ACERCA DE ESTE EPISODIO
What makes an analytics or intelligence product indispensable when technical sophistication alone isn’t enough to drive adoption, renewals, or sales? Why do POCs stall, why does adoption stay flat, and why aren’t prospects nearly as excited about your (impressive) analytics tech as you are?
It’s that the value never becomes obvious to the humans in the loop who do the buying, using, and justifying.
In this episode, I provide a framework for identifying the personas (roles) and experiences that can turn sophisticated analytical capability into perceived value. We’ll explore the five essential control surfaces you’ll need to address in your product and why founders and product leaders need to look beyond technical development (e.g., the delivery of AI models, dashboards, MCP connectors, agentic capabilities, and traditional interfaces).
I also examine the tensions that can emerge when incentives and goals for end users are not aligned with those of management and executive/fiscal buyers. Why does the efficiency ROI you sell to a management champion get read as a job threat to the operator/user whose adoption you need to succeed? I’ll answer this, plus the reasons AI can complicate those dynamics, how to prevent your product from creating an Invisible Intelligence Gap for customers, and why one past podcast guest’s “shipping the meter” matters much more than another feature. (That will also explain why I don’t think dashboards are dead in the age of AI.)
Highlights / Skip to:
- Short-term stakeholders you shouldn’t forget to satisfy (particularly during POCs/Demos) such as legal, compliance, and the game of defense “value be damned” they are playing (4:14)
- Not every mouth is equally hungry: deciding which personas deserve the most product attention (8:23)
- End users of your product such as developers, analysts, business users (often ICs) operating your product daily—and why the real bar is whether they would complain to the C-suite if your product went away (9:12)
- How managers of ICs (e.g., sales directors, customer service managers, VPs of data, etc.) might need something very different than end users, and why the manager’s needs might be a threat to those very IC users. The 3-part fix? Making all parties look successful to their superiors; improving the lives of those stakeholders; and arming champions with the evidence fiscal buyers need (11:08)
- The unique needs of executive and financial stakeholders who might have the most decision power while using your product the least (15:59)
- Why “shipping the meter” and the Invisible Intelligence Gap decide whether your product survives the next budget cut (17:07)
- The “AI Agent” as a “user” of your product: Why I think agents ride in a sidecar attached to humans and what you need to do to enable your customers and their AI agents to be successful (21:23)
- Why figuring out what control surfaces/UIs/UXs you may need to improve is the easy part if you know what they are a response to (26:37)
Links
- 197 - Agentic AI Isn't a Moat for Analytics Products.This is. - My episode on viable moats for BI/Analytics products in the age of AI
- The Invisible Intelligence Gap
- Behavioral Signals CEO Rana Gujral on “Shipping the Meter” is in Episode 198
- Need help identifying the 5 control surfaces in your product and satisfying the human users behind them? Schedule a free discovery call with me
