PHILADELPHIA—The market for sports and entertainment event sponsorships is, historically speaking, “intellectually insulting,” says Mark Piening, founder and CEO of Circle Media, a marketing agency.
That’s because brands have spent marketing money—what Piening estimates is $20 billion a year in the U.S.—on these happenings without insight into their audience or their effectiveness in engaging with it.
It’s a prime example of a space that cries out for measurement because such events are one of the best ways to connect with potential customers, Piening says. Attendees are essentially “opting-in” to an experience where emotions are engaged and sponsors are present. “It’s about connecting to those emotional experiences,” he says.
The Data Content conference, organized by the Software & Information Industry Association in Philadelphia on Oct. 15 to 17, highlighted this and several other use cases for marketers to collect and analyze data in fresh settings, applying data to digitize and bring new measurements to traditional ways of doing business.
For example, Piening says his firm hopes to help marketers better spend their event sponsorship dollars. He pointed to event registration, ticketing databases and social media channels as sources of data. His firm can analyze them and present the analysis to clients as “audience intelligence,” which they can then use to build an “audience relationship.”
Online Commerce Borrows an Old Retailer’s Trick
Another use case at the conference illustrating the spread of marketing analytics is the online mystery shopper.
Mystery shopping is nothing new to the retail space. When it comes to e-commerce, however, such old-fashioned tactics as sending testers into the field are innovative. Typical online customer review and comment technologies can be unreliable and uncontrollable. Either every customer is giving 4.5 out of 5 stars, or trolls plant gruesome (and perhaps not earnest) comments. Enter a new service that provides online mystery shopping, and some of the Web’s biggest sellers, such as Google, Amazon/Zappos, GNC and Blue Nile, perk up their ears, says John Ernsberger, co-founder of a company providing such a service, Stella Service.
Online mystery shopping still requires certain analog elements to succeed. Stella employs an army of mystery shoppers to physically buy items online and return them.
Stella then collects data through every transaction and interaction, which allows clients to learn how they fare against named peer customers. Clients can also receive customized reports. For instance, say a department store wants to start shipping furniture to the West Coast; the data affords them the opportunity to analyze how the experiment is going, in comparison to specific other retailers who offer the same service.
Analyzing In-Store Foot Traffic
On the brick-and-mortar side of the retail industry, the ability to measure traffic and sales at individual stores has been a staple of retailers for some time, and technology has existed for decades to visually capture foot traffic as customers enter and leave a store. But retailers have never been able to track those customers while they are actually in the store.
RetailNext has applied camera technology and the emerging world of visual analytics to do just that. It is one of several firms involved in using technologies, including smartphone sensors, to analyze shopper activities with an eye toward optimizing in-store displays and other features.
“We are collectors of movement,” says John Crimmins, the company’s vice president of strategy.
The analytics tool from RetailNext allows a retailer to overlay a heat map onto its store floor plan to visualize customer movement. Customer traffic can be analyzed across different times of day, by how long customers lingered in particular spots, and whether the traffic led to sales and at what rate. The capability exists to track one person through the store, Crimmins says, including monitoring employees to gauge their interaction with clients. The technology will also enable the tracking of wireless devices, and though anonymized, can allow store managers to identify when a particular device re-enters a store.
“We have taken the roof off the brick and mortar store,” Crimmins says.
Retailers are increasingly seeking such capability, he explained, in large part because they can detail their customers’ movements on their online stores. Why not their old-fashioned ones too?
A New Kind of Loan Risk Score for SMBs
Improved data access and analysis have also allowed a startup bank to come to the rescue of an underserved market: Main Street businesses. Small and midsize businesses (SMBs) can find it difficult to access capital. Nearly half that seek it do not get any business capital while 13 percent get some capital—but not nearly enough—according to James Hobson, COO of OnDeck Capital.
Hobson’s company offers to fill that need by collecting and digitizing traditional banking and credit data and using it to create a new kind of credit “score” for SMBs. Datasets can include cash-flow, customer reviews and velocity of transactions.
OnDeck promises a fast banking experience. The loan application process is quick (one can be completed in 10 minutes online) and loan decisions are received as soon as 24 hours. OnDeck Capital has delivered more than $600 million in loans across 700 industries since 2007. The average loan size is $35,000.
Hobson says he does not see OnDeck as a disruptive competitor to existing banks; rather, he foresees the value of its analytics platform — essentially a short-term working capital ratings tool –as an instrument for all banks as well as nonprofit community lenders.
Matthew Brodsky is a freelance writer based in Philadelphia. Follow him on Twitter: @MatthewLBrodsky.