How to Know a Client Is a Good Fit Before You Say Yes
Impossible d'ajouter des articles
Échec de l’élimination de la liste d'envies.
Impossible de suivre le podcast
Impossible de ne plus suivre le podcast
-
Lu par :
-
De :
What if the client you're about to sign is the one you'll wish you never had?
This episode isn't about learning to spot red flags after they blow up your business. It's not about having better luck, being pickier, or trusting your gut more. It's about building a real, repeatable step into your sales process — one final "vibe check" — so you catch the mismatch before the contract, not after the reviews start coming in.
Here's the spoiler: the best predictor of how a client will treat you after they sign is how they treated you before they signed — and almost none of us are watching for it.
By the end of this episode, you'll have a 5-signal framework you can start testing for on your very next sales call — one that tells you whether a prospect is going to protect your team's capacity or quietly drain it, before you ever sign the contract.
In This Episode:
- Why one bad-fit client costs far more than lost revenue
- Why bad-fit clients almost never look like bad fits on paper
- How one client built a 15-minute founder "fit call" into her sales process
- Using AI to identify patterns across your past bad-fit (and best-fit) clients
- The 5-signal framework: process behavior, expectations vs. fantasy, how they talk about their last vendor, boundary testing, and the "saying no protects a yes" reframe
Homework: Before your next sales call ends, ask one boundary-testing question — response time expectations, weekend availability, what's in scope versus billable — and pay attention to how they push back. That single answer will tell you more than the entire pitch did.
Connect with Melissa:
Book a free consultation with Melissa → https://www.melissafranks.com
Learn more about On Call COO fractional services → https://www.melissafranks.com
Watch the Episodes on Youtube
Instagram: instagram.com/melissa_franks
LinkedIn: Melissa Franks