Comment by jmuguy
5 hours ago
Well specifically with just the AI agent/customer support product I think businesses would do well to handle this themselves rather than hoping a one size fits all solution from Intercom would serve them. Not just from a bespoke AI solution but also on cost. The other aspects of Intercom's product, the little chat bubble, CRM, can be had for much much less from dozens of competitors.
I think they mostly benefit from time in market and name recognition. The AI angle was a good bet to make when they made it, but is increasingly less of a differentiator.
I don't think SaaS is dead - but I think for a product like Intercom, that is very expensive, they get eaten alive by smaller SaaS + in-house AI agent.
The problem is that Fin prices at $0.99 per outcome. Only for companies with tremendous support volume would it even begin to make sense to build in-house.
There's a wide swath of companies that do < (say) 20,000 cases monthly where the economics will never make sense. And a company finds Fin successful as it grows to 20k/mo, why would it decide to take on the headache as it grows to the 50k/mo? or whatever level where the economics could feasibly make in-house work?
$0.99 could be the profit margin of small ecommerce businesses too so it might not make sense for small businesses.
Let's say the small e-commerce business does 500 of these outcomes per month. ~$500 all-in cost at Fin.
I'm curious how you would calculate the other side of the ledger, the in-house approach. Assume the e-commerce business does not employ any AI/ML experts or programmers or anyone whose workday has ever been interrupted by a Github outage (this is the normal case for most businesses, not an artificial handicap). I'm curious how you would structure things to make an in-house more efficient than the $500/mo all-in.
Man you are delusional.
You clearly have never ran a business and don't understand the dynamics of the make vs buy decision.
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