Hi Aditi!
I was just looking up Locale. It’s an exciting space. Good luck!
In the category we’re working in, the need for AI enabled use cases means delivering in a way that the AI lands in some part of an existing workflow, which is either manned by a human or intersects some fairly old legacy system!
We realized fairly early on that most of our products would never work in a self serve model. Our challenges revolved around convincing people to trust the AI, trust value and trust that it won’t break the systems they already had in place. And that automatically meant we were going to pick the enterprise route for sales.
Then we had to figure out how to price the up front integration vs. the recurring API parts. We iterated a lot on the pricing. It was directly a function of the RoI and value we were able to generate for our customers. And then of course, the upsell and cross sell cycles continued once that trust was established.
We don’t do services. You can’t have armies of humans in the loop when you’re delivering real time personalization, data extraction, classification related use cases. But in the first few years, we had the luxury of customers who allowed us to experiment with them on use cases, to iterate and learn. This is very important for enterprise. Those early supporters, adopters can often be the difference between take-off and crash.
I speak to a lot of early stage founders and this is the singular question that keeps coming up - customization vs. productization! There is no right answer. Every business is different. If your goal is to build a SaaS company, don’t let the customization eat you whole, is all I tell them. Building in the ability to customize, into your product workflow can also be a great way to deal with this. Hope that helps!