The sudden popularity of chatbots is understandable considering that we’ve been talking to machines regularly since Siri’s debut in 2011. But while nearly every smartphone user has tried a voice assistant, many people are too embarrassed or uncomfortable to talk to their tech in public. In 2016, Business Insider reported that the four largest messaging apps surpassed the four largest social networks with monthly active users. This shift signals that chat bypasses the friction of voice recognition with texting; a message or search can be entered and translated with less error, faster. The benefit of chat is that it can be intelligent and personal. Increasingly, chat is getting easier—and many people are more comfortable typing than talking. If the number of times Siri “didn’t quite catch that” were replaced with direct, useful responses in a chat, a lot of people would be happier.
While a shift in use indicates that “chatting” has become the preferred mode of communication for many people, it also suggests that consumers may just as happily chat with businesses and banks, as they do with their family and friends. According to Gartner, the key aspect of conversational commerce is that “it allows users to converse in their platform of choice, and therefore takes channel transparency to the next level.” Financial services will not only benefit from an inexpensive customer support tool, they stand to gain tremendous value from the data that chatbots can collect.
A Changing Landscape: Virtual Assistant or Data Scientist?
A chatbot is a conversational algorithm that you interact with via a chat interface. Early on, chatbots functioned mostly as informational proxies or niche virtual assistants powered by rules-based logic. Now, as major messaging platforms have opened APIs to third-party developers, it’s possible to make complete transactions without leaving the chat. For example, you can shop at H&M or Sephora on Kik, or order lunch from Taco Bell on Slack. Now, FinTechs are cashing in on this new technology as well. Pure plays like Digit, Plum, and Cleo let you save, budget and transfer money through a friendly, ongoing relationship with a chatbot directly in Facebook Messenger. As the possibilities grow, so does the data. Because chatbots are being developed with artificial intelligence via natural language processing and machine learning, they’re optimized for collecting data. After all, they are data.
The difference between a rules-based chatbot and an intelligent chatbot is the data behind it. Many chatbots from the past few years have been limited in a very vertical way; the right answer depends on asking the right question. Until recently, data has revealed behavior through mouse-clicks, screen-taps, time on site and shopping cart activity. But generating a human-like conversation with the customer presents a much more dynamic method for understanding customer needs. A one-to-one relationship with the customer means the possibility of understanding emotion and intent.
Chatbots and Data Collection
While chatbots are still relatively new, their benefits are hard to ignore. A chatbot strategy that optimizes the data a bank already owns has many benefits. Chatbots reduce costs by eliminating and qualifying customer inquiries, increase sales through personalized offers, build brand loyalty across channels with a consistent voice and add value by teaching financial literacy. In many ways, a chatbot is a positive feedback loop. Using data to appropriately segment and target its users, a chatbot can engage these users and collect more data. As the chatbot gets smarter, it gets better—and so does the data. The loop repeats and improves.
Chatbots built into a customer support strategy work well at scale and help limit costly turnover. According to a 2016 report from Forrester, 73% of people say that valuing time is the most important thing a company can do to provide great customer service. But while chatbots will help reduce traffic to customer support centers, they won’t replace it. Savvy banks are using chat assistants as an additional tool to help customers, not as an overhaul to replace support staff. Unlike waiting hours or days for an administrator to respond to a question over email, or the hassle of navigating a traditional call center, chatbots can connect you quickly to human agents in the same interface, if they can’t answer your question or request. This makes the experience faster and more convenient.
The Challenge and Opportunity of Chatbots in Financial Services
Initially, the flagship use case of the chatbot was customer service. 7, an AI development company, estimates that chatbots may reduce call center volume by 35% and email traffic by up to 50%. But more than saving cost, chatbots make it personal. Because chatbots can identify and verify users automatically, they can go further than customer service. Besides merely answering questions, chatbots initiate conversations, too. Recently, Forrester argued in a report that banks must create this kind of value and relevance in customers’ everyday lives in order to avoid commoditization.
According to the report, “Firms will deliver personalized and contextually relevant interactions by combining profile data about who customers are, historical data about what they have done and situational data about what’s happening in their lives now. When digital banking leaders get personalization right, they will then be able to offer digital services that are as simple as each individual customer needs them to be.”
Because chatbots can learn, banks face the challenge of teaching chatbots to engage differently with different users. A small-business owner may want help filling out lengthy applications, signing forms, and keeping track of financial documents. But a retiree will need help with transferring funds between portfolios and accounts. By responding directly to a user’s needs through a conversational interface, financial services can personalize the experience, and in turn, use this information to develop even better products and services.
Chatbots are one tool that can help banks get personal. And many big banks have deployed chatbots already, including Wells Fargo, USAA, MasterCard and Capital One. In the fall of 2016, Bank of America introduced Erica, a chatbot that responds dually through text and voice. Also, Erica can talk to you, too. By studying your spending, Erica might let you know how you can pay off your Visa bill faster, or help you identify opportunities to refinance a loan. Another example is a new chatbot from Western Union and Facebook Messenger, which lets you easily send money worldwide through a card or an account, without leaving Messenger.
Chatbots and the Bottom Line
As chatbots move from help desk to interface, their value increases revenue and data collection. Most mobile users spend time in just a handful of apps, where they find the most value. According to a report from Personetics, close to 25% of downloaded apps were abandoned after just one use. Chatbots make it easier to identify why people are engaging with the bank, how much they know about available products, where they get frustrated or abandon transactions and whether or not they are satisfied at the end of their experience. Knowing this information will let banks adjust the experience to create what Forrester calls “personal value ecosystems.” That is, digitally connected products and services that individuals combine to help satisfy their needs and desires.
Chatbots make life easier. Whether you need to ask a bank a question, or move money from one account to another, chatbots can fulfill that request quickly and easily. More importantly, chatbots are a solution for personalization. As Forrester suggests, one out of three people today thinks all banks are basically the same. Chatbot or not, banks will need to challenge this opinion in order to avoid the disintermediation from FinTechs and other marketplaces. The result won’t just be convenience, but consumers that recognize that banks know who they are what they need. Better yet, not just consumers, but happier customers.