I wanted to expand a bit on my last post about inventory integration, on two points.
The Effect of Long Shipping Times
First, I discussed how a product’s inventory status (in stock versus out of stock) has a significant impact on conversion rate (CVR). Adlucent also found that long shipping times can have a similar impact. From a customer’s point of view, if a product will not ship for 10 days, it might as well be out of stock—as long as there’s another retailer who can ship it faster. Deep Search measures the decline in CVR with extended shipping delays and pauses keywords when the delay will cause a drop in CVR. These rules are unique to each retailer. Deep Search then re-allocates the investment elsewhere.
The Future of Inventory Integration
Second, I wanted to briefly mention a challenging inventory-related problem Adlucent is working on: how to predict CVR for a product with multiple attributes (such as size and color) when only a subset of those product combinations is out of stock. A particular shoe, for instance, comes in multiple sizes and colors, and the same keywords might drive buyers to the same product page. But what if only the popular size 10/brown shoe combination is out of stock? Deep Search would respond by using predictive search algorithms to model the temporal drop in conversion rate and apply this until the particular size/color combination is back in stock.
Image courtesy of ACCTivate