The Drum caught up with Marc Keating of Stein IAS to discuss his understanding of the emerging sector.
The Drum together with Stein IAS has been honouring the individuals who are pushing forward their business by using martech platforms, giving them a chance to speak openly about the changes in martech and have them recognised as Top Martech Heroes within the industry.
Keating spoke to us about the biggest martech trends from the past year, key challenges overcome within the sector and shares his predictions for 2019.
What are the biggest trends you’ve identified in martech in 2018?
AI has become one of the hottest trends in B2B this year, but its application within marketing beyond programmatic, personalisation and predictive data technology has been limited. The challenge for martech vendors now is how they embed AI and machine leaning capabilities within their stacks, beyond predictive data and analytics, which has been its initial application.
Also 2018 has been the year of ABM tech activation, as brands start deploying ABM platforms to activate intent data and deliver account targeted advertising and web personalisation.
This year, digital transformation has been higher on the agenda of most organisations, and as brands digitise their offerings and create new tech-driven service models and platforms, there has been more pressure on CMOs to transform the marketing function and GTM strategies. As part of this drive, immersive content experiences, AR/VR/MR, blockchain, AI/ML, personal assistants and chatbots are just some of the uses to address in 2019 and beyond.
What do you think have been some of the biggest challenges in effectively implementing martech in 2018 and how have organisations overcome these? (Or do you think they still have a way to go?)
At a strategic level, one of the biggest challenges that brands have faced is selecting and connecting the right tools to power their CX strategies. We’re seeing a rationalisation of the tech stack as brands begin to align technology investment more closely with the business and marketing strategy and overall integration goals.
2018 has also been the year of compliance as brands navigated the minefield of GDPR, which forced organisations to address their marketing, data, digital media/programmatic, content and tech strategies. In many ways, it has made organisations go back to basics by placing permission-based marketing at the heart of their strategies, with inbound, content marketing and contact preference centres driving effective data acquisition and nurture strategies.
At a more strategic level, GDPR has made organisations prioritise their data strategy in terms of how they capture, structure and manage first, second and third-party data for marketing activation and how they unlock data silos to build a 360-degree view of the customer. This has seen the wider adoption of data management platforms and an increase in the adoption of customer data platforms, which I believe will increase in 2019 as brands put the foundations in place to feed AI technologies with relevant data.
What new skills or practices, if any, do you think the industry will need to learn with the evolution of martech?
Over the last 10 years we’ve seen the rise, fall and rise again of martech and we are now entering an inflection point where the tech that has powered GTM and the CX will be very different than the emerging and disruptive technologies that will power it in the future. This is going to highlight and create skills gaps at all levels of the marketing and digital function and with a greater prioritisation of the stack and the deeper integration of tech across the customer journey, brands will also need to rethink their operational models and the teams and resources within them.
C-level marketers will need to adapt to a new lexicon as the tech stack layers of CRM, content management and marketing automation blend with predictive, AI and data science platforms.
At the practitioner level, talented individuals that understand the technology and have the strategic marketing intellect to align it with the marketing and business strategy will be in demand. Connecting the dots between the “Mar” and the “Tech” is where the biggest gap is. Designing “click to conversion” experiences that blend creative, content and media requires a new type of “CX orchestrator”. When AI and machine learning become fully bedded into the stack a new type of marketing architect will be born.
Where you do expect the martech industry to head in 2019?
2019 will see five rapidly evolving martech characteristics begin to become commonplace as we see the birth of the “cognitive marketing cloud”, enabling one-to-one intelligent experiences across the brand-demand continuum.
Today, creative and content are mostly built as complete executions, sometimes with multiple versions developed for each persona or segment. But a handful of marketing AI players have illuminated “tomorrow” by beginning to “atomize” creative: breaking complete executions down into smaller objects. Tomorrow, this ‘recombinant creative’ approach will be required to feed automated marketing and programmatic advertising systems capable of dynamically constructing millions of individualised experiences.
This is where increasing targeting precision leads to the ability to recognise an individual (based on big data) and craft a unique experience using recombinant creative and content. The next wave of individualisation will be far more dynamic, and work across many more touchpoints, orchestrated by AI and enabled by big data and by integration of the adtech, martech and emerging sales tech stacks.
A corollary to individualisation, adaptability in this sense is about re-defining buyer journeys in real-time based on automated analysis of audience engagement data. Tomorrow’s automated tools will need to adapt the buyer journey path at every stage and turn, driven by their digital body language. Instead of being limited to a single channel, there will be a new kind of ‘adaptive campaign canvas’ across all channels and that adjusts in real-time.
Near-future marketing automation platforms will have adaptable campaign canvases and experiences that build themselves. A self-learning AI platform will compile disparate elements together to create the ultimate real-time, adaptive, optimised experience for each user.
Future multi-channel adaptive campaign canvases will adjust the entire buyer path in real-time, not only based on behaviour and profile data but also previous conversion data for that target user profile. And they will continuously learn from all their previous interactions and get better and better and better at knowing when to convert, and what’s converting.