TechBytes with Graeme Finneberg, Country Manager, UK, mediarithmics

Tell us about your role at mediarithmics and the team/technology you handle.

mediarithmics is an end-to-end Data Marketing Platform (comprising DMP, DSP, CMP, Marketing Automation, and DCO technologies) — or as we call it more succinctly, a Universal Data Platform. I’m responsible for the planning, execution and delivery of strategy across the UK. This includes growing the mediarithmics client base and revenues amongst large publishers, e-commerce brands and media alliances by providing them with the best tools and technology they need to take control of their data.

What is the state of media sales in Mobile Marketing and Advertising Technology?

As the industry matures, we are seeing less in the way of big changes. Instead, we are seeing a greater focus on quiet evolution and companies looking at how they can improve and tighten up what they are doing to create better results.

This is particularly true in AdTech where we are seeing a new generation of technology that essentially does what generation 1.0 did, but better. It has been refined and improved to correct the shortcomings of the original tech. So, for instance, DMPs can now be graph-based, which means that as consumer data is collected it doesn’t have to fit neatly into pre-prepared segments, so it is now possible to collect, store and use much richer data at scale than before.

In addition, new AdTech can be built in a way that means data isn’t compressed. The benefit of this is that old tech can take two weeks or more to populate the segments an advertiser wants, whereas with uncompressed data it’s possible to build hundreds of segments in minutes so that real (rather than estimated) audience numbers can be identified. This means that advertisers and their agencies will know straight away if the audience type and volume they need is available. This is particularly helpful for publishers who previously often had to guess the size of the segments advertisers wanted, which often led to letting them down or under-selling inventory. It’s a tough market out there for advertisers and publishers with so much uncertainty, so all these tweaks to improve ad performance are important to help marketers justify their budgets.

How do you enable your customers to benefit from your advanced expertise in Universal Data Marketing offering?

Our platform allows brands to launch personalized, cross-channel marketing campaigns in real time using programmatic technologies. For publishers and e-commerce sites, mediarithmics provides the tools to protect, structure and leverage the value of their data, helping them to create new, profitable business models.

Tell us more about the technology engine driving cross-channel marketing campaigns.

At mediarithmics, we have what we call a Universal Data Marketing Platform (UDMP). This includes a CDP (Customer Data Platform), which is one single database to house all of a company’s data from all sources. It also includes a DMP (Data Management Platform), which seamlessly integrates with the CDP for activating the data. By having one single platform to both house and activate the data we ensure that our clients can create better informed, more effective cross-channel marketing campaigns across email, programmatic, mobile, CRM or wherever — and these can be carried out in real time.

How do you see the Mobile and Video Advertising landscape evolving with the maturity of Content and Video Monetization?

We are going to continue to see better adaptation of short-form content designed for mobile, which is something that most users will welcome. I don’t think I’m unusual in fearing the 30- or 60-second ad clip that gets served when I just want to see a 10-second piece of content. Consumers aren’t standing for it anymore and this approach is more likely to damage brand relationships than create new ones!

Generally speaking, we need better investment in different creative and the evolution of the mobile and video advertising landscape is likely to help this. Whereas before clients spent their big budgets on TV ads, video is now people rethinking how they do TV as they realize that it bridges a gap between digital and TV. TV ads are, therefore, being filmed differently so that they can be repurposed and targeted across other digital channels — especially for mobile where they need to be in a ‘snackier’ format for on-the-move viewing.

Tell us more about your work in the field of Data Unification, Management and Activation. How much of it is managed by AI/Machine-Level algorithms?

One of the biggest challenges I face daily is helping companies to understand how easy it can be to take control and unify their data. They worry about how long the transition will take and assume they’ll have to start from scratch. With mediarithmics, it’s relatively quick and pain-free, even if a company has hundreds of data sources. For example, for publishers, our Activity Analyser does away with the costly and time-consuming issue of having to transfer many different media brands with different taxonomies, and instead converts all the information across all websites into a singular language.

Tell us about the product roadmap you have designed for mediarithmics. Which technology providers could better leverage your products?

It’s less about specific technology providers and more about retailers, brands and anyone who wants to makes their data work harder for them, whether that’s to sell more products or to better inform them about their existing customers. Publishers, for example, are in a position to reap huge benefits from our product. At the moment, they are under pressure to deliver compelling reasons for advertisers to spend with them — they are losing revenue to the likes of Google and Facebook because they just can’t compete with their advertising offerings.

We can help them to pool their data in cross-publisher alliances, which create the scale and data richness that they need to compete. As well as big publishers, we can help more niche companies come together to pool inventory and data to allow heightened targeting. A great example would be the travel sector with travel publications and broadcasters collaborating with travel comparison sites, airlines, online travel agents, etc. For the right brands, the kind of data that a ‘vertical’ alliance would create would be extremely powerful.

What are the opportunities and risks you foresee in the way Big Data is shaping Data Marketing strategies for 2020-2025? How do you prepare for these disruptions?

Big data presents a massive opportunity but marketers need to get smarter about how they leverage their data assets. Post-GDPR, they must rely less on 3^rd party data in favor of 1^st and 2^nd party partnerships. They also need to focus on the quality of the data combined with how it’s being used within the contextual environment. As brands demand more transparency across the supply chain, we’ll see more businesses moving towards an in-house solution that gives them full control of the process and value chain.

We’ll also see an increase in Machine Learning technology to upscale 1^st party data by examining the usage patterns of existing known users versus unregistered users, to create an accurate, deterministic match. It’s essential that marketers have a closer look at what data they currently possess and ask themselves whether they’re truly maximizing their opportunity to monetize it, whether that be through improved website performance, customer marketing or direct revenue generation.

What are your prediction for Digital and Data-Driven Advertising in 2019-2020. Is anything going to disrupt Google, Amazon, Facebook and Apple (GAFA) getting the lion’s share of digital ad budgets?

Ove the next couple of years, expect to see a rise in media alliances looking to dent the GAFA hold on the ad market. However, rather than being the ‘pure play’ media alliances we’ve seen to date, like the Ozone Project in the UK, I believe we’re going to see some changes. Pure play media alliances are great for scale but they lack the richness of data that the likes of Facebook offer. To truly compete they need to add information such as gender, interests, friends’ interests and transactions to navigational data.

So, the new look alliances that we are likely to see are ‘super alliances’ like the Gravity Alliance in France, which include telecoms firms, large retailers, search firms and content providers in addition to media brands. By adding non-media brands to an alliance, it is possible to build not only scale, but a unique picture of consumers, providing a real depth and richness that goes beyond the GAFA offering, including contextual, search, geographic, transactional and purchase intention data. Plus, this kind of alliance is in control of its own ecosystem and members are able to monetize all of their first-party data across all of their sites. So for me, the biggest disruption for GAFA is likely to come from collaboration and great technology creating something very powerful.

Thank you for answering all our questions!