Competition is a war.
If you’re familiar with cap table software, it’s entirely likely that other company names spring to mind – and it’s true, our product has entered a contested market where competition is a war on multiple fronts:
- Acquiring net-new customers that have no existing provider
- Keeping those customers from leaving for the competition
- Winning over customers from the competition
Competing on the first two points is relatively straightforward. We have no shortage of opinions or ambition regarding how the capitalization table space can be evolved and reshaped to save everyone involved time, money, blood, sweat, and tears.
But we’re also dealing with a market where the incumbents are well-established and entrenched. As a result, winning customers over from the competition can feel like playing tug of war against a wall or a highly-competitive game of seesaw where the fulcrum is set in your opponent’s favor.
When building a product in contested markets, it’s not just about building a better solution or finding disgruntled or dispassionate customers of the competition. You need to overcome hurdles like switching costs that act as leverage against you in convincing prospective customers that the benefits they gain after they have made the switch are outweighed by the pain that comes with moving providers.
Moving the needle with AI.
Large Language Models have taken the world by storm and there is a lot of activity in the tech industry as companies experiment with it and fold it into their products. The wave of Ask Me Anything windows and chatbots entering products is a great introductory use of the technology to enable customers to better understand or gain insight from your data in ways you may not have foreseen or had the bandwidth to build out all at once. But as I mentioned, it’s not just about building the better solution.
In the same way that LLMs can be used to help customers understand the data on your platform, the right set of prompt models can be used to quickly derive data from documents and artifacts that you haven’t authored. By taking that capability and applying it to other aspects of your business like white-glove onboarding services – which have traditionally been an effective but expensive means of reducing switching costs for customers, you can regain some of the leverage lost in competition against incumbents.
We’ve done just that with Mantle Equity, and now our customers can come with data from other platforms, with a pile of unorganized documents, even with their own bespoke spreadsheets – and we utilize AI to extract that information and rapidly normalize it into our own data model.
Going above and beyond.
The real game-changer? As we’ve implemented this process, our platform identifies errors in customers’ data that have gone unnoticed for years. We’ve caught and flagged issues for at least 75% of our customers to date, ranging from minor discrepancies to mistakes that could have cost them tens of thousands of dollars down the road in legal fees in the heat of a financing round close.
Not only is our onboarding flow lifting the burden of switching costs away from our customers, it’s giving them a health check of their cap table data that sets them up properly for the future. Now, when the next renewal for customers of incumbents come up and the sticker shock sets in, we’re giving them plenty of reason to pause and consider their next move – because they feel like they can move.
Scratching the surface.
At Mantle, we’re just scratching the surface of how we can evolve cap table management, and we want as many companies to benefit from that as possible. To get there, we need to shift that tipping point to our advantage, and AI is helping us get there.
To learn more about how Mantle leverages AI, check out: AI-Driven Document Integration: A Paradigm Shift in Equity Management.
*Originally presented on stage at Collision 2024.