1. Provide a 30 second chime bell to help people exercising keep track of time. Keep the chime soft and just below the noticeable threshold but loud enough for those who need it to hear and keep track of their workout.
2. Build a discount program around co-coaching. Call it ‘trainer for a day’. Everyone who works out even occassionally knows that you learn a lot from watching other gym member’s routines. Provide a discount program that allows loyal members to volunteer 15 – 20 minutes of their work out time with a new member and get them on their way. This will not necessarily cannibalize patronage of any personal trainer services offered, rather it will delight that occassional gym goer who really does not want the commitment of a personal trainer, but could use an enhancement to their routine every now and then. The gym could charge a ridiculously low amount and then apply part of that money towards a discount for a regular gym member who does say 3 hours of co-coaching. The person who is co-coached gets to rate the ‘trainer for a day’ and those ratings will determine whether that person gets picked in the future for more of such sessions. Of course there is some form of scheduling required, but that should not be too difficult to work out once you have a couple of regular gym goers volunteer to be ‘trainers for a day’.
3. Send your members an analysis of their gym habits every month to keep them motivated. Think about it. The gym already has data on your comings (and probably goings). While they mine that data on the back end to maximize their profit, why not share it with customers to help them keep track of their habits. It will not be difficult to do, technically speaking, but it will be such a help. That way I don’t have to keep marking x-es on my calendar.
If you have ever searched for a new home appliance on Amazon.com you are probably used to how complicated it is to make sense of product reviews. Sometimes I finish reading a review only to realize that it was written 5 years ago, but Amazon’s sorting algorithm judged it ‘most relevant’ and made it stick to the top of the list. Depending on how much I know about the product I want to purchase, I might click on “see all customer reviews” and then there is even more information to sort through. Now, if you are making a high involvement purchase, you might very well want to spend the time. A high involvement purchase refers to a product that is expensive, can lead to serious consequences or is linked to one’s social image. A lot of times, you really don’t care as much but you sure don’t want to buy a crappy product and have to go through the hoops to return (or lose the money completely).
In such cases, I have found Amazon product reviews (and practically all product reviews) to be greatly lacking. This calls for a long needed disruption. When I say this, I really am not referring to the kind of disruption (pun intended) Google intends in this space. The recent change to their terms of service is modeled after what sites like Facebook and Bing search to fetch recommendations from people you know to help ease you along and support any intentions you had to buy. Amazon, before you go this route as well, please listen to a voice of reason.
I agree that buying is a social activity. When we desire a product and we search for it or read a review about it or even ask for a recommendation, we are also trying to learn by observing the outcomes from another individual’s behavior. Observational learning occurs when people use their observations of others to update their own private beliefs and to take actions, leading to a bandwagon effect that occurs rapidly. Such effects are sometimes inappropriate, fleeting, and can be reversed fairly quickly and easily. (Walden and Browne, 2009).
Using our friends to advertise products to us might work for some items (local services, for instance), but for many other items I’d much rather look elsewhere for a recommendation I can work with. Consider the simple fact that for any purchase decision you want to make, there are both intrinsic and extrinsic elements that might influence your choice. An intrinsic element might be the actual quality of the product, or if it does what it says it does; while an extrinsic element might be more social, i.e does my friend own one.
On Amazon, there are better ways to display product reviews that would be more effective for conversion. For instance, I wonder why product reviews are not being displayed as time-series trend-lines or why there isn’t more sophisticated matching of multiple products according to their reviews. Yeah, I know you can sort products according to their average reviews, but how about comparing the reviews for both product side by side. Research on how people process such buying choices also point out that some form of multi-attribute comparison is done between competing choices, and information is more useful when it is presented in a way that matches the task to be done.
In fact, a robust product review system should be able to allow a consumer to compare correlations of two different product ratings over time to determine whether one product has a better history than the other… not just an average rating that really does not say much. I mean, this is common sense stuff – but think about how useful it would be to look at how people have rated a product over time, and then compare those ratings between products. The reviews can even included weighted averages or more sophisticated algorithms to reduce how sharp the spikes are over time. The same way, these reviews can be averaged for all similar products from a particular manufacturer, reviews for newer versions of the same product can be included – and the customer review can become another starting point for search and getting better product recommendations – this time from people entirely unknown to you. A lot less creepy, right?