Harnessing the potential: AI insights for enhanced customer service content creation
By Nico Beukes, Managing Director of Northern Europe for Yext
Many marketing teams have been taken with the idea of using AI, including large language models (LLM) like ChatGPT, in content creation. The allure is obviously the huge amount of time it could save businesses working with tight budgets and a stretched to-do list. However, others have felt trepidation, especially around issues such as copyright and accuracy when creating content.
These mixed feelings have opened a conversation around AI’s role in content creation, or whether there even is a role at all. I think it’s fair to say there’s space for AI’s current capabilities, especially in areas such as customer support content and focus will likely grow here.
However, the fears some have around the usefulness of AI is not unwarranted, and they raise a key point in that AI will only be helpful in content creation if it’s used and applied properly.
Customer support content, such as Chatbots and search functions, is one area of content creation that could majorly benefit from AI if implemented strategically. And it’s certainly something that should be explored when budgets are growing increasingly scarce. Currently, poor customer service is costing businesses $75 billion a year, according to Forbes.
While increasing the headcount of service agents may provide customers with the high touch experience they expect, it’s just not realistic for businesses contending with a turbulent market. The average cost of a live support interaction, whether that be on phone, email, or chat, usually amounts to $13 each time, according to Harvard Business Review – which is pricey.
At the other end of the spectrum, a simple, automated service via Chatbots and FAQ pages is much more cost-effective. But it’s not exactly customer-friendly, often creating frustration. For example, 70% of customers use self-service customer content support, but a mere 9% resolve their issue, according to Gartner.
So, what’s the solution? And where does AI-generated customer support content come into this?
Is ChatGPT and customer support content a winning combo?
ChatGPT and other large language models have the potential to elevate existing FAQ pages and ChatBots by providing genuinely useful information tailored to the customer’s individual needs and delivered in the brand’s tone of voice. By doing this, it positions the business’ customer support in that happy medium between high touch but costly support, and cheap but useless self-service support.
By using language learning models, data can feed directly into your content management system. In turn, search, FAQ, and Chatbots would be updated with the most accurate information in almost real time. It means the customer’s problem is more likely to be resolved as it arises, leading to better satisfaction levels, despite there being no additional time needed from employees.
But hang on, what about the accuracy of ChatGPT data? The AI model only knows the world up to 2021, meaning it’s impossible for it to feed back the latest information into your Chatbot. It’s this point that many naysayers use to dismiss AI in customer content support completely. But inaccurate data is not true of all AI systems, which complicates the conversation.
Preventing misinformation and delivering helpful content
High quality customer support content relies on presenting customers with accurate information. This means AI must be using a reliable source of information, hence the concern over ChatGPT. It also means that AI’s role needs to be accounted for in content strategy, and measures must be put in place to establish an approval workflow to ensure brand standards are maintained and any AI mistakes identified.
Realistically, LLM tools like ChatGPT are still developing, and it’s important that processes are build around its weaknesses to bolster its efficiencies. Remember that AI is a tool and while it can help speed up content creation, there still needs to be human input. The problems arise when AI is left to its own devices to create content.
If you’re considering unlocking the benefits of AI content creation, then there needs to be some governance around what AI will do and what human employees will do. Make it clear from the start what AI will touch in terms of content generation, and what standard employees should be holding content to during reviews and optimisation.
It’s also possible to moderate the source data that AI is pulling from in order to generate content. Building a knowledge graph means a business can carefully curate accurate sources about the brand. This graph can then be combined with a conversational AI interface to present the customer in need with a human-like answer.
Seamless customer experience across digital touchpoints
AI’s role in content creation is currently at a transitionary phase. There are certainly benefits to be gained from AI content which could improve customer experience across digital touchpoints. But these advantages are only going to accessed if the right processes (which I’ve mentioned above) are put in place to support AI content creation.
So, what’s the point of putting in time to setting up these processes? Does that not undo the time-savings gained from using AI-generated content?
No, because AI is likely going to become very standardised within content creation, and being able to sort out these processes now is going to unlock more competitive benefits as they arise. For example, AI generated content is increasingly being integrated into more and more formats such as voice assistants, Chatbots, and written content.
Essentially, AI is going to be able to cover a lot more digital ground than customer service agents and marketing teams can do on their own. And in a tough and competitive economy, providing helpful information across as many touchpoints as possible seems like the safest and most strategic option.
Uma Rajagopal has been managing the posting of content for multiple platforms since 2021, including Global Banking & Finance Review, Asset Digest, Biz Dispatch, Blockchain Tribune, Business Express, Brands Journal, Companies Digest, Economy Standard, Entrepreneur Tribune, Finance Digest, Fintech Herald, Global Islamic Finance Magazine, International Releases, Online World News, Luxury Adviser, Palmbay Herald, Startup Observer, Technology Dispatch, Trading Herald, and Wealth Tribune. Her role ensures that content is published accurately and efficiently across these diverse publications.