“Data-Driven Thinking" is written by members of the media community and contains fresh ideas on the digital revolution in media.
Today’s column is written by Zimm Zimmerman, vice president of personalization at Merkle.
Yes, it is still marketing.
At its core, marketing is still focused on the fundamentals, including brand reinforcement, a compelling offer, incredible creative and a desire to drive a predefined conversion.
The marketing community has adopted an arsenal of technology that helps it understand, manage and execute against any context, with the appropriate content, across any means of connectivity. This amount of technology and data has resulted in the rise of the marketing robots – real-time algorithmic decision engines that automate the orchestration of connectivity between context and content.
While marketers argue over whether these decision engines should own or manage the customer experience, with the utilization of automated algorithmic decisioning engines (or artificial intelligence), robots already are managing more of the customer interactions across all marketing channels. And they’re even seeping into service centers and sales.
With the rise of automation, what role do humans still need to play in the marketing ecosystem?
Marketers provide the fuel, conversations and directional data sources that power the technology.
Providing The Fuel
First and foremost, decision engines and AI both rely on lots of data. However, at some point, this data focus must be directed and fine-tuned. While a lot of data can be beneficial, too much data may be distracting.
It is up to marketers and data scientists to define the amount and type of data fueling the technology. Over time, humans will focus on understanding and optimizing the decision engine’s data usage to drive optimal performance. So while the technology runs on data, marketers provide access to premium-grade data.
To manage a customer’s interactions across multiple channels, robots will require a vast repository of collateral that has been developed and defined by marketers. Marketers need to outline the metadata associated with each piece of creative so that decision engines can process and learn which piece works on a customer on a segment-by-segment basis – or, in some cases, an individual-by-individual basis. Creative metadata is the fuel by which robots will optimize the copy, creative and call to action to an engaging and conversational level.
Defining The Customer Journey
While the collateral provides a piece of the conversation, marketers’ understanding of the goals and objectives of the customer journey will still be paramount to helping guide and power the machines. Marketers will need to clearly define and flag each stage of the customer journey that leads to a defined conversion, which could be anything from a product purchase to a form completion.
These flags, along with other journey-related data, will once again help decision engines understand the progression of the customer from one point to the next and optimize the experience.
The exciting part is when the tech learns how to move each customer segment smoothly and even efficiently through the customer journey, while leveraging the right conversational pieces at each stage of the journey.
In the coming years, we can expect to see more decision engines and AI infiltrating every aspect of marketing, sales and services. While artificial intelligence and processing speeds boggle the mind, companies will still need the marketing team.
Companies will need data scientists to provide and optimize the data leveraged by the technology.
Companies will need marketing creative teams to develop the collateral to maintain customer conversations.
Strategists will also be needed to define a strategic customer experience that helps align the tech to companies’ business goals and objectives.
The success of this technology is heavily reliant upon marketers’ strategy, creativity and data. All of this technology is nothing more than the newest form of execution and analysis – at least for now.