Hottest Marketing Job Title of 2019

One of the best ways to gauge the direction the marketing landscape is trending is to note how teams are being staffed as well as the make-up of those teams. What does 2019’s top trending marketing job title signal to marketers about the direction we’re heading? What does it say about the skills required by a modern data-driven marketer in order to get ahead in a competitive field? Let’s discuss and dive into what we individually and organizationally must be done to best optimize the combination of marketing people and ever-smarter technology.

A recent report by IBM Watson Marketing covering a variety of trends identified the ‘Director of Marketing Data’ title as the “hottest new role” for 2019 in part based on organizational needs to drive deeper human and technology connections in order to produce better outcomes. Do you need a ‘Director of Marketing Data’? According to the report the answer is “yes” if you want to gain mastery over your data and make the most of its potential to drive better marketing results.

Advanced customer segmentation, deep personalization and lazer-guided messaging can only be achieved if data is gathered, organised and interpreted in the right way. But today there’s an even more pressing need to better manage data: the rise of machine learning and AI.

The evolution of intelligent marketing tools makes data management of “mission-critical’ importance according to IBM. This claim is supported by a MemSQL survey of company executives which identified machine learning and AI as the most significant data initiative of 2019.

The technology is no longer an exotic concept to be considered at some point in the far-flung future. Neither is it the exclusive domain of the world’s biggest companies; there’s an AI solution for businesses of almost any size. It’s here and ready to be utilized…

…But only when you’re ready.

Because AI isn’t just a tool to be bought. It requires a savvy understanding of how it will benefit the business (think customer), fit within the marketing team’s operations and also how the team will have to adjust to it.

That’s where the ‘Director of Marketing Data’ comes in, but whether you create a new role for the task or simply re-educate and empower current marketing heads, your team, not to mention technology, needs to be capable of coordinating and managing data in a more fluent way.

So, where’s your strategy?

Let’s start by looking at current uses of AI and machine learning – and what this means for marketers…

Today’s Intelligent Marketing Machines

Today’s AI and machine learning tools are capable of fulfilling business requirements across a broad spectrum of services including financial, retail, healthcare, logistics services and more. However, for marketers, predictive analytics and natural language processing (NLP) are perhaps the two most significant as they underpin many AI tools and services.

Predictive analytics use data, statistical algorithms and machine learning techniques to identify the likelihood of future outcomes based on historical data. Use cases vary greatly. At the cutting edge, it’s being used to predict consumer trends that have yet come to pass, such as in the case of Black Swan Data successfully analyzing social conversations around green tea in order to predict future tea drinking trends.

A more basic example is the classic recommendation engine which offers suggestions based on previous buying and search patterns. Facebook’s algorithm, which matches ads to users, helped it make $16.6 billion of ad revenue last year.

Meanwhile, natural language processing technology underpins the ubiquitous chatbot. In an ideal world, chatbots or automated customer service assistants help provide customers with the right information as and when they need it, learning from past interactions to become ever more useful to users.

However, consumers are not always convinced. According to research by Acquia, nearly half (45%) of consumers said they generally find chatbots ‘annoying’ — with 78% of consumers citing their impersonal nature as being a key problem. We wrote more extensively about this very issue as part of our dive into Balancing Human & Artificial Intelligence.

Clearly, some organizations are failing to implement the technology successfully or properly collate customer feedback to highlight areas that need improvement.

Getting ready for AI in Marketing

So, while there are plenty of cases where AI and machine learning is providing huge benefits to businesses, there are also many stories of bad implementation.

A study by MarTech Advisor revealed some of the common challenges that companies faced when implementing AI. They included:

? Lost Customer Centricity – 63% felt they lost sight of the customer

Key lesson: ensure the customer is front and centre of your AI agenda.

? Organizational Gaps – 72% felt there were gaps in skills, roles and policies

Key lesson: don’t rely on a ‘learn as you go’ approach – unless you’re starting off on a tiny scale.

? Data Management – 44% cited data and analytics challenges.

Key lesson: get your data ready and aligned across the whole team before implementing AI.

? Too Much Too Soon – 81% indicated trying to do too much with the technology before they were ready.

Key Lesson: Master a Specific Use First

Together this summarizes a key point: rather than leaping in and making avoidable errors, organizations are better served to master their current data setup. That requires integration of all the data points of your various IT and marketing platforms.

A user’s journey must be trackable from the moment a user clicks on a PPC advert, arrives on your website, signs up to your newsletter, enquires about your product, enters the CRM system and then gets served by the customer services team. It should be a seamless user journey with the different platforms talking to each other, exchanging data.

It’s only on this basis that you can be truly ready for the next step of AI and machine learning.

As IBM’s report states:

Those companies where marketing struggles to partner with IT, customer support and e-commerce and to integrate relevant data across channels, functions and systems will essentially be limiting their AI marketing systems from making accurate or reliable decisions and recommendations.

For many companies, it means there’s still a lot of work to do. Which is partly why a new report by Episerver predicts that AI will fail to gain mainstream adoption among marketers until at least 2021.

As Joey Moore, Episerver’s Head of Product Marketing, explained:

“…while marketers are investing more and more in technology, some of the basics are being missed. Many marketers still don’t have a responsive website or a clearly defined mobile strategy and, of those that do, many more are not providing a seamless omnichannel experience.”

In other words, the first step towards AI adoption is getting the data basics sorted first.

What Can We Learn from 2019’s Top Marketing Job Title?

AI and machine learning promises a lot, but can it deliver? That depends on whether you’re ready. Really, it’s something that needs to be worked – rather than rushed – towards.

The latest Customer Experience Trends report from Acquia suggests many will benefit from holding fire. It reveals that 84% of marketers want their various marketing technologies to work together but are unable to make that happen. And yet the same percentage say more marketing tech will play a part in their strategy!

Whether it’s the fear of missing out or the allure of what’s shiny and new (and most likely buffed up by vendors); today’s decision makers are still too keen to hit the ‘buy’ button. But perhaps there’s something else… buying things is easy, getting your marketing data in order is hard work.

All the evidence points towards the need for an extra someone who can own and coordinate cross-organizational marketing data.