In my opinion, if you want to learn anything, build up institutional knowledge, get better at serving people and get them to their desired result at a faster speed, the answer is to productize your coaching business.
But what does this mean?
Recently I appeared on William Winterton's new Coaching Success Radio podcast to share some tips on this topic.
We're talking about the necessity of serving a narrow niche, offering killer content, and why you should offer your coaching as a product.
Interview On Productizing Your Business
Watch the Jason Kanigan interview hosted by William Winterton on productizing your business here:
>> Jason Kanigan is a business strategist and conversion expert. Book your consultation with Jason by clicking here. <<
SaaS AdLabs hosts this interview with Jason Kanigan on the unexpected challenges of scaling tech firms. We cover:
the biggest issues Cold Star sees over and over, in both small companies and larger firms, that block them from scaling smoothing and fast
Why franchising may be the wrong option for you, and the things you need to think about before considering using it as a growth tool
What tech firms can do to dramatically lower their cost of customer acquisition...and why nearly all founders cut themselves off from this possibility
Why all SaaS companies should have a dedicated individual which job is to figure out way to reduce churn rates.
Watch the full interview right here:
Process Engineering for Scaling Tech Firms
Business owners whose time is tied up, whose management team is stuck in a complex mire of training employees and outsourcing, who are tired of seeing quality issues that should have been fixed long ago...these folks are in a situation Cold Star Tech can get them out of. Process engineering is the key tool for accomplishing a better outcome, and getting business owners feeling confident that they have clarity.
>> Jason Kanigan is the founder of Cold Star Technologies, a professional services firm focused on helping tech and manufacturing companies smooth the bumpy road of scaling fast <<