Increase your social impact with data

Posted on April 25, 2013 by COI Team

Every day more companies benefit from the data explosion by using data as a product or service. Governmental organizations own large amounts of data that could be used to create new value. In order to increase their social relevance, this ‘hidden’ value should be unlocked by participating in the recently emerging information ecosystems.

Data as a strategic asset
Over the past two decades practically every organization has in some way dealt with digitization, which has led to significant adjustments in business models. Recent developments prove that we are at the beginning of a new digital era. Because of the explosive growth of the number of ‘sensors’ like machines, smartphones and cameras, the amount of structured and unstructured data has grown exponentially. Neelie Kroes (European Commissioner responsible for the Digital Agenda) even calls data the new oil for the digital age.

Every day more organizations find ways to benefit from the fading lines between data collection and distribution. New technologies that convert collected data into valuable assets become more accessible and result in more bang for the buck. By combining internal and external sources, organizations are able to unlock value from the new information ecosystem leading to opportunities beyond your imagination.

Governments are on a great pile of data
Governmental organizations can use information and communications technology to increase efficiency in order to better people’s lives. The Dutch WRR report iOverheid describes the impact of extensive digitization of society and the role of the government. Thanks to the use of IT, the government will transform from an e-Government to an i-Government which is based on data processes like collection, enrichment and distribution of information. A boost for this transformation is the Open Data legislation which is introduced throughout the world. This legislation holds that once government tasks are completed, government data will become public in order to stimulate re-use by other parties. The creation of social value by opening up government data (Open Data) is estimated by the EU at €70 billion. Already in 2009, the US government made the transition to an organization aiming to unlock as much value from data as possible with the Open Government Directive.

Just sitting back and wait for data to be unlocked by others will, in many cases, not suffice for governments to actually create this social value. Governments need to facilitate and interact with other public and private organizations and citizens. Governments from 56 countries already launched a joined platform. A next step would be to create an interactive (Open Data) community stimulating innovation. The latter is under construction in the Netherlands under the government policy regarding top sectors. It can be seen as another incentive for governmental bodies to become active in the data arena. However, government organizations are doubtful about how an active role regarding data should be approached, and, consequently, for which needs and customer groups. In fact, government organizations are actually confronted with a classical positioning question in a whole new ballgame.

Consciously building a position instead of waiting on the sidelines
The success of government organizations is largely determined by their social impact and their visibility in the marketplace. Data provides the opportunity to increase this impact since it can help improve current tasks and/or provide in more needs. Off course, data can also be re-used by other parties. The EU Commission hopes data to be a catalyst for change. By building an external positioning around data, government organizations could focus on specific needs in order to increase their social impact and its visibility.

Nolan, Norton & Co. developed a widely applicable model for governments to build an external positioning based on data. A number of elements are important to build an external positioning based on data.

The first element consists of guiding principles based on the organization’s mission, (ministry-wide) policy goals, values and formal tasks. The second element contains the role that can be chosen. A role describes the way in which information could meet the needs in the market. The optimal role is determined by the market needs (Demand) and the extent to which the market itself can provide in those needs (Supply). The fourth and last element includes all preconditions including legislation and policies.

Four different roles for a governmental organization
The center element on which an external positioning regarding data is based, is the choice of a particular role. Definition of a role is based on two dimensions, the attitude towards fulfillment of needs and the degree of enrichment of the provided data products and services. In other words, the attitude describes ‘how?’ and the degree of data enrichment ‘what?’.

Given the position on the horizontal and vertical axis, four archetypal roles can be identified. Each role describes in behavioral characteristics the way in which the needs in the market are met. Organizations are able to choose a role as ‘Controller’, ‘Connector’, ‘Enricher’ or ‘Entrepreneur’. The choice of a particular role depends on the market demand and the extent to which the market itself can provide in those needs. For each need and each customer group a different role can be considered. In fact, the optimal role could change through time due to dynamics in demand and supply.

It not just a new perspective, it’s a disruption
The development of a traditional organization to an organization in which data is used as a strategic asset confronts organizations with radical changes regarding, strategy, organization, culture and technology. Significant barriers must be overcome like ‘unit’ thinking and the lack of right skills and technological/analytical knowledge. Emphasis should be placed on thinking and acting in ecosystems. This requires both Public-Public as Public-Private Partnerships. Therefore it is advisable to start the positioning on small scale and on experimental basis. By doing so, it can be directly shown that government organizations can increase their social relevance with data. Ready to pick up your game?

More bang for the buck? IT’s possible!

Posted on November 30, 2012 by COI Team

‘We fail to deliver our customers the information they really want.’
‘IT is too expensive and does not live up to its promise.’
‘Almost all of our IT projects overrun on budget and time.’
‘Our systems are slow and not up-to-date.’
‘The only person available to reprogram that system is two months away from retirement.’
‘New technologies emerge too rapidly for us.’

Just some random quotes that probably sound all too familiar to today’s CIO’s and IT decision makers of many organisations.

Over time, many organisations have seen their IT systems grow in terms of size, complexity, level of integration and percentage of the annual budget. The increasing dependence on technology and ever increasing need for information from decision makers and customers has driven investments in hardware (for example storage, processing power, network capabilities) and software (for example ESB, BI). In fact, large investments in IT often cost more than planned. But did these investments really pay off?

Legacy systems not up for the task?
Many investments in IT have not necessarily increased performance, brought more control or mitigated risks. Dependence of critical operations on IT has grown. And, as recent examples in the Dutch banking industry show, the occurrence of downtime and unavailability of services to customers can severely impair organisation’s public image. Furthermore, existing systems require ongoing development and maintenance to operate as desired which drives recurring costs. Many organisations still run legacy systems not as a deliberate choice, but as a bare necessity. On top of that, existing systems are often unable to deal with the data explosion we have witnessed in recent years.

Fortunately, new technologies (e.g. Hadoop, NoSQL class databases such as Mongo and Cassandra) have emerged, enabling both incumbents as well as ‘new kids on the block’ to benefit from the huge amounts of data available to everyone today. To put things into perspective: today, over 250K open-source technologies are considered viable for deployment in the near future. Technologies enabling stream processing (Storm & Kafka), large scale querying (Drill & Dremel), statistical programming (C), graph analysis (Gremlin & Giraph) and analytics platforms (SAP HANA) are considered to be amongst the most promising technologies today. But what makes these technologies so important?

New technologies – new opportunities
Organisations in a wide range of industries are already using these new technologies to shift their playing field. These organisations are competing on information and can leverage the benefits of big data. They use technology to provide services previously unavailable to customers, such as large scale customized deal making, personalized travel advice, personalized rebate coupons and detailed insights into customer’s behaviour. Deployment of these new opportunities requires new technologies and implementation approaches. But what is keeping many organisations from benefitting from these new opportunities?

Many of the traditional technologies primarily supported processes within the organisation or even business unit. Data and information was generated and applied primarily to the benefit of business processes or as a residual of the business processes within each business unit. Accordingly, IT systems and interactions between for instance applications and databases were designed with a strong internal focus. However, this internal focus has proved to be a barrier when trying to provide competitive data driven services and products to customers.

Open up and thou shall find!
Organisations today have to be able to combine information from both inside as well as outside the (fire)walls of their own systems. On various dimensions, the design and deployment of IT systems is likely to change dramatically. Technology architectures will have to open up!

Ecosystem focused; IT systems will no longer be part of the just the enterprise, they are part of an entire ecosystem, in which information necessary to compete is produced outside far more than inside
Loosely coupled; IT systems will no longer be highly integrated, but rather be loosely coupled and relatively easily “distributed?”
Highly scalable; processing power and storage can be increased rapidly and at low costs
Customer oriented; IT systems no longer produce services designed by IT, but services requested by customers
Give AND take; creating information not only for yourself (need to own), but to share with others as well (need to share)

One step at a time
Does the above mean that organisations have to start (re)designing their existing IT systems to reap benefits from these new technologies? Not at all! Like approaches to business model innovation, taking a small stepped approach using methodologies such as agile software development (for instance SCRUM), organisations are able to combine existing data from internal sources with data from the outside world in an incremental fashion. These organisations assign small, multidisciplinary teams that are used as catalysts for the introduction of these new technologies. Experimental use of for instance APIs or parallel distributed computing technologies (such as Hadoop) is a good way to slowly introduce technologies within the organisation. Successful examples of organisations using this approach are emerging as, Disney shows.

In contrast to the large investments required in the past, these new technologies can be introduced at relatively low costs. Many of the technologies are open source and they do not require specific powerful hardware to be run. Through these new technologies, formerly highly integrated IT systems can now be opened up to the world!

Simultaneously powerful and nimble!
With the right approach, every organisation is able to use new technologies and provide new products and services to customers. Small, dedicated, cross-functional teams (consisting of for instance data scientists, marketeers, AND technologists), a careful selection of new technologies and a deliberate, iterative process can provide new opportunities to your organisation. In fact, these new technologies can make your systems more nimble than you’d ever imagine!

From ‘Summer love’ till ‘Death do us part’

Posted on July 20, 2012 by COI Team

Building lifetime customer relationships on relevant marketing information

Have you ever dated anyone who wanted to know everything there is to know about you on the first date? Who was secretly checking your text messages while you weren’t there? Or on the contrary, have you ever been in a relationship where after 20 years you found out you didn’t really know one another because you had nothing in common and never shared any information?

If the answer to any of the questions above is yes, then you might agree that building relationships takes time, trust and effort from both sides to make it work. That being said, doesn’t the same thing apply to building customer relationships? In their eager quests for profits and revenues, many companies tend to forget about the common goals of a customer relationship, causing painful break-ups. Engaging your customer in each step of your relationship by competing on information, may help ending this blind love.

The Customer Engagement Cycle

Be attractive and visible

As with all relationships, there are various phases of customer engagement that all challenge you in your usage of communication and information. It starts with making sure your package is right. Have you thought about what your company has to offer and what you want to get out of your relationship? In other words, have you done some workouts to shape up the value proposition in your business model?

Business model “Be attractive”

Then, there is the question about where to find that perfect date! Instead of waiting for something to happen, why not go where your prospects are? Today’s information society makes it much easier to target the audience you want. Google AdSense, for example, enables you to show your web ad only on those websites that are visited by your target audience. Or consider real time bidding to decide yourself how much a relevant ad impression is worth to you. Also, more and more companies are turning to social advertising in order to get in touch with their prospects.

But, as always, being too desperate might make you unattractive! There is a thin line between being relevant and being intrusive. This is where ‘permission marketing’ might help you out. The Belgian platform Permesso.be, for example, offers a community where customers sign up and list their interest profiles, gaining relevant gifts, discounts and vouchers in return, thus creating a win-win situation.

The art of seduction

So now you’ve found your match (or even better, they have found you)? Then it all comes down to making the right impression, doesn’t it? Sales funnel optimization and personalization of your product or service offerings can improve relevance and make your more eligible to your clients, triggering them to make that first buy. Also, have you thought about the cross- and upsell possibilities to make them feel at ease?

Lego has developed a customer experience model that helps them to create just that perfect experience, asking themselves where they can add positive experience, which points in the process are the tricky ones and what kind of information is needed to make the magic happen.

Growing your relationship and staying valuable

OK Casanova, so you’ve made the deal, delivered the goods and got all the information you need to send the invoice, you’re good to go. Might even send a direct mailing someday or deploy a call center to get some recurring sales. But what if you could grow your relationship to be a lasting one? Apart from the transactional information you’ve got, how well do you really know your customer? Did you ask them how they want to be treated? What their preferred contact channels are? Do you know how you could be of extra service to them?

Based on the customer information you’ve gathered, imagine how data-crunching, profiling and customer segmentation could help you to set up the perfect loyalty program, creating real customer retention. That’ll refrain them from turning to your competitors!

In sickness and in health

Everybody likes to feel special, don’t we? So why not consider going the extra mile sometimes, no strings attached? For example, take a look at KLM, who have recently introduced KLM surprise. By monitoring social media behavior and surprising people with a personal gift they try to make the waiting time in the airport more fun.

But things aren’t always looking bright, off course, and no matter how much effort you put into your delivery, one day you’ll mess up. But hey, doesn’t everyone? It’s not about the fact that you did something wrong, it’s about the way you act to solve it. Might want to take a look at the Dutch 2012 Gouden Oor nominees and the way they have organized their complaint management? After all, would you want to be the “Mr. Perfect” in the following movie?

Thought so.

How convenient!

Posted on June 22, 2012 by COI Team

If you like this, you’ll probably like that as well

After leaving the blue and yellow of an IKEA store behind me, I always find myself puzzled by all the additional stuff they made me purchase. It strikes me how many times during a walk through their one-way maze you see an item and think: “How convenient, I could really use that, I should probably buy it just in case”. When buying a lamp, I always buy the conveniently placed two-pack of light bulbs, although I only need one. And my new wall clock really needs those batteries, and I’m not sure if I still have them at home. I better buy those as well.

Something similar happens online. Take Amazon. When viewing the new biography of Steve Jobs, a list of recommended items, under the header “Customers who bought this item also bought” is shown by the website. I must say, the biographies of Albert Einstein, Richard Branson and Benjamin Franklin also seem like interesting reading material. I usually hop from recommendation to recommendation to find the book(s) I like. It brings you to options you would probably not find on your own. And it makes you buy more stuff, just like IKEA.

Crunching the data for more relevance and personalised experience

How do these companies know what their customers want? How does Google know what I’m searching for after typing in two characters? How does Target know a teen girl is pregnant before her father does? Through data mining: a mix of artificial intelligence, statistics and database systems.

Discovering a strong relationship between purchasing item 1 and item 2 might be very profitable to a convenience store. Wal-Mart takes its recommendation role to the next level. WalMartsLabs, the innovation venture of the organisation, released Shopycat, a Facebook application helping shoppers to skip stressful shopping nightmares and find better gifts for friends and family members. By combining shopping data with social media profiles (filled with ‘likes’ and interests), they recommend a personalised gift advice.

Web advertisements use the same principle. If you are a 28 year old male, who likes travelling, you’re more likely to click on an advertisement for a cheap flight to New York, than a women’s clothing ad. Companies track web users online, and build up a profile based on their behaviour. These profiles of individuals, constantly refreshed, are bought and sold on stock-market-like exchanges.

Advertisers once primarily bought ads on specific Web pages—a car ad on a car site. Now, advertisers are paying a premium to follow people around the Internet, wherever they go, with highly specific marketing messages.

Just visit Exelate’s website, one of the companies involved, to find out what they have collected about you.

But what if you can predict what might happen in the future. What if you could predict a customer’s future behaviour based on his store visits in the last year? Dunnhumby (the lead analytics company for Tesco) ran a competition on Kaggle to predict when supermarket shoppers will next visit the store and how much they will spend. Players were given a data set that included details of every visit made by 100,000 customers over a year from April 2010 to March 31st, 2011. Based on one year’s worth of purchasing data, players had to predict when each of the 100,000 customers would next visit the store, and how much they would spend on that visit. The winning entry was 208% more accurate than the existing benchmark (and earned a Russian professor $ 10,000).

Think about what that means. They can predict, based on our visits (mostly registered by our loyalty card), when we will return to their store. I don’t even know when I will return to the store! And if the model predicts a decline of our visits or spending, they send us a coupon to lure us back into their store. Dunnhumby has already proved its added value through analytics. Mr. Humby, one of the founders, literally wrote the book on it: Scoring Points: How Tesco is winning customer loyalty.

It’s not a coincidence

The next time you find a coupon in your mailbox, or the basil next to the tomatoes, or a relevant advertisement you are about to click while thinking “How convenient!”, just realise it’s not a coincidence, but the result of a comprehensive model created by some gifted data junkies which makes your behaviour part of their equation. Just imagine what could happen in the future when ordering pizza:

“Taking it a few steps further might feel as an invasion of your privacy…”

Ninja skills for business model innovation: Lean, agile & data driven

Posted on May 21, 2012 by COI Team

Companies that want to unlock the value of data by competing on information face the challenge of reinventing their business model around a data driven value proposition. Like a startup, they have to develop a new sustainable and scalable business model. Traditional product and business development practices based on large upfront investments in research and product design and endless development tracks simply will not do. The traditional “waterfall” methodology followed in most large IT projects does not work in today’s highly complex and uncertain business environment. The risks and costs associated with first developing the complete product before testing and releasing it are too high. Moreover, since most data products are web based services instead of physical products, the tools and infrastructures are available today to follow a more iterative and agile development process. More like a ninja…

Successful information driven companies have learned to be more like a ninja, by adopting emerging startup theories like customer development and the business model canvas. This post will outline three steps that can help you innovate your business like Instagram, Pinterest and Facebook do.

1. The big picture: A business model perspective

The first step towards competing on information is often a brainstorm session with different stakeholders to come up with a longlist of possible information based value propositions. From this list a selection is made towards a shortlist of most attractive and feasible opportunities. As the idea funnel further narrows, it becomes more important not to focus on the value proposition in isolation. Instead a broad and holistic business model approach is required to fully understand the potential of the value proposition. The business model canvas is an excellent tool for this, since it forces the people involved to think about all nine building blocks and their interdependence. The information based value proposition is at the core of this business model and needs to answer the question: “what customers’ problem is solved by the information based product of service that the company wants to offer?” The eight other building blocks each have their own specific challenges that need to be addressed in consistency with the value proposition to make the business model successful.

Source: Nolan, Norton & Co. 2012; adopted from Business Model Generation, Osterwalder & Pigneur 2010

2. All guesses, no facts

Once an attractive and feasible business model is drafted around an information based value proposition, it is still nothing more than a set of assumptions on how the new business will deliver value. At this point, we are at the stage of the business model hypothesis. Without realizing that we are at the hypothesis stage, the company can fall in the trap of executing a plan without finding evidence for the assumptions that underlie the plan. The next step in the business model innovation process is therefore to condense a set of testable hypotheses from the business model canvas. These hypotheses describe the most crucial elements of the business model and the biggest “leaps of faith” that were made when drafting the model. In the example below a few important business model hypotheses are listed for the data startup, Fashiolista.

Value proposition hypothesis:

Fashion lovers are willing to collect and share their online fashion discoveries

Revenue model hypotheses:

Fashion vendors are willing to place an affiliate link on the Fashiolista site
Targeted advertising will increase the conversion rate of online fashion shoppers
Third parties are willing to pay for fashion trend reports based on Fashiolista’s data

Customer channel hypothesis:

Integrating Fashiolista with social media (Facebook, Twitter) will lead to a viral growth effect (k-factor > 1)

3. Do like Elvis: Get out of the building

Once the business model hypotheses are listed, it is time to design experiments and collect data to test and validate the hypotheses that underlie the business model. Since there are no facts inside the building, you need to get out and approach real customers.

Once you have interaction with real (potential) customers, feedback loops and experiments can be created to collect data in order to validate or refute the different assumptions of the business model. A good way to conduct these experiments is by building a “minimal viable product” (MVP). This is the most “lean” version of your business model. It includes only the most essential features for delivering the value proposition. Every other feature that can be stripped without making the business model non-functional should not be built at this stage. The sole purpose of the MVP is to collect real customer data to validate the assumptions in the new business model. By trying to sell your MVP to early adopters in your customer base, you can start collecting feedback (and evidence) on the most important building blocks of the new business without a large upfront investment in time and money. If a certain assumption proves to be false, you come up with alternative solutions to test. After a number of these iterations, the core business model will come closer to what is called a “market fit”. From this point onwards, you can start implementing additional features based on customer feedback to further scale the business. A suitable approach is the use of A/B testing. By splitting the user base in two, a control group is formed that will not receive the new feature (or a different version). By comparing the actionable metrics of both customer groups, it can be inferred if the added feature is indeed adding value.

Following these steps will promote a more lean and agile process of business development that is aimed at building a new business model based on real data and validated assumptions instead of management judgment and indirect market studies. Companies like Google and Tesco use this experimental approach with great success.

Once incumbents will start applying this approach to building a data driven value proposition to start competing on information, they will become true ninja’s in outperforming their competitors…

This post was authored by www.businessmodel-lab.com

His Royal APIness

Posted on April 24, 2012 by COI Team

Amazon
“We’re going to aggressively expose ourselves!” is what Jeff Bezos reportedly said (while ‘aping a flasher opening a trenchcoat’) when deciding that Amazon would open up its vaults of product data in order to fuel innovation through external developer communities. In 2002 Amazon launched its e-commerce web service and (together with eBay) pioneered the digital business ecosystem. They used something called an API…

Open up! Make money
APIs, or Application Programming Interfaces, are so much more than just the interfaces between software applications. They enable information to flow from within a company to the world outside (and across the globe) and more importantly in a way that it can be re-used. As we learned from the Amazon example, when data is valuable enough, external developers will come and do amazing things with the data that is available to them. Here are a two other interesting examples:

Dutch online retailer bol.com launched their open API earlier this year offering access to product information such as descriptions, customer reviews etc. The open API has already led to the development of a mobile scan app that uses bar code scanning to give access to the bol.com catalogue and gives the option of buying items online. It’s apps like these that, by focusing on specific customer interests (offline shopping in the example), find additional revenues for bol.com;
Visa recently announced its V.me service, a PayPal-like online payments system. V.me allows people to enter their card information only once and shop online without the hassle of having to re-enter a 16-digit credit card number at each and every checkout. Visa will release V.me with an API to stimulate developers to incorporate it into their products and services, for in-app purchasing for example.

APIs are in fact a great way to generate additional innovation and revenue with your data. Sam Ramji of Apigee compares opening up business data through APIs with evolution. APIs help explore and exploit ‘niches’ which leads to a ‘wild variety’ of apps, restrained only by whether or not customer value is being created. Not surprisingly, more and more companies are developing and publishing APIs. Earlier this year The Programmable Web’s directory of public APIs (the tip of the iceberg so to speak) hit the 5,000 API milestone and the growth curve shows that this number is accelerating.

Ok, now what?
You recognize the value potential of developing APIs, but where to start? Apigee has found that successful API initiatives usually have stages:

Stage 1: Internal APIs – create an API for internal purposes, the development of a mobile app for example. The development team is able to learn how to work with APIs on a small scale
Stage 2: Partner APIs – share the API with a few key partners who want to develop their own new apps with it. The development team is able to learn how to provide support to external developers and maintain an open API under relatively safe circumstances
Stage 3: Open APIs – share the API with everybody, effectively pursuing a platform strategy

The advantage of such a staged approach is that the amount of risk and investment can be increased in a controlled fashion as well as the usability of the API to the outside world.

Roger Ehrenberg of IA Ventures argues that companies need to create ‘an API-culture’. This can be done in a number of ways such as working closely with a few start-ups or by organizing ‘hackathons’ and challenges. The bol.com open API for example was explored and experimented with during a tech rally.

As always, senior management has to be convinced before any real progress can be made. With so many great examples at hand, creating management buy-in should become easier going forward.

Archimedes
Archimedes once said “Give me a lever long enough… and I shall move the world”. We know now that in the world of business such a lever actually exists and that it’s called API. In the hands of creative people and smart companies, APIs are magical and powerful things. They help form digital business ecosystems that generate way more value than the sum of their parts. APIs put a multiplier on the worth of your data. What’s not to like about that?

So go on, expose yourself and celebrate His Royal APIness! Archimedes would have loved you for it.

We have come a long way since Henry Ford

Posted on April 16, 2012 by COI Team

Henry Ford: ‘You can have your car in all the colours you want as long as it’s black’

Wake up!
‘Personalization’ is not a new term, since Henry Ford personalization has come a long way. Personalization became popular in the mid 1990′s with products such as ATG and Broadvision as a means of elevating a website to enhance the visitor experience. Early pioneers of personalization are companies like Amazon and Ebay. In 2008 personalization of websites was taken a step further by means of mass customization. With customization people can interact with an experience, website or product in the way that they want to interact. Dell computers or Nike iD are examples of personalization by means of mass customization.

Today’s personalization is the result of technology integrated into a website that allows the server to modify layout which is presented to each viewer. Two individuals accessing the same website simultaneously may see two completely different sets of information.

The next generation of personalization takes it one step further; websites are tailored in such a manner that two visitors going to the same website will see different content. Personalized content may be advertising, items for sale, screen layout, menus, news articles, or anything else presented in your browser. This content is selected based on a user profile. User profiles are based on previous and current surfing behaviour and the device on which a website is entered.

Who are doing it?
By leveraging visitor’s behavioural data, one can deliver relevant content based on visitor’s needs and lifestyle. Here are some examples of personalization on websites:

Hi presents its online web store content based on previous surfing behaviour and type of device access. Hence visiting the website on a Blackberry or Iphone will result in different content and a higher conversion ratio for Hi;
Various airlines and tour operators use previous search behaviour for their pricing strategy. Searching for the same ticket multiple times using the same computer will result in a higher price every time you search for it. Planning on booking tickets? Do it the first time, or use a different IP address for the search and booking of your tickets;
Baynote is a recommendation technology provider and is a Software as a Service example. It observes real-time user behaviour on a site and looks for implicit, emergent patterns. It uses collective intelligence and an affinity engine to analyse the data. Common behaviours which it tracks include page refers, queries, mouse movement, time spent on a page and peer behaviour. Baynote uses data to show you the actual article you are currently looking for.

Abovementioned websites are considered to be part of the so called ‘Liquid Internet’. Liquid Internet is the name for a new generation of websites on which content no longer has a fixed format or position.

How to make personalization work?
In order to personalize your brand experience, the first step is to recognize the opportunity of using big data to drive the next generation of customer experience. The second step is to put the right platform in place that provides agility. A platform that is able to respond to the changing demands of customers in order to deliver a personal experience. The third step is to measure: traffic, user feedback, customer inquiries, bounce ratio, returning customer ratio, sales data, user demographics; anything that will help you make measurable improvements. Then develop and test these improvements in order to actually collect data that works. Then lastly the delivery of personalized content should be automated. Several specialist parties will be more than willing to help you to make personalization work.

So what’s the catch?
By segmenting customers to the individual level, brands can create a more personalized, relevant experience. Currently 50% of US online shoppers actually expects to be offered promotions or merchandise that reflect their past online shopping behaviour and purchases. More importantly, 46% of shoppers reportedly would buy more from retailers that personalized the shopping experience across channels. Companies which have personalized their content on their website based on consumer analytics have seen their conversion rates increase significantly.

Engage your customers
Personalization can be an effective method to increase customer loyalty and thus profitability per customer. It creates the opportunity to deliver a unique tailored brand experience that separates one brand message from another. One can offer more relevant product offerings, marketing communications, pricing and promotions by putting the customer’s individual wishes at the centre of your strategies. Personalization ensures higher customer satisfaction which will result in more engaged customers with an increased brand spend and growth.

Paying for service with personal data

Posted on March 30, 2012 by COI Team

You’re being followed
Imagine walking down the street on a sunny afternoon. You’re heading for your favourite supermarket. A man is following you. He is wearing a trench coat, a moustache and reflective sunglasses covering most of his face. He is carrying a notepad and in it he records your every move.

He even follows you inside the supermarket. He notes your shopping route, your shopping items and your payment method. You wait for him by the door. You grab him by the shoulder and ask him with annoyance “What are you doing, why are you following me?!” His answer is clear and simple: “We want to provide better service, so we want to know everything about you”.

Although this might seem absurd, it appears to be day-to-day business online. This disturbing image illustrates how Facebook has loosened its privacy settings since 2005 to expand your (or: its?) network. Google received a wave of criticism by updating its privacy policy to “provide a better service”. Critics say it only helps Google pitch its advertisements better. Moving to a remote village and abandoning all electronic devices looks like the only way to opt-out of Google’s all-seeing eye:

“If you have something that you don’t want anyone to know, maybe you shouldn’t be doing it in the first place” Eric Schmidt, former CEO Google

Data = value
One of the fastest-growing businesses on the Internet, a Wall Street Journal investigation has found, is the business of spying on Internet users. The study found that:

50 US top websites on average installed 64 pieces of tracking technology onto the computers of visitors, usually without warning;
tracking technology is getting smarter and more intrusive. The Journal found new tools that scan in real time what people are doing on a Web page, then instantly assess location, income, shopping interests and even medical conditions;
these profiles of individuals, constantly refreshed, are bought and sold on stock-market-like exchanges that have sprung up in the past 18 months.

However, spying on customers is not only an online activity. According to this New York Times article, traditional stores go to great lengths to find out everything there is to know about their customers. Appropriately named retailer Target sends specifically designed ads to pregnant women in their second trimester, which is when most expectant mothers begin buying a variety of items, such as prenatal vitamins and maternity clothing. Target is able to identify approximately 25 products which, when analysed together, allow them to assign a “pregnancy prediction” score to each shopper. More importantly, the store can also estimate due dates to within a small window, so it can send coupons timed to very specific stages of pregnancy. Customer data is also a key element in Tesco’s business model.

Privacy, the new currency?
These examples may sound like a brutal invasion of your privacy (and some of them are). But when used appropriately (and with consent), analytics of personal data can create a win-win situation for business and consumer. This article advocates that privacy could be the new currency of the web. The equation boils down to how much privacy the user is willing to give up in exchange for the features and functionality a site provides. A recent study on the so-called monetisation of privacy backed up the theory: Given the choice between one digital service offering a great deal of privacy and one € 0.50 cheaper without such promises, consumers opted for the cheaper option. This behaviour might apply to non-digital services as well.

Managing privacy
Current legislation is inadequate to deal with the new and swiftly changing world of social media, online user generated content and big data. That’s why the US government and the European leaders are proposing new laws and regulations to protect the personal information of their citizens.

But is it possible to regulate this ever-changing landscape or can companies and consumers be prepared? Some take aways:

Companies can proactively implement the OECD Privacy Principles. They provide the most commonly used privacy framework, reflecting existing and emerging privacy and data protection laws and facilitating the creation of leading practice privacy programmes and additional principles
Companies and consumers can use third party data vaults such as Personal or the Dutch QIY to explicitly manage personal data
Consumers should make educated choices on what to share and where to share it (both online and offline)

The value of data and privacy is a hot topic. Companies should find the right balance in order to serve their customers in the best possible way. More information on this topic can be found on our website.

Nolan, Norton & Co. launches Competing on Information blog

Posted on March 2, 2012 by COI Team

For the past two decades, virtually every company has faced some form of digital disruption, first as a result of ongoing automation of business processes in the nineties and, soon after, due to the shift towards online distribution channels and company-client interaction in the noughties. The most recent fusion of developments indicates we are currently at the start of a third wave of digital disruption. The amount of information companies are processing and storing is exploding exponentially. At the same time, technologies capable of gaining value from these high volumes of information are becoming mainstream at acceptable costs. A growing number of companies have found ways to turn these developments to their advantage, building new value models with information as an essential part of the customer value proposition. These companies have started Competing on Information. Continue reading →

Competing on Information Blog

Unlocking new business and revenue models