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Technology continues to make for new possibilities for marketing, and the role of the marketer — now more of a moving target — is changing with new tech, more channels, and, as we’ll discuss in this post, accumulation of more data.
The worlds of technology, data, and personalization have converged. If this were a tale, it might sound something like this: cloud computing broke on to the scene within the last decade… enabling better storage and organization of what we’ve deemed big data… marketing automation tools have standardized and accelerated all the things we can do with data… and AI (such as chatbots, predictive content engines, adtech, and 1:1 personalization) have catapulted all of this into another stratosphere.
How are marketing teams evolving? Where are they getting the skillset to deal with data? As the world around becomes more fragmented and complicated (and as new technologies like blockchain and AR/VR come to the forefront), how can you simplify all of it for better outcomes? And where do your opportunities within all of this lie?
The Impact of Big Data on Marketing Organizations
In short, big data is now and will continue to augment marketing in many important areas. Soon, AI will do the same. Today, almost all marketing organizations are using big data, and while first-party data is your most valuable asset, data itself has become both commoditized and democratized, as I wrote about a couple weeks ago.
I’m most interested in where data is going — the functions or features data will enable which doesn’t already exist. Rule- and outcome-based marketing is one area that’s going to take off.
At the moment a human decides on the strategy and tactics behind achieving a goal. Imagine, though, if we could categorize content and products, as well as categorize customers in cohorts and events. Having an interface that enables us to just define the goals — but that lets the machine execute towards that goals without the marketer to select which content for which client on which channel at what time — would be a revolution of what is, today, the status quo in marketing execution.
“Imagine a future where marketers simply define goals — but where a machine executes in selecting #content, #channel, and which #customer to send to” says @eisenhut_dan CLICK TO TWEET
The Marketing Team of the Future: Mapping out Your Team and New, Key Roles
AI skills are spreading quickly. Do marketing organizations need dedicated data scientists or machine learning experts to leverage data for AI?
Part of the promise and benefit of AI-driven marketing platforms is that you don’t need developer-like or AI skills — marketers with no technical experience can now reap the rewards of such systems.
But that’s not to say there isn’t a market for or value in people with expertise in that area.
If you only have one source of data entry and 100 products, it might suffice to just use business rules across relational tables vs. letting the machine decide. If you leverage multiple channels and have several thousands of items, this is where the matrix of combinations begins to get complex to manage. If you have never used any machine learning approach before, ideally you’d first contract with a software provider who also offers to consult outside of pure software. Once they prove the value of a machine learning approach, the next step is to evaluate how your own team can learn the same skills by engaging with the experts. If your own team realizes they will not be able to handle the day to day, then you should reach out to specialized talent platforms using popular networks like Upwork, Topcoder, and Kaggle.
But with this in mind, what new, key roles might your marketing team of the future have?
The new marketing organization
The new technologies and advancements in data science that we’ve been discussing will open the door for new kinds of leadership and managerial roles in some (mostly retail) industries. Here’s three new jobs that will begin to emerge.
► Chief Experience Officer
Many customer-centric leaders have been clamoring for a Chief Customer Officer for a bit now. Soon, we’ll start to see the emergence of a related position, the Chief Experience Officer. This person will purely take care of the customer experience for companies that sell any products and services.
► Augmented Reality Manager
AR/VR technologies are becoming a core part of marketing. But the development of the technologies hasn’t really sat “in marketing” because most marketers can’t program these kinds of machines and the development of them isn’t a marketing activity. Soon, though, the gap will tighten and uniquely-talented people with both right and left brain competencies 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, like customer support chats. Bots hold great potential for both desktop and mobile. 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.
New & emerging technology will warrant new #marketing jobs like CXO, Augmented Reality Mgr, & Bot Developer CLICK TO TWEET
How Blockchain Will Impact Marketing, Data, and Your Team
Data protection and privacy are huge concerns right now for consumers. If it seems like cryptocurrency and blockchain are all the hype, it’s because they are. But how will blockchain encryption impact marketing in the near term? I see three ways.
As brands continue to pull online ad spend amid concerns over data safety, deploying blockchain for ad verification could prove to be a supportive endeavor for marketers.
Blockchain could provide a mechanism for brands to know ad placement. The global forecast for revenue lost to ad fraud in 2017 is approximately $16.4 billion (Business Insider). Considering how expensive ad delivery auditing is today, blockchain offers a cost-effective alternative – decentralized ad auditing.
With blockchain, you could potentially take ad deliveries from a server, and then release them to the mining machines, which would then analyze them for fraud. Simple indicators like a “non-live” browser supposedly seeing an ad can help determine if the ad delivery actually took place. The next step down the line may be identifying that kind of fraudulent activity, and blacklisting it in real time.
► Data Protection and Regulatory Compliance
With the GDPR coming into effect across all major markets, you can also leverage the blockchain technology to store large volumes of customer data securely.
The technology benefits from being securely encrypted and decentralized are that such measures offer an alternative to traditional data storage methods. Additionally, regulatory compliance to the GDPR that will require marketers to take consent from their customers can also be managed through blockchain.
Blockchain experts expect marketers to use this technology to negotiate consent in an era of mandatory digital consent.
► Media Buying
Facebook and Google have transitioned their business models around their programmatic advertising and display ad offerings/networks. Google is essentially the middleman that helps advertisers and website owners build trust with each other.
But what if an advertiser and a website owner already trusted each other? They wouldn’t need a middleman to take a cut off of their profits. By using blockchain technology for programmatic buying, advertisers can easily verify if a user is authentic, and ensure that the website owner is only charging the advertiser for real clicks. Blockchain could very well change Google’s display network model approach.
The On- and Offline “Data-to-Device” Relationship Will Improve CX
Marketers are already starting to use offline data to influence the digital experience. One untapped area of data management is how online behavior influences offline advertising and offerings.
If I walk into a store, I’d love to have a personal assistant — based of all the data points I’ve given a company via every channel — that could support me in buying decisions of more expensive or luxurious products. A personal assistant like this could be accessed either via an iPad I can take with me when I enter a store (and get product locations based of online wish lists, browsing, cart, or purchase behavior) or even a human consultant.
➤ Use Case Example: Let’s say I walk into a furniture store. I indicate, upfront, to a sales consultant which products, materials, and colors I’d like to talk about in detail instead of the painful process of losing time by being consulted around products I already dislike. This is just one simple example how the unified customer profile can create a positive sales experience for both sales consultant as well as the client.
Data and augmented/virtual reality
Ever wondered what the implications of all of this customer data you’re collecting will be on augmented/virtual reality systems once you have them? Let’s not jump forward too far (these technologies are several years in the future), but it never hurts to take a look into the crystal ball.
Amazon Go has already spurred the next phase of retail by letting you get in and out of a store quickly — with their in-store systems, you select what you want and walk out without standing in line.
This in-store experience (paired with same day delivery) will not only decrease the cost to run a physical store, but will also finally offer a means for impatient window shoppers to start to buy more.
On the other hand, wearables like Google’s Glass project could start to render additional information about products you view. If you’re on a diet, the overlay can show you, in advance if the selected product is exceeding your daily calorie limit, or maybe if a piece of furniture will look good in your own room. Based on your running behavior, it could also recommend the best running shoe for you.
These are just simple examples how data can start to support humans to actually get meaningful advertising based on real day-to-day interactions with products.
Today, there is very limited information about how we use a product we purchased. But we’re not far off from having a real-time marketing data interface that would allow a marketer to note customer behavior or intent within a brick-and-mortar store and then be able to react to that behavior (with an incentive or product recommendation) before the customer leaves the store. The real challenge will be the time investment into a rich customer-facing interaction — the relevant data and the needed technology already exists.
Closing Thoughts
As a result of all this evolution and convergence of tech, marketing, and data, it seems like data science has become a core competency for any high-flying marketing team. Historically, data work had laid with the IT folks — but they’re now embedded within the fabric of any marketing team that’s trying to knit together their data-driven strategy.
For now, continue to improve your data quality by using clean collection methods. Continue learning and experimenting with new capabilities with a keen eye to the future — looking out for one or two of these pieces of technology that could give you a competitive advantage down the line. ◾
