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šÆ Intercom's risk-free purchase strategy
A playbook for pricing AI in your products
Read time: 3 minutes 56 seconds
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I realised we crossed a fun milestone a few weeks ago:
1 million reads of Strategy Breakdowns articles.
You reading this email puts us at something like 1,226,989 reads.
The internet is such a quirky thing.
Hope you enjoy - thanks for being here.
ā Tom
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Chess Move
The what: A TLDR explanation of the strategy
Not all software should be SaaS.
Intercom, a leading customer support solution, recently adopted an interesting pricing strategy for their AI chatbot: āFin AIā.
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Rather than a fixed monthly recurring fee, Fin uses a āpay-per-resolutionā structure, charging customers $0.99 for each customer inquiry it successfully resolves.
This means that Fin customers only pay when they receive the outcome they (and their own customers) want the most - a resolved conversation.
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š” | Strategy Playbook: Only charge your customers if you make them happy. |
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This move follows CEO Eoghan McCabeās viral Twitter thread, announcing their $94m bet on AI customer service through several screenshots of a private internal strategy email.
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Jackpot for strategy nerds
Here are some mental models you can use to think about Finās pricing strategy.
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Breakdown
The how: The strategic playbook boiled down to 3x key takeaways
1. Make it an obvious buy with pricing that starts at $0/mo
The ācost-per-resolutionā pricing structure eliminates upfront financial risk for customers.
Like ācost-per-clickā Google Ads, or ācomission-per-successful campaignā on Kickstarter, customers are guaranteed to pay nothing if the service doesnāt deliver the expected value, which minimises psychological barrier to adoption.
Rather than passing exact API costs directly to the customer (a common AI app pricing model, often involving a āBring Your Own Keyā mechanic), Intercom only charges if their solution actually does its job. Otherwise, they eat the cost themselves.
This demonstrates the confidence they have in their own product, which subsequently improves customer trust. Customers know that Intercom doesnāt generate revenue if Fin doesnāt deliver, so the āperceived valueā of Fin increases.
Intercomās trust in themself ā Customer trust in Intercom.
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Plus, a fixed cost-per-resolution allows companies to easily model their cost-savings when using Fin.
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Products with pricing models that allow for clear cost-benefit analysis make for easier purchase decisions.
2. Align your financial incentives with customer value
By making revenue-generation dependant on customer success, Intercomās interests are aligned with their customers.
Intercom is financially incentivised to continuously improve Fin, since the better Fin is at resolving customer issues (i.e. improving āResolution Rateā), the more revenue Fin generates per customer.
Adding features like multilingual support or debugging tools benefits both Intercom and their customers.
This virtuous cycle means customers have high confidence they will enjoy sustained value creation.
Beyond just product improvements, Intercom is incentivised to help customers uplift the overall maturity of their Customer Support organisation. Since Fin is only as helpful as the content its trained on, Intercom provides extensive self-serve docs, best practices, and optimisation tutorials for customers to benefit from.
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As a customerās internal support content gets better, so does Fin - along with Fins resolution rates.
3. Let customers use it exactly when they need it (and not when they donāt)
For some customer segments, a change like this introduces some downsides. For example, small startups with high ticket volume might experience a necessary price increase.
But Intercom doesnāt make Fin mandatory to use. Nor do they make it a one-size-fits-all solution.
Customers who opt-in enjoy a suite of flexible customisation tools to ensure Fin works in a way that suits their specific needs.
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Here are a few customisation options available:
Audience Targeting Rules - Define which customer types, customer locations, products, services, or sub-brands will trigger a conversation with Fin.
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Omnichannel support - Decide where to use Fin, including Intercom Messenger (web, iOS, and Android), as well as WhatsApp, Facebook, Instagram, SMS, and Email.
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Custom Answers - Build bespoke answers to the most important questions for increased accuracy, consistency, and specificity.
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Workflow Embedding - Define when to trigger Fin within your existing workflows, and when to handoff to a human support agent.
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Usage Limits - Set alerts and hard limits to prevent Fin from triggering beyond your allocated budget each month.
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Performance Reports - Constantly monitor and assess Finās performance, with filtering for any parameter, to ensure you are getting what you need from it.
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Fin doesnāt replace your current toolbox (if you donāt want it to).
Itās an electronic multi-tool thatās been added to your toolbox, with no upfront cost, that you only pay for each time you get tangible value from it.
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Rabbit Hole
The where: 3x high-signal resources to learn more
[1 hour 23 minute watch]
Paul Adams chats with Lenny Rachitsky on why š±š³šŖš¤šŖšÆšØ sits alongside š°šÆš£š°š¢š³š„šŖšÆšØ as 2 of the most complex design problems a product org faces.
Plus, how their design principle of āAlign price to valueā led to Finās novel pricing structure.
[20 minute read]
The inherent structure and repetition to customer queries makes customer support a prime candidate for AI revolution.
But building an industrial-strength AI customer service agent is an enormous engineering feat and prioritisation challenge.
Hereās a candid āOff-Scriptā interview with intercomās VP of AI explaining the companyās biggest strategic bets today.
[7 minute read]
Fin isnāt just a product.
Its a product that continuously improves adjacent products.
āThe customer question comes in, agent tries to answer, increasingly it can. If not, it goes to the copilot. Copilot helps the human rep answer. And then all the data goes to the AI insights engine. Then the manager can use all of this to improve both.
So it's this kind of flywheel effect. In theory, a human rep should only ever answer the same question once.ā
Thatās all for todayās issue, folks!
Thanks again to our sponsors Kinde and Mixpanel - both tools worth checking out for anyone building products in 2024.
ICYMI, last week Strategy Breakdowns turned 365 days old, so we published a retrospective with transparent behind-the-scenes details.
Click here to read about our weird and wonderful first year.
ā Tom Alder
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