“AI is dependent on human programming and its learning is dependent on the quality of data.” –Themintmagazine
Have you ever interacted with AI (artificial intelligence) and wondered how it knows the information it tells you? The answer lies in its knowledge base, a crucial foundation for creating effective and intelligent AI experiences. AI has become increasingly popular in recent years, providing businesses with a new way to engage with their customers. However, building the knowledge of AI (Artificial Intelligence) requires input. For example, ChatGPT gets its input from a wide array of internet sources.
It is about the quality of knowledge versus the quantity of knowledge that is most important as the principle. “Garbage in, garbage out,” is applicable here. So, ensuring the quality of the data that powers these “digital workers” is crucial for delivering efficient, accurate, and engaging experiences. Otherwise, these digital experiences may actually create negative customer experiences leading to detractors for a brand.
The Imperative for Quality Knowledge
Quality knowledge is the cornerstone upon which effective AI conversations occur. The essence of this lies in the notion that the system reflects the data it has been taught. Take ChatGPT as an example; it is trained on a myriad of internet sources, which can range from highly credible academic articles to less reliable information. This indiscriminate training approach can sometimes result in the dissemination of misleading or incorrect responses (hence, the disclosure on the OpenAI website). That is why a curation of knowledge is critical before designing AI conversational flows.
The sheer volume of data is not necessarily the most important for specific business use cases for AI. Further, ingesting data sources where the quality of information is not fully understood can result in unexpected outcomes for customers. A more introspective approach is essential for organizations curating the right data set to train their artificial intelligence solutions. Some prime targets for sourcing this information are an existing internal knowledge base, FAQs, or even an organization’s own website.
This foundational information needs to be accurate, up-to-date, and cohesive. It not only enhances efficacy but also avoids flawed output, which may lead to negative customer experiences, erode trust, and hurt your brand reputation.
The good news is that once the information has been collated, then this is where technology is a differentiator. Various leading AI technology solutions offer an easy user interface to synthesize this information and “train” the digital AI worker with this knowledge. This is more important than designing AI conversational flows because knowledge training like this increases the vocabulary of a digital worker solution. After all, listening and being able to understand is a key aspect of any communication as well as being able to clearly articulate a point of view, whether human or digital.
“People’s searches dictate their opinions, desires, likes, queries, and pain points.” –Olsenmatrix.com
Broadening Data Sources
While formal knowledge bases provide a foundational layer of information for artificial intelligence training, we should also look beyond this for a comprehensive library of knowledge. Frequently asked questions (FAQs) are amazing sources of practical, user-focused questions and answers that can improve a digital worker’s conversational abilities. An organization’s FAQs offer a view into what real-world concerns and queries customers may have, thereby offering a great basis from which to teach. If this content does not exist, it can easily be crafted in partnership with contact center service teams who are very familiar with the FAQs of their customers. Similarly, product or service manuals contain a wealth of technical information and problem-solving guides that can provide good source material. It is here where you would establish identification flows of a product or service to match to corresponding technical support materials. Do not discount information within your own website either. Generally, these sites have much of the critical market-facing content customers may be interested in learning. Your website contains your industry-relevant language, brand market positioning, and perspectives that can be leveraged as source material to create the foundational knowledge base for your AI conversations.
The SEO Connection
In collating multiple data sources for training artificial intelligence solutions, one completes a data inventory that may have secondary value to an organization. It is an opportunity to remove old or inaccurate content, simplify and optimize processes for easier transaction ability, and identify opportunities for proactive instead of reactive customer experiences. An audit can be completed against knowledge available internally to an organization versus the knowledge made available externally. This exercise usually identifies opportunities to make knowledge externally available for increased customer education and self-service.
By placing additional useful information for customers to be available externally on a website; it can also significantly elevate your website’s search engine optimization (SEO) performance. Let’s break down how this works. First, there’s the aspect of keyword synchronization. A digital worker will need to be taught industry-specific terminology so they can appropriately interact with users. If industry or brand-specific terminology is required to train a digital worker, then it is likely this information would also be useful to be made available for customer education as well. You will find there is considerable alignment between digital worker vocabulary and having those same industries or brand-specific keywords on your website to boost your site’s SEO scores. After all, search engine indexing could be argued as an early artificial intelligence solution.
In addition, when we deploy artificial intelligent solutions, we can drive an enhanced user engagement score on websites. Search engines prioritize websites that offer users a smooth and engaging experience, and the more engaging a site is (measured by user activity on your site), then the higher your score. An engaging AI experience that your customers love with substantially elevate these metrics, which is critical to higher SEO rankings. Further, AI systems that effectively address user queries and guide processes are pivotal in reducing bounce rates and improving a website’s SEO by preventing premature visitor exits.
Market Intelligence Benefit
Processing these data points into actionable insights requires experience, but this is where iCXeed excels as a business process innovator. Our experts review customer intents with a cognitive lens toward proactivity, digitization, and/or automation. Where there are identified gaps, we use the opportunity to optimize these business processes or improve these digital worker interactions. It is about delivering to your customers a simple digital interface that reduces dependence on human support. You are now armed with the intelligence to build such a solution.
The collection of such data while engaging in AI conversations offers a unique constructive collaboration. It empowers businesses to refine their offerings and strategies based on real customer sentiment providing a rich source of information that can shape an organisation’s decision-making and strategic planning to be more customer-centric.
Are you seeking fresh perspectives and alternative approaches to customer experience? We believe that traditional BPO partners may not be entirely focused on the total customer experience, which should encompass far more than the common performance indicators of CSAT, AHT, FCR, and NPS. It’s time to think like a business process innovator and view your contact centre with a digital-first customer experience lens. Learn more here.