Artificial intelligence (AI) instruments are in every single place. You can barely go to the bathroom with out an AI system there prepared to help. Every instrument in your CX stack is leveraging some form of AI for market segmentation or personalization. But the worth of AI for CX doesn’t cease at instruments.
In reality the prepackaged instruments are usually not essentially the most useful factor about AI in your CX. The pondering that goes into designing and constructing AI techniques is itself essentially the most highly effective instrument for reexamining your buyer expertise. Let’s dig into three AI problem-solving ideas and see how you should use them to refine your CX stack and create distinctive buyer experiences.
AI Inspiration #1: Problem Reduction
In the 1950’s first wave of synthetic intelligence, researchers created a software program program that might mimic how people resolve issues. The design of the Logic Theorist program was primarily based on breaking issues down into smaller, easier issues. By fixing every part downside, the intelligence system constructed as much as fixing the main downside. The options to the minor issues compounded into the final word answer.
CX challenges can current as large, overwhelming issues. Using Problem Reduction, you are taking an enormous downside like making a 360° view of the shopper throughout all your enterprise platforms and scale back it to 1 preliminary query: “What needs to be done to do that?”
You’re saying, “Well … it’s not that easy.” But it truly is. Let’s check the logic with a non-technical downside. Imagine your aim is to get a e-book. Problem Reduction breaks it down into choices for reaching the aim:
- Buy the e-book.
- Borrow the e-book.
Each requires further steps. Do you could have cash to purchase the e-book? If so, you’re all set. If not, a brand new downside has emerged: “Get Money.” Decomposing issues lets you view many various methods to unravel the identical downside, revealing the bottom price (time, sources) possibility.
Let’s sketch out a Problem Reduction for our 360° view:
- Goal: Obtain a 360° view of every buyer.
- Option: Use one system for all our knowledge.
- Problem: We presently have a number of techniques.
- Problem: All the techniques are disconnected.
- Option: Connect all the info throughout techniques.
- Problem: No uniform identifiers for purchasers throughout techniques.
- Problem: Different techniques outline a buyer in numerous methods.
- Option: Implement Business Intelligence (BI) system to create a single view.
- Problem: No normal BI system throughout departments.
- Problem: Each division has a special level the place an individual turns into a buyer.
- Option: Use one system for all our knowledge.
Using Problem Reduction, you may map out potential options. Your CX stack helps you resolve issues, however AI pondering reveals you tips on how to resolve them.
Related Article: Robotic Process Automation: Power to the People in 2021
AI Inspiration #2: Tasks and Processes, Not Jobs
You’ve most likely heard: AI is destroying jobs! But that is the mistaken approach to consider AI. AI isn’t about jobs, it’s about duties. In enterprise, a set of duties make a course of. A group of processes make a job. AI pondering forces you to interrupt down “work” to the duty stage, even additional to the press stage when you’re utilizing Robotic Process Automation (RPA). When you concentrate on your buyer expertise, are you pondering on the touchpoint stage, activity stage, course of stage or job stage?
No matter which CX know-how you’re utilizing, you’ve most likely constructed a buyer journey map. Different mapping methodologies have completely different representations. For our functions, consider a journey map as a sequence of phases and the emotional context of the shopper that accompanies every part. Do your phases have the correct stage of granularity to adequately characterize a buyer? For instance, in mapping a buyer’s assist desk name journey, do you embody transfers and their attendant emotional transitions? A part could also be too high-level to present an correct image of what’s actually occurring.
Leverage your CX stack to get the correct constancy of information. You would possibly must tweak your system to seize extra knowledge on particular phases. The secret is to establish the constancy that works for your enterprise and tune your techniques (and diagrams) accordingly.
AI Inspiration #3: Enhancements, Not Replacements
AI isn’t a substitute for people. We at Mind Over Machines discuss this quite a bit, together with in our Workforce Ascension & Enhancement (WAE) framework, as a result of employees are afraid of automation till they see its outcomes. AI can’t do every little thing. It can’t even do most issues but. AI can do very specialised issues that it’s straight skilled to do. Beyond the constraints of AI, automating each facet of enterprise for price financial savings reduces innovation and worth technology. If every little thing is completed the identical approach each time (how AI must do work), there isn’t any artistic spark towards organizational development.
AI-powered CX techniques allow people to create increased worth buyer experiences together with your model. And the nice information is your workers already know tips on how to greatest use the time created by CX automations. Just ask them. But be ready for criticisms of your present CX stack that point out you aren’t getting the ROI you anticipated. If your staff spends extra time managing the know-how than innovating private touches alongside the CX journey, it’s good to study whether or not your instruments are literally enabling enterprise or simply getting in the best way.
Related Article: Do CDPs Really Make Marketers Independent of IT?
AI: From Hammer to Mindset
“When all you have is a hammer, everything looks like a nail.” AI has flooded the enterprise world a lot that we see AI solely as a instrument, a hammer to be utilized to every little thing. Approaching AI as a mindset will allow you to maximise its worth for your enterprise. Don’t get hung up on new CX instruments and options. Use the pondering and problem-solving strategies of AI engineers to rework your CX from know-how stack to impactful, value-generating functionality.
Tim Kulp is the Chief Innovation Officer at Mind Over Machines and a member of the a member of the Forbes Tech Council. He’s attempting to alter the world.