As soon as the first chatbots appeared on the market, businesses were promised mountains of gold from savings on customer communications. Juniper Research predicts that by 2023, bots will save the banking sector, healthcare, and retail worldwide up to $11 billion per year. But seeing a profit in monetary terms is still something far from everyone manages to achieve. Here is what trips businesses up in their pursuit of artificial intelligence and how to learn to save (and even earn) with conversational AI.
Executives often place too many hopes on implementing conversational AI. Companies come to developers with ambitious goals like: "I want to fire the entire sales department — let the bot sell." But a bot won't plug a hole in your strategy or marketing; a bot won't suddenly shower you with customers and money. A bot is a tool. The catch is that businesses often don't know what they want from it.
A startup's options include initial consultation, delivery processing, order confirmation, lead generation, and so on. Russian businesses still view bots exclusively as a cost-saving tool, rather than a revenue-generating or audience-expansion tool. Yet a smart marketing skill for a voice assistant can generate net profit. An inspiring case study was demonstrated by Nike earlier this year: during one NBA game broadcast, TV commentator Ernie Johnson announced that right then, while the game was on, viewers could order a pair of Nike sneakers from a limited collection simply by asking Google Assistant. The sneakers cost $350, and 15,000 people reserved them in 6 minutes.
You don't have to act on such a grand scale right away — even a conversational game for a voice assistant that offers the user a discount on your brand's product at the end can boost sales.
Reducing the costs of maintaining a contact center, for example, is easy to calculate based on OPEX (operating expense) — this includes rent for premises and equipment, employee salaries and training, and other expenses, including daily customer service costs. On the other side of the scale are the investments and labor costs of building a bot, the volume of requests typically handled by employees, and the traffic the bot will be able to handle.
Efficiency is a more complex story — it's more about the level of customer happiness. You write to a bank's chat saying you need to reissue your credit card, and the bot sends you to a branch — because the operation requires your physical presence. Did it work efficiently? From an automation standpoint — yes. It recognized the request, correctly identified the topic, and provided the answer built into the scenario. But the customer is hardly happy.
It's strange to expect that after implementing a bot — or rather, merely from implementing one — your profit will suddenly jump. You need to look at all business processes together. If the deal cycle lasts 3-4 months, you need to thoroughly understand your sales, upsell, and customer support cycle to know where the bot fits in. You can't blame the bot for a customer leaving if it did its job and provided a consultation, but the customer encountered poor delivery, service, or a defective product. A bot is just part of the team.
The full version of the article is available at: https://incrussia.ru/understand/ai-truth-about-bots/
Not Understanding the Purpose
Executives often place too many hopes on implementing conversational AI. Companies come to developers with ambitious goals like: "I want to fire the entire sales department — let the bot sell." But a bot won't plug a hole in your strategy or marketing; a bot won't suddenly shower you with customers and money. A bot is a tool. The catch is that businesses often don't know what they want from it.
A startup's options include initial consultation, delivery processing, order confirmation, lead generation, and so on. Russian businesses still view bots exclusively as a cost-saving tool, rather than a revenue-generating or audience-expansion tool. Yet a smart marketing skill for a voice assistant can generate net profit. An inspiring case study was demonstrated by Nike earlier this year: during one NBA game broadcast, TV commentator Ernie Johnson announced that right then, while the game was on, viewers could order a pair of Nike sneakers from a limited collection simply by asking Google Assistant. The sneakers cost $350, and 15,000 people reserved them in 6 minutes.
You don't have to act on such a grand scale right away — even a conversational game for a voice assistant that offers the user a discount on your brand's product at the end can boost sales.
Confusing Profit and Efficiency
Reducing the costs of maintaining a contact center, for example, is easy to calculate based on OPEX (operating expense) — this includes rent for premises and equipment, employee salaries and training, and other expenses, including daily customer service costs. On the other side of the scale are the investments and labor costs of building a bot, the volume of requests typically handled by employees, and the traffic the bot will be able to handle.
Efficiency is a more complex story — it's more about the level of customer happiness. You write to a bank's chat saying you need to reissue your credit card, and the bot sends you to a branch — because the operation requires your physical presence. Did it work efficiently? From an automation standpoint — yes. It recognized the request, correctly identified the topic, and provided the answer built into the scenario. But the customer is hardly happy.
It's strange to expect that after implementing a bot — or rather, merely from implementing one — your profit will suddenly jump. You need to look at all business processes together. If the deal cycle lasts 3-4 months, you need to thoroughly understand your sales, upsell, and customer support cycle to know where the bot fits in. You can't blame the bot for a customer leaving if it did its job and provided a consultation, but the customer encountered poor delivery, service, or a defective product. A bot is just part of the team.
The full version of the article is available at: https://incrussia.ru/understand/ai-truth-about-bots/