As I mentioned in my previous post, there are emerging technologies that are enabling completely new approaches for managing eCommerce experiences. In the coming 18 to 24 months I think we’ll see adoption of such technologies and eCommerce sites will become more responsive to a customer’s individual patterns and more profitable for eCommerce companies as a result.
Products viewed, products added to cart, products removed from cart, and many more product centric bits of data. All the while it is monitoring the behavior of shoppers on your site, it can also be set up to monitor competitor prices.
Once the data begins flowing into the QuickLizard system, rules can be triggered send alerts about products being deleted from a user’s cart, products being purchased only with a bundle, competitive price differences – the list goes on and on. And, perhaps best of all, they offer plugins for some popular eCommerce platforms that allow for rule actions to be automated. For example, let’s suppose the following take place:
- A shopper adds a widget to their cart
- Your site cross sells the customer a gadget, which the shopper adds to their cart
- On checkout, the shopper only buys the widget.
- This pattern repeats a dozen times throughout the day
QuickLizard could use that series of events and, upon checking pricing rules and competitor pricing, could automatically lower the priced of the gadget to see if shoppers begin to checkout with the item in their cart. And if you’re worried about the automation bit, alerts can spur you to take the same action manually.
As eCommerce continues to mature we will continue to see new technologies emerge that leverage the vast amounts of data generated by typical customer interaction with web sites. This information, appropriately used, can be used not only to help eCommerce companies increase profits, but can also be used to provide better customer experiences for the end user. The latter, in my opinion, that is exactly the type of thing for which customer data should be used.