Autometrics takes an hourly pulse of Web traffic at 150 car-buying sites to give auto makers predictive insights about buyers.
A new breed of third-party analytics company is emerging. These businesses collect data, study it using big data techniques, and deliver predictions and other insights back to clients. But unlike an earlier generation of data syndication services, their value is tied to ever-faster processing of massive datasets.
Autometrics aggregates car shopper data to help its clients better track retail demand, competitive trends, media effectiveness, and cross-shopping. The basket of metrics for its automotive clients is a very powerful predictor of consumer intent, Stephen Shaw, group chairman and CEO, told InformationWeek in a phone interview. Autometrics reports on the purchase intent of more than 25,000 new car shoppers every hour across more than 150 third-party car sites such as Edmonds.com.
For every shopper, it captures their preferred make, model, trim, and zip code. The data can be parsed at the national, regional, and market level for more than 210 markets.
The 3 billion-record database, which now contains online shoppers' activities dating back to 2008, is analyzed nightly. Fronting the database is a Microstrategy BI tool. Manufacturers can pull the reports dynamically via FTP or cloud storage services like Dropbox. A few are even drawing the data directly into their BI systems.
With the Autometrics data in hand, auto makers can decide whether or not to provide extra dealer offers and incentives to buyers or invest in additional paid search campaigns.
Autometrics' data is useful, but it hasn't revolutionized how agency Saatchi & Saatchi Los Angeles (SSLA) handles campaigns for its client, Toyota. That's because automobile campaigns aren't always trying to drive shoppers into buying tomorrow -- or even next month. "Many campaigns are designed to increase awareness and consideration over a long sales cycle from several months out to even years," Conrad Nussbaum, analytics director at SSLA, told InformationWeek in a phone interview.
Nevertheless, the daily data extracted from third-party car-shopping and review sites gives clues about consumers and markets and can reveal interesting correlations. For example, when a Toyota Tundra truck helped move the Space Shuttle Endeavour from a hangar at Los Angeles International Airport to its permanent home at the California Science Center in Los Angeles last October, Autometrics data indicated that shopper interest in Tundras increased across the country, and increased at four times the national average in Los Angeles, according to Nussbaum.
Shaw co-founded Autometrics in 2000 and initially offered services to a variety of industries, including automotive and insurance. It added financial services in 2007, just before the worldwide economic crash. "After that, we reexamined our business model," Shaw said drolly.
But, he added, the recession turned out to be advantageous for his company because it forced Detroit's auto makers to realize they had to change [and] become more efficient. They saw that they needed better ways to align their production to demand. "Consumer surveys and six-week-old sales data weren't enough," Shaw said.
Autometrics' fortunes have also been helped by the much-reported data scientist gap, which presents an ongoing challenge for its customers. "Their biggest challenge is they don't have the analytical capabilities on board," Shaw said.
There's no single migration path to the next generation of enterprise communications and collaboration systems and services, and Enterprise Connect delivers what you need to evaluate all the options. Register today and learn about the full range of platforms, services and applications that comprise modern communications and collaboration systems. Register with code MPIWK and save $200 on the entire event and Tuesday-Thursday conference passes or for a Free Expo pass. It happens in Orlando, Fla., March 17-19, 2014.
6 Tools to Protect Big DataMost IT teams have their conventional databases covered in terms of security and business continuity. But as we enter the era of big data, Hadoop, and NoSQL, protection schemes need to evolve. In fact, big data could drive the next big security strategy shift.
Big Data Brings Big Security ProblemsWhy should big data be more difficult to secure? In a word, variety. But the business won’t wait to use it to predict customer behavior, find correlations across disparate data sources, predict fraud or financial risk, and more.
Join InformationWeek’s Lorna Garey and Mike Healey, president of Yeoman Technology Group, an engineering and research firm focused on maximizing technology investments, to discuss the right way to go digital.