“Bots are the new apps,” and companies are rapidly investing resources in reaching their customers in the most efficient and productive ways. There are already hundreds of bot frameworks that are being built to help companies engage with their consumers via messaging and chat interfaces. At RapportBoost.ai, we agree that conversational commerce is the wave of the future. We believe the real challenge on the horizon will not be in determining *what* to say, but *how* to say it. Using the right language, cadence, sentiment, and timing will be key to helping humans AND bots build relationships with customers that encourage them to engage more deeply, purchase a good / product, or just walk away with a positive experience.

Research has shown that 93% of communication is nonverbal. Factors like tonality, inflection and body language matter immensely. Therefore, digital communication is especially difficult because we’re robbed of those factors when we can only express ourselves through a keyboard. Anyone who’s texted with friends, used online dating sites, or communicated with customers via web chat can vouch for the fact that it’s difficult enough for human beings pick up on subtle nuances and sub-text through text messages. There is no question that bots will struggle even more to understand some of the subtleties of chat-based conversation. The solution is the combination of both human + machine, or “human in the loop”, where the machine merely surfaces recommendations while the person is ultimately responsible for making the ultimate decision. This ensures that there’s always a human being behind the wheel, but still allows us to continually enable our artificial intelligence engine to learn and improve.

Companies spend billions of dollars optimizing their marketing spend, A/B testing different messages, making sure that it’s on-brand, and trying to hit the right tone. Why would they leave their customer engagement to chance once consumers have communicated back and moved further into the sales funnel?

We believe that applying those same language and communication optimization techniques to later stages in the customer lifecycle will be key to minimizing churn, maximizing engagement and growing both revenue and margins. So, we’ve built an analytics engine that examines company-to-customer communication and recommends messaging that is most likely to boost rapport.