The following blog post was written by Lindsay Tjepkema, Director of Marketing at Emarsys.
Data and its implications for marketing are everywhere. News surrounding Facebook’s questionable use of user information and a handful of recent legislative changes and regulations around the use of personal data have dominated headlines. Regardless of how these news stories, regulations, or breaches have impacted you, it may feel at times like the future of data is more intimidating and uncertain than it is exciting or inspiring.
The key thing to understand is that while the foundation of what we know about and how we use customer data is indeed shifting, I’m here to tell you it is actually moving in an overall promising and positive direction.
What is the future of data?
In combination, all of the changes that are taking place around data capture, storage, access, and use point to several takeaways I’ll touch on in this post:
- The democratization of data is expanding — but ownership is being restored full circle to the consumer.
- You still need quantity and quality when it comes to data — that hasn’t changed. But how you get it and what you do with it… that’s changing big time.
- AI and machine learning are here and will continue to accelerate the pace of innovation of how we can act on all the data we have. As a result, new roles will emerge within the marketing org (or as a “dotted line” into it).
Whichever school of thought you fall into — whether you’re mindfully ignoring the data landscape or maintaining a hesitant and uncertain view (or even excited about it, like me!) — preparing for the future of data will bring you returns tenfold… if you’re willing and ready.
The vast majority of data today is generated through a handful of technologies that consumers are using every day. As a result, the brands that own those assets/systems/apps — Apple, Amazon, Facebook, Google, Microsoft, etc. — own most of the customer data in the world.
But soon, data ownership will spread. Every brand will have access to the tech and tools to collect customer data. Your product, website entry points, content, omnichannel approach, and customer experience will be the determining factors as to whether customers hand over their information.
To the “omnichannel” point: the biggest issue currently plaguing most marketing teams is unifying various data points from separate sources into one consumer data platform — all while trying to unite email, social, mobile, web, and print into one “source of truth” when it’s time to identify and determine who to target.
Frankensteined tech stacks are a pervasive problem that not only pose serious organizational risk, but also restricts a cohesive experience across channels for users. It blinds you too — if you’re only able to look at data points for individual channels, you’re depriving yourself of the whole picture.
Even with artificial intelligence and machine learning breakthroughs on the cusp, you still need a high quantity of high-quality data to survive and thrive.
You don’t need endless or copious amounts of data; you need enough high-value data to accomplish your goals. With this in mind, it’s important to understand:
- Which channels (2-3) are you trying to drive most traffic to?
- Which channels are driving consecutive product/content views?
- Which channels drive profitable and repeatable conversions?
Once the consumer journey and all touchpoints are defined, determine which data points you want to use from those interactions. This could be a signup with a preference center to better understand website visitors, a mobile phone number at checkout that supports a mobile shopping club, a product view to drive relevant content, dates when these events occur, and more.
As a side note, the GDPR is a blessing in disguise. It requires a higher threshold of consent for customers to opt-in; but that also means that people who sign up really, truly want to hear from you!
Once the sources and interactions are identified, this can be satisfactory for machine learning systems and self-learning algorithms to start making predictions about who the right audience is, what content to serve them, when to serve that relevant content, and which channel is ideal for engagement.
Using data for AI and machine learning
The reality today is that many solutions billed as AI are just basic logic-based systems guided by human programming. Beyond basic pattern recognition, most AI systems aren’t that “intelligent.” But with the democratization of data and continuous development and iteration of software, could this change? I think so.
The function of AI is dependant on the amount and accuracy of data, as mentioned. So once you have data, you can actually rely on AI and ML to take action. For example, you can drive more revenue from first-time buyers or win back more defecting buyers by using AI to optimize content and offer for each person.
You will define the audience, the time of trigger, the content, and the channels, but the machine will execute. In the near future, AI will start learning each area of manual steering and the marketer can start to replace one element at a time (e.g., AI should define the right channel for Content A to be displayed to Customer B).
As we start to replace human decisions for who to target, when to send, what to offer, and on which channel, next-gen AI solutions will start to be strategy-driven and marketers can mainly focus on conceptualizing and creating — without having to focus on the tactical execution of that strategy.
Future roles of the new-age marketing organization
New marketing technologies and advancements in data science will open the door for new kinds of leadership, managerial, and tactical roles. Here are three new jobs that will begin to emerge.
Chief Experience Officer – This person will oversee all aspects of the customer experience to ensure every interaction with the brand at all stages of the buyer’s lifecycle are positive, purposeful, and consistent.
Augmented Reality Manager – AR/VR technologies are becoming a core part of marketing — but the management of these technologies hasn’t really sat “in marketing” because most marketers can’t program these kinds multi-sensory machines. Soon, uniquely-talented technologists who “get” the tech and the market will manage the entire AR experience, especially in retail.
Bot Developer – Bots are already serving purposes across the Internet, transitioning what were basic, human duties into automated replicas. Where mobile apps stand today, bots could stand tomorrow. Marketing-related bots will require developers to program them to not only be smart but also benefit the brand.
Data Scientist – These numbers geniuses will piece together the data, the customer experience, and marketing. They’ll provide much-needed insights into audiences and their behavior.
The big picture
If you didn’t see the big picture by now, the future that awaits us will require, not only an appreciation for data, but also an understanding for how it is collected, managed, and used to maximize the customer’s experience.
First-party data is one of the biggest business assets you have (even bigger than your website, your technology, and your employee base). Data is the lifeblood of any e-commerce organization because of the amount and depth of customer insights it can enable. Data helps you understand the essence of WHO your customers are.
Whether you realize it or not, marketing and data have a co-dependent relationship for e-commerce organizations. It is the brilliance of marketers (and their ability to shine a light on all of this data) to illuminate all of the possibilities, and then create amazing experiences that resonate and drive growth.
Want more detailed information? For more, check out the following resources:
- Can your infrastructure handle the future?
- More on GDPR re-permissioning
- What to do with non-compliant data
- More on how to use big data
- More on risk mitigation related to data
Lindsay Tjepkema is the Director of Marketing at Emarsys. She and her team deliver resources that empower marketers to seek out solutions and strategies that will allow them to thrive by focusing on what they love – strategy, content, and creative – not the technology, itself. Although her true love is tech marketing, she has worked in a range of industries, from life science to talent management, economic development to software development, eProcurement to social networks and more. She has crafted and executed B2B and B2C strategies for brands like Intel, LinkedIn Marketing Solutions, OfficeDepot, SalonCentric, Ashley Furniture, and more. Her experience is built on time spent leading in-house teams, in agency settings, and independently running her own marketing consultancy.