Creating a unique personalised filter by using machine learning and leveraging semantics

IN-DEPTH: LikeCube’s co-founder Eleanor Ford talks about machine learning, a technique that can complement or even disrupt more traditional marketing communication strategies, and how the same is signalling the beginning of a new era in online travel.

Published: 27 Aug 2010

IN-DEPTH: LikeCube’s co-founder Eleanor Ford talks about machine learning, a technique that can complement or even disrupt more traditional marketing communication strategies, and how the same is signalling the beginning of a new era in online travel.

By Ritesh Gupta

One of the critical steps in shaping up true one-to-one marketing communications is related to organising, analysing and segmenting the database.

Many companies make the mistake of rushing through these strategic steps in order to implement the tactical portion of their marketing plan. This is termed as a critical mistake.

A one-to one marketing communications plan is a 360-degree examination of the customer: their intent, motivations, demographics and psychographics, geography, media consumption, as well as transactions.

Desires aren’t static

A strong understanding of the target customer base and the product catalogue is certainly a must have, but it is also important to acknowledge that people’s desires aren’t static, says LikeCube’s co-founder Eleanor Ford.

Ford says they evolve and change rapidly, faster than the time it takes to do a manual analysis and segmentation of a marketing database.

“As an example, a customer may be, within the same month, looking at planning a family vacation for the summer, searching for a romantic weekend gateway, and booking a business trip all from the same website. He might also be reviewing restaurants and sharing comments about an exposition he saw while sharing his location from his mobile, which says a lot about who he is. How does your one-to-one marketing strategy accounts for this? Clearly, there is a need to become much more agile, dynamic and holistic,” pointed out Ford, who is scheduled to speak at the forthcoming two-day Online Marketing and Social Media Strategies for Travel Summit Europe 2010 (5-6, October) to be held in Prague.

“I think communication should be based on the context, the search and the journey – e. g. how one’s taste might change or evolve over time. It all comes down to finding the right stuff for that person at that moment in that place. It’s about narrow-casting communications in real-time. Database segmentation alone can’t address it any more.

New Era

Ford says the opportunity lies in the amount of user generated data, which is exploding (e. g. ratings and reviews, likes, check-ins) thanks to mobile phone and social media platforms.

“We are at the beginning of a new era in online travel, the one of machine learning, which can complement or even disrupt more traditional marketing communication strategies. LikeCube uses machine learning and leverages semantics dynamically understanding what people might like at the moment they search, creating a unique personalised filter through which they can see what’s most relevant to them,” shared Ford.

LikeCube uses two types of data:

  • Meta-data (categories, attributes, tags, etc) and,
  • User activity (ratings and reviews, check-ins, buying history, wish lists, searches, click-stream, etc).

The company says it can personalise a site using any combination of the above data. This means solutions like when a user searches for a type of product (e. g. romantic hotel in Paris), results in only products that LikeCube’s algorithms estimate a user will like.

Assessing the maturity level, Ford says travel personalisation is still in its infancy.

She added, “One can look at Amazon which has spent 10 years on personalised recommendations for books and products and is now certainly reaping significant benefits from it - about 30 percent of their revenues come from products recommended by their engine -, but many people still complain that it isn’t good enough at predicting all types of products. So there is plenty of room for growth.”

“However, the travel industry is an agile business sector often keen to gain advantage through new technologies and creative solutions which is why this business sector has been one of our key focuses in recent months,” said Ford.

Machine learning - algorithms that use data to infer behavioural patterns and predict things - is highly dependant on the amount and type of data available.

“We are seeing an exponential growth of data at the moment that can be used in different ways to learn about people and places, and this involves identity, location, actions and things that are yet to be even thought of. With that growth will come smarter and smarter applications, that are truly sci-fi in terms of service delivery, understanding, intuition,” Ford said.

Online Marketing and Social Media Strategies for Travel Summit Europe 2010

LikeCube’s co-founder Eleanor Ford is scheduled to speak at the forthcoming two-day Online Marketing and Social Media Strategies for Travel Summit Europe 2010 (5-6, October) to be held in Prague.

For more information, click here

Or contact:
Gina Baillie
VP Global Marketing & Events
EyeforTravel
London, UK: +44 (0)207 375 7197
gina@eyefortravel.com

 
 
 

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