In the world of analytics, there's no shortage of smart, innovative people to learn from.
Joining in with the analytics community allows you to explore new ideas, rediscover foundational beliefs, and be inspired by the thinking of the people around you.
It comes as no surprise, then, that there are some great analytics quotes out there, from VCs and founders, from growth gurus to product people, all thinking about pushing to make analytics even better.
Whether you're looking for advice from some of the best in the business or you want to find some wisdom to fire up your team, we've compiled 48 analytics quotes to inspire you.
Growth — everyone wants it and almost nobody seems to be quite sure how to get it. Startups, small wins, and best practices for data and metrics are just some of the things that the growth wizards below have mastered. And, unlike those half-baked growth bloggers and fast talkers you end up next to at conferences, they actually know what they're talking about.
“Different verticals need different terminal retention rates for them to have successful businesses. If you’re on e-commerce and you’re retaining on a monthly active basis, like 20 to 30% of your users, you’re going to do very well. If you’re on social media, and the first batch of people signing up to your product are not like, 80% retained, you’re not going to have a massive social media site. [...] What you need to do is have the tools to think, ‘who out there is comparable’ and how you can look at it and say, ‘am I anywhere close to what real success looks like in this vertical?’”
“Tracking marketing is a cultural thing. Either tracking matters or it doesn’t. You’re in one camp or the other. Either you’re analytical and data-driven, or you go by what you think works. People who go by gut are wrong.”
“Time and money are your scarcest resources. You want to make sure you’re allocating them in the highest-impact areas. Data reveals impact, and with data, you can bring more science to your decisions.”
“Have a vision for what you are trying to do. Use data to validate and help you navigate that vision, and map it down into small enough pieces where you can begin to execute in a data-informed way. Don’t let shallow analysis of data that happens to be cheap/easy/fast to collect nudge you off-course in your entrepreneurial pursuits.”
“Execution is so critical. Sometimes you just need to try something, see what works and move forward.”
“When we initially started testing email subject lines, we defined the success criteria as driving an email open. This seemed to be the most straightforward since the Pinner reads the email subject line and the next action is to either open it or don’t. What we found, however, was that defining success with metrics that were further downstream (i.e. clicking on the content in the email) was more effective.”
“If there’s one takeaway it’s that it’s okay to do small wins. Small wins are good, they will compound. If you’re doing it right the end result will be massive.”
“The most important thing we've done to improve our user onboarding was to define our activation metric and get serious about tracking the inputs to that metric. Agreeing on what a successfully "activated" account looked like, and understanding all the individual actions to get there, allowed us to take our new user onboarding to the next level. We formed a cross-functional team dedicated to increasing that metric. The team is able to clearly prioritize ideas and projects since we all agree what success looks like. That activation metric is paying huge dividends to our users and our company.”
“There’s more objectivity in one customer sharing their passion and love for a product with another than there is in ads or promotion. It allows the company to spend less to achieve lasting growth.”
The people that understand how analytics shape a business best are the people that live and breathe building businesses: CEOs and founders. They've seen it all, they've built it with data, and we've got their best analytics quotes, right here.
If you're looking for insight as to how you can better structure data within your business, or you're trying to dig into the hearts and minds of your customers, there's surely a nugget of wisdom out there for you.
“You can’t run a business today without data. But you also can’t let the numbers drive the car. No matter how big your company is or how far along you are, there’s an art to company-building that won’t fit in any spreadsheet.”
“As you gain fresh insight from your data, it opens the door to new questions. As you have new questions, you need to update your instrumentation and analysis. Saying the process is “done” is saying you understand everything there is to know about your users, product, and channels.”
“Analytics software is uniquely leveraged. Most software can optimize existing processes, but analytics (done right) should generate insights that bring to life whole new initiatives. It should change what you do, not just how you do it.”
“If you pick the right metrics for success, you will be able to significantly improve the focus of the whole team and thus improve your business. Developing these metrics should be done first by making hypotheses about your business and validating / invalidating these hypotheses. From there you will have a good base understanding that will allow you to determine what metrics to focus on and how to define success for your business.”
“The goal is to turn data into information, and information into insight.”
“You want everyone to be able to look at the data and make sense out of it. It should be a value everyone has at your company, especially people interfacing directly with customers. There shouldn’t be any silos where engineers translate the data before handing it over to sales or customer service. That wastes precious time.”
“We’ve tried to put passion and art and love and creativity ahead of revenue and valuation and buzz and traction, discovering that the latter can often follow the former.”
“Of course hard numbers tell an important story; user stats and sales numbers will always be key metrics. But every day, your users are sharing a huge amount of qualitative data, too — and a lot of companies either don't know how or forget to act on it.”
“We live in a time where data is all around us, and there’s a lot of great advice to show us how to make better use of data. However, I’ve found that in some cases this can be a huge waste of time, especially early on with your startup. Replace some of your current focus on quantitative data to qualitative data).”
“The single most important thing we've done for onboarding is planning past the first session. Let's say you have a SaaS application and know that new users who take actions X, Y, and Z end up being really successful.
It's tempting to build a linear new user flow that encourages them to take these 3 actions then call it a day. But that's just not how humans evaluate software - most of them will hardly complete one of the three actions in their first session. [...]
Planning past the first session matches your funnel to your buyer's decision making process. It means aligning your in-product experiences, email campaigns and sales/customer success outreach to reinforce the user's success path.”
“The problem with Silicon Valley is when you build an app you are expected to make the app go viral and reach millions of people. This is the worst way to think about it — it’s much better to get 100 people to love you. There was no way we could get 1M people on Airbnb, but we could get 100 people to love us. This is when we decided to do things that wouldn’t scale. Getting 100 people to love you is hard — getting people to like you is much easier than getting people to love you.”
“I learned a lesson from watching other companies who held onto things too long. If you look at the history of companies that have succeeded and the ones that have failed, there’s a pretty clear pattern that the ones that have succeeded typically morph every couple of years into something new. And that change is fairly uncomfortable.”
“[For early-stage startups,] data is never there when you need it most. At best, data can help you make very small, incremental decisions. But if you’re a startup, you’re focused on big, broad swings — and data has no place in that. You don’t have enough users to draw any meaningful conclusions, and even if you did those users aren’t necessarily representative of your long term target audience. You’ve got data, sure. But not enough to make a genuine, data-driven decision, and pretending otherwise is a recipe for disaster.”
“Use analytics to make decisions. I always thought you needed a clear answer before you made a decision and the thing that he taught me was [that] you’ve got to use analytics directionally…and never worry whether they are 100% sure. Just try to get them to point you in the right direction.”
“Your metrics influence each other. You need to monitor how. Don’t just measure which clicks generate orders. Back it up and break it down. Follow users from their very first point of contact with you to their behavior on your site and the actual transaction. You have to make the linkage all the way through.”
Venture capitalists have a unique perspective on business and analytics, because they evaluate from an outside perspective. Often becoming a VC after years of experience in business, investing, banking, or founding, a VC's future professional success depends on their ability to determine what will sink and what will swim.
Churn, metrics, growth, and conversions are just some of the things that we've got “on the record” from VCs.
“Merely measuring something has an uncanny tendency to improve it. If you want to make your user numbers go up, put a big piece of paper on your wall and everyday plot the number of users. You'll be delighted when it goes up and disappointed when it goes down. Pretty soon you'll start noticing what makes the number go up, and you'll start to do more of that. Corollary: be careful what you measure.”
“Your users are your guidepost. And the way you stay on the right path in the early stages of a startup is to build stuff and talk to users. And nothing else.”
“For predictive analytics, we need an infrastructure that’s much more responsive to human-scale interactivity: What’s happening today that may influence what happens tomorrow? A lot of iteration needs to occur on a continual basis for the system to get smart, for the machine to “learn” — explore the data, visualize it, build a model, ask a question, an answer comes back, bring in other data, and repeat the process. The more real-time and granular we can get, the more responsive, and more competitive, we can be.”
“You must constantly try to disrupt yourself. The most successful companies embrace cannibalization at the core. [...]You need to innovate and be willing to threaten the core of your business in order to survive. Or you'll die!”
“I often see teams that maniacally focus on their metrics around customer acquisition and retention. This usually works well for customer acquisition, but not so well for retention. Why? For many products, metrics often describe the customer acquisition goal in enough detail to provide sufficient management guidance. In contrast, the metrics for customer retention do not provide enough color to be a complete management tool. As a result, many young companies overemphasize retention metrics and do not spend enough time going deep enough on the actual user experience. This generally results in a frantic numbers chase that does not end in a great product.”
“Don’t obsess over these sub metrics, but obsess over the key metrics that tie into your revenue growth. Everything can be measured, including engineering, PR, product and marketing. If you have your engineering team agree to measure the output of features quarter over quarter, you will get more features built. It’s just a fact. You have to measure every functional area. Measure them all and have everyone agree to the same growth goals to support your revenue, and magical things will happen.”
“If an Internet company could obsess about only one metric, it should be conversion. No other metric so holistically captures as many critical aspects of a web site – user design, usability, performance, convenience, ad effectiveness, net promoter score, customer satisfaction – all in a single measurement. Yet despite the remarkable power of this metric, it is alarming how few companies today truly understand conversion and how to optimize it. As such, it is time to pound the table again – conversion is by far the most powerful Internet metric of all.”
Thought leaders, especially in the tech world, are focused on the possibilities in front of us and push everyone to get smarter, faster, and stronger. From world-class writers and researchers to data scientists that pioneer our methodological approaches, the analytics quotes from this group pretty much covers all the bases.
“You don’t need to learn what customers say they want; you need to learn how customers behave and what they need. In other words, focus on their problem, not their suggested solution.”
“Data isn’t useful without the product context. Conversely, having only product context is not very useful without objective metrics...”
“Errors using inadequate data are much less than those using no data at all.”
“When you are dealing with a torrent of data, being able to construct different levels of aggregation is really important, because you want to make sure you’ve used your software intelligently with respect to that large amount of data, and bring to bear the contextual data you need to answer the question at the level of aggregation that you need to answer it.”
“If statistics are boring, you've got the wrong numbers”
“Data are just summaries of thousands of stories – tell a few of those stories to help make the data meaningful.”
“[A data-first strategy] is the quest to implement systems (usually massive) to collect data of all shapes and manners before all else. [...]It is being hyper-conservative when it comes to creativity and experimentation because of quant-issues. It is represented by 90% of the data budget invested in Agencies and Consultants driving implementation and re-implementation and hyper-customization of the code. It is represented by the act of creating crazy data thresholds for any initiative to get off the ground. [...] Data is important. I believe it can help drive your business strategy smartly. But, a data-first strategy, defined as above, is nuts. It will only slow down your progress and allow your competitors to crush you like a bug (even if you are a top player in your market today!).”“You can have data without information, but you cannot have information without data.”
“A screen full of analytics data looks like a secret code, and in a way it is. That data has a lot of information in it, and it’s impossible to make sense of it without the key. Put another way, data can give answers, but only if you ask the right questions."
“The key is to let computers do what they are good at, which is trawling these massive data sets for something that is mathematically odd, and that makes it easier for humans to do what they are good at — explain those anomalies.”
“Data is a precious thing and will last longer than the systems themselves.”
"One metric alone doesn’t tell you what’s happening with your site; as ever Analytics is about taking your data and outside influences (i.e. time of year) and building insights from all of it.”
“In a marketing analytics worldview, companies must have an accounting of and insight into all of their marketing programs in all of their channels, including web/browser, mobile apps, TV/video, social, paid media, field, print, outdoor and others. If your organization is still stuck in the web analytics mindset, it is time to reinvent your analytics practice, leveraging all of the available marketing analytics tools to make faster and better decisions and drive your business.”
“For every $20 you spend on web analytics tools, you should spend $80 on the brains to make sense of the data.”
Product is at the heart of analytics, but it can also be the source of great frustration. How do we understand our product with numbers, experiences, aggregate data? Nobody can answer this question perfectly, but these experts can give you a huge running start.
“As a publicly-traded company you have to do a lot of long-term planning with respect to revenue. You have to become more predictable for investors. And revenue is tied to products that have to ship to meet projections.”
“Data and A/B test are valuable allies, and they help us understand and grow and optimize, but they’re not a replacement for clear-headed, strong decision-making. Don’t become dependent on their allure. Sometimes, a little instinct goes a long way.”
"About 10 years ago, a video went viral on YouTube showing a toddler holding a paper magazine and trying to use it like an iPad, swiping and pinching to zoom, and it didn’t work so she just looked at it thinking, ‘It must be broken.' It was obvious evidence of a new generation of digital natives. Today we’re witnessing a new revolution of data natives who expect their world to be ‘smart’ and seamlessly adapt to what they want.
A data native is someone who expects their world to not just be digital, but to be smart and to adjust immediately to their taste and habits. For example, a magazine should not only be digital and interactive — it should be personalized. It should tell you what you need to know based on your interests, location, preferences. The expectations have shifted.
[...] Without big data analytics, companies are blind and deaf, wandering out onto the Web like deer on a freeway.”
“The only thing that matters is getting to product/market fit. Product/market fit means being in a good market with a product that can satisfy that market. You can always feel when product/market fit isn’t happening. The customers aren’t quite getting value out of the product, word of mouth isn’t spreading, usage isn’t growing that fast, press reviews are kind of “blah”, the sales cycle takes too long, and lots of deals never close. And you can always feel product/market fit when it’s happening. The customers are buying the product just as fast as you can make it— or usage is growing just as fast as you can add more servers.”
“A big theme that I keep coming back to is, where is the love? It’s basically just finding out which users are passionate about the product. What is the use case on the product that those people have? Why do they actually love the product? And that gives you a good core of information to guide every part of your business. So messaging, you want to reflect that, but also, now that you know that, you want to make sure that you can really get a lot more people to that particular type of use case and that particular type of gratifying experience. So understanding user gratification is really critical in all of it.”
“In my time as a product manager, I was constantly reminding myself to talk to customers more. It might have been to talk about existing features, something under development, or customer pain and processes for product research. It was easy in the beginning, because we knew most of the people using the tool as we worked on the initial version. Even as we got bigger, my feelings usually boiled down to these four words: talk to customers more. I think a critical skill, however, is learning how to talk to the right customers.”
If there's anything that we can take as an overall message from our experts' analytics quotes, it's never stop learning, exploring, creating, and diving headfirst into improving your product and your company. There's always a new angle to try and — luckily — there's usually someone out there who has a bit of knowledge that can help you bring your novel ideas to life.
Want to learn more about how Scuba can equip your team -- both technical and not -- with the tools for data analysis? Contact us today!