Bot platforms are rapidly proliferating in the technology ecosystem. In the past, I’ve written about the increasing fragmentation in the bot platform space and how it could become a problem for the market. From bot platforms delivered by messaging platforms such as Facebook or Slack(Botkit) to cross-platform bot development frameworks such as Microsoft’s Bot Framework, Howdy or Dexter, bot development technologies are emerging everywhere making it hard for developers and organizations to select a single platform for their efforts.
Like its mobile and web market predecessors, the large number of bot platforms creates new opportunities for cross-platform frameworks in different areas. Technologies such as Google Analytics or MixPanel in the analytics space or IF-THIS-THEN-THAT in the integration area have established themselves as cross-platform solutions for mobile and web applications. The current fragmentation in the bot space, creates an opening for venture capitalists and startups looking to build the next generation of cross platform capabilities in areas such as security, analytics or testing applied to the bot market.
Five Cross-Platform Opportunities for Bots
There are several market opportunities for cross platform technologies in the bot space. Extrapolating lessons from the mobile and web ecosystems, there are a few areas that offer immediate opportunities to enable cross-platform capabilities in an already fragmented bot ecosystem.
Analytics is one of the massive areas of opportunity in the bot market. Functionally, cross-platform bot analytic frameworks should extract metrics and intelligence from natural language interactions. A robust cross-platform bot analytic solutions can also become the key to unlock new markets such as advertisement in the bot space.
A/B Testing is another cross-platform area that is experiencing some serious challenges in the bot technology ecosystem. A cross-platform bot A/B testing framework that validates the effectiveness of new features or natural language commands should become a strong addition to the current bot market.
Managing the lifecycle of content used by bots across different messaging platforms is another are of opportunity in the bot market. Similarly to the web and mobile content management systems(CMS), a bot content management solution should control the lifecycle and process of content that will be delivered as a response to specific natural language commands. Additionally, a bot CMS should be responsible for formatting the content based on the capabilities of specific messaging platforms.
Natural language integration(NLI) is a fairly new field. In the context of bot platforms, an NLI framework should enable the communication with line of business systems and other services using natural language sentences. This type of framework can enable consistency in the integration interfaces across different bot platforms.
Bot models bring new challenges from the security standpoint. From data privacy, access controls or detecting new threats, security should be a foundational component of bot development frameworks. The current market offers new opportunities for a cross-platform bot framework that enables consistent security models across different bot platforms.