What difference will artificial intelligence and machine learning make to marketing leadership and strategy in 2019? CMO asks the experts
As the hype around artificial intelligence (AI) and machine learning (ML) has exploded, data ethics, trust, bias and fairness have all surfaced to combat inequalities in the process to make everything intelligent.
"There are many layers to data morality, and while ML advancements won’t cease, they’ll slow down in 2019 as researchers try to hash out a fair, balanced approach to machine-made decisions,” predicted talend A/NZ country manager, Steve Singer.
“Part of the issue with data morality with AI and machine learning is that numbers and scenarios are crunched without insight into how subsequent answers came to be. Even researchers can have a hard time sorting it out after the fact.
"But in the coming years, while it won’t lead to complete transparency with proprietary algorithms, the black box will still become less opaque as end users become increasingly educated about data and how it’s used.”
Fiftyfive5's Collier said getting a handle on unstructured data, which comprises 80 per cent of the world’s data, is a problem facing all businesses in 2019 and one that AI will finally help solve.
Unstructured data refers to data sets that do not contain a ‘set record’ format such as documents, social media feeds, digital pictures and videos, audio transmissions, sensors used to gather climate information. These will provide richer insights into customer behaviour and perceptions, helping marketers to get closer to their customers.
“AI will draw insights from voice, image and text analysis and help marketers synthesise these disparate data sources to deliver insights on behavioural patterns of consumers that remain otherwise elusive," Collier said. "Furthermore, even greater value is extracted by combining a business’ structured data with unstructured data. Marketers will glean insights they have never had before to help improve targeting, creative and, indeed, the overall value proposition for customers."
As examples, she noted analysis of images loaded to Instagram, call centre call recordings analysed for sentiment and themes, and categorised verbatim comments in feedback surveys will all help marketers uncover insights previously not possible.
"AI enables this analysis to be undertaken at scale and improve day by day as it is exposed to more and more of the same data," Collier added. "Spikes in images loaded here, unprecedented 'likes' there, and sentiment peaks across the data sources, be they voice, text or image, all combine to enrich our understanding of the consumer and help us make better informed decisions.”
With data accuracy and rigidity being significant pain points associated with current BI solutions, artificial intelligence-enabled marketing intelligence (MI) platforms have become the panacea for modern marketers. Rather than provide a historical snapshot of data, MI platforms provide marketers with the data accuracy, flexibility, real-time insights and ability to scale that’s been sorely lacking.
Because of this, we see marketing intelligence disrupting business intelligence (BI), said Datorama chief marketing officer, Leah Pope.
“BI lacks the marketing expertise required for a marketing-facing solution. This means BI has fallen short of meeting marketer’s expectations. Now that MI has arrived though, a paradigm shift is set to start playing itself out next year,” she predicted.
“Many popular BI tools currently lack the agility to integrate data sources from across the various point solutions within the typical marketing technology stack. With enterprise marketing departments already trying to make sense of more than 90 source systems, that number is only expected to grow in the coming years.
“This is a foundational problem that has yet to be properly addressed by most technologies in the market today.”
Again, however, it's the human element that comes to the fore as AI powers more transparent marketing platforms and programs.
“Today, the power of artificial intelligence is augmenting how marketers reach their goals from data integration to real-time insights," Pope said. "Although industry pundits and Hollywood would like the general public to perceive this as the age where there’s a rise of the machines, that couldn’t be further from the truth. That’s because AI will not replace marketers at the end of the day, it is only there to further empower teams in their respective efforts."
Take, for example, many marketers’ day-to-day routine, which largely consists of cleansing and preparing data for analysis. "In 2019, AI-powered solutions will continue to gain market share, allowing marketing teams to focus more of their energy on the strategic and creative tasks critical to their function - and bottom-line growth,” Pope said.
What's more, in the not-too-distant future, AI-powered data integration will become the norm for marketers looking to accurately track customer journeys, Pope said.
"As consumer expectations have changed, they require personalised marketing treatments. 'Spray and pray' type of communications are no longer acceptable,” she said. “Marketers must deliver programs that reach buyers with the right incentive at the right time on the right channel. Anything less is not going to entice customers to adopt any businesses respective product or service."
In order to be successful in this hyper-competitive landscape, Pope advised marketers of all stripes to turn to marketing intelligence to better understand their programs and to push/pull the correct levers to improve upon their respective key performance indicators (KPIs).
Employment Hero CMO, Cat Prestipino, also expected to continue to see marketers integrate machine learning into campaigns.
“For example, we rely on machine learning to help us make smarter decisions on how to reach our customers, the messages to send them and where our sales team should focus their team. We’ve seen huge success with small machine learning tests run in 2018 and we’ll be doubling down on those in 2019,” she said.
On a final note, head of marketing Asia-Pacific for Quantcast, Rachael Townsley, said marketers will continue to look to automation to increase efficiencies and personalisation.
“AI and ML technologies that help marketers to automate will continue to grow. With budgets tightening, automation will help marketers scale more effectively, help inform decisions quickly and reduce operating costs. And with AI and ML driving increasingly more efficient data analysis, marketers will find it easier to deliver hyper-personalisation to their customers, from content creation to unique customer journeys,” she concluded.
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