Idea: HelpGen – Auto-Generate Help for Apps that doesn’t Suck
Let’s face it – online help sucks. Online knowledge bases usually suck too. This is a problem I’ve faced both with my own companies, but also in using a wide array of web and mobile applications. Why does help always suck? Because it’s an afterthought, usually written by a harried human who has 5 other jobs and for whom this is not job 1. Taking the opposite approach, while the machines are getting smarter, they are not yet able to write context-sensitive help that could actually tell you how to use a product. Or could they…?
MVP (Minimum Viable Product):
Use machine learning combined with assisted workflows to help organizations create instant help and knowledge base materials for their products. HelpGen would first traverse the site or mobile app in question, making note of terminology used, available buttons, and inputs, and other interactions possible on each part of the application. HelpGen would then guide the user to write content for each term, control, and step on each screen of the application – using machine learning to suggest content whenever possible. By monitoring the application for updates, HelpGen would also flag changes requiring help content update. By removing the friction from keeping help up-to-date, HelpGen could dramatically lower the complexity and cost of maintaining quality context-sensitive help.
Market: 5M+ applications deployed globally
The number of web and mobile applications has exploded over time, so app stores alone (this doesn’t count millions of web applications) count roughly 5M applications globally. The top 10% of all applications might see enough use to require ongoing maintenance – but that is still likely around 1 million applications globally. SMB SAAS solutions in related spaces like support / chat / feedback capture provide both a likely business model and comparison on market size. Various reviews of applications in the help/support space seem to indicate that $50-100/month per customer is rapidly attainable, with broader feature sets required to expand beyond that. This implies a total addressable market size in the $5B range, which is quite reasonable as a starting point.
Scoring (0-10 scale, up to 2 points per question): 7 points
1. Is it Transformative? 1 point
The HelpGen concept would be truly transformative if AI or ML could be used to automate the entire process – but as with most use cases, that’s not possible just yet. This is more likely to be a guided process for some time, which is still far better than the status quo.
2. Revenue Market Size or Eyeballs: 1.5 points
As discussed above, comparisons with other leaders in the customer support space indicate a thriving and rapidly growing market. I consider a $10B addressable market to be the gold standard, and this idea isn’t far off that.
3. In a Growing Market? 1.5 points
This market is growing as rapidly as cloud and mobile apps themselves, since all require some form of help and support.
4. Difficulty, Barriers to Entry, and Competition: 1 point
Many existing players in the help/support space may choose to attack this idea if it begins to gain traction. This is also not a winner-take-all market, providing some room for a well-built product to grow without being sidelined immediately.
5. Riding Hype or a Trend? 2 points
AI and machine-learning are arguably THE trends of the moment, and while arguably overhyped, HelpGen could definitely ride this marketing wave.