Reflections on time in the Valley (Fort Valley, that is)

Posted on May 17, 2017Leave a comment

This month, I stepped back from my full time role as Head of Analytics at Sestra to explore other opportunities. I’ve had more time to reflect on my goals, and I hope that this post might inspire you to take some similar steps!

Reflection 1 – Take time to reflect (how meta).

I’m the type of person who throws myself into whatever I’m working on – my job, a side project, flag football, or a new video game. I’m also incredibly future-oriented and it’s important to me to feel like I’m working towards something. It’s hard for me to check out and enjoy some down-time.

Luckily, my wife’s family lives in a peaceful, rural area, and whenever we visit, it’s great to just sit back and take in the moment. The view here is always beautiful, but this year it’s especially awesome. It’s hard to see, but in the tree in front, there’s an oriole nest (like the Baltimore Orioles!). I’d never seen one of them in person, let alone in such a beautiful setting. I didn’t have my DSLR with me, but they’re extremely pretty birds!

While I was enjoying this view, I reflected on what I could do to accomplish my career and lifestyle goals.

By intentionally setting aside time to relax and reflect, I gave myself the space to make tangible changes. I’ve had some of these ideas for a while, but without pausing my busy life to work through them, they were just theories. Turning those ideas into actions required me to step back from my projects and, yes, stare out the window for a little while.

What ideas do you have that could become actions with focused reflection?

Reflection 2 – Make good habits easier than bad habits.

I enjoy video games and I’m pretty good at them. Unfortunately, the same personality trait that has served me so well in my career – the ability to get completely absorbed in a task or project – can take my gaming from a pleasant outlet to a bad habit. How many hours have I sunk into gaming that could have been directed towards a project? More than I’d care to say. Even the act of writing this post is making me think back to the last time I went on a real video game hiatus, and how much of a difference it seemed to make in my ability to string together days of writing, exercise, and similar activities.

The highest rank I’ve gotten in this game!

How can I improve? I could set aside an hour a day for gaming and try to stick to that, but I’m not very successful with that type of strategy. I’d rather just avoid buying the carton of mint chocolate chip once than have to avoid it every time I open the freezer.

So I went with a more drastic measure. As I was in the middle of writing this post, I uninstalled Hearthstone (my current game of choice) from my laptop and phone. It’s not a total barrier, but if I get tempted to play again, I have the ten minutes of installation time to reconsider.

I know I won’t stay away from video games forever – and I don’t want to, either. On the last Smart Passive Income Podcast I listened to, the guest discussed having a distractions device with all your games and social media, so that you can take those distractions off your main device. That seems like a reasonable idea for whenever I decide to ease back into video games.

*Note from 4 days later* This single moment of strong decision making has 100% enabled me to finish this post. I’m certain the time I’ve taken to edit and rewrite would have gotten buried under many rounds of Hearthstone, if it was still installed.

Reflection 3 – Habits are easiest to alter in times of other change.

Remember when the word “inbox” called to mind the image of a tray on your desk that you actually emptied from time-to-time? Well, I don’t either, but I understand that’s how it used to work. When I started writing this post, I had almost 8,000 emails in my inbox. I have long dreamed of returning to the nirvana-like state of Inbox Zero, but I knew I was never going to be able to work my way through all of these messages.

So, I declared inbox bankruptcy. Remembering that habits are easiest to break or form during times of change, now is the perfect time for me to reset! With my job transition happening, I have the opportunity to start fresh and redevelop some of my good habits that have slipped over the past few years. One of those is offloading some of the cognitive drain caused by to-do tasks sitting in my inbox in the form of thousands of emails.

Oh Hello there Inbox Zero! Long time no see.

*Note from 4 days later* – Still going strong! I’ve been able to batch actions and then archive emails that come in and maintain the cleaner inbox.

Reflection 4 – Managing your energy helps accomplish more

Work-life balance is more about weaving together my passions at work and time spent on other pursuits than partitioning “day job” from “rest of life”. The same SPI podcast I mentioned earlier also talks about managing your energy, which means you need to know when you’re most and least productive and design your schedule accordingly.

Ever since college, I’ve known that one of my most effective work periods is in the evening after dinner. Last night I came back from on-site time with a client, ate dinner and walked with my wife and dog, napped, and then accomplished a ton from 7:30 – 10. Generally, I’d checkout around 9pm if I was working in the evening, but when you’re in the flow, you just want to keep going!

Jack helps my family take time to go for walks!

When a job boxes you into 9-6 (or expects 9am-9pm), there’s a lot of dead time in there because you’re forced to work at times when you’re just not that productive. When you can re-energize with a walk, nap, or your favorite TV show, you’re going to feel much more engaged during the time that you’re working. This another huge remote work/being your own boss perk, because I can take the time to keep my energy up and work efficiently. For example, since I know that writing requires high engagement, I schedule it during my more productive hours. I’m hopeful that at some point writing will become less of a struggle to me and more of a relaxing pursuit, but for now, it’s still a high energy/concentration activity.

Sometimes finding your true north again means going to a physical and mental location where you can disengage from the day-to-day and reflect on your opportunities, values, and goals. Fort Valley is that place for me – I go there to relax and spend time in nature with family. I encourage you to find a time and place where you can do the same!

Unicorn or Zebra: Redefining Success at Startups

Posted on March 30, 2017Leave a comment

As a founder, it’s important to know what success means for your company and how it impacts your financial goals, company culture, and hiring practices. Defining something as nebulous as success is intimidating, so let’s break it down.

Do you want to be a unicorn or a zebra?

To find out, check out this month’s post over at Entrepreneur’s Handbook.

9 Best Startup Analytics Tools to Learn

Posted on February 28, 20172 Comments

What are the most desirable analytics tools to learn? Let’s find out.

For folks looking to build a career at a startup, I love Wealthfront’s Career Launching Companies List. Wealthfront considers attributes of different organizations that means there is a higher likelihood of landing in a role with upward mobility, and the chance to prove yourself. Opportunities at these companies should set you on a solid path in your career. So, what are the most in-demand analytics tools at these organizations? I did the research. Check it out!

Plus, when you’re done, get the rest of my Guide to Startup Analytics Skills, Tools, and Titles.

The number by each tool is the percentage of companies on the Wealthfront List that is running that tool.

1) Google Analytics (78%)

No surprise that Google Analytics tops this list. If you want to do web analytics at basically any stage company, take the time to learn GA!

2) Google Tag Manager (56%) / Segment (11%)

Tag management is a critical path tool for managing analytics effectively. GTM is extremely popular (and free), where Segment offers a ton of additional functionality on top of being an event management tool. Plus, to get a little bit meta, Segment is also ON the Wealthfront list. Bonus!

3) Facebook (50%) / Google (60%) / Bing Ads (27%) / LinkedIn Ad (22%) Pixels

It’s interesting to see Facebook ad pixels so high up this list. Successfully measuring your marketing spend is a critical component of a web analyst these days and Facebook/Google top the list, with the others used less often.

4) Optimizely (34%)

I’m excited to see that such a large percentage of these companies settling on an experimentation / optimization tool. Optimizely lets you run basic website experiments extremely easily, and with a sophisticated team and development staff, you can do amazing testing.

5) Marketo (31%)

The highest ranking marketing automation suite. Personally, I’m a hubspot fan, but once you learn one MA tool, you can basically work in any of them. It looks like Marketo is the one you should choose to learn first.

6) Appnexus (25%) / Adroll (20%) / Quantcast (14%) / Demandbase (11%)

These third party advertising tools all have strengths and weaknesses, and could be a post on their own. Make sure to do your research and see which might be able to help any particular project or company that you’re working with! Side note here, too – Quantcast is also on the WF list!

7) Crazy Egg (18%)

Crazy Egg is a cool UX analysis tool helping you understand how users interact with your site (whether they take intended behavior, or not).

8) Mixpanel (7.8%) / Amplitude (6%) / Kissmetrics (3%)

Frankly, I’m mildly surprised that these tools are so low on this list. My inclination as an explanation is that by the time a company gets on the Wealthfront Career building list, they may simply use custom-built in house tools in lieu of options like these 3.

9) Hotjar (9%) / Fullstory (3%)

Watch real-time examples of users using your product. Learn where they struggle, experiment, and improve!

If you want to learn more about what to look for in your next startup analytics job, go get my Guide to Startup Analytics Skills, Tools, and Titles.

Do you have questions about Startup Analytics? Comment, or head to my contact form.

**If you’re curious, these counts were done by scanning each company’s homepage using ghostery. I know that won’t capture 100% of the tools being used, but it’s a pretty good estimate.

This hiring mistake still happens in 2017?

Posted on January 26, 2017Leave a comment

What’s in a name (on your resume)?

One of my passions is helping people look for jobs at early, exciting startups. Whenever I hear that a friend is job hunting, I check in to see how her experience is going. One recently had a demoralizing experience that confused me enough to write about.

Let’s set the stage.

Imagine a candidate who exceeds the experience requirements for a job position. We know that not every candidate and company is the right fit, but her expectations are high. After submitting an application in their recommended format, she expected to at least get a preliminary interview. But, she doesn’t even hear back. Being a strong, and aggressive, she follows up with the recruiter to see where her application stands.

What Happened?

The recruiter told her, “You have a strong background, but we are looking for someone with deeper SaaS Analytics experience in name brand emerging companies for this role.”

Wait, What?

What does that even mean? Based on the job positing, she’s an amazing candidate. It is clear that the company is looking for something else, even though they won’t ask for it explicitly.

I’d typically be more specific about her credentials to prove that skill fit, but I don’t want this article to show up in Google results for the person’s name. As much as I’d like to call out this particular company for what I consider a ridiculous hiring requirement, I’ll refrain from doing that, as well. However, this company is decidedly not a name brand. As a bootstrapped organization with a successful founding team, the resume of the person in this role will have no material impact on the company’s fundraising or business opportunity. All that matters is her skill set.

So what gives? Why would a company value a high-profile resume line item over demonstrated experience?

Our candidate followed up with the recruiter to ask for more details about this questionable response, but she never heard back. So, she came to me with a lot of questions about what this response means and how she can learn from it. What can she do about the fact that she hasn’t worked for Facebook or Google?

In my opinion, wanting experience at a “name brand” company is a lazy shortcut for hiring decisions. I’m sure this organization gets tons of applications, and maybe they only want to talk to folks from Facebook. But, this company is an all-remote organization! They have the opportunity to find talent anywhere in the country, from even the humblest origins. By choosing to limit themselves to candidates from well-known companies, they are limiting themselves to candidates from the Bay Area, New York, and a few other big cities. As a remote organization, why would you blow one of your main hiring advantages by enforcing a secondary requirement which reverses that benefit?

So what can a job applicant do?

Unfortunately, our candidate wasn’t missing a critical skill that she can learn through classes or side projects, so this is a harder problem to solve. Here are a few pieces of advice for her and anyone else who feels their application was unfairly dismissed:

1) My favorite answer is a classic one. Check for connections. If you can find a friend of a friend to make a referral, you’re much less likely to get lost in the shuffle of bad hiring practices.

2) Reach out over top of the recruiter, first. I’m sorry for recruiting folks. If a resume lands in the inbox of an executive team member, it’s more likely to get acted upon than if only a recruiter sees it.

3) Suggest a trial project. A qualified applicant like my friend probably has an idea of what the organization’s pain points are. If she suggested a solution to that problem, instead of a generic application to an open position, it’s likely that she would have gotten a more satisfying response.

4) Don’t let an outcome like this get you down. Remember, stuff like this happens all the time to even the most qualified candidates. It feels frustrating and unfair to be overlooked when you know you would have done a great job in that role. Just remember that it was the company’s hiring mistake, not yours. There will be another role, a wiser hiring manager.

These types of applications stand out from everyone else’s generic resume. It’s clear from this case that the company in question missed out on a talented applicant for a bad reason. Don’t let it happen to you!

Want to make your analytics job application stronger? Sign up to my email list to get my guide to in-demand analytics skills (coming Early Feb) or my course on startup analytics!

How people find out your product is awesome – User Acq 101

Posted on December 15, 2016Leave a comment

User acquisition can seem like a daunting task; heck, even the name is daunting. All “user acquisition” really means, though, is getting people to use your product. A huge part of this is helping potential users find your product. At Speek, we knew that it takes hard work to help people know that we are making conference calls awesome. This is where “user acquisition” comes in.

Basically, it all comes down to the sad truth that the movie Field of Dreams didn’t tell us the whole story: if you build it, and you get the word out about it, then they will come.

Some tips from the trenches:

1. Be scientific.

No matter who I’m working for, I help prioritize being a “data-driven company”; in every aspect of our decision-making, we want to rely on actual data and analysis, rather than vague notions of what people might want, or worse, what any competitors are doing. With user acquisition, you want to be very “Darwinian” in your approach. We look at cost per acquisition, or CPA, i.e. the cost of each acquisition channel (e.g. paid advertising through Google AdWords) versus how many users that channel successfully brings in. For example, if you pay $3/click on AdWords, and 5% of those clicks convert into users (through registration, purchase, subscription, etc.) then your CPA for that channel is $60: it takes $60 for you to get one user. Working with hard numbers like this goes a long way toward demystifying the whole process.

2. Cast a broad net, then narrow it down.

When trying to minimize your CPA (i.e. lower the cost per acquired user), you want to try as many channels as you can reasonably afford (in time and energy as well as dinero), and then scale individual channels up or down (or phase some out entirely if the CPA is too high), based on your budget and goals. In B2B, I’ve see some folks have success with paid lead sites, for example. Niche sites like Appterra and getapp.com help you target audiences you think are particularly suited to your product, while Google Adwords, Facebook Ads, and LinkedIn Ads are all good general resources.

3. Optimize(ly)

User acquisition isn’t only about looking for new channels to reach potential users; it’s also about optimizing your presence on channels you’re already using. I’ve written before about optimizing performance in Apple’s App Store – though take it with a grain of salt now that it’s several years old – and also keep in mind that A/B testing should most definitely be applied to user acquisition; I love Optimizely, whose name says it all.

4. Make app stores your friend.

Basically, optimizing your app store presence for user acquisition amounts to making sure you are taking full advantage of your title and keywords. In addition to our own work on this at Speek, we use Sensor Tower, and it has been a godsend, allowing us to track performance and fine-tune our approach.

Once you are happy with where you are ranking (though you could always be happier!) make sure that those downloads are converting into actual user acquisition (purchase, registration, etc.). If not, the middle steps (e.g. a welcome screen, a tutorial…) might need some tweaking.

5. Organic SEO is the best.

Speaking of keywords, you are probably familiar with the idea of “Search Engine Optimization”, or SEO, but just in case: SEO is the simple idea that you want to be as attractive to search engines as possible, so that you will rank as high as possible when people search for a keyword related to your product. There are a lot of shady ways to do this which used to run rampant around the Internet, but now that Google has basically taken over the universe, in part by constantly refining their search algorithms, what you are going for is optimizing your organic search: if spammy SEO is the equivalent of cheating on a test, than organic SEO is actually studying, and maybe bringing your teacher that apple, you know, just in case.

Basically, Google likes it when legit sites link to your web page. For example, Speek wants as many outside sites as possible linking to www.speek.com. This tells Google that Speek is the most relevant search result anytime someone searches any variation of the term “conference call”. Tactically, we do this through PR and Press mentions, guest posting on third-party blogs, sites and publications (again, these must be legit articles: don’t be spammy, or Google will find you and hunt you down like the dog that you are) and getting people to link to the Speek blog. For a good example of somebody doing SEO the wrong way, check out this great article about RapGenius getting penalized recently by google.

I also recommend the ClickMinded SEO course (update for 2016 – Clickminded is still awesome!) if you’re looking for way more information than I can get into here.

6. Nothing beats word-of-mouth.

You should absolutely take advantage of tools from A/B testing to organic SEO, but at the end of the day, there will not be a single bigger boost to your user acquisition than positive word-of-mouth – even though struggling to measure this kills me. And the best way to get this is simply to have a superior product. No matter how many brilliant marketing strategies you embark on, if at the end of the day they are leading the way to a crappy product, all of your work was basically for naught: not only will users be trumpeting the glories of your company to their friends, but they will feel cheated (because, well, they kind of were) and they will instead tell people how much you suck, which is not what you are going for.

So besides not sucking, what else can you do? First think about whether there are any aspects of your product that lead naturally to word-of-mouth. For example, when a Speek user organizes a call, all the participants on the call are introduced to Speek. There is an implicit recommendation in choosing our service over another, and if the participants’ experiences are pleasant ones, they are much more likely to reach for Speek the next time they are the ones doing the calling.

We also try to maintain an active presence in the tech world, not only with guest posts and PR releases (as above) but in social media and participation in press conferences. Your co-founders also serve as de facto ambassadors of the company every time they head to an event, even when it results in a butt tattoo.

Correction: especially when it results in a butt tattoo.

This article originally ran on the Speek blog – I’ve made updates for 2016 where applicable, but it’s still a good set of lessons!

Watson Analytics at IBM World of Watson Conference

Posted on November 1, 20162 Comments

When I say IBM, you say … cutting edge machine learning? When they sponsored my trip to the 2016 World of Watson conference as a perk of my involvement in the IBM Predictioneers Social Influencer Program, I wasn’t totally sure what to expect, but I was pleasantly surprised with how advanced Watson and Watson Analytics have become, and the data accessibility that they’re focusing on across many different product lines. As it turns out, IBM is a contender for future analytics implementations that I will do. Here are my 4 key takeaways from the conference.

1) Watson Analytics is a powerful data discovery engine for folks without the technical chops to run multivariate regressions.

The most powerful feature for moderately technical to business side users is the ability to ask – literally in text – “what factors contribute to sales” and the combination of Watson’s natural language processing, and its Watson Analytics data engine will return a chart for you with the primary drivers of sales from all of the data sets that you have access to. Since IBM is still a large-enterprise focus, they have relatively sophisticated data governance capabilities, but for a less strict environment (like most of mine), you can likely surf through your entire corporate data set with relative ease.

There’s even a free trial and a relatively inexpensive option for a single user to experiment with. Not something that I expected from IBM, but frankly, I was excited to be able to work with a new tool like this. I’ll be interested to see how I might work it into my own workflows over the next year. There’s a ton of technical capability there, and Watson Analytics does a relatively good job automatically choosing visualizations for different data types, while allowing more knowledgeable users to customize as needed.

2) The Watson Data Platform and Data Science Experience is IBM’s play to “bring machine learning to the masses”. It might work.

The most noteworthy announcement from the conference for me was the introduction of the Watson Data Platform. This is an AI powered tool that can ingest data at 100gb/second and help you analyze it alone, or collaboratively. Need to feed insight back to your developers? You can do that. It’s theoretically only several clicks from ingesting data, running some machine learning algorithms, and sharing those results with your team. I haven’t worked with it yet, but needless to say, if IBM can deliver on that promise, there’s nothing else currently out there that can compete.

Check out the explorer video:

Or hop over to fellow Analytics Expert Jen Underwood’s first take on the Data Platform.

3) Semantic natural language data exploration is an incredibly powerful use of the language recognition that we all saw illuminated on Jeopardy.

Most people are familiar with IBM Watson from the amazing feat on Jeopardy several years ago. By beating Ken Jennings at the game he had mastered, Watson showed that language processing was becoming strong enough to rely on. The really incredible part was that Watson could recognize a play on words. While this feat, in particular, isn’t all that important for a business user, its implications are. Allowing the functionality that I mentioned in point 1, watson can help your business user get access to the right data whether it’s labeled sales, revenue, order_price or something else.

4) Generally, the cognitive computing era – IBM’s preferred phrase for what others would call Artificial Intelligence or machines that can teach and learn for themselves – is almost here.

It’s clear that IBM is trying hard to encourage folks to consider cognitive machines as a complement to human intelligence and work, but even with that effort, I’m not convinced. We saw several demos where the combination of new technology (IoT, drone cameras, etc) will simply replace humans where applicable: faster, cheaper, better. Need photos and damage assessment from a hailstorm? Queue up that drone, feed the images to Watson, be done in hours, not days or weeks when an inspector is available. Have Cancer? When Watson can ingest every medical paper ever published and can 99% match, and 30% improve upon the diagnoses of a trained cancer review board, why wouldn’t I just go straight to the computer? Need a tutor for the SAT? With Watson, a personal digital tutor is available to everyone, not just those who can afford $100/hour personal sessions. When we make a mistake driving, we learn from it. When a computer AI makes a mistake driving, every car running that software learns from it. After a few generations, why would I every trust a fallible human driver again?

While IBM is making a concerted effort to push Cognitive computing as human assistance, I sure see obvious human replacement opportunities. Be sure that as you develop your career, you don’t become stagnant. Lifelong learning will help you maintain opportunities to grow into areas that still need human creativity and critical thinking while offloading repetitive tasks, even complicated ones, to cognitive machines!

Analytics Career Office Hours

Posted on October 4, 2016Leave a comment

After my last career focused post, the folks at Springboard invited me to participate in an office hour session for their students. In the session, Lewis King (Founder at Telligent Data) and I helped these students understand what types of analytics jobs are available. You can view that video below:

Hit me up if you have any questions!

Analytics Jobs at Startups and How to Find Them

Posted on September 6, 2016Leave a comment

Since I started mentoring with Springboard, I’ve been reflecting on how the students might go about finding analytics jobs, and what exactly someone means when they say that they want to find a job with a startup. “Startup” means many things to many people. How big is too big to be considered a startup? There’s no clean cut definition, but I want to point out what different types of analytics jobs tend to be available at companies in different stages of their growth.

You can think about these stages in terms of funding levels, team size, or responsibility sets – they all move roughly in sync with each other. I will try to point out company attributes that I consider important. If you’re looking at starting your career in analytics, or at what your trajectory could look like, I hope the following thoughts are helpful. Make sure to note – I naturally gravitate towards tech because that is what I know and where I have the most passion. Similar thoughts may or may not hold as you move to other industries. Finally, if the company that you are working for has an analytics component as part of the core functionality (think Tableau – an analytics tool, Salesforce – a product where data provides core information to a manager, or Baremetrics – a product where data and visualizations ARE the product) then there could be a role for an analytics person at any stage.

With regard to the examples, be sure to keep in mind the time of publication of this article – I’m hopeful that the information here holds over time, but the specific companies will definitely move through different stages!

Super-Early: 1-5 employees, pre-seed or early seed (0-$750k)

This stage is all about proving traction – to yourself or potential investors. Analytics will help you measure it.

Where to look: angel.co – it’s free for startups and pretty focused on serving them effectively. It’s my go-to for early stages. Hacker News Jobs – YC’s hacker news jobs board is a terrific list, too, but it’s heavily trafficked. Standing out is hard, so be sure you’re a rock star.

Demand Generation/Growth Hacking/Marketing

The most impactful use for analytics at this stage only matters insofar as it generates additional growth. Help the team focus on a particular metric that matters to the business, but be prepared to adjust that metric quickly as you learn what’s important. You should be testing the effectiveness of marketing channels, either in terms of benefit for your time, or benefit for your money. When tracking product analytics, and the behavior of your users in the product, don’t get sucked in to looking at the number exclusively – understanding when you need to use qualitative feedback here is crucial. My advice? If it’s something that you’re interested in, reach out and see if you can do a free or cheap project for them. If you can prove that you can get them 10 (or 100) users, and why your data shows you that those could be loyal users, they’ll find room for you.

This role may or may not even be advertised – you sort of need to look around at local incubators and get involved in your local tech community and startup a conversation with folks working in areas that you are interested in. Be prepared to work on a “prove it” project.

Founder

Be prepared for all of the struggles of being a founder (working another job, or taking no salary, or whatever you need to do). Maybe you focus on analytics, but calling this an analytics role is generous.

Early Stage: 3-10 employees, small amount of funding ($500k-$2M), some traction

A company at this stage might be hiring for a real analytics person, but it’s more likely that you’re coming on as a marketer. Additionally, you’re likely on your own, to sink, swim, or fly. Try to find similarly placed folks at other companies at a similar stage (or a stage further) to help guide you. The expectations on you are likely to be intense, and you need to be ready to measure your own success along with that of the team. It’s an incredibly exciting time at a company, but is absolutely stressful. As long as you keep up with your growth goals, you can start understanding the product analytics as well, and ensuring a robust tracking implementation so that when you hit the next stage, you’re ready to rock and roll.

Where to look: Angelist – you can sort by size/stage, (and maybe Linkedin or TheMuse – some companies will be there but sorting through the noise is harder). Same deal with Hacker News Jobs as above.

Marketing Analytics (Growth Marketing / Growth Hacking, Paid Ad Specialist, Content Analytics) –

It’s possible/likely that a company at this stage is exploring how to best spend their personnel resources and financial resources in the quest for loyal paying users. If you are excited about focusing on data around marketing channels, content generation and measurement, ROI of paid advertising, and have a creative side to go along with your data chops, this might be fun for you.

Early-Mid: 10-30 employees (<$5m funding) – Decent traction

The analytics jobs at a company in this stage are likely similar, but you may not need to be all-things-data to all people. Hopefully if you’re leading those efforts, you can start building a team, and if you are trying to break into the industry, this is probably the first stage that there’s plausibly junior roles becoming available. If you want to have someone to learn from on the job, this is the smallest bracket that I’d start to look at. It’s also where an analytics driven product manager starts to become more of a must have than a nice-to-have. You likely have a larger number of customers – enough for A/B testing to start having a measurable impact on the product side.

Product Analytics (Data Analyst, Data Analytics)

At this stage you’re at least likely to be focused on product metrics, but still related to growth of the product. Depending on the makeup of the rest of the team, you might get some guidance from your executives on Lean Startup style metrics, but be prepared to learn as you go and be mostly self sufficient. It’s important here to focus on Dave McClure’s Pirate Metrics – What events, marketing sources, or user product choices lead to Acquisition, Activation, Retention, Referrals, and Revenue?

A company at Chariot‘s size is looking for a growth analyst.

In addition to the roles mentioned earlier, which are similar in focus, but more widely available at this stage, you can also start to look for:

Product management

If you have a mild design background, and enjoy being the voice of the user on your team, you might consider product manager. This takes a really good grasp of many aspects of the business, but the core of a product manager’s role is making the product successful, and a strong analytical background helps immensely. If you can use data effectively to inform what features to build, and equally importantly what not to build, you can have success. Towards the later stages here, there may be junior roles in this field available, but as we’ve seen before, at the earliest stages, a startup will likely expect you to come in and hit the ground running in your given role, so you likely need some experience.

Middle Stage: 30-100 ($5-30m funding) – significant traction and user base

If I was trying to start my career and break into the startup world, I would look hard at the opportunities in this stage. If you find a company that’s growing quickly, your role can grow quickly, too. You’ll have more senior folks there to learn from, and you’ll understand how analytics can really drive a company forward: you’ll have large enough data sets for your analyses to make noticeable differences. Finally, this is the stage where your ability to buy top shelf analytics tools starts to appear. As a startup techie, you probably keep abreast of the latest greatest software, but in order for your organization to afford it, you’ll have to have proved your value as an analyst and the value of that tool. The more data you have, the more value the tools bring, the more likely that you can see positive ROI.

These teams are also where you start needing multiple people in roles, so you don’t need to be the World’s Best Analyst on day 1. You “only” need to be very good, or be able to prove to them why you will be.

Check out my friends at VideoBlocks hiring for an entry or midlevel Analytics Specialist:

AnyPerk is another great, growing startup looking for a senior analyst.

Late Stage: 100-300 employees ($30M+ raised)

Late stage companies have enough folks on the team to start to really specialize. The marketing analytics folks may start to branch from the product analytics, and you’ll start to see an analytics group form. Additionally, it’s where you start to drift away from really being a “startup” to me. In the context of companies over all time, sure, these are potentially still young, but the atmosphere really starts to be more like a “real company” and less like the early days of a startup. That has benefits – higher salaries, lower risk of the business folding at any given time, and better resources for doing what you need to do. But it also has drawbacks – this seems to be about the stage where not everyone can have a real relationship with the executive staff, and it’s also typical at this stage to have much lower equity offers due to the market salary and lower risk profile.

If you’re looking for your first job, try checking out Springboard to build your skills before you apply. I’m a mentor for them and think that they give you a good baseline set of skills.

Segment (coincidentally, one of my favorite tools of all!) shows some of the specialization happening:

Not all jobs are in San Francisco! Check out this job listed on The Muse by When I Work for a Business Analyst and Data Hacker.

Not-really-a-startup (but could still be awesome): 500+ employees, Tons of Funding (or Profit)

People tend to over-generalize tech companies as startups. Once you have a series C, hundreds of employees and national name recognition, you’re not really a startup. That said, there are still cool opportunities at this type of organization in analytics. Plus because of their size, there are more opportunities to find a specific niche that you’re interested in.

Another example here is Uber. They’re hiring analytics folks across literally dozens of roles:

Operations Analyst, Marketing/Growth Analytics, Operations/logistics manager, strategy analyst, etc. Plus, everyone has heard of them, so there’s somewhat more street cred in working at a place like that. If you go to a big national tech company like them, you can learn what it’s like at a high-growth organization and how to work with a high performing team. Want to work overseas? They have that option, too! Just don’t be confuse your peers at a company of 30 by assuming that working at uber has anything like the same startup environment as they do.

I hope that this has given you a good background in where to look and what to look for to break into analytics in the startup world. Whether that’s early in your career, or later, there are amazing opportunities for folks with analytics skills at companies in all shapes and sizes. Congratulations on working your way into an awesome field, and don’t hesitate to comment here or hit me on twitter (@smlevin11) if you think I can help you narrow down what you’re looking for.

Lean Analytics: The one metric that matters

Posted on May 18, 2016Leave a comment

In a data-driven organization, setting metrics and Key Performance Indicators (KPIs) help drive your business forward. While knowing various metrics about your business can help you in different ways, I’m a big proponent of the Lean Analytics concept of One Metric That Matters (OMTM). A savvy entrepreneur (and hopefully, the entire team) will know at any given moment what the most important metric to them happens to be at that moment. With this type of singular focus, you can drive meaningful change to your business without suffering from data paralysis.

An organization’s OMTM can and should change depending on the stage of the company, the short-mid term goals that you’re trying to achieve, and the type of business that you’re in. During my time at Speek, we changed our core metric a couple of times when our goals or strategy changed, and at Sestra, we know exactly what our focus is for the short term. Today I’m going to walk through how we landed on each of these metrics and how they impacted the business.

Speek’s Early Days: Registered Users

First, let’s talk about the early days. I wasn’t with Speek at the very beginning, but looking back at the data from that time period, and talking with the people who were there, it’s pretty clear that the goal was very much top-of-the-funnel. We were positioned as a B2C product with a friendly brand and we were looking for registered users. The team focused heavily on marketing and optimizing the signup process in order to encourage users to try us out. The biggest giveaway here is that we were measuring campaign effectiveness in terms of cost-per-registration.

Classically, you want to look at some number further along the line, but let’s be realistic here. How are you supposed to test any theory or figure out what’s working and what’s not when you don’t have any users? How can you measure a loyal user acquisition if you’ve only been around 6 months and half of your users are from the last 6 weeks. You have to make SOME assumption about certain types of users being better or worse than others, and basing your earliest days on “all users look alike – so let’s acquire registrations as cheaply as possible” is not the worst way to go. It’s crucial though not to mistake a shortcut in the early days for what you should be doing in an ongoing manner.

Registered Users:
–Easy to Measure
–Cheap to Acquire
–What else are you going to use when you don’t know what’s important
–Not ideal, but not terrible

Phase 2: Active organizers

As the company grew and users churned off or stuck around, we started to have more actionable data around user loyalty and usage. This was around the time that I started, and one of my first projects was a deep dive on our marketing spend from a loyal-user acquisition stand point. The biggest takeaway was that one of the best acquisition sources based on a cost per registered user metric had one of the highest churn rate of any source. This helped us realize that it was time to move to a more robust OMTM, but we certainly wish that we had migrated sooner.

After some more data digging around our best users, we shifted our focus to the concept of an Active Organizer. This type of user is someone who has hosted at least one call with at least one other person. That gives us the opportunity for a viral interaction, and shows someone who is actually using the product. Sure, it still has some drawbacks like not distinguishing tire kickers, but it’s a much better indicator of growth: these people are showing speek to someone else and are many, many times more likely to pay.

Active Organizers / Active Users
–Much more meaningful indicator
–Create Viral Growth
–Still thinking of B2C, but encouraged the transition to B2B

In a textbook case of “you get what you measure for” our new registrations dropped 30-40% mostly losing paid acquisitions who didn’t convert anyway, and bumped our activation rate by almost 100%.

Again, we made product and marketing decisions based on this metric. For example a scheduling widget enabling people to invite another person or spending marketing dollars on another salesperson since the salespeople inherently pull someone onto a call with 2 people.

Best Fit: B2b Sales Demos

This leads me to phase 3, where we really saw success. Our number 1 leading indicator of revenue was number of sales demos set. The product/marketing/word of mouth generate inbound leads, and we made substantial improvements geared towards generating even more inbound leads in our subsequent releases. We even shifted our onboarding from a freemium model to a free trial model, to help turn all of those free registrations that we get into true sales leads.

Additionally, we worked the predictable revenue model of setting outbound sales demos. These inbound and outbound sales demos are just two sides of the same coin working to increase the number of demos that we set. And so when you asked me up through the time of Speek’s Acquisition, “what is your One Metric?”, my answer was sales demos.

Sales Demos
–Best indicator of future revenue
–Drove switch to a free-trial model and away from freemium

Make sure your One Metric Keeps up

Each adjustment to the One Metric was driven by the needs of the company at the time. When you’re deciding on your one metric, be sure to keep in mind your company stage, needs, and business model. Those can all change and your OMTM may change along with it!

What’s the One Metric That Matters for your business?

Quick Hits: The Hard Thing About Hard Things – War and Peace in Business

Posted on April 26, 20162 Comments

The Hard Thing About Hard Things: Building a Business When There Are No Easy Answers

There are a bunch of business books that I want to read – and this one’s been on my list for a while, but they’re relatively expensive. But, I rediscovered the library! So I can read it for free. While I’d certainly rather own it, and frankly, I’d rather read it as an ebook than a hardback, it’s worth the tradeoff.

Premise: “the most important lesson in entrepreneurship: Embrace the struggle.”

In the first chapter or two, the most interesting thing so far is to realize that this renowned tech VC/entrepreneur certainly has a somewhat old school attitude towards his businesses. The mindset of his writing and lessons reminds me a lot more of “traditional” leadership than it does of the new wave of tech founders. I’ve been reading things like Rework and Reinventing Organizations lately, which skew young and techy and controversial, to some degree. But THTAHT is definitely more of a smack in the face to some of the new-gen principles. Below are some key quotes that help portray Horowitz’s views.

1) “Figuring out the right product is the innovator’s job, not the customer’s job.” This actually sounds like Steve Jobs – but it goes against a lot of Lean Startup type principles where customer desire and feedback drive your product development. This approach of design a product that you know the world needs before it does it also a key tenet of Peter Thiel’s Zero to One. The takeaway for me here is to remember that customer validation has limits, as does everything, and not to take it as gospel, even though I lean towards Lean methods more than complete unending of a market.

Key Takeaways: Lean doesn’t always win and Life of CEO at VC backed startup is rough

2) “Go home and tell your spouse that Ben needs you for the next 6 months”. Horowitz talks about the Darwin Project at one of his companies (Opsware) with the entire team working in the office for 12 hour days for 6 months. I completely get the idea of everyone working ridiculously hard for a block of time in order to keep the company alive and build something great, but again this goes against a lot of the value system that I want in a leader/company.

It’s also interesting to me to think about how a situation like this could work on a distributed team. It doesn’t necessarily feel like it’s possible, and really, their company probably would have gone out of business without it. I suppose I have to recognize that there are other forms of operation than the ones that I would prefer, and that in some cases, those more aggressive styles can achieve great things. That said, I’m still up in the air about whether I think it’s worth it. Obviously the andreessen horowitz team helped push people to the open internet, and that’s a terrific thing, but for this opsware product – yes they sold to HP, but was it worth the crazy lengths that they had to go to? This probably isn’t a good attitude for a VC-backed tech founder, but at this particular moment in my life, I’m not convinced VC-backed is the lifestyle that I want. I do want to build a great company, but it’s important to me to build one that’s sustainable and does right by employees and families. Even so, I’m glad that I’m finally reading this book because so far, so much of my reading has really only reinforced the particular way that I would prefer to operate, and Horowitz just gives a very different view on what success can look like.

3) “Peacetime CEO vs Wartime CEO”. Horowitz acknowledges that the roles and responsibilities of a CEO change dramatically based on how the company is doing. He even admits that different leaders will thrive under different conditions, and that being good in one of these roles doesn’t make you necessarily good at the other. When the company is growing, and generally healthy, a CEO’s role shifts towards recruiting, morale, and motivation. During wartime, the role focuses on daily survival and how to keep the company alive. In certain cases that can lead to extremely counter-intuitive decisions (like him selling off his core business at one company). At any company and for any leader, it’s important to understand which type of environment you’re operating in.

Do you prefer Ben’s cutthroat approach to management? You can’t argue with its effectiveness. I just hope that there’s a better way.