To shift a services-oriented company to a product mindset, frame productization as a competitive advantage. Repeatable, productized solutions offer greater market differentiation than purely custom builds, leading to more effective competition and new deal wins. This tangible benefit helps secure buy-in from sales and leadership.

SaaS companies scale revenue not by adjusting price points, but by creating distinct packages for different segments. The same core software can be sold for vastly different amounts to enterprise versus mid-market clients by packaging features, services, and support to match their perceived value and needs.

During a transformation from services to product, identify and commercialize the reusable tools that services teams have already built to support clients. Instead of starting from scratch, productizing these existing "mini-products" aligns them with the broader product strategy, saves development time, and leverages proven solutions.

The one-size-fits-all SaaS model is becoming obsolete in the enterprise. The future lies in creating "hyper-personalized systems of agility" that are custom-configured for each client. This involves unifying a company's fragmented data and building bespoke intelligence and workflows on top of their legacy systems.

SaaS companies serving SMBs in non-tech industries can create a new revenue stream by offering a managed service—using humans-in-the-loop but framed as an "AI boost"—to run marketing campaigns for them. This provides immense value and captures more of the customer's budget.

Most successful SaaS companies weren't built on new core tech, but by packaging existing tech (like databases or CRMs) into solutions for specific industries. AI is no different. The opportunity lies in unbundling a general tool like ChatGPT and rebundling its capabilities into vertical-specific products.

Instead of pursuing complex, open-ended consulting projects, partners can scale more effectively by creating productized, "turnkey AI" offerings for specific business units like legal or marketing. This approach lowers the adoption barrier for customers by delivering predictable results for a defined use case, making it easier to sell into departments or smaller businesses.

Constantly delivering custom solutions is inefficient and destroys profitability. Instead, define a standardized, repeatable service package that can be sold and delivered consistently, maintaining high margins and simplifying operations.

Agency owner Katherine Ferris was initially skeptical of all-in-one platforms like HighLevel, viewing them as a 'jack of all trades, master of none.' However, after multiple long-term, tech-savvy clients insisted on using it, she was forced to learn the system. This client-driven adoption ultimately transformed her business model.