Business Franchise Australia


Using AI to pick the best franchisee candidate


Jaffrey Ali, Chief Product Officer, FranConnect


When growing your franchise, precision franchisee selection is one of the most important factors. Get it right and you get growth, get it wrong and failure is almost certain through the dreaded franchisee churn. A monumental choice.


So which key performance indicators should be considered, and how can Analytics and A.I. play a role in the decision making?


By evaluating both data-driven metrics and behavioural assessments across critical financial, experiential, motivational, and interpersonal categories, a franchisor can obtain a 360-degree view of each franchisee prospect to inform their decision.


Firstly, there is the candidate’s financial capabilities. This includes information such as the candidate’s credit score, net worth, and existing assets, to ensure they have the necessary capital to invest in the franchise, and the capacity to secure additional finances if required.


Second, is their experience in business and franchising. Have they managed a franchise before? Was it successful? Which industry are they coming from? What transferable skills do they have?


Thirdly, one must consider their motivation. This is harder to measure and consider through traditional means. How aligned are they with your brand values? If they are an existing franchisee, how have they performed under your brand up until this point?


And finally, what are their interpersonal skills like? Would customers be satisfied with them at the helm? Are they a leader, and can they build a team? Do they have emotional intelligence, and can they communicate well? Do they have the correct mindset for the role? Again, traditionally this is considered through an interview only, making it challenging to measure and compare.


By leveraging an analytics and AI engine, candidates can be measured on numerous metrics relative to top-quartile benchmarks of similar candidates across the whole franchise industry who are already in similar roles, and who went through the same selection process.


This data may include many metrics around financial performance, operational efficiency, customer satisfaction, and demographic information. Not to mention flagging early potential risk metrics and red flags, such as financial instability, legal issues, or a history of poor performance in previous business ventures.


Machine learning algorithms can then analyse these massive datasets to identify correlations and patterns that may not be immediately apparent to humans.


NLP algorithms can even analyse text data from candidate applications, interviews, and customer reviews to extract valuable insights about the candidate’s communication skills, attitude, and suitability for the franchise opportunity.


AI-powered behavioural analysis tools to assess candidates’ personality traits, leadership abilities, decision-making skills, and other relevant characteristics based on their online behaviour, social media profiles, and interactions with the franchise brand.


Through these huge and disparate datasets AI compares prospective franchisees against what the model what an ideal candidate would look like based on industry high-performers, to a very high degree of accuracy. And given AI algorithms are always improving, the accuracy of probability for success is going up every day.


AI and analytics can enable a franchisor to optimally select owners with the highest probability of excellence. By then regularly tracking their score progression, franchisors can also gain an early warning system for challenges along the way.


Furthermore, the use of AI in franchisee selection is not only beneficial for the franchisor but also for the prospective franchisees. By using data-driven insights to match candidates with the right franchise opportunities, AI can help ensure that franchisees are set up for success from the start.


This can lead to higher franchisee satisfaction, lower turnover rates, and ultimately, a stronger and more profitable franchise network. As the franchise industry continues to evolve and become more competitive, the adoption of AI and analytics in the selection process will likely become increasingly common, if not essential, for franchisors looking to stay ahead of the curve and build a thriving franchise system.


Franchisee selection is one of the most important parts of a franchisor’s role and something notoriously hard to get right. Just like in other parts of the industry, AI is revolutionising how happens and improving success. It’s time to get on board.