Headless CMS Architectures

thumbExplore why Enterprise Digital Ecosystems are creating a new style of content management architecture

I find mid tier CMS vendors the most interesting, they are the vendors that are the most innovative and challenging to the guys  at the top.  However because of their nature they are marketing their products to users that like everything wrapped up into a suite of capability.  This is where things can go wrong and prevent those vendors from enjoying some of the benefits of working with enterprise clients.  A way to break through this barrier is through architecture of the product.  Creating product architectures that enable customers to have a great degree of choice and flexibility in the implementation of the platform into their business.  The best approach to do this is the decoupled approach or headless CMS model.  The following white paper explores some challenging approaches to mid tier CMS vendor architectures;

Headless Content Management Architectures White Paper


Further to the initial white paper I will publish a video and podcast on this subject in the next week.

Big Data Diary

I was recently asked by Figaro Digital to keep a record of all my data interactions over the course of a single day and to explain their significance.

Here’s my story behind my daily big data trail:

Monday 8 April 2013:

I’m heading to Chicago today for a business trip. I have a long flight ahead of me so I’ve prepared several downloads from BBC iPlayer onto my iPad. I’ve also downloaded several audio books onto my iPhone to listen to on the plane whilst working, and for my training runs between meetings up the Lake Michigan coastline.

The data day

I wake early and book a taxi to take me to the airport via my iPhone application. The app knows my home address, it has my credit card details saved and can send a clean, wifi-enabled cab within minutes of ordering. Rather than the driver ringing the doorbell and waking the kids up, an SMS arrives to tell me that the driver is waiting outside. I sneak out of the house and jump into the cab.

As usual I’m bored straight away so I check Facebook, Twitter and LinkedIn, which is something I regularly do first thing every morning. I have received a couple of requests from LinkedIn but post nothing myself. We come into traffic on the north circular and I’m worried about flight times as I always leave it to the last minute. I look at Apple maps to check traffic conditions. Luckily there are no major problems so I should get to the airport on time.

Next I decide to check in for my flight. I downloaded my favourite airline app some months ago which means my boarding card is already waiting and my loyalty card is input so I have access to the lounge and have not missed the valuable points I collect from each flight. It shows me some hotel options with good discounts and at the usual standard of quality which my company affords me, so I select one and book it.

My flight is shown as departing on time but I’m flying out of T5 at Heathrow, famous for its three satellite terminals and I want to know which gate I’m leaving from to give myself enough time. The airline app doesn’t give me the gate details but TripIt does. It’s a neat little app that stores all my travel plans, from flights, hotels and car hire, and keeps track of everything from delays to reward points, constantly alerting me about my travel plans. It also keeps my family in the loop about my whereabouts and allows my colleagues to book the same flights and hotel as me if we’re travelling together.

I arrive at the airport and in less than 40 minutes after leaving my house, big data has entered my world, harvested valuable information and provided me with equally rewarding data.

Harvest and reward

The entertainment downloads I made last night have all been logged and tracked against my profile and they allow me to be targeted with more personalised content in the future. Equally, they know where I’ve downloaded the content from and to, so they know which devices I prefer These are then logged as interest types on my profile for future push personalisation. For the organisations, logging this information in the Enterprise Resource Planning (ERP) platforms enables them to source further content to reach my demographic.

For organisations to do this effectively they need to harvest my data through clever apps and utilities, such as reward programmes. They then need to join the dots and build my profile around all of the interactive touch-points I have with that organisation. Algorithms are then used to extract and understand the data meaning. Finally, all this needs to be applied back to the user through apps and websites.

This enables the user to feel rewarded and ultimately, helps ensure that the organisation gets more custom from that individual. As consumers get more tech savvy, they enjoy utility, such as not worrying about collecting boarding passes, which ensure that the organisations they use the most know they are valued customers and will be rewarded.

Into the cloud

There’s no form of big data in the queue through the security lane. I hope the new security scanners aren’t sending images to the cloud, but something in me suspects that they are.

I often wonder about data privacy and who gets access to what. I run to the lounge, fly through the reception with my app (it is great that there is no need for a boarding card and loyalty card to get in). I grab a coffee just before my TripIt app makes the airport announcement noise – big data has pushed a live feed of departure and boarding announcements to my phone. I take one look and head to the appropriate gate. Jumping on the flight, I get settled and take off for the real clouds. I know for the time being that I’m disconnected, but this will become limited as most airlines are now investing in wifi on planes.

Seven and a half hours later I land at Chicago O’Hare International Airport. Data from the immigration queue, fingerprints, photos and passport details goes straight to the US government’s private cloud. Goodness only knows what happens with that data!

Virtual data – real utility

Once I’ve made my way through security and collected my luggage, it is time to make a decision on how to get to the hotel. I have quite a few meetings throughout the week in various locations. Is it cheaper to use public transport all week, rely on cabs or hire a car? I opt for the car hire. Out comes the iPhone again and I fire up one of my favourite apps provided by Zipcar. I’m already a member of the car club so they have my driving license details and credit card details saved. I type in my location and see that there is a car free for three days and that it’s located in a nearby short-stay car park.

I head to the car and using my iPhone app, I click the ‘car unlock’ button. It sends a message to the cloud, checks my details then sends a message back to the car’s little black box, unlocking the car as if I had pressed the key fob. I hop in and drive to the hotel; the black box keeps a record of my mileage and charges my credit card accordingly. All the while, big data is recording mine and the car’s whereabouts. Now that’s real utility; the ability to hop in a car parked at the bottom of your street and pay as you go without having forms to fill in.

Dropping my bags off at the hotel, I drive to an office complex to get some work done. Each user pays a subscription to use the space (including a hot desk and meeting rooms) and uses their own technology to conduct their day-to-day business. The cloud and big data have a big presence here; they are being used to network, share ideas, innovate, collaborate and work on projects in a more flexible manner. This use of big data is not only about companies harvesting data, it is about using big data and the cloud in new ways to create a virtual, more globalised, connected world.

Easy access

With most of today’s examples, the biggest benefit of big data is to make my life easier. We still have to be vigilant about privacy and companies must continue to only use data to provide an enhanced service, giving consumers something back rather than selfishly marketing at them. All in all, it is about making our worlds much easier.

So, where next for big data? For me it is clear: on an average day I need to see the dots being joined around my touch-points with a particular brand. Whether it is an airline, car hire service or booking a hotel, I don’t want to keep retyping. I want convenience, quick access, intelligence and utility. Organisations that get this formula right and continue to innovate their service culture using big data will benefit in the long-term.



Cloud Computing

Cloud computing has certainly gained momentum over the last 12 months.  It has no doubt struck accord with cash strapped businesses.  But our view is cloud computing is too low down the software stack and is predominantly concerned with vitualising platforms.  As more and more businesses compete in this space we see the value of cloud computing moving up the stack and unleashing its service orientated flexibility on the domain of traditional software as a service vendors.  Confusing?  They both operate in the cloud but for pure software as a service vendors to add even more benefits to business they need to reach into organisations.  Clouds will grow tentacles into businesses as the membrane between the traditional I.T. systems and the cloud gets thinner.  What does this mean in real terms?

Data will become the platform but it will extend with its applications into the cloud.  As with the web the data will reside in the cloud along with an app store approach to enterprise applications.  Internal private clouds and infrastructure will become agents to the cloud.  The cloud concept will increase up the value chain where cost savings are only half the reason why people will make the move.

Building a viable e-commerce business model

For the last week I’ve spent my time on helping produce a viable e-commerce business model using latest enterprise class commerce platforms, a well informed seo and media strategy and a decent runway to break even. This is not the first time may I add, but it does take into account some new challenges.

The saas world, e-commerce 2, global markets and the improved use of pay per click have made it even more a numbers game to make the business model work. Obviously your product needs to be good, but if it is and you have the right partners in place and the right technology it is simply a case of playing the numbers to get a return on investment? Sounds easy? Not quiet that easy. Its a fine art, where you need to apply your skills and know how to finally tune your system to get the most out of it. Its only through experience and through having the right partners can you guarantee the numbers game will work.

To get it right depends on your conversion path and this starts by having a coordinated approach between brand, traditional advertising, pay per click, social channels and traditional product channels. All need to be identified and a strategy developed to create a buying conveyor belt to your e-commerce cart. It doesn’t start with just your site its starts a lot earlier.

Choosing the right platform and partner to route this conveyor belt through the buying process will lead to successful conversion.

The platform needs to be able to take the feeds of potential customers from all these conveyor belts. It then needs to show case the product well, display options and link to other products to engage the user and stimulate their buying emotions. This is where saas platforms that have one model to fit all fail to deliver. They fail to capture the channels and trigger the buying responses. A wholly owned platform tailored to your product, brand and customer will win hands down when it comes to maximising conversion. It requires multi channelled approach to commerce and there are only a few platforms out there that do this well.

So if you are looking to play the numbers conversion game you need to be in full control of the whole engine from advertising spend, ppc, seo to platform and design. You need to control it all in order to fine tune the animal. This I believe is critical to achieving your business plan. However think SasS when you implement.  Build the As A Service element for your global markets but own the technology yourself.

Big data can we make sense of it all?

With Big Data becoming increasingly talked about, are there really solutions out there that can maximise intelligence within this data and make it clear enough for businesses to make sense of it and act on it?

My view is that its not as simple as just rolling out clever analytical inference tools like Autonomy as this just creates another layer of data. What I feel is needed is a set of communication skills that are inbuilt in most digital agencies.  Combining these skills with technology, business knowledge and your business requirements will enable us to produce clever and clear dashboards with your organisation’s data.  Whether its a set of analytical reports or e-commerce conversion statistics, we can design the tools and dashboard to manage your KPI’s, present the information to your team, collaborate on the actions and get moving with the necessary change. Technology alone won’t solve Big Data, but technology combined with a good set of communication and design tools can produce clear answers to your company’s big data challenge, more importantly it will help you and your colleagues make sense and make better decisions.