moon phases

Using Human and Machine for Better Customer-Centric Experiences

by John Wells, President, RAPP US

Man versus machine doesn’t need to be a fight to the death. One entity doesn’t have to emerge victorious over the other. Why don’t marketers try to accentuate the strengths of both in order to create a “best of both worlds” dynamic that pushes the customer experience to new heights?

It’s entirely possible. The balance between humans and machines will continue to find its equilibrium. Humans will continue to provide the training and the brainpower. Machines will bring the speed and the bandwidth, which should alleviate humans from doing tasks that may be low-value or that machines simply can perform better. In fact, more than 80% of retailers plan to implement some semblance of intelligent automation by the end of 2021, according to a National Retail Federation survey.

Ultimately, the fact remains that the customer experience cannot be improved upon without the human element. Humans can accomplish great feats without machines, but it’s not true the other way around. Machines can certainly help enhance what people bring to the equation, but they cannot replace the business understanding and context that humans provide. Machines can take human input and understanding and provide tangible outputs, making wide-scale changes very quickly based on human decisions. But the emphasis is “human decisions.”

Adapting in Warp Speed

Finding the precise balance between human and machine involvement to create the most impactful experiences for customers is a delicate dance. The process is iterative and starts with humans in terms of direction, goals, and the types of experiences a brand wants to make. The machines can then take all of the human insights and inputs, which provide decisions and outputs for the humans to react to and govern.

From there, the machines can deliver on those decisions with unmatched speed and accuracy. Thorough human governance can happen if there are business shifts, and individual necessary changes can be made that are then dynamically rolled out via the machines. One hand washes the other, so to speak.

The end result (ideally, at least) is a manageable balance that helps strengthen customer-centric experiences at scale. This balance allows for greater insight, processing, and speed. If you are not enabling large sets of data and content to be analyzed, arbitrated, and rendered by machines, you will be slow and inefficient in your ability to react and go to market. Companies would be wise to take advantage of a machine’s endless computing power. Whereas humans can make sound decisions for only a certain length of time before fatigue sets in, machines can crank out approved algorithms in perfect fashion for as long as necessary.

The machine can make millions of decisions and produce results very quickly. The human, meanwhile, can take what’s in the best interest of the business and make changes so the machines can scale those across the organization. The result is a dynamic, flexible brand that’s adaptive and hyper-responsive to customer preferences.

With the help of artificial intelligence and machine learning, companies can better understand their customers’ journeys and anticipate their needs. On the sales side, the combined efforts of machines and humans can make the shopping experience seamless and delightful. Further, marketers are able to build campaigns that effectively target the right customers with the right messaging, with product recommendations or personalized correspondence sent at the right time.

Marching in Lockstep

At RAPP, we have seen the greatest impact on initiatives with businesses that are looking for enterprise-wide orchestration across business units. While you can start small to build out a proof of concept, the greatest area of opportunity and impact is developing a business model that considers all the aspects of the customer experience across the business — and where the machine can bring unbiased and impartial business recommendations to light. Humans can decide what is in the best interest of the consumer (and, ultimately, the business).

As the balance between humans and machines continues to evolve, companies have a few priorities to establish. One, the process of internal business governance that provides the inputs for the machine needs to be ironclad. You get out what you put in, so the data that is used to create algorithms and make recommendations needs to be clean and high-quality.

Businesses need to clearly define what the machines are better at doing than humans and understand the impact to the overall company culture. Companies also need to recognize when decisions are being made that may be in contradiction to what the machines are telling you. Machines will not understand the intangible component to business decisions — yet. Skilled individuals will always need to provide the context of data to the machines, not vice-versa.