How I Used Data-Driven Decision Making to Land a Startup Job

Autopilot on 9th of Dec 2016

How I Used Data-Driven Decision Making to Land a Startup Job

Data-driven decision making is a huge trend in the startup world—especially for marketers, who are increasingly expected to disregard their intuition and make decisions backed up by verifiable data.   “If it hasn’t been tested or proven, it’s merely an opinion,” writes Jaco analytics CEO Danni Friedland. But even sophisticated marketers don’t always know what that looks like. That was our inspiration for this post. We wanted to break down an actual data-driven decision into stages, giving you a taste of the process.


When I first started my content writing business in February 2016, I faced a significant hurdle: I had to convince future clients that I could deliver high-quality content, even though I had never worked as a content marketer. For this reason, in addition to publishing samples of my work on Medium, I decided to use Twitter to demonstrate my knowledge of content marketing best practices—what Altimeter, a Prophet Company, calls a “content as currency” strategy. “This archetype is embodied by companies who create high-quality content that serves to educate customers, give them exclusive information, and provide them with expertise that is related to the field of their products/services,” writes Omar Akhtar, Managing Editor and Analyst at Altimeter. The strategy was effective in growing my online presence. It helped me grow from just 117 followers on February 1 to 481 followers on May 1—an increase of 311% in just 3 months (about 62% per month on average, well over the average month-over-month growth of 7.91%). Twitter follower growth It was a phenomenal achievement, but I had already begun to wonder: Am I attracting the _right _followers? After all, only a small percentage of my followers inquired about my services. Plus, increased credibility was worthless if I appeared credible to the wrong people. This lingering concern ate away at me until early May, when I decided to make a change.

Data-driven decision making

After coming to the realization that what I was doing wasn’t working, I knew that my next move needed to be backed up by credible research, data, and analysis. If I wanted to see results, I would need to:

  1. Ask the right questions

  2. Collect and analyze the data

  3. Make an informed decision

Asking the right questions

One of the most important steps in making a data-driven decision is asking the right questions, because it helps you frame the entire process. Ask the wrong questions, and you risk collecting irrelevant data, coming to the wrong conclusion, and ultimately failing to get the intended results. In this case, before I could revise my social media strategy, I had to reflect on and answer 3 questions: “What are my objectives?” Social media marketing takes considerable time and effort. On average, I spent an hour each day curating relevant content and another 30 minutes engaging with my community of followers—nearly 550 hours per year! Scheduling social media posts That means that, at my median hourly rate, I was investing almost $41,000 per year in social media marketing. Unless I could achieve decent ROI, it wasn’t worth doing. For this reason, my objectives were simple:

  1. Get valuable gigs (those that were either well-paid or offered considerable exposure—preferably both)

  2. Build and maintain strong relationships with my clients to ensure I keep the customers I worked so hard to convert

My engagement strategy was proving effective. (By the end of the year, several clients had raved about my online presence, and I had even been featured on Search Engine Journal’s 100 Amazing Women Marketers to Follow on Twitter.) But I wasn’t getting as many gigs as I would have liked, which led me to ask: “What segment of followers delivers the most value?” As a solopreneur, I wasn’t concerned with creating the kind of brand presence that would have customers lined up around the block. In truth, I could only produce so much without compromising the quality of my work. But to land more gigs, I knew I needed to be more visible to my target audience—blog editors and other content marketers responsible for hiring and working with freelance writers. Despite targeting this audience from the very beginning, my strategy hadn’t been as effective as I had hoped. If I wanted to change that, I needed to determine which segment of followers delivered the most value and work backwards from there. “What are they interested in?” After identifying a segment of high-value followers, I would also need to uncover their pain points and interests. That information would inform what content buckets I included in my revised social media marketing strategy.

Collecting and analyzing data

To answer these questions, I collected and analyzed data from two sources: SocialRank and Twitter. First, I used SocialRank to determine how many of my customers were originally engaged Twitter followers. Most engaged followers After requesting my report, I discovered that two-fifths of my most engaged followers worked in the B2B SaaS industry. Many of the faces I saw were clients who had interacted with me on social media for weeks (and, in some instances, months) before requesting a quote. As I reflected on this data, I realized that this segment was responsible for the vast majority of my revenue. Without realizing it, I had engaged with a specific community. Why? Because I was genuinely interested in what that community talked about. And, as a result, I had included references to B2B SaaS companies in the content I wrote, which in turn attracted the attention of that community. (Phew! That was a mouthful.) Next, I downloaded every tweet that went out between February 1 and May 1 to determine what type of content attracted the highest engagement. Download Twitter data What I quickly noticed was that, more often than not, the content topic was secondary. Sure, content about content marketing was interesting to content marketers. But what appeared to matter more was the brand behind the content. To verify my assumption, I opened Twitter to determine who engaged with my most popular tweets. Sure enough, content I curated from brands like Moz and Buffer attracted more engagement—but not just from anyone. This content appealed to one segment in particular: B2B SaaS marketers. My conclusion? B2B SaaS marketers wanted to learn from one another, which made sense because the industry is known to move fast, experiment often, and openly share what they’ve learned with others.

Making an informed decision

Based on the analysis above, I revised my social media strategy to emulate Altimeter’s “Content as Community” archetype, which suggests that it’s worth pursuing a community-driven strategy if people within your community are more likely to buy than those who aren’t. What exactly does that strategy look like in practice? Well, instead of restricting myself to tweeting about content marketing (which was effective in attracting followers, but unsuccessful in creating sustainable demand for my services), I now create and curate content that appeals to content marketers who work in the B2B SaaS community:

  • content published by reputable B2B SaaS brands

  • content about working in the B2B SaaS industry

  • news that impacts the B2B SaaS industry

It may seem counter-intuitive, but restricting myself to a niche audience has been super effective. Why? Because companies—and the people who work for them—in the B2B SaaS space are intimately familiar with one another. In such a tight-knit community, everything I write (and later promote on social media) gets seen by others in the industry. In other words, it’s easier to get exposure. Get recommended Plus, because many people within the industry know each other, word travels fast! So, the editors I work with often recommend me to others.  

Better results than I could have imagined

Six months later, I can say with confidence that I made a smart decision. Not only did I continue to grow my followers, but I attracted more of the _right _followers—leading to more gigs as well as more valuable gigs. It also helped me boost my Twitter engagement and social media marketing ROI. Boost Twitter engagement rate But that’s not all… I recently landed a full-time role with one my best clients: Autopilot. (Yep, you read that right!) As Autopilot’s new Content and Community Marketing Manager, not only do I get to contribute content to the Liftoff Blog, but—as a result of my online presence—I also get to manage Autopilot’s social media marketing and community efforts. Score! **What’s your process for making data-driven decisions? Let us know in the comments. **

comments powered by Disqus