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Zenefits hints at marketing's future

News, 17 September 2015

NEW YORK: Zenefits, a provider of "all-in-one" human-resources software, is demonstrating how combining some Silicon Valley-influenced flair and rigour can help marketers drive rapid growth.

Matt Epstein, the organisation's vp/marketing, discussed the two year-old company's communications strategy at the Marketing Nation Online virtual conference held by Marketo.

"We are an incredibly data-driven org," he suggested. "Data has been our North Star." (For more, including practical examples, read Warc's exclusive report: Zenefits offers marketing lessons from Silicon Valley.)

Having seen revenues grow from around $2m in 2013 to a forecast $100m in 2015 - as well as achieving a valuation of $4bn - this model has undoubtedly paid off.

The main tactics supporting this dramatic expansion include A/B testing, marketing automation and, more recently, doubling down on "growth hacking".

Although these technique are regarded as cutting-edge, the channels initially employed by Zenefits to establish and finesse its brand positioning were rather unglamorous, and led by email and online display ads.

"If a bunch of people are clicking on your ad but people aren't converting, it probably means your pitch is bad or your positioning is bad," said Epstein.

"Or if no one's is clicking in your ad, it means your tagline's off. We went through hundreds of tests in all of these cases, and that's how we landed on the pitch we have today."

After finalising its core proposition, Zenefits has embraced approximately 30 marketing channels. But it has retained an emphasis on rigorous analysis alongside a continuing desire to move rapidly and decisively.

The latter principle is exemplified by the phrase "Ready. Fire. Aim" - a coda which Zenefits believes can guide brand custodians seeking to act at speed.

"This is actually a mantra we have internally, and it's obviously about creating a bias for action … If you're happy with a campaign you worked on, you almost definitely spent way too much time on it," Epstein said.

"You could waste a lot of time trying to build the perfect thing instead of just getting it out, learning that it works and getting data back to re-test your hypothesis."

Data sourced from Warc