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155 chatbots in this brand new landscape. Where does your bot fit?

Image Credit: KeyReply

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Since we started building bots at KeyReply more than two years ago, the industry has seen massive interest and change. This makes it hard for companies and customers to figure out what’s really happening — so we hope to throw some light on this industry by creating a landscape of chatbot-related businesses. There’s no way to put everyone into this landscape, so we have selected examples that give readers an overview of the industry, such as notable or dominant providers and tools widely used to develop bots.

To put everything into a coherent structure, we arranged companies along the axes according to the functions of their bots and how they built them.

On the horizontal axis, the “marketing” function refers to a bot’s ability to drive exposure, reach, and interaction with the brand or product for potential and current customers. The “support” function refers to a bot’s ability to assist current customers with problems and to resolve those problems for them.

On the vertical axis, “managed” refers to companies outsourcing the development of bots to external vendors, whereas “self-serve” refers to them building their bots in-house or with an off-the-shelf tool.

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Spinning out concentric circles

From the inside out, the concentric circles represent:

  • Platforms: The messaging platforms that enable the existence of bots through robust send-and-receive APIs, frameworks, and ecosystems.
  • Brands: Companies that have launched and experimented with bots in that quadrant (for example, Managed x Support).
  • Providers: Companies that have the capabilities to deliver exceptional work in that quadrant.
  • Tools: The supporting tools used by providers, brands, or developers to deliver bot experiences.

Here are some of our observations about each of the concentric circles.

Platforms

In this study, text is the main interaction mode we explore (we might explore voice bots in another study).

Facebook Messenger is one of the leading chat platforms, with over 1 billion daily active users worldwide. With a strong push internally within Facebook for Messenger bots, lots of companies and developers alike have been heavily investing in such bots.

SMS remains a baseline option, and companies continue to use it to send automated reminders and information. As different messaging apps gain a foothold, such as Line and Telegram, their bot platforms will become more attractive for companies to invest in. (WhatsApp as a bot platform is still conjecture at this stage.)

By platforms, the type of bot content and interaction paradigm also differs. Line and Kik bots tend to be more brand engagement focused, and are more likely to be “loudhailer” type bots (mostly announcements and promotions) than SMS or Messenger bots, which tend to be more varied across support and brand engagement.

Brands

Brands are companies that have launched their own bots, split by bot type in specific quadrants as defined above.

Marketing bots tend to be largely campaign-driven, where they can be used effectively for driving engagement in short bursts. Longer-term marketing or sales efforts in the market are still mostly experimental, as it may be hard to define metrics for success without a strong indicator from the proof-of-concepts.

Support bots, however, have been around for much longer, and customers are already used to them. Metrics for deflection and customer satisfaction may also be more well-defined; hence there will be a “flight to quality” in this space to those providers that genuinely can deliver on their promises to answer customers well, not piss them off, and elevate the support experience.

Tools

These are supporting tools used by the providers and brands or by bot developers.

This is a section that is pretty hard to characterize, because many companies won’t just reveal their tech stack where you can find them. Just based on our own exploration and interviews with other bot companies, these are some of the more useful tools that contribute greatly to the bot-building endeavor.

Using this landscape

What does your business need: marketing or support?

  • If you require constant interaction with consumers to drive engagement or sales (whether companies such as Victoria’s Secret or even governments such as Gov.sg), consider a marketing chatbot.
  • If your products require heavy customer support or assistance (electronics companies such as Apple), you should focus on a customer support bot.

How do you do it: buy or build?

  • Does your company have the resources and capabilities to build software in-house? For example, Skyscanner has a strong existing tech team and robust algorithms; hence, they can apply that to their flight search bot.
  • Does your company have the resources to cope with complex NLP and data science issues that might arise? If no, then you might be better off outsourcing the development of bots, which is not your core business.

Should you do it: strategic or faddish?

  • If your value proposition involves providing convenient and fast service to your customers, then developing bots in-house may enhance your value proposition and strengthen your company’s competitive advantage in the long run.

What do you want to invest: all-in or experimental?

  • Do you want or need to have a full control of conversations or customer data and already have a good idea what a bot should achieve? If yes, then find an enterprise-grade provider or build it in-house with a specific team dedicated to the project for at least 3-6 months.
  • If you’re simply experimenting with bots, then it’s fine if you sandbox some data and build a small use case on the cloud, working with a provider for a proof-of-concept or hacking together a bot internally.

What’s next

We’ll continue updating this map as we go along. If you think there’s a brand, provider, or tool that should be added, please let us know! If you’d like to argue for or against any classification, tell us that as well, and we can have a healthy debate.

Thanks for reading, and don’t forget to share if you found this useful!

More examples for each quadrant can be found on the KeyReply blog.

Carylyne Chan is the COO at KeyReply, a enterprise bot platform.

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