During campaign season, the Obama re-election team made sophisticated use of data mining applications.
If you were an Army veteran working a union job, and the campaign targeted you as a likely Obama voter, then another union member who had served in the military would be asked by the campaign to give you a call, or send you a Facebook message, urging you to vote.
And while the apartment industry is slow to adopt new technologies, many of the largest owners are now mulling how they can best use the mountains of data collected every day at their communities and on their websites.
"Today, people search based on number of bedrooms, location, price point. The truth is, if you asked them what they really want to know, it would be, what are the people like that live there? What are their habits and hobbies?" says Tom Toomey, CEO of REIT UDR. "So the next search engine is going to be around the social media aspect, which is what type of people live here, and what do they do? And the mechanism to collect that data is all on our websites."
While social media has played a significant role in changing the scope of the multifamily industry, plenty of industry experts still doubt its use in data mining.
“It’s clearly not something that’s going on very much because it’s very hard to get information from residents on social media right now,” says Steve Lefkovits, president of Emeryville, Ca.-based Joshua Tree Conference Group. “It’s difficult to get actionable information.”
Lefkovits is a proponent of social media and its uses, but is skeptical of it in the data mining sphere. While the sites are good for referrals and generating a small percentage of leads, personal information about residents that might be used to benefit the industry are protected by privacy laws, which would theoretically prove data mining on social media useless.
And because social media is so broad, it’s difficult to manage its data.
“At this particular moment I’d be pretty hard-pressed to find a data driven application aimed at multifamily, much less an analytical use for social media,” Lefkovits says.
In the multifamily sector, there’s been a high failure rate in the investments of expensive projects driven by software that garners this data, he says, adding that its purpose may be better suited for big research companies. Moreover, operators must distinguish between data mining and predictive analytics.
“They’re disappointed in Big Data analytics because of the number of human factors,” he says. “Data must be actionable. That’s why it’s so difficult for multifamily to see a big role in data mining or predictive analytics.”
The most difficult of social media is that rich media sites yield little data about residents, failing to add real value to analytics that are no better than typical marketing tactics. “It’s always going to be a niche practice [in data mining], whose cornerstone is pricing,” Lefkovits says.