Why CEOs should spend up to half their time recruiting

Published December 17, 2019

Hiring the right people may be the most important thing you do when you start a new company. But how much time should founders spend on hiring when there are so many other competing demands?

Last week, we discussed team-building and several other issues during a panel on the Extra Crunch stage at Disrupt Berlin with Cloudflare CEO Matthew Prince and Red Points CEO Laura Urquizu.

“I was looking through early emails the other day,” said Prince . “I had forgotten how hard it was to hire people in the very beginning. I think that [Cloudflare co-founder] Michelle [Zatlyn] and I spent probably at least 70% of our time in the first two years just begging people to work for us.”

While it’s a hard job to get right, Prince said he didn’t believe that this was a job he should have outsourced to recruiters. “Fundamentally, as the founder and leader of an organization, your job is to attract and retain the best best possible people,” Prince argued. “And so even to this day, at least a third of my time is spent on recruiting.”

Red Points co-founder Urquizu agreed, noting that she also spends at least a third of her time on recruiting. But she also argued that as you grow as a company, your needs may change and you may need to let some people go.

“I usually say that what brought us here is not going to bring us to the next stage — and that includes people,” she said. “It’s not pleasant and it is very hard when you have to say ‘bye’ to people that have been with you in the journey for two years, or for one year, or three years, but then you need to find the next people that are gonna come along with you in the next stage.”

Out of the box influencer strategies to accelerate awareness for your startup

Published September 18, 2019

Kamiu Lee
Contributor

Kamiu Lee is CEO at Activate, an influencer marketing technology platform and agency that partners with brands and influencers to tell engaging and compelling stories across social media at scale.

For new brands, growing awareness and gaining the trust and credibility of consumers are two of the most important yet challenging marketing objectives. As an added constraint, most startups don’t have the budgetary flexibility to activate mega-influencers and celebrities that have national attention at their fingertips. However, new research from ACTIVATE found that smaller-tier, more accessible influencers are a top choice for marketers – they enable brands to tap into niche communities and offer superior engagement rates.

Surveying over 110 brand marketers, PR professionals, social media managers and agency executives, we found that 64 percent of marketers are choosing to utilize micro-influencers very often, as opposed to larger creators, mega influencers and celebrities. We also found that more than 44 percent of marketers are repurposing influencer-created content following a sponsorship, a practice that extends the ROI of an influencer campaign and can help startups attain valuable visual assets for future marketing use.

While mega-influencer content rights are often negotiated to steep rates, those of smaller tier influencers are more affordable, as the influencers themselves also benefit from the added exposure.

With this in mind, when developing an influencer campaign, it’s critical not to feel constrained to the most popular creators, and instead think out of the box and consider what factors will be most important to the audience you’re specifically trying to reach. When being thoughtful about how you’re implementing influencers, smaller creators can be just as impactful as their larger counterparts.

Let’s go through some of the most impactful emerging influencer strategies, to grow awareness, without growing debt.

Key influencer casting strategies to drive targeted impact

The right way to do AI in security

Published April 10, 2019

Artificial intelligence applied to information security can engender images of a benevolent Skynet, sagely analyzing more data than imaginable and making decisions at lightspeed, saving organizations from devastating attacks. In such a world, humans are barely needed to run security programs, their jobs largely automated out of existence, relegating them to a role as the button-pusher on particularly critical changes proposed by the otherwise omnipotent AI.

Such a vision is still in the realm of science fiction. AI in information security is more like an eager, callow puppy attempting to learn new tricks – minus the disappointment written on their faces when they consistently fail. No one’s job is in danger of being replaced by security AI; if anything, a larger staff is required to ensure security AI stays firmly leashed.

Arguably, AI’s highest use case currently is to add futuristic sheen to traditional security tools, rebranding timeworn approaches as trailblazing sorcery that will revolutionize enterprise cybersecurity as we know it. The current hype cycle for AI appears to be the roaring, ferocious crest at the end of a decade that began with bubbly excitement around the promise of “big data” in information security.

But what lies beneath the marketing gloss and quixotic lust for an AI revolution in security? How did AL ascend to supplant the lustrous zest around machine learning (“ML”) that dominated headlines in recent years? Where is there true potential to enrich information security strategy for the better – and where is it simply an entrancing distraction from more useful goals? And, naturally, how will attackers plot to circumvent security AI to continue their nefarious schemes?

How did AI grow out of this stony rubbish?

The year AI debuted as the “It Girl” in information security was 2017. The year prior, MIT completed their study showing “human-in-the-loop” AI out-performed AI and humans individually in attack detection. Likewise, DARPA conducted the Cyber Grand Challenge, a battle testing AI systems’ offensive and defensive capabilities. Until this point, security AI was imprisoned in the contrived halls of academia and government. Yet, the history of two vendors exhibits how enthusiasm surrounding security AI was driven more by growth marketing than user needs.