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You can now download our latest ‘Ask the Experts’ Disruption report

 

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‘Ask the Experts’ GDPR report

‘Ask the Experts’ report on Unleashing Marketing and Data Technology’s true potential

‘Ask the Experts’ report on Key Marketing and Data Opportunities and Challenges for 2017 and beyond

Knowledge Bench – Practical applications of AI

Knowledge Bench – Practical applications of AI

Thank you to everyone who came along to our latest Knowledge Bench event on Wednesday 24 May. We enjoyed drinks, canapés and chat with a whole host of Data and Marketing Technology experts as well as having some cognitive fun with Watson!

Our focus for the event was AI and Cognitive computing, exploring what it means for the market as well as taking a look at some practical applications of machine learning in action.

We welcomed speakers Derick Wiesner from IBM and David Fearne from Arrow to discuss the topic alongside our experts and heard about some truly innovative projects that are pushing new boundaries in machine learning.

David Fearne, Technical Director at Arrow ECS, gave a fascinating insight into his ground-breaking project, How Happy is London?, a live demonstration of large scale data analytics that has recently seen him win the Software and Services category at the Data 50 Awards.

David also gave us sneak peak at other innovative AI projects underway at Arrow, including a brand new project to see if twitter can predict the general election and an exciting charity initiative based on cognitive computing that is designed to help the most vulnerable in society. He left everyone feeling inspired and opened up a new world of AI possibilities!

We were also lucky enough to hear from Derick Wiesner, IBM Commerce and Digital Marketing Agencies Segment Leader, Europe, who talked through some fascinating real world examples of Watson in action.

What was really clear from all our speakers was that AI is here and is already being used in so many ways to help businesses. As David showed us, ‘machine learning is now part of daily life’.

 

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Amplify showed that Watson is out of the lab

Amplify showed that Watson is out of the lab

I’m back from IBM Amplify 2017 with renewed enthusiasm for Watson Customer Engagement. I left Las Vegas with a sense of purpose; feeling IBM has real direction with A.I and cognitive computing in Watson. Its nailed its transition from on-premise to SaaS and its proposition is strong and clear. Watson is out of the lab and into the marketplace, ready to be discovered…

A.I and Cognitive is left, right and centre     

There are many compelling reasons to use Watson but what clearly came out of out Amplify last week was that A.I and cognitive is left, right and centre for IBM.

I saw some really dynamic presentations from Harriet Green, Richard Hearn and Will Smith, who all spoke fervently about redefining customer engagement in the cognitive era and the opportunities that Watson will bring to connect with customers as individuals.

Ginni Rometty’s address also convincingly set out how bringing cognitive capabilities together with the cloud will enable new innovation to solve problems and create new marketing solutions.

The new wave of people at IBM has led to a change in culture, with those at the heart of the organisation driving a real understanding of A.I and cognitive.

Watson heralds a new era     

With IBM Watson Customer Engagement, cognitive is now accessible through its simplified product range and easy to understand language.

There’s a new clarity with Watson. Its highly structured and well-defined platform, its user-centric design, smooth integration and cognitive expertise is just waiting to be discovered.

The challenge now is for businesses to understand how A.I and cognitive can be practically applied.

Grant Williams 

 

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It’s time to get practical with A.I and cognitive computing

It’s time to get practical with AI and cognitive computing

Everyone is excited about A.I and cognitive computing – the boundless opportunities, the raft of applications in development and the promise of a new era ahead for marketers. I’m excited too, especially by how these technologies are already being used, but I see many businesses falling into a trap. In the rush to embrace A.I and cognitive computing, many of the practicalities around its implementation are being overlooked.

Truly understanding the technology

As I wrote about last week in the Huffington Post  a large part of harnessing the opportunities cognitive computing and A.I can bring is in truly understanding how these technologies work and how they can benefit an organisation. There’s still a lot of confusion around this.

Many organisations mix up predictive systems and cognitive systems, for example. Predictive marketing is based on analysing huge amounts of data and automating responses. True cognitive computing is teaching a system to think like a person and learn as you train it. It can take data (which does not have to be personal) and learn from this. This, in conjunction with A.I technology opens up a huge range of new ways to reach and interact with customers.

Importantly, although cognitive computing is designed to learn and run independently, it will always work best in partnership with people. For example, cognitive technology can run automated tasks such as reporting or email campaigns, freeing up people to focus on creativity and delivering better customer experiences, such as Augmented Intelligence.

Don’t be seduced by gimmicks 

Whilst organisations are keen to stay one step ahead of their competitors, they do need to look beyond a ‘gimmick-led’ application of these technologies and instead investigate how it can be applied to actively improve personalised customer experience.

To do this, organisations need to step back and start with the customer. Understand how customers are interacting with a brand and what kind of experience they are looking for. People don’t necessarily want a relationship with a brand, they just want a good experience.

The North Face is one example of where cognitive computing is being practically applied to deliver this kind of experience. Users visiting The North Face website can have a similar experience online as in-store, thanks to intelligent natural language processing technology that helps customers choose a jacket by asking a series of questions and learning from the answers supplied. Powered by IBM Watson cognitive computing technology together with Fluid XPS the retailer can provide customers with outerwear suggestions tailored to their needs, creating a more engaging, relevant and personalised shopping experience.

Getting your house in order

Perhaps more fundamentally though, businesses first need to get their own houses in order before embarking on implementing new technologies such as cognitive or A.I.

Innovating and pushing the boundaries of what is possible through the use of exciting technologies is of course great. However, in order to gain value from groundbreaking technology and turn it in to something that will deliver significant improvement to their customers, it is vital that organisations strike the right balance. As Kevin Kelly, author and founder of Wired famously said “perfect what you know”.

 

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Taking steps towards cognitive computing

The concept of cognitive computing and A.I has been much discussed recently, in the same way that real time marketing was a few years ago. While there have been a limited number of practical applications of this technology to date, there is no doubt that the concept is set to dominate the landscape for some time. All the big players such as Adobe, Salesforce and IBM are vying to take the lead here, with IBM’s Watson in particular making waves in the industry.

The next few years will see organisations start to get to grips with what cognitive computing can offer. While there is much fascination with the potential for cognitive, there is still an element of nervousness from many organisations, especially when it comes to A.I. This is not unfounded, as A.I has not yet reached the point where it can run without careful human monitoring.

There are still fundamentals to be worked out to achieve true machine learning where the machine is fully responding and recalculating on changing inputs without any programming from a human party.

More fundamentally, though, businesses need to look beyond a ‘gimmick-led’ application of these technologies and instead investigate how it can be applied to actively improve personalised customer experience.

For example, this could take the form of a holiday company knowing that an individual likes to ski, has two children aged six and nine, has been on skiing holidays before in the February half term and favours Italian resorts over French ones, and then drawing information from 1st, 2nd and 3rd party data as well as analysing weather statistics and flight information and then offering appropriate holiday options based on this information.

Again, data is the key here. The more relevant data that is gathered, the more personalised the experience for customers. The importance of having excellent processes in place to capture and manage data is perhaps more significant than ever. As data scientist Bradley Voytek famously said while at Uber: “I don’t need to know everything about everybody. I just need to know a little bit about a whole bunch of people.”

Those that succeed will be the ones who can properly leverage both data and technology to make customers’ lives better.

 

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