Multi-Channel Commerce & Retailing

For the last decade and a half, we as technology consultants have been spending a lot of time and energy trying to get a bulk of the offline world online. From processes, paperwork, stores, directories to design, commerce, finance and everything that comes in between. And our efforts have borne us some really good fruits.  Thanks to innovation in technology, the world is a whole lot better place today. Technology has eliminated long queues from banks, given us a chance to share our opinions about products and services and created a new world, cross border citizen out of all of us.

But I cannot help but think that all this while we have only been focusing on getting more and more of our offline world, online and have somehow ignored the offline space along the way. Our experience has got us to build a wonderful world online and perhaps its time for us to collect choicest goodies from the online world and get them to the offline stores. Let’s try to crystal gaze and see what could happen, particularly in the retail space, if we turn our Online! World around and start thinking about !enilnO

The Fish Market Days

Before I start talking about the possibilities that lay ahead of us, it might be a good idea to set some context of old style retailing, whose flavour can be seen in today’s fish or flea markets.  When compared to large retail stores, these markets operate in a very different mode, particularly the way they market their products. If you are a regular at any old world market, your hawkers would know you by name. A courtesy greeting will welcome you as soon as you approach them. Most vendors would also know what you usually buy and how much.  As a regular, most people like and avail special discounts on their orders.

Even if you are a not a regular, the way the hawkers try to sell you stuff is quite different.  Some would start yelling out special offers and prices as they see people approaching. Some experienced hawkers can also make out what products you would be interested in, depending on what you are carrying in your shopping bags and try to make personalized offers.

So, what’s the Big Deal?

None of the Fish market selling is rocket science. We have built very superior systems and websites which can make personalized offers to the customers based on their demographic and purchase history.  On some advanced eStores, no two users see the same offers, or even the same search results. Everything is personalized online; we have really cracked this space wide open. But what about the offline world?

Think about your favourite super store for a minute and you’ll realize what I am trying to convey. When a customer goes to HisFavouritySuperStore.com, he is greeted with personalized offers, personalized recommendations, he is able to share opinions and reviews about products and do a lot many interesting things.

Now, when the same customer goes to HisFavouritySuperStore, the experience becomes pathetically trivial! Today Store shoppers are not even greeted by a personalized greeting. Personalized offers and recommendation sounds way too futuristic for now. A regular customer may get a personalized greeting when he approaches the till, but for the other 95% of the time when he is roaming in the store, he is totally on his own.

Some stores try to get around this problem by sending personalized coupons through snail mail.  That does work to some extent, but is that the best that we can do? I believe we have the technology in place today to convert each and every store shelf into a fish market hawker. With a dash of !enilnO thinking, the physical stores can bring a big pie of the online goodness to the brick and mortar world.

Really!!? But, How?

The new world store scenario would have to rely on the personal assistant that they send shopping with every customer in today’s world. The difference is that in the new world, this assistant will do a lot more than just carrying your groceries for you. Yes, I am referring to the erstwhile shopping cart. What we could do is mount every shopping cart with a medium screen display device, the size of your in-dash GPS system with the ability to exchange information with numerous sensors placed throughout the store, in different aisles.

As the customer enters the store and picks up the trolley, he can activate the personal shopping assistant by swiping his club card. Now, as this customer navigates from one aisle to another, sensors placed on these aisles will tell the trolley its present location in the store taxonomy. With a quick exchange of bytes with the central server, the shopping cart can start making personalized offers to the customer based on his past purchase history.
Wait, there’s more! Ever had a customer pick up a new product and wondering if they should give it a try? With a few touches on our new device, customers will be able to access product reviews and ratings with other users and take the unpredictability and guesswork out of their shopping experience.

A shopper’s life can be made so much simple if he does not need to memorize the list of all the products that he needs to buy. In this new world, the shoppers can go to the store’s online website, login using their club card, create a shopping list online, save and logoff. Now, when the pop in to the store and activate our new shopping cart by swiping their club card, their shopping list will be downloaded to the cart’s display device. More creative stores can also map the shopping list to the store’s layout map, telling the shopper where all the items on his shopping list are placed. Voila! The added plus is that since the cart already knows what the customer is going to buy, it can utilize this option for an effective cross and up sell.
Remember those shoppers scrambling from one aisle to another, with a shopping list and pen in their hand? So, 2008-ish!

What are we waiting for?

Your guess is as good as mine! The idea outlined in this post can be implemented with the technology that we have at our hand today. It is very conceivable and does not involve any abracadabra. What seems to be missing from the equation are a few creative stores and technologists who can imagine turning Online! Around 180 degrees to !enilnO.

Posted by Amit Jnagal at 12:42 PM | Permalink | Comments (7) | TrackBacks (0)

It is easy to agree with the need for a performance model, but how do you build one.  Here is one approach that is suited for a transactional site:

You have just decided to replatform your general merchandise eCommerce site.  What should be your first step? 

A lot of companies start by contacting software vendors and build partners , getting quotes, writing detailed requirements, creating new business flows, etc.  While all of these are needed, they miss the most important step, the performance model.  A performance model is simply the number of transactions that must be accommodated, detailed by type, along with the expected response time for each transaction type.  For example, a Home page view is one type, taking an order is another, taking a return order is a third type, etc.  A performance model must be one of the first steps, if not the very first, because without it, everyone who will be involved in engineering the site will be guessing at the size of the task at hand.

Start with the orders/day.  Most companies know how many orders they take every day.  Next, you plot the trend line of orders in 2007 verses orders last year verses orders this year.  This will give you the year over year growth trend.  Using this line, you can create a rough estimate of next year’s and future year’s traffic.  Then factor in anything that will make next year and future years different than the past.  If you are in a recession, you may flatten the trend line some.  If you are investing a lot of money in advertising the site, then you will steepen the line. 

Next, translate orders into that into page views.  The best source of this information is from your Web analytics vendor like Coremetrics or Omniture.  Your own Web server statistics may provide these also.  Armed with this, you will be able to create a ratio of page views/orders.  For example, if you take 2000 orders/day, and serve 2,000,000 page views/day then your ratio would be 1000:1, which means that on average, every time your customers view 1000 pages, they place an order.

Following this, you can project the number of page views/day based on the order data.  A complete model requires additional data like “number of returns” number of order status queries, but those too can be estimated using the historical ratios of returns/order and queries/order.  Once you get the business to bless these numbers, you can contact the vendors of all stripes and provide them with consistent load data from day one.

It is critical to publish this data to everyone involved in the project in order to avoid having multiple estimates floating around.  I have seen projects where each development team was given a different load model.

Posted by Stephen Alan Potts at 11:19 PM | Permalink | Comments (0) | TrackBacks (0)

This post is Part II of a series that discusses the online customer acquisition funnel and how to improve conversion rates.  The customer acquisition funnel is a construct that helps visualize the junctions at which an online portal looses the attention of a visitor. 

A side note about online shopping cart abandonment…  Wouldn’t it be interesting if people behaved the same way in a real store as they do online?  I could imagine people at the grocery store piling a basket high with goods and then for whatever reason just ditching it in an aisle and then running out the store.  Most cases one would think, “What was that all about?!!”.  That’s pretty much what happens in the E-Commerce world, whether it is shopping cart abandonment or at the landing page.

In this post I will be talking mainly about landing pages.  Landing pages are the first thing that a user sees when they access your portal.  This might be your main page, or if you are savvy, it might be a personalized page based on the traffic driver that brought the user to the site.  As a general rule of thumb, you have about 3 seconds to grab the user’s attention before they decide to click the back button.  In analytics terms, the rate of ‘back button pushing’ is called the landing page bounce rate and is defined as (Visitors who leave on landing page) / (Total visitors to landing page). 

Ideally, you would want to have a landing page bounce rate associated with each “high traffic” landing page on your website.  This allows you to get a picture of not only which landing pages are working but which traffic drivers are driving qualified visitors to your site who are interested in the products you are trying to sell.  However, in order to disambiguate the influence of each factor on the bounce rate, it will take a little analytics.

Landing page optimization can loosely be categorized into two classes: 1) Subjective optimization based on design, usability or other bases such as our perception of the users intended goals; and  2) Mathematical optimization based on analytical models and behavioral data.  The most powerful landing page optimization schemes utilize both simultaneously.

I have always found the mathematical optimization portion quite interesting because it allows you to test several different design scenarios on a population of people.  This can produce some very interesting results as populations of human beings can sometimes behave in unanticipated ways.  For instance, you might find that increasing the size of the title font from 16 to 18 on the landing page decreases the bounce rate by 5%.  Does it make any sense? I say no, but it is sure easy to conjecture some reason after you have the answer!

The best way I have found of performing these types of mathematical optimizations is through multivariate statistics.  This class of statistics differs from split A/B testing, which is the testing of two different scenarios during a single experiment, in that it allows you to test multiple variables at one time without a huge magnification in the number of behavioral samples you need to capture.  For instance, you can test the title font height, background color, header image and body text in a single experiment.  Simply speaking, strict A/B testing would require four separate experiments.

The combination of subjective landing page optimization with mathematical optimization allows you to finely tune your landing pages to decrease bounce rates.  It also allows you to disambiguate the influence between a traffic driver and the actual landing page on the bounce rate.  If you then perform these optimization exercises on all of the high-traffic landing pages, a picture begins to emerge as to which design elements are working, which ones are not, which audiences need to see what content and how to best capture their attention.  This then sets you up for being able to personalize content and user experience based on the traffic driver source and other user specific incoming information. 

Since the landing page is the first and largest junction in the ‘Acquisition Funnel’, changes as small as a percent in bounce rate can have dramatic effects on the downstream number of visitors who become engaged in the site.  I can’t stress enough how important it is to get a landing page optimization program in place and get it done correctly.

Posted by Ted Gaubert at 07:08 AM | Permalink | Comments (1) | TrackBacks (0)

Amazingly – or perhaps not – ZenithOptimedia* suggests there was more than $200billion of worldwide advertising waste in 2007 (*Global Advertising Analysis)! Waste is defined as money spent on messages which reached the wrong audience or none at all. Clearly the need for targeted messages integrated across delivery channels is needed now more than ever. With 29% consumers’ time spent online in 2008 but internet advertising representing only 8.5% of total advertising revenue – something has to change.

Already we can see this being taken on board. ‘Adverting Age’ predicts some of the largest advertisers in the US will each shift half their $1billion-plus budgets to digital media in the next 3 years. With such a massive change of emphasis across channels the crucial questions will become the 3 ‘W’s’:

·        When to target?

·        Where to target?

·        Who to target?

These simple questions will keep advertisers awake at night, and form the foundations of all marketing presentations in the years to come.

Traditionally, demographic data has served as the baseline for potential buyers. However this neglects the multiple roles a person can fulfil. As well as being a voting adult of certain gender and location, marital status and credit rating the same person can be a parent, avid gamer, day trader, sports fan, etc. etc. the list is almost endless. Clearly a move from this dated demographic ‘macro-segmentation’ to ‘micro-segmentation’ is essential. To make these new digital advertising budgets effective new solutions will need to supplement current demographic information with data insights to include consumer behaviours and preferences across all channels.

Key to succeeding in this endeavour is the challenge of collection and collation of huge volumes of data across the multiple channels an organisation may operate across. Harnessing this ‘global’ data view will provide the building blocks to assemble highly relevant audiences for the advertising spend, for example:

·        Detailed anonymous profiles with full visibility of an individual

·        Analytics engine

·        Detailed modelling and visualization capability

·        Continuous running and dynamic update of models containing thousands of ‘micro-segments’

·        Real time updates based upon individual behaviour

·        Auto delivery to of campaigns to relevant channels for advertising and content targeting

·        Comprehensive reporting to provide a single, integrated view of the targeting metrics, advertising management, inventory, orders and sales applications.

This will provide a transparency and level of measurement and accuracy not currently possible with today’s limited approach. This will showcase more effective targeting of the advertising spending and provide greater relevance for both content and advertising. This will create a virtuous cycle where successful advertising increases sales and customer loyalty leading in turn to more effective data inputs and follow on advertising spending.

All we can hope is the message behind such large figures - $200billion – is understood loud and clear. In turn as advertising acts upon this ‘wake up’ call we will finally see the promised move towards an effective use of advertising spending across the relevant channels through accurate real-time targeting of content and advertising.

- / -

Accreditation: Paraphrased from original article in Teradata magazine. “On target – Effective advertising centers on insights about consumer behaviour” Tim Bridges, VP Media and Entertainment CGNA.

Posted by Billy Byatt at 06:45 PM | Permalink | Comments (1) | TrackBacks (0)

In the past year, online travel industry faced a lot of challenges globally but amidst all this the best thing that has happened to the Indian online travel industry was the opening of railways reservation APIs by Indian Railways. Currently, OTA (online travel agency) business in India is expected to be approx. $800 million and depends largely on air travel related transactions. Till now, Indian Rail Catering and Tourism Corporation (IRCTC) was the only provider for online train ticket bookings in India but with the Railways opening its inventory for private players this space is ripe for some huge changes this year.

Why this move by Indian Railways is noteworthy?

I believe this will lead to a lot of usability innovation by various travel websites in India and there have been clear cut signals coming from various players in the past 3-4 months to uphold this fact.

Thomas Cook & ClearTrip announced the facilitation of online booking of train tickets in July 2008 and Sep 2008 respectively and yet many more are expected to join the party. (Provided Railways ease the entry restriction criteria and provides the permission to use the APIs).

1. Thomas Cook – became the first travel website to integrate with Indian Railways to provide train ticket bookings online using Railways APIs. They have done a good job and have made the process of booking tickets easier as compared to Railways own website.
2. ClearTrip – cleartrip.com soon joined Thomas Cook and integrated with Indian Railways and along the way it simplified the whole process of online booking than what Indian Railways site offered. Users can see availability of multiple dates together and an availability calendar which we all are used to seeing on many international travel websites like Expedia, Orbitz etc. In my experience, using ClearTrip can save you around 15-20 minutes per transaction where you need to check routes and availability. I would like to classify this as the first wave of usability innovation and expect ClearTrip to maintain its lead in the coming phases.
3. makemytrip.com – Another big player in the Indian Online travel industry and expected to soon compete in this space. Makemytrip.com haven’t launched the online railway booking facility yet but the ‘Coming Soon’ page on their website calls for ideas from the users and I think it is a great idea and a good approach to go about collecting ‘User Generated Requirements’. Train booking can sometimes be a very complicated process with options like break journey, various types of concessions and quota availability in Indian railways.
   
   
   
4. 90di – 90di (expanded to read 90 degree internet) -‘Simple Search for Complex Travel’- also deserves a mention since we are talking about innovation (though they are not using Railways APIs yet and their solution is slightly different). They launched natural language search for travel needs in Aug 2008 and added more features in Oct 2008. They seem to be doing a great job on interpreting natural queries and thus making the train booking process much simpler. Their filters deserve a special mention; for e.g: by having a carrier name in the query automatically filters the results for that carrier. (Check out here). Below are some of the examples of the travel queries which they interpret from their website -

With Indian Railways opening up their APIs, one missing link in the Indian travel eco-system is available now and many more players are expected to provide integrated Train + Flight search functionality which 90di already has on their site but currently without the use of Railways API.

We will see many more sites offering similar functionality this year where you can book Flight, Train, Bus, Cabs and Hotel all together in one single transaction.For now it looks like the Indian Railways APIs are too strict for start-ups which can put a damper on an end to end innovation but start-ups like 90di has a work around for that and are redirecting users to Railways authorized sites for final payment transaction but having successfully offered natural language search and integrated Train + Flight search. I believe such revolutions may very well spark on the interest of the big players (like Expedia, Travelocity, ClearTrip etc.) in start ups who can innovate in this space, which will be good for the industry as a whole.

I am even more excited by the mention of 'e-auction of passanger tickets' in the status repot for IT projects by Centre for Railway Information Systems (CRIS -the IT wing of the Indian Railways). If railways provides APIs for e-auction as well, there will be a lot of changes which can be expected here and this will definitely make it an interesting space to watch out for in the future.

Trivia - A little known fact about 90di is that it was started by 3 ex-Infoscions (2 of them were part of SETLabs). (http://www.90di.com/travel/about/team.html).

Posted by Rockey Nebhwani at 11:12 AM | Permalink | Comments (8) | TrackBacks (0)