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Artificial Intelligence in Customer Experience: 10 things to consider

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Artificial Intelligence (AI) has been there for several decades now but has followed hype cycles of renewed ‘springs’ and cold ‘winters’. 2017 started a new dawn in the AI lifecycle with promises of game changing evolutions to customer experience.

For one very simple reason – we, as consumers, want to do more with less. We want our lives to be easier. Omnipresent smart devices coupled with improved technology of AI promises to deliver that panacea.

But are enterprises maximizing on this opportunity to deliver a better customer experience? Many organizations are indeed investing in AI to enhance their CX or to make their product & services smarter and more efficient. However, a recent study by Capgemini’s Digital Transformation Institute found that most companies were not applying a consumer lens when designing AI initiatives; only 9% of organizations check on consumer preferences when thinking about AI implementation, and as many as 62% of organizations prioritize cost of implementation and 59% of organizations prioritize expected ROI ahead of consumer comfort or solving customer pain points, which scored the lowest.

Despite these barriers and the somewhat early maturity of AI, it can’t be disputed that AI provides immense potential for delivering great CX. When done right, it is a big differentiator and results in significant benefits – such as greater advocacy and increased loyalty. So, I believe there are several reasons why enterprises need to start thinking of introducing AI within their businesses.

Here is a list of 10 things to keep in mind:

1. Average Joe is not only increasingly aware of AI but is satisfied: Increasingly consumers are what we call “AI-aware”: they are consciousof having interactions enabled by artificial intelligence (be itchatbots for customer service, facial recognition for consumer identification, voice conversation via a smart speaker or a smartphone, etc.). Our research suggests that 69% of the customers were aware and satisfied with their interaction, because they felt they had greater control over the interactions, enjoyed 24/7 availability and achieved faster resolution.

2. Customers are beginning to expect ‘Intelligent recommendations’: Intelligence is part and parcel of everyday life – it is a default. So much so, that the limitations of AI can often be frustrating. We wantAI to have the ability to hold a sensible conversation with our preferred language and be able to use personal data to better provide more relevant recommendations.An ideal example would be Spotify being able to understand your choices and recommend right music for you.

3. But, they still want to talk to “Humans”: Here is the catch. Though we want to interact with machines, we want them to be human-like. Even when we are very aware that we are talking to a ‘machine’ we want it to have human-like qualities such as show empathy, humor and emotion. Our research suggests that people do like the voices of Google, Siri or Alexa and the choice they provide between male and female voice.

4. Customer preference and CX should be at the core of your AI strategy: AI implementations should never be a ‘me too’. The core of AI and Digital CX transformation should always start with providing improved experiences for your customers. Our research suggests that only 9% of the organizations think about customer preferences when implementing AI and that 62% focus on costs!

5. Consumers pay more for better CX: It is clear by now that the best way to attract consumers is to provide them with superior experience. And they don’t mind spending more to get it. In our previous research, we found 80% of the consumers are willing to pay more to get better CX. These consumers also bring in better advocacy and loyalty.

6. Technology continues to evolve: We must not forget that despite all the hype, AI is still emerging and has earlytechnology issues for first adopters. Cognitive Computing, Deep Learning, Natural Language Processing, Computer Vision, Machine Learning, Neural Networks, etc., are all in a constant state of evolution. There are better versions of “intelligence” that are coming out more frequently now.

7. Be prepared to make changes to your Core: Often in the pursuit of better CX, enterprises tend to focus their efforts on the front-end of enterprise IT systems. But, it is becoming clear that these front-end changes are beginning to drive the changes to the core. It could be Cloud, API, IoT, etc. Some enterprises who are reaping benefits of better CX already, have started to rebuild and realign their core.

8. Keep your data aligned and organized: AI thrives on data and associated analytics and insights. The best CX is provided when you influence the customer behavior in ‘real-time’ and when its tied to the business context of that moment. For example, an electronics major has a maximum chance of conversion when a customer, who is looking to buy that Home Theater, having done enough research, is at the store and just completed the demo. Time is ripe to push that 10% discount offer now! So, it’svital to have the data that can influence the customer behavior, organized and ready for extracting analytics insights.

9. AI can’t make moral decisions: There are many conversations regardingAI and its ability to make moral decisions. A common example is how should a self-driving car manage the terrible choice between hitting a person on the road versus hitting a tree and thereby hurting the driver? Suffice to say AI is not (yet) equipped to consider all the factors to make complex decisions, particularly the ones related to human morals or emotional empathy.

10. Fully understand the risks involved: Most of us know the story of AI gone wrong in Arthur C. Clarke’s novel, 2001: A Space Odyssey, where HAL 9000, the killer supercomputer, started killing humans to protect its own ‘life’. This scenario is probably a thing of the past and such a doomsday is not likely to happen. But there are still lessons to be learnt from this fiction – when customers entrust their personal data to enterprises, it’s imperative that such data is protected and used for the ‘right’ reasons in improving CX. Similarly, the wrong analytics should be kept away from human life-threatening situations, for example the wrong diagnosis of a patient condition.

In conclusion, thanks to evolving and adaption of AI into CX, we are beginning to see enterprises are attempting “true” personalization with predictive capabilities in real-time. This means better listening to your customers, understanding the context and providing them with a CX that they would like to repeat, over and over again.

By Darshan Shankavaram, EVP & Head – Digital Customer Experience COE – India

If you have an interesting article / experience / case study to share, please get in touch with us at [email protected]


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