canfitpro Official Magazine | May/June, 2023

The Turning Point of AI

HOW IT’S CHANGING THE

By Ian Mullane

As someone who has been involved in Artificial Intelligence (AI) and machine learning for over a decade, I can confidently say that we have reached a turning point where AI is becoming more common and incorporated into every corner of life.

When it comes to the fitness environment as we know it today, AI can be recognized as the forcemajeure providing more personalized, efficient, and cost-effective solutions. For example, AI-powered Fitbit, Strava, and MyFitnessPal, all monitor users’ physical activity and provide them with tailored advice. Additionally, AI-based digital coaches such as Jaha and Endomondo are able to provide real-time feedback and personalized guidance to users, resulting in better long-term results.

Outside of fitness, we have been using AI in our daily lives for a while, but mostly in singular features that do not offer much interaction beyond completing a task. You can look to Amazon’s Alexa and Google Translate as everyday examples of this in practice. More recently, there was the public-advent of Large Language Models (LLMs) like ChatGPT showing us the potential and accessibility of AI applications, with thirdparty developers now integrating this technology into their own applications.

While this development is exciting, it is not entirely new. The first version of GPT was released in 2018 by researchers at OpenAI, and IBM’s Watson, arguably the first example, developed in the mid2000s, gained widespread attention after competing on the quiz show Jeopardy in 2011.

However, what we are seeing now are tools that are ready for mass adoption, with their potential for exponential improvement within the next twelve months simply staggering. Furthermore, when we combine AI with automation, we have an incredibly powerful tool set that can improve every aspect of existing sales processes and metrics, from open rates on emails to member retention and sales conversions. Furthermore, we can reduce manual, low-value interventions and increase the certainty that an action is actually being taken, at the same time.

For example, let us consider the standard fitness industry sales process, the series of engagements that decide whether a potential customer becomes a member or not. There can be multiple lead sources, but the majority comes from paid social, paid search, organic search, referrals, and email campaigns. However, how these leads are dealt with is often identical regardless of the source, and in many cases, when the volume is high, leads are serviced unevenly and, in some cases, not serviced at all.

Ideally, we want to ensure that every inquiry is serviced based on their probability of success as well as a level of personalization or service expectation based on the source and the information provided. Machine learning can train a model to look at historical leads, their sources, eventual outcomes, and their value and then score each inbound lead automatically. With this scoring, we as fitness operators can prioritize the highest value/probability leads and allocate them to where it is likely to see success. This marriage of technology exists and is available. Smart fitness operators are already realizing the opportunity in these advancements, leveraging dramatic improvements in the way AI helps them spot the best members, identify attrition risks, and automate actions that will future proof their membership revenue.

Taking it one step further, by automating beyond lead routing, we can manage volume optimally as well. Once we have scored our lead, we can then decide based on the value/probability and the current volume, whether to allocate it or to answer it through automated engagements. This approach ensures that regardless of volume, we are always focusing on the highest value/ probability leads. In times of high volume, or for lower value prospects, automated routines can deliver the required initial engagement and act as a filter to tune the value/probability of the leads further. The impact this can have on your bottom line is clear.

In conclusion, AI and machine learning have arrived. They are here and they are leading the conversation, paving the road ahead for sales and marketing teams across the fitness industry regardless of size or niche. No longer are they distant possibilities on the technological horizon and no longer are they the reserve of multinationals with billions of dollars to spend on digital transformation.

The AI used today by ‘ahead of the curve’ fitness operators is already in continuous learning mode, updating its understanding every hour of every day, tuning its performance to deliver more accurate revenue and membership predictions that ultimately amount to better profit margins.

In this way, we see that the benefits enjoyed by clubs using this technology now will increase at the same rate as their AI learns and the technology powering it improves, thus forever changing the landscape for fitness operators.

Ian Mullane is the founder and CEO of Keepme, a SaaS platform dedicated to driving operator revenue through AI-powered insights and tools. An economist by training, Ian’s career has included roles with the foremost players in FinTech, including COO at Sungard. He also successfully set up and ran Singapore’s VANDA fit.