Predictive Analytics Example
As a follow up to some recent posts, this one will hopefully give you a better idea of predictive analytics in action.
Recurring Orders
Just recently, I received an order from a dietary supplement supplier for multi-vitamins. The ones that I buy made by AST Sports Science, are much better than your typical One-A-Day vitamins and are geared towards athletes. I’ve been buying them for about ten years now through a few of different suppliers.
Enough background, here is where the predictive analytics comes into play. I take one vitamin a day and typically buy two bottles at a time. There are exactly 100 vitamins in each bottle. Now, I am disciplined and take one every day. It doesn’t take a statistician to tell you that in roughly 200 days, I am going to need more. Let’s assume that I miss 10% (20 days) due to forgetfulness. Let’s also assume that I want my next shipment before I actually run out so there are no missed days (10 days).
Days supply lasts +200
Missed days +20
Days for early notification -10
Reminder in 210 days
Predictive Analytics at Work
The supplier should be able to predict, with confidence, that I will need another shipment of two bottles in roughly 210 days. My supplier, who I’ve been using for many years now, should now setup an alert on my account. That alert could simply send me a reminder e-mail in 210 days about a reorder. Or, the supplier’s system could setup the same alert and then gear offers or discounts toward what I’ve bought historically. Again, not rocket science, the key or value added is to make it as easy as possible for the customer (me) to make repeat purchases without overdoing it or annoying the customer. By doing these simple things, the company can probably reduce customer turnover and increase sales. Heck, the company can pool customer data and determine what the most bought product is where vitamins are in the order. It really is scary how powerful predictive analytics can be when utilized effectively.
Want to see some basic and advanced predictive analytics in action, just check out Amazon:
- What do customer buy after viewing this item
- Latest from authors you have previously purchased
- Personalized Recommendations
- Books frequently bought together
- One-click ordering
Start today and think about how you can add value and improve your customer’s experience. If you start thinking and talking about predictive analytics, I guarantee you will impress some people and most importantly, your boss.
Have any good examples or stories to share, post a comment or send them to me.
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October 22nd, 2008 at 10:53 am
You could go even further with that example – they could factor in the shipping time from your last order, and figure out if you typically reorder order every 100 days because you’re sharing your bottle.
October 22nd, 2008 at 11:34 am
Hadley – thanks for the comment, which is a great point. There are so many variables that can be taken into account to improve the customer experience and increase profit for companies. These things are so easy to put in place if the data exists, yet so many companies do nothing.
This particular company sends me a weekly specials email, which includes items I have never or would never order. Instead of annoying me with junk e-mail, customize my experience and tailor offers based on my historical orders.