Why bots make poor customer service agents
By ian tomlin | Jun 09, 2021
Customer Service Experience is the most frequently targeted area for digital transformations in the corporate world today. This is understandable. In a world that has come closer thanks to mobile telecommunications and the always-on web, buyers want to serve themselves with products, services and knowledge at any time of day. To achieve that level of service delivery capacity, firms are turning to bots.
The fact is, even when powered by artificial intelligence, most chat and voice bot solutions for online messaging chat aren’t proving that effective in responding to enquirer needs.
The problem? Chat and voice bots aren’t born clever. They have to be programmed to respond to questions. Normally, that exercise is largely manual and guided by trial and error guesswork.
Training chat and voice bots is a task that’s become the bain of IT teams. Fortunately, Artificial Intelligence (AI) technology plays a key role these days in helping bots to learn. Using AI means designers can ‘feed’ bots with lots of data to learn from overtime. That pre-supposes that enquirers continue to ask questions, and, if your bot isn’t very helpful, that can become increasingly unlikely.
The role of Natural language Processing (NPL)
AI is just one technology employed by bots to learn. To maximise their effectiveness, bots need to understand a great deal about linguistics, and that’s where NLP comes in. Wikipedia describes Natural Language Processing as a subfield of linguistics, computer science, and artificial intelligence concerned with the interactions between computers and human language, in particular how to program computers to process and analyse large amounts of natural language data. In the case of bots, one of the biggest challenges for ‘trainers’ is to overcome the challenge of missed intents. These are occasions when the bot simply doesn’t have a clue what the enquirer is talking about. You can imagine, for a newborn bot, this happens more often than not. Traditionally, the only way to train a bot to learn new intents has been to have an IT analyst sit there and program them in one at a time, chiefly because the AI engine doesn’t have enough data to learn, or its intellect to interpret language is insufficient.
INTNT.ENGINE is one way to overcome this. It is a Software-as-a-Service (SaaS) platform that companies can painlessly plug into their technology ecosystem to train bots to constantly learn the complex nuances of language they don’t have the skills to learn organically. Learn about INTNT.ENGINE
What happens once you’ve got trained chat and voice bots?
Training your bot is completely worth it, and with platforms like INTNT.AI, it’s no longer the burden on IT that it used to be. Consider what your customer experience looks like having trained your chat or voice bot: Suddenly, your bots are conversationalists because they listen well and ask the right questions to help direct your enquirer to the most appropriate solution–without having to transfer enquiries to voice customer service agents (saving lots of money). Furthermore, they are available to your audience on mobile, tablet and desktop 24 hours a day, 7 days a week! They never tire, they never take breaks, and they constantly capture data insights about what matters most to your customers and prospects.
Thanks to AI-driven platforms like INTNT.ENGINE, IT teams no longer need to dedicate IT resources to manually programming bots. Instead, bot managers need only focus on exceptions presented to them by the training platform, requiring a simple one-click acceptance to progress.
Bots can grow to become your biggest source of new business and market research
What many business executives ‘miss’ when they consider the RoI of investing in bots is the fact that today, customers and prospects with buying needs often find themselves with no simple way of exploring solutions other than searching the Internet for articles on their favored social channels. Strategies to source new sales leads often default to paid advertising on the web. These sales leads are expensive, sometimes costing up to £200 per lead in industries like financial services. on other occasions, prospect business finds its way onto popular intermediary sites like comparethemarket.com, confused.com and moneysupermarket.com–which means they have to pay commissions for the leads they receive.
A simple alternative is to train your bots to be useful. In live case stories, INTNT.ENGINE is producing hundreds of new leads every day for its customer base through its ability to train bots to identify missed intents and recognize them as new business opportunities.
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