These two new players join Krillion, Milo, NearbyNow and a few others trying to solve the long-standing problem of how to connect online product research and offline buying. However their approaches are very different: Retailigence integrates with retailer software and systems, while Goodzer crawls for inventory data with no direct retailer relationship.
I’m late posting on the formal launch of Retailigence because last week I was busy at the Local Social Summit and IYP Search Meet events in London.
One of my three presentations at those events was about the state of local product inventory. US IYPs have flirted with adding local product data (through partnerships) but they’ve generally offered poor integrations of the data and mediocre user experiences to date. Outside the US market, Sensis and European Directories have tried in Australia and in Amsterdam. But both said they were unhappy with the outcome.
Demand for product inventory information is something that grows as consumers move toward their purchase decision. However, according to some recent consumer data published by JiWire, users care more about store locations than product inventory. Partly that’s about retailer loyalty. It’s probably also because nobody has done a great job with product inventory integration so far.
The launch of Goodzer (this week) and Retailigence puts some pressure on existing players and begins a race to scale. The first data vendors/syndicators that can reach scale across a meaningful range of categories will see lots of demand for their content (as well as acquisition offers). Most companies and shopping comparison sites aren’t going to try and develop the relationships or the technology that enable real-time product inventory to be exposed online. However they will all take this data once it becomes broadly available.
Retailigence announced that it raised $1.5 million in an initial round. The company already has a number of partners with more on the horizon. It integrates with key enterprise software vendors and systems such as SAP as its way of getting access to the data. This is the “OpenTable” approach. Crawling is faster but less accurate as a general matter.
The company’s business model is based on use of its API; however in limited circumstances there’s a CPM/impression-based fee being tested. There are also other performance models possible — such as a fee for driving a customer into a store. NearbyNow was collecting such a fee at one time.
Retailers love the idea of driving people into stores; a local customer is worth more than an e-commerce buyer. However they don’t like the idea of being compared on price at every turn. This is the contradiction and challenge for all at the heart of local product inventory search.
We’re now at something of an “inflection point” for local product search. This was (and still remains) a hard problem to solve, especially at the SMB level. I think that the chart above will look somewhat different in a couple of years as consumers gain more experience with local product inventory search and come to expect this information to be available.
See also: Milo adds deals and coupons.