According to Dilip Bhatia, VP, Chief Customer Experience Officer, Lenovo, we can expect the next few years to be significant for the acceleration of AI technology, and with the popularity and commercialization of technologies like ChatGPT (and others), our world will become far more efficient in many ways.
The pandemic saw a “techceleration,” what are some of the changes that came about in CX as a result?
During the pandemic, the world had to make quick adjustments to meet external and internal customers’ needs once face-to-face interactions were no longer an option. Investment in technology to help mitigate the distance created was mandatory to ensure consistent engagement among teams, partners, and customers. Those changes included designing new working models (working from home, hybrid models) and using technology to facilitate that transition with remote collaborative tools, differentiated support delivery, and adjusting process and policies to reflect the new reality.
We noted how the importance of audio and camera skyrocketed for products being used by people working, learning and creating from home. Based on gathered consumer feedback, device users of all ages suddenly started caring about their camera and sound quality. We even had to sticker where these were on laptops at first because some people had never used them before. As a company, we wanted people’s equipment to be optimal for their changing needs, no matter if it’s an entry-level product.
Also, there was a major shift in meeting customer expectations. I tell my colleagues that our competition isn’t strictly other PC makers regarding how high we set the bar on service. Rather, our competition is from innovation rivals across other categories. Companies born on the Internet have eliminated much of transactional friction that can bog down operations which served them well during ‘techceleration’, as such, their customers have the same high expectations of all companies. Lenovo is ahead of the game in part to its already customer-centric company culture.
A few of the more memorable ways global Lenovo teams delighted customers during that time of great change (and quarantine) were: Our service delivery team in Argentina designed and implemented truck support during Covid-19 shutdowns. Literally going door-to-door ensuring needed repair service was done for our customers without requiring them to leave their home. While in India several purchased PCs were hand-delivered to households when supply chains were strained to help families stay productive. I loved hearing all the stories of how teams across the world were going above and beyond to embrace the CX culture even during a pandemic.
AI is already being used in CX. What further kind of changes can we expect with generative AI applications like Chat-GPT/GPT-4 and the others that are coming on the way?
Over the past few months, we saw AI capabilities expand and it’s practically impossible to determine the limits. We can expect the next few years to be significant for the acceleration of AI technology, and with the popularity and commercialization of technologies like ChatGPT (and others), our world will become far more efficient in many ways.
We’ve seen AI migrating from word-based categorizations, sentiment analyses, and long-time model training to generative content, empathy creation, and unlimited verified content creation.
In terms of improving the customer experience, one behavior that can be expected to change is the speed at which content is created, validated, and made available. Insights that can be extracted will benefit all stakeholders, enhancing how big data can be read and helping people understand critical problems and compare products and services.
Regarding how Lenovo as a world technology leader can continue to accelerate digital transformation toward a new AI paradigm, these are all areas that require increasingly demanding operating environments where Lenovo already has a strong foundation. Ultimately, this growth will lead to higher demand for computing power, presenting a significant opportunity for our business.
What are the specific AI tools, apps and techniques that Lenovo is using in the field of CX?
Lenovo is continually improving customer experience using analytics, Artificial Intelligence (AI) and Machine Learning (ML). By consolidating global surveys, responses over time (nearly 11M over 3+ years), and online product comments (66M+) into a single data-lake, we’re able to perform robust analytics across these data domains and use AI/ML to extract granular drivers of satisfaction that could otherwise go unnoticed.
Internally, we’re using AI to understand customer sentiment, areas of improvement, risk reduction, and improvement of processes and policies. For instance, Lenovo’s voice of customer listening tool is powered by a Natural Language Processing (NLP) engine processing millions of comments from reviews, forums, blogs and social channels. We employ an AI spam filter to help us identify only the most important themes in real-time, thus giving functional teams an early warning to any issues impacting a customer’s end-to-end experience so they can act.
We must consider the diversity of all our customers and partners, respect their preferences, and the best method to deliver what they are looking for. It’s a fact that new generations were born online and are mainly willing to engage through online channels.
What’s more, our CX team utilizes ML and regression analysis-based methodologies to predict the OSAT impact (higher/lower) of any discovered themes based on incremental changes in one or more areas simultaneously, helping teams prioritize which actions to take, and when. We’re also piloting a Risk Analytics module using AI/ML algorithms to help signal to sales team when a client retention plan may be in order.
As of now, all our chatbots are AI-driven and customer-facing tools. We are experimenting with many different tools and technologies (ChatGPT, Bard, etc.) to understand better which model (or combination of models) suits our business and partners better. Our CX team is still in the “sandbox” phase and has started exploring key use cases in support, e-services, and e-comm, building points of contact to evaluate the integrity/reliability of results and risks, and identifying partnerships to help accelerate solution delivery.
How are various industries and verticals using AI differently in the field of CX?
AI models may be ‘shiny objects’ but they’re not one-size fits all. It depends on what information is available and what kind of issue/situation you intend to address. We see search engines having the most potential in the market now because, over the years, the amount of content available is disproportional to the human ability to consume and the validity of the information shared. We see investments from different industries in AI enhancing intelligent assistants, communication channels, self-service support, sales generation, and customer retention.
When it comes to CX and keeping pace with the competition, a better challenge is to benchmark against yourself – that way, your focus becomes lifting your performance by monitoring your CX metrics and instituting technologies that positively impact the end-to-end experience, and not on someone else’s approach.
Going forward, is the focus totally going to be on the digital customer in CX given the fact that everything is going online?
Not really. We must consider the diversity of all our customers and partners, respect their preferences, and the best method to deliver what they are looking for. It’s a fact that new generations were born online and are mainly willing to engage through online channels, e.g., social media, but we see the need for human connection and exchange within the same generations too.
What’s often overlooked about customer communication is the need to let customers choose how they want to communicate, even if they choose not to. Also, customers want to know what is relevant to them, so we need to deliver timely information without being intrusive.
Any business can understand the needs and preferences of its customers by listening. Today, you can listen to your customers’ feedback in many ways. Some effective ways to do so are big data analysis, customer surveys, chatbot logs, email exchanges, phone conversations, research projects, customer advisory forums, and face-to-face meetings.
As a company, you must constantly ask: ‘what are customers saying on social media? On product forums? In chat sessions, on WhatsApp, and email?’ The tech to support CX is always evolving and always improving. ChatGPT is an example!
How are you exploring the application of AI-generated content within your devices?
Sure, you can bet that Lenovo intends to leverage this popular technology in its smart devices and other products in the works. We’re also exploring the application of AI-generated content in our solutions and business.
For example: We can optimize and tailor generative models in Lenovo smart devices to generate custom content.
We can also use AI-generated content in product marketing and building awareness.
We’re also developing a new approach that combines data and knowledge, known as hybrid learning, to improve large-scale AI models.
Additionally, we’ll need to address the challenge of adapting large-scale AI models in new environments,
domains and tasks. This is known as adaptive learning, where we’re actively researching and developing solutions.