AI and Bot Strategy

15.12.2016 |

Episode #10 of the course Building your own Facebook Messenger bot by Carylyne Chan


Many people have been throwing around the term “artificial intelligence,” with seemingly everything these days being AI-powered. However, at the heart of most AI applications is machine (or deep) learning. How do all these fit within your view of the future?


How does a bot fit in your strategy?

For most of us today, differentiation is the de facto strategy; in a crowded market, only differentiation can command greater loyalty and higher prices. For example, many companies say they care about customer service, but only a few really make it their core differentiation. What is the core function that truly drives your business, its relationship with its customers, its partnerships, and its choices? For example, a new-age logistics company is more likely to be winning with its technology than purely its supply chain.

A bot should fit within your core strategy. If your core differentiator is customer support, a chatbot is perfect. If your main function is marketing and branding, a chatbot can help you engage customers repeatedly over time. If, however, you care most about a personal relationship with your customers, it may be less likely to be relevant unless your customers are largely millennials.

Your chatbot can serve a strategic purpose in your strategy cascade, helping you to win and differentiate in markets. Your chatbot can help you enhance your value proposition and increase your competitive advantage against less innovative competitors. By having a direct line of communication and an automated engagement and support option, you can increase loyalty and save costs as well.


Do you need an AI strategy?

As the major technology powerhouses like Google, Facebook, Microsoft, Amazon, Apple, and others continue to push the boundaries with AI, many other organizations stand to benefit from their breakthrough findings. Simply by leveraging advancements in AI today, many companies can already improve their big data processing abilities, which have contributed to countless new uses—even novel ones like reducing wildlife poaching, beefing up cybersecurity, countering terrorists, dealing with climate change, and so on.

For many of our businesses, data is the new lifeblood of decision-making. There is a real threat of information overload, and there are fewer people who are equipped with handling data than those who aren’t. As such, there is a pressing need for you to be able to identify key trends in your data and use them creatively to drive business results while deterring the competition.

AI is hailed as the fourth industrial revolution. AI will change the power dynamics in the business world in quite the same way as the Internet did. It is better for you to be prepared for this and take advantage of its superpowers as soon as possible.

In this course, we learned about the Messenger bot platform, how to choose the right use case, and craft dialog and improve it with NLP and ML. We also thought about how to integrate workflows into the bot, test and launch the bot, and measure its performance over time. Finally, we explored some potential pitfalls, other platforms it can be extended to, and how everything fits together in your strategy. Phew!

I hope this course was helpful for you in planning how to build your own Messenger bot and gave you perspectives around the purpose and environment bots serve. Thank you for learning with me, and feel free to reach out with questions or suggestions!


We can also help you build your bot (sometimes you just don’t want to DIY); find out more here and get in touch!

Learn more


Share with friends