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Katy Gwilliam

Marketing Partner

About this Author

Katy leads Marketing and Communications for iProspect in the UK and is focused on delivering the agency's mission to become a critical partner for business growth. During her three and a half years here, she has worked with talented specialists across the network to generate market-leading thought leadership, events, case studies and content.
Before iProspect, Katy worked in MarComms at dunnhumby, The Telegraph and dmg media.

AI and Machine Learning Breakfast Briefing

In a recent poll of marketing professionals, iProspect found that although 79% of people know the difference between Artificial Intelligence (A.I.) and Machine Learning (M.L.), less than 25% are actively using these technologies in their current plans. This is despite 61% wanting to apply them to their 2018 marketing strategy. To address the research and outline exactly how performance marketers can make the most of the opportunity today, iProspect experts gathered on 29 November for our latest Breakfast Briefing on A.I. and Machine Learning. Alongside Google and Eurostar, we explored the possibilities, put the principles into practice, and unveiled our proprietary machine learning tool, iProspect CORE. As Stefan Bardega, iProspect CEO UK & Ireland, who opened the event explained, our role as performance marketers is to generate transformative business outcomes using the most advanced techniques and disciplines. A.I. and M.L. are two of the most powerful developments to impact performance marketing in recent years so it is imperative to be prepared. To demonstrate how Machine Learning can be put into practice, Sophie Wooller, Director of Data & Technology Products, and Josh Carty, Data Scientist, used crowd-sourced decision-making to predict the fate of passengers on the Titanic. Tapping into the principles of Machine Learning, the audience worked together to plug different criteria into a custom-built algorithm. With each iteration, the model’s accuracy improved, bringing to life the learning element of M.L. and highlighting the need for human involvement. iProspect’s Director of Performance Media Products, Caroline Reynolds explained how effective CORE had been for high-speed travel service Eurostar. A Machine Learning-powered optimisation engine that automatically analyses, activates, and optimises media based on our bespoke algorithms, CORE processes data at a rate of 6bn rows per minute. With speed, efficiency and effectiveness at the centre, CORE delivers 2x the impact of performance media with unprecedented speed and accuracy. Taking a deeper look at its infrastructure, Caroline overviewed the tool’s four stages: 1) Data Collection, 2) Data Storage, 3) Planning & Prediction, 4) Activation. It’s at the Planning & Prediction phase that Machine Learning comes into its own as algorithms evaluate decisions and adapt to create the optimal activation plan for performance media. This simultaneously activates CORE’s learning system through platforms such as Google Adwords, Bing, Facebook Business Manager, and Google DoubleClick Bid Manager to optimise innovative strategies and implement changes automatically in real time. In only five weeks, CORE yielded impressive results: a 12% reduction in Cost Per Click, a 26% increase in conversion rate and, crucially for Eurostar, a 30% improvement in Cost Per Acquisition. Eurostar’s Head of Marketing & Brand, Guillemette Jacob, said “iProspect are key to driving our digital transformation journey. CORE is the latest example of how the agency collaborates to provide innovative solutions that address both our business and digital needs.” Rahul Parmar from Google’s Cloud Platform then joined iProspect’s Head of Global PPC for a ‘fireside’ chat discussing the latest innovations in A.I. and M.L. He reflected on the democratisation of the technology, explaining that we are now seeing it become more accessible. While much of it remains high-end and requires skilled developers to build custom platforms, in the short-term there are APIs and products that enable brands to leverage M.L. quickly and effectively. Over the past few years, Google has been using A.I. to tighten up the feedback loop in G Suite to implement quick and effective channel adjustments, and automatically identify the biggest cross-selling and upselling opportunities within Soothsayer. On the optimisation side, Deep Mind uses algorithms to optimise Power Usage Effectiveness and improve efficiencies in data centres. Jack Swayne, Managing Director of London and Stafford, closed with the three key takeaways for brands to prepare for the Machine Learning opportunity. Define the challenge: clearly articulate the business challenge, start with a number of different hypotheses, and develop a Machine Learning research roadmap now Understand your data: audit the data you currently have and that you can access, understand your data governance, warehousing and QA capabilities, and start smaller analysis projects as soon as possible Get the technology and expertise you need: consult with experts early, and keep talking. Explore data management and analysis platforms to find the right solution for your business, and create training plans to develop your internal knowledge and skills around M.L. Find out what some of our speakers thought were the key takeaways from the event in the video below: For more guidance on Machine Learning and CORE download the whitepaper, and if you missed the Breakfast Briefing watch it in full here. 0 4 min read

Has Technology Enhanced or Damaged Our Experiences?

With technology advancing at an unprecedented rate, it is challenging to stay ahead of the latest developments. The so-called Fourth Industrial Revolution is blurring the boundaries between physical, digital and biological, and digital transformation is disrupting almost every industry. At iProspect, we are constantly evolving to keep our clients at the forefront of emerging technologies, placing innovation at the heart of everything we do. Yet, while one could be forgiven for assuming the tech revolution is nothing other than positive – another rung on the ladder to ‘tech nirvana’ – have we ever stopped to explore the impact of technology on our experiences? We partnered with One Question conference to find out. On 7 June 2018, Sophie Wooller, iProspect UK’s Director of Data & Technology Products joined a lively panel moderated by Marketing Week editor, Russell Parsons, to explore the conundrum: Has technology enhanced or damaged our experiences? Alongside, Samsung’s Head of Innovation, Katie Baker, and IBM’s Chief Strategy Officer, Jeremy Waite, Sophie discussed the opportunities and challenges posed by the tech revolution and what they really mean for marketers. The 45-minute debate flowed to uncover three broad themes: Product orientation vs Customer Orientation, Personalisation vs. Personification, and Datafication & Trust. Product orientation vs customer orientation The panel opened with Russell asking whether an increased emphasis on tech and innovation has rendered marketers guilty of ‘product orientation’. Sophie highlighted that while product may be an easy place for marketers to start because it’s tangible and fixed, it should, ultimately, be about customer orientation. “It gets more difficult when you try to work out what the consumer wants but there are so many tools that help us navigate the needs of our customers quickly.” Expanding on Sophie’s point, Katie suggested that marketers should be using customer orientation to inform product orientation. “Rather than targeting people by demographic we must instead understand how they are using tech and tailor our marketing strategies accordingly. While there is so much focus on tech and innovation, our job as marketers is to take a step back and tell the story.” She pointed out, however, that a huge proportion of the market simply isn’t there yet. Personalisation vs. Personification So, if it is about customer orientation, should we be doing more personalisation? Sophie explained that asking people ‘do you want more personalisation?’ is a hard question to answer when they don’t fully understand all the possibilities. “Personalisation to a point is great, but not to the point of being creepy! If what we are doing is contributing, and we can do more of it in a sensible way, that is great. But we must always go back to the responsibility question – how can we strike the right balance to make it useful for the consumer?” IBM’s Jeremy Waite elaborated, suggesting that we should be using A.I-based tech to move away from Personalisation and towards Personification. “Personification is about understanding how your audience feels. That means knowing a little bit about a lot of people, enabling you to deliver the right messages at the right time in the right way, without having personally identifiable information.” Datafication & trust Does this mean, though, that we have we been over-‘datafying’ marketing? Sophie disagreed: “We need to prove that what we are doing is working, so there must be some level of measurement and framework.” However, she reinforced the responsibility aspect, adding “we will never use more information than we need.” For marketers, gaining the trust of consumers is paramount. After all, trust breeds loyalty. Ultimately the end goal is to be useful for consumers, so we must be responsible for ensuring everything we do contributes to that positive experience. As Katie pointed out, “There is a lot to do to reach true brand loyalty. At Samsung, we’ve moved from targeting anybody using big data to being more selective.” Jeremy concluded by reminding us that the collision of data and tech has created both challenges and opportunities. In a nod to the rising influence of A.I., he emphasised that technology is paving a new path to trust, pointing out that “perhaps we are moving away from the idea of trusted brands and towards trusted digital assistants.” The verdict While there were clear arguments for both sides of the debate, the resounding answer from all three marketers was that technology has enhanced our experiences – with two caveats: 1) we must act responsibly in the innovation and application of tech; 2) a good robot must be accompanied by a good human. 0 4 min read

Katy joined iProspect as Senior Marketing & Communications Manager in summer 2016 and is responsible for delivering the agency’s MarComms strategy. She has spent the past nine years in media and marketing, both agency and client side, working for dunnhumby, dmg media, The Telegraph and Nexus PR, where she created and delivered strategies to develop brand awareness and engagement in line with business objectives.

Katy Gwilliam

About this Author

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