M: Facebook’s ‘MoneyPenny’ Will Be Money for Consumers and Advertisers

At scale, M would generate data encompassing a huge portion of consumers’ purchase paths, from the moment a user enters consideration to when he or she finally converts.

Facebook’s new virtual digital assistant — MoneyPenny, or ‘M’ — could give Facebook an abundant source of intent data that goes far deeper than Google’s search data. That is, Facebook may soon rule the gold mine of information that enables advertisers to give customers exactly what they are looking for.

At scale, M would generate data encompassing a huge portion of consumers’ purchase paths, from the moment a user enters consideration to when he or she finally converts. Data that capture both consumer intent and the nuanced consideration criteria that go into decision-making can give advertisers unprecedented insight into that journey.

Asking M to “find me an Italian restaurant that won’t be too busy at 6:00 p.m. – one that’s highly rated, on the water and good for a first date” provides more data than a standard search query. It contains priorities, context, and potentially even decision reasoning. Combine that with the psychographic and demographic data the platform already collects, and you have an immensely powerful dataset for marketers to tap into.

M would give Facebook multidimensional intent data from two new data sources: user’s queries into M, and the operator’s behavior and action within various third-party apps.  The “Operators” on the other end of M are the people who translate a user’s request into the multitude of other interfaces that might be needed to arrive at, or deliver, a user’s desired outcome.

Decisions that used to be made on a single intent signal can now be segmented and optimized based on the person as well as the degree of intent. Targeting accuracy and the relevance of ads served to its users will increase. Advertising waste will go down. Profits will go up.

Similar intent would no longer be viewed as identical. Search queries on Google may be similar or even the same, but the desired outcome and the path taken to get there are often very different.

For example, Facebook could watch a user request a plane ticket and understand both the hard parameters the user provides (depart on Tuesday, Jan. 14; find the lowest possible price) and the flexible parameters (time of departure doesn’t matter; may leave from any airport in the New York metro area). Over time, information like this would enable Facebook to understand which people are willing to travel out of any airport around NYC, so long as the price and day are right.

If M were to be rolled out to all users across the platform, what would be the impetus for consumers to adopt it?

Simple: M enables consumers to request and receive curated information, then act on it, using natural language, just as we’ve been doing for thousands of years.

Facebook already drives amazing results for advertisers, thanks to its rich consumer data, and the way it integrates marketing intelligence at scale directly into its ad tools. By piping M’s information into its advertising algorithms, Facebook will provide users with an even better experience across the entire web, and drive tremendous increases in advertisers’ ROI. This unprecedented level of insight into consumers will bring marketers closer than ever to reaching the right person in the right place at just the right time.

James Donner is director of ad insights at SocialCode