Think about the last time you went into a store. You walked around, took some items off the rack, maybe went into the change room to try them on…and often, without making a purchase you leave. It’s a physical world, not a digital one.
Online, you do the same thing. You browse the catalog, check out the inventory, maybe even put something into your cart, then leave.
What’s the difference? Well, when leaving the physical store there is but a memory of you having ever been there (save for some strategically placed security cameras). However for the online shop, there’s a click by click trail of every item viewed, page navigated, and cart filled. A complete history.
In today’s digital world, we expect that our digital trail will be used in future personalization and marketing tactics. Perhaps retargeting abandoned shopping cart customers. Maybe a homepage personalized with items from the last visit? What about emails filled with coupons for items that were viewed online. All viable and routine tactics of today’s digital marketers. But how do we use that trail to influence the non-digital shopping experience?
Let’s assume you run a contact centre and a retail store network. You set campaigns live for the mass customer segment. Product X at $100. Product Y at $200. For the majority of customers, that’s a sensible model.
How though, would you handle a customer who called your contact centre or visited your retail store after having been to your online shop and browsed specific products at specific prices. What if the product was on sale before and now was back to regular price? What if the customer bought something online and was now walking into your store having not bought any accessories along with it?
Would you offer them the sale price? Would you promote the accessory? Of course you would – problem is – how do you inject markers of digital behaviour into the retail or assisted channel experience?
Well, it’s not that hard!
Today, the intersecting of digital analytics, mobile devices, customer login information and loyalty program data allows for online behavior to be crossed into the terrestrial world. Imagine a contact centre agent knowing the specific item you last looked at online. Or the retail rep at checkout recommending an accessory for the item you last bought online. All achievable outcomes.
It’s really a question of the governance of what data to use and in what scenario to use it, versus the capability to do it at all.