Carbon DMP has been shortlisted for the AI & Machine Learning Awards 2019, plus our own Ryan Jessop has been nominated for Data Scientist of the year.

The Computing AI & Machine Learning Awards recognise the best companies, individuals, and projects in the AI space today.  Carbon DMP is honoured to announce that it has been nominated for a number of awards.

Built natively on Clicksco’s own data lake, Carbon uses machine learning to better understand the needs, behaviours and intent of consumers from acquisition, through to engagement and conversion. Accurately identifying consumers with purchase intent is at the very heart of digital marketing, providing a route to boosting profitability, while increasing efficiency.

Best Emerging Technology

Having launched in February 2018, Carbon is revolutionising digital marketing by leveraging intent data and AI/ML driven tools challenging the industry to deliver ever more highly targeted ads, products and content tailored to online audiences who are ready to buy and crucially, offer a solid return on investment. Carbon is the only Data Management Platform that matches online customer behaviour and scored intent to create high value audience segments.

Carbon currently processes 150m+ monthly uniques adding to the 1.25bn+ customer profiles and 4bn+ intent data points stored and profiled on the platform.  This data can be queried to uncover deep audience insights, create bespoke audience segments, and exported to all major DSPs and social platforms to fuel customer acquisition, audience monetisation and anonymised data sales.

Carbon is delivering impressive results for a range of high profile clients including publishing giant Archant, and leading customer acquisition media agency All Response Media.

Most Innovative ML/AI Technology

Carbon uses machine learning to better understand the needs, behaviours and intent of consumers to enable marketers to generate more engaging digital experiences and drive more profitable outcomes.  Publishers can view their complete audience profile and discover the niche interests and behaviours of individual consumers to identify monetisation opportunities. Advertisers can profile consumers interacting with their brand – the intent, interest and behaviours they show – to retarget them through various channels or seek lookalikes that share similar attributes.

Our dedicated team of data scientists push innovation through data and machine learning, fuelling our market-facing products and tools.  For example; Audience Match™ is a premium tool for both publishers and advertisers to broker programmatic direct deals by identifying where there is audience crossover, as well as extending audience reach through lookalike audiences.  Using its machine learning algorithms over time, Carbon also automates the discovery of Intelligent Audiences i.e. those most engaged audiences with highly desirable elements.

Data Scientist of the Year

Ryan Jessop is a rising star data scientist employed by Clicksco within its Carbon division.  A Durham University graduate, Ryan Jessop came to Carbon as a KTP (Knowledge Transfer Partnership) Associate at Clicksco with a brief on Machine Learning (ML) and Artificial Intelligence (AI) advancements with the aim to create innovative tools to better understand digital customer behaviours.

Ryan’s own research led to an algorithm being developed that allocated an ‘Intent Score’ to a consumer, replacing the binary ‘Interest’ versus ‘Intent’ label that is traditionally used in the industry.  Ryan also occupied a leadership role on a collaboration between Clicksco and Pivigo (www.pivigo.com) – an initiative called Science-to-Data-Science (S2DS) – to support PhD graduates moving into Data Science roles.

Ryan is already making an impact within the industry, and was recently named winner in a prestigious national awards scheme, as the ‘Best Future Innovator’ category in the KTP Best of the Best Awards.

The awards will be announced at an awards ceremony on Wednesday 3rd July at the Jumeirah Carlton Tower. Check out the full list of nominations here.

Comments

Leave a Reply

Your email address will not be published. Required fields are marked *