Iris Finance

gm. imagine not having iris MCP on your phone

Profit is up 18%, without touching marketing. Iris connects Shopify, Amazon, Meta, QuickBooks, and your bank, showing profit by product and channel in real time. Some SKUs were bleeding margin. Others, nearly cut, were 42% profit.

Six hours of reports shouldn’t be needed to see profit. Shopify revenue looks good, but Amazon and Meta fees are eating your margin. Iris Finance shows real-time profit by product and channel, plus a 13-week cash forecast.

Cohort forecasting with customer segments is on the biggest unlocks in forecasting accuracy for your online sales channels I mentioned this briefly on an Intuit webinar last week - but in this video im showing you how in Iris Finance you can use customer segmentation to gain enhanced accuracy in your financial plan. One example is segmenting on product. Different products retain customers at totally different clips - a good use case for AI to pour over your data and figure out. This matters not just for sales planning but also for inventory planning. You can't just assume that all of your customers are going to come back at the same rate, when in reality they have different spending patterns and are coming in on different products. With Iris, the workflow is simple. We help you identify which types of segments actually have true predictive power, and then we build cohort models based on those segments that flow through your revenue model, and then downstream to your inventory planning process. The result is better accuracy in repeat revenue forecasting. Having high confidence levels in your repeat revenue forecast is what allows you scale your CAC target without compromising EBITDA margins. Over time, as you get more and more customers - you can tolerate higher CACs as the repeat customers start to contribute more and more gross profit to the business. Doing this exercise across DTC, Amazon, & TikTok Shop not only helps you steer your business with more confidence, but along the way you will identify which products create the most LTV, which marketing campaigns are worth doubling down on, and which are worth ditching. If this sounds like something your brand could benefit from - hit my DMs!

We just launched Iris MCP 🚀 Everyone is building AI agents, but they break as soon as they touch finance tasks Why? Finance & operational data is ESPESICALLY messy & siloed - and messy data means more hallucinations and less reliable agents For example, If you're connecting Claude to Quickbooks & Amazon, those two systems will show different numbers for revenue, meaning your agent can't answer a question as simple as 'what were our sales last month" - let alone build any analysis or modeling. Iris MCP gives agents secure, governed access to clean, normalized, agent friendly structured data from 1000s of sources: - ERPs, Accounting ledgers, & AP systems - Amazon/Shopify - Ad accounts, SMS, & email - Retailers - Bank Accts / Credit Cars - Subscription platforms and more. One central & USABLE AI optimized data store for all your data is how you build agents that will actually drive value in your business. My favorite things customers have built so far that are not iris-native yet: - Cash level monitoring agent - Inventory level monitoring agent - Revenue reconciliation agent Good data is your advantage. Shoot me a DM if you want to connect to iris MCP

Dashboards can hide real profit. Fees, shipping, and COGS turn winners into losers. Iris Finance shows profit by product in real time, across Shopify, Amazon, Meta ads, QuickBooks, and bank data. Brands can shift spend, recover profits, and make smarter decisions fast.