will be primary representative of this section. Later phases will introduce SMS enabled gateways, custom “MakingSense” hardware, which will be cheap yet provide easier way to share data from the consumer.

 

:: User Journeys:

For Sellers (Retailers/Producers)-

1. gets account registered at ‘MakingSense Portal’.
2. get API if to connect to their card scanners /billing machines/users db/inventory/product catalog
3. gets products mapped to “Reward points”/discounts/freebies
4. product manufacture can offer discounts for their product using the API by registring their product

5.product manufacture can register their product to get insight for their product across globe
6.retailers get insight for their retails chains –anything sold though their system
7.retailers can buy insights (not customer details ) for other regions/ segments
8. product manufacturers can buy insights (not customer details) for competing brands and similar products

For Consumer –

1. Registers at the Portal — if he is from a retailer’s database, he can map his account to this system.
2. Connection to his SNS account (facebook) is encouraged (with some additional reward for it)
2. downloads free “makingsense” mobile app, and starts using
3. scan the barcode of any product he purchased and rates the product.
4. For each feedback on different (at least different batch of same product with in a specific time period range) the products, gets “reward points” or discounts codes or freebies coupon codes.
5. If retailers/product manufacturer has sponsored rewards, based on accumulated points, he can redeem them at their store. Else these can be redeemed at the “makingSense” dashboard at the portal.

:: Benefit:

For Sellers (Retailers/Producers)-

emerging market is the next potential
even high tech/high end goods are behaving like FMCG goods…
micro -insights are required to plan the market startegy adjustment
conventional type of large scale survey’s are not going to help much due to high cost and field immersion efforts and time.. — go-to-market is accelerating so ..time has value … micromax makes a phone in 70 days

So new age trend is required to gather data in real time ..to connect goods that are not even digital , we need those data
IoT will help in rapidly accessing this.

They get the following insight from the solution:

customer’s insight
————
who bought
how many times bought
which part of the year bought the most
consumer’s insight
—————————
liked? great – good – bad ?
what else he likes in the same product line ?
what similar product he uses?
what similar product he likes most ? what brands?
collective consumer insights
—————————-
how many such buyers are in the region who are potential buyer?
how is collective preference?

predictive market forecast
—————————-
in which part of the year the product consumption is going to increase — manufacture more and ensure smooth shelf-space management
who are competitor brands
how a product is behaving in a segment?
value curve?
what should be the status?

if connects to his SNS account/FB/retail shopers card — then u get location, age, gender, type etc. — new gold mine where every one will want to invest.

For Consumer –

1. Consumer is rewarded for any feedback he shares for any product he uses.
2. Apart from regular discounts, reward points the customer can get these additional discounts in purchase/freebies which can bring customer delight leading to more involvement and customer engagement (so no matter if consumer does not buy from registered retailers or products.)

 

 

 

 

 

:: Business model::

Business model is mostly through subscription based to access competitor analytics
Along with it the access to premium data and value added services like (customizable report, goal alignment, market strategy etc. ) can be a major source of revenue .

retailers get 100% discounts to access their data — all real time
retailers get 20-30% discount in viewing their competitor’s data in the same region or segment

retailers not listed in the program to have to pay full to get data for a segment
retailers not listed in the program can not view their data

consumer gets 2% bonus discounts or points to submit the feedback on every item he uses

 

 

:: Market Size::

As per ESOMAR Global Market Research conducted in 2011:

Global Spending on Market Research is 32 Billion USD.
Out of this Emerging Market share is 24% == 8 Billion USD
Out of this only Asia Pacific spending is == 5 Billion USD.

India & China are major share holders of 5 Billion USD
India == 40% of 5 Billion USD = 2 Billion USD

Based this 1st year
target in five 1st tier cities.
assuming 30% investment is done in these 5 cities == 0.6 Billion USD
assuming we get 30% of this share in 1st year == 0.2 Billion USD

That results in 100 Cr INR Revenue in 1st year .

 

 

 

:: Potential competitors & Competitive advantage of the idea::


Amazon Dash
Dash is a product by Amazon that allows to facilitate the consumer to order new products from Amazon store

 

 

Dash:

Hardware based + amazon portal is available for consumer to buy
Only limited to Amamzon portal
No-whitelabelled system — Amamzon uses it for it’s own usage.
It’s is NOT a feedback based model, the bigdata only shows which segment is purchasing which product.

 

Making Sense:

Special marketing-insight platform – unique and first of it’s kind.
Specially designed to handle multiple vendors, retailers and consumers along with reward points/incentive management model .
Unique analytics with predictive strategy formation
works across cross platform, outlets, cross multi-channecommercialal platforms both counter based or online.

 

SWOT  Analysis

Strength: 

Cross platform – mobile, tablet, PC, kosk, custom hardware
works across cross platform, outlets, cross multi-channel commerceial platforms both counter based or online.
Can appeal to consumers, retailer, manufacturers

Can be scaled from FMCG to insurance, banking/finance sectors.
Weakness:
New concept, new to the market — disruptive business model for market research where customers are incentivised for their feedback directly.
Requires fund to maintain the incentives/ rewards for the end-consumers.
Large scale imkplementation can bring meaningful results??????
Opportunities:
New unique business model.
Regional market is drib\ven by fragmented retail / distribution channels
Specially FMCG market is highly un-organised
Penetration of single super markets, and online selling is low.
Specially in India the coverage of super markets (Big Baazar, )
Market insights
Threats:
Dash making it’s platform focused on marketing research
Marketing research companies replicating this model– alternative models
Retail chains making their own platform — will get limited view only only their customers..still they need to spend more in their marketing agencies.

 

 

:: Why it’s a killer Idea? ::

The incentivise/rewarding consumers for their feedback is what will make it more successful.
Whether the product the consumer gives feedback on is purchased from the registered retailer or not, he is definitely getting the reward points or freebies from the site.
If he purchases the product from the registered retailers, then he is getting additional discounts or reward points.
On top of it if the product manufacturer registers, then the customer is getting more discounts!

It’s a tripple advantage for the customer.

Now, this is a new strategy where the customer is prompted to buy the product from specific manufacturer, from a specific retailers toget advantage of this.
While the whole aim is to get feedback and analytics running, this model also induces a new competition on product manufacturers to provide discounts to bring down the final competitive price to retain customers at the same time the customer is also getting benefitted.

This model is disruptive in nature where every one is getting benefited :

Manufacturer and Retailers – reduction in market research spending , gettingf realtime analytics — the mood of the segment- customer retaintion strategy formulation , attaract customer to their outlets and
Consumer — reduction in home budghet, get incentive, rewards for their feedback.

 

 

 

As per Tim Ambler of London Business School, “Marketing Productivity” is measured through the following 5 ponts :

1. routinely research consumer beavior?

2. routinely report research with financial matrics?

3. compare results with previously forecasted in business plans

4. compare with level achieved by your competitor using the same indicators?

5. adjust short term performance?

 

All of these are taken care in the  blue print of “MakingSense”

 

 

 

 

 

 

 

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Indoor Mapping in Consumer or Retail Vertical and it’s impact on UX

Mapping and localization for indoor mapping is gaining momentum in consumer verticals of IT and software services industry to propose new age technological solutions and process re-engineering services that helps in providing value added features to the consumers of the verticals. Also the consumer data mining and data analytics are pushing new dimensions with the indoor mapping technologies to provide new insights into the consumer and end-users’ psyche. This ultimately opening doors to provide better and delightful user experience for the user during his shopping experiences.

 

Technology Used for Indoor Maps

 

Despite the fact that the location determination of mobile users within a building has attracted much attention lately due to its many applications in mobile networking including network intrusion detection problems, it is challenging due to the complexities of the indoor radio propagation characteristics exacerbated by the mobility of the user. Global navigation satellite systems (GPS or GNSS, which act as the benchmark for the standard Map related applications development, are generally not suitable to establish indoor locations, since microwaves will be attenuated and scattered by roofs, walls and other objects. Due to the signal attenuation caused by construction materials, the satellite based Global Positioning System (GPS) loses significant power indoors affecting the required coverage for receivers by at least for satellites. In addition to this, the multiple reflections at surfaces cause multi-path propagation serving for uncontrollable errors. So the most popular among the technologies that are employed for indoor mapping scenario is the wireless technologies like Wifi and RFID.

In Radio-Frequency identification (RFID) systems, the simple concept of location indexing and presence reporting for tagged objects are used, that only acts as the object identification. Typically RFIDs do not report the signal strengths and various distances of single tags or of a pulk of tags and do not renew any before known location coordinates of the sensor or current location of any tags. Operability of such approaches requires some narrow passage to prevent from passing by out of range. In Grid concepts, a dense network of low-range receivers may be arranged, e.g. in a grid pattern for economy, throughout the space being observed. Due to the low range, a tagged entity will be identified by only a few close, networked receivers. An identified tag must be within range of the identifying reader, allowing a rough approximation of the tag location. Advanced systems combine visual coverage with a camera grid with the wireless coverage for the rough location.

 

The use enhanced Wi-Fi infrastructure to provide location information actually provides the missing piece that only RFID can not provide. WiFi infrastructure help in establishing more accurate and stable landmarks, which serve to anchor the various partial trajectories. This approach uses Received signal strength indication (RSSI) – that is a measurement of the power level received by sensor. Because radio waves propagate according to the inverse-square law, distance can be approximated based on the relationship between transmitted and received signal strength (the transmission strength is a constant based on the equipment being used), as long as no other errors contribute to faulty results.

 

Once the user and/or the tracking objects are located and tracked for their movement, the resulting data is mapped to the pre-built indoor location map to provide meaningful observations on the user’s location in particular section of indoor space and based on this the shopping experience of the user can be enhanced.

 

Indoor Maps in Consumer or Retail Verticals

During the last few decades, research on localization for exploration and navigation in indoor environments has made significant progress. However this technology was not accessible to the consumers till Google declared “indoor maps” as the future of consumer facing verticals, which successful attempts in utilizing this technology in shopping malls, museum and related public places where the real-time user analytics based on his location inside the shop helped formulating a set of customized offering to the user to make his experience easier and delightful.

IKEA, one of the world’s leading home furnishings company, uses Google indoor maps for improving customer’s experience in navigating the stores that are typically “typically a two level building that ranges in size from 200,000 sq ft to 450,000 sq ft–the average size is approximately 320,000 sq ft” and which typically “can work against” the “IKEA’s goal is to make the customer feel comfortable and in control of their shopping experience” — “People can have a hard time navigating the store. There have been stories of people saying that they feel like we are are purposely keeping them in.We want to make their shopping experience as easy as possible” (Google).

In a typical customer’s experience in a large sized mall, or shopping store can be frustrating, when he “want the option to quickly find their way to a particular product or throughout the store”(Ibidem,1)and this is mostly the consumer sees as the product he “needs”. Whereas the shopper or the store owner’s intention in most cases is to “encourage customers to find items they didn’t know they needed” – which is in fact conflicting with the thought line of the customer that is more inclined towards the self-gratification through the identification of items of his need.

 

 

The common set of expectations that lies among the conflicts of interests between the shop/store owner and the shopper provides the foundation that helps sustaining the user experience of the shopper in such an eco-system. The common set of expectations mostly revolve around the concepts of getting (for shopper)and providing (for shop-owner)the best possible experience. The common mission when equipped with the technology, such as indoor maps, sets the momentum of better usability and at the same time offers avenues for more cash flow for the store owner.

Most of the mall or stores which have implemented indoor mapping technology have been profitable by capitalizing “on the growing population of smartphone users” who can use the technology through their handsets. As of March 2012, over 106 million people in the U.S. owned a smartphone with Apple and Google having market share of 30% and 51% respectively — which shows that a significant mass of the consumers are also depending on mobility as a medium to consume the technology aided services. This fact is itself acting as a catalyst to propel the usage of indoor maps in consumer sector. (comScore, 2012).

 

Keeping the user in-touch during the whole experience

 

One of the successful features of the indoor mapping eco-system is to keep the user informed at every step of his experience and maintain a communication thread between the user and the system. A sample flow is shown below where the two way communication is illustrated.

 

 

The illustration above highlights how a simple two way communication is established between the user (through his app on his mobile) and the indoor mapping backend running and performs the analysis of user location data to execute productive actions that meets the user goals and helps improve the user’s over shopping experience in the store.

(c) 2013-14, Samir Dash

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UX Simplified: Models & Methodologies: Digital Edition [Kindle Edition] ISBN: 978-1-3115-9110-4

My  recent title is available on Kindle for download. This book covers basic models and methodologies that are revolved around User Experience (UX). The discussed topics include User Experience, Information Architecture, User Interface, Usability models, User Centered Design (UCD), User Centered Software Design (UCSD), different Software Lifecycles (SDLC) and how usability models fit into SDLC models.

The details of the book are as follows:

UX Simplified: Models & Methodologies: Digital Edition
by Samir Dash
ISBN: 978-1-3115-9110-4
ASIN: B00LPQ22O0

Kindle Price (US$):$1.87
Kindle Price (INR):Rs. 119.00 includes free international wireless delivery via Amazon Whispernet

http://www.amazon.com/dp/B00LPQ22O0/ref=r_soa_w_d

 

 

UX Simplified: Models & Methodologies: Digital Edition [Kindle Edition] ISBN: 978-1-3115-9110-4

UX Simplified: Models & Methodologies: Digital Edition [Kindle Edition] ISBN: 978-1-3115-9110-4

Major topics included in this book are :

• Why “UX: Simplified”?
o The Diverse Disciplines: The ABCs of UX
o User Experience(UX)
o Information Architecture(IA)
o Interaction Design (IxD)
o User Interface Design (UI)
• Usability and Mental Models: Foundations of UX
o What is Usability?
o System Models
o What is a “Mental Model” exactly?
o Most-likely Mental Model
o Conceptual Model
o Challenges in Usability Measurement and Metrics
o A List of Factors for Generic and Consolidated Usability Model
o Heuristics:Measuring Usability
• Engineering and Design Processes: Usability and User Centric Approach
o Usability Engineering
o User-Centered Systems Design (UCSD)
o Usability Design
o User-Centered Design (UCD)
o Don’t get Confused: UCD vs UCSD
o UCD Models and Process
• Software Development Life Cycle (SDLC): Where and How User Experience Models fit in?
o Software Development Life Cycle (SDLC)
o Waterfall model
o Spiral model
o Iterative Development Model
o Agile development
o Challenges in UX Integration to Different SDLC Models
o Usability Designing Process
o How Usability Design Process Fits in Different Phases of SDLC?
o How UX Fits in Different Models of SDLC?
o Challenges with Agile model of SDLC to implement UX
o Lean UX and Agile Model
• Agile in Usability Design:Without Reference to SDLC
o Usability Designing Process
• Lean UX: Another Agile UX?
o The Beauty of Lean UX: Everything is familiar
o Foundation Stones of Lean UX:
o Lean Startup method: The concept of “Build-Measure-Learn”
o Minimum Viable Product (MVP) – Prototyping at it’s best in Lean Startup Method
o Principles of Lean UX

  • File Size: 1435 KB
  • Print Length: 86 pages
  • Simultaneous Device Usage: Unlimited
  • Sold by: Amazon Digital Services, Inc.
  • Language: English
  • ASIN: B00LPQ22O0