Analytics brings science into business and transforms decisions from a subjective "gut-feeling" to an objective read of the market. Data-driven businesses always outperform their competition regardless of the employees' talents.
Being an entrepreneur is the ultimate adventure, careerwise. It’s an intimidating journey with many challenges that no matter how much experience you have, can still catch you off guard. The trick is to understand and prepare for every possible outcome. Fortunately, you can achieve this with startup analytics.
With the help of analytics, you can make sense of the risky and unpredictable, which will allow you to make smart decisions for your business. In this sense, we can say that analytics have a grounding effect and power the decision-making process for growth strategy and tactics.
However, knowing the importance of analytics is not the same as knowing how to use them to your advantage. In fact, many founders who are new to entrepreneurship are confused regarding the usage of analytics, and others might need help keeping up with new trends and tools that will put them ahead of the competition.
So, let’s try to demystify the world of analytics. In this article, we’ll cover the basics, give practical examples of using analytics in different stages of your growth, and finally, talk about ways to contextualize analytics and use them for different purposes.
Analytics brings science into business and transforms decisions from a subjective “gut-feeling” to an objective read of the market. Why is the latter better? Some people might believe that senior professionals with years of practical experience in the field know what works. And, while they would certainly make better decisions than newbies, data-driven businesses always outperform their competition regardless of the employees’ talents. According to recent research findings, data-driven organizations are 23 times more likely to acquire customers, 6 times more likely to retain customers, and 19 times more likely to be profitable. Moreover, 62% of businesses, such as IBM, believe that data analytics gives them a competitive advantage.
The math is clear! Employees are inherently biased and customers form a dynamic system that constantly changes, which means that you need analytics to create a bridge of trust and productive communication between your brand and your audience. Plus, time and money are scarce resources that you can’t allow to waste on low-impact areas.
With the right metrics, you can set goals and measure the progress you’re making toward them. At any time, you’ll know that you’re in the process of improving, and if not, you’ll be prepared to make a well-informed change that will get you back on the right track. This is possible because you’ll identify trends and patterns, opportunities, risks, problem areas, and successes.
Additionally, it’s hard to attract investors if you have nothing to show off. Monthly reports that clearly show your progress and data-powered forecasts regarding your business potential will convince others that investing in your business is a lucrative opportunity.
Last but not least, metrics are an important motivational factor for the employees. When your team knows exactly how their work impacts the progress of the company, they feel important, valued, and motivated to keep doing their best work.
The arguments above paint a fairly good picture of the importance of analytics in general, but they don’t tell us much about which analytics are the most important for startups, for larger companies, or for specific industries. In this sense, you might still feel like you’re in the dark regarding how you can use analytics in your business, so let’s change that.
The first thing you need to understand is that there’s no universal answer that works well for everyone. A complex interplay of a lot of factors determines the usefulness of analytical data for certain businesses at a given stage of their development.
Today, most experts would agree that the stage of your product is a predominant factor that reliably predicts which metrics are most useful and necessary for the time being. For example, in the beginning, you should focus on engagement metrics and qualitative feedback because these two insights will reveal how the audience is responding to your product, whether you need to improve something, and if there are other customer needs that you can satisfy by adjusting your product.
In the next stage, once you’ve established a good relationship with your target audience, it is time to attract new customers and scale up, which means growth metrics come into focus. However, growth metrics is a very vague term and encompasses a lot of different things such as signup percentages, invite rates, etc. Depending on the type of business and your short-term and long-term goals, growth metrics will differ significantly from company to company.
Figuring out which growth metrics work best for your business is something you must do on your own, but we will help you by going through some of the metrics that are important for businesses in different stages of development and size.
Sometimes, founders are focused so much on what to measure, that they come to believe a top-down approach will yield the best results. What we mean by this is reading a bunch of articles that discuss the best metrics they can follow, and based on that, they come up with an analytics strategy. While this is not always bad, it’s better to place your business in the center of attention and look at your business goals to ask yourself: how can I translate my goals into measurable data? What is the best indicator that I have made progress toward achieving this particular goal? Then, you should go online and try to figure out what is the best way to measure success in that particular goal.
Although this bottom-up approach is more fruitful, it’s also more challenging as it requires your company to produce actionable data, which, in turn, requires clearly defined priorities for every step of the way. It’s hard to know what works for you now, if you haven’t tracked anything since the beginning.
So, let’s start from the very beginning and see how your analytics strategy should develop over time.
The first stage starts with day one - you and your idea - and it usually lasts until you have at least 10 employees. This isn’t much, but it’s a fundamental period that shapes the product development process. For this reason, you should put all your analytical efforts into your product.
This is also the moment when you need to install Google Analytics, especially if you’re an eCommerce business. Also, if you develop a software, make sure to have real event tracking.
Needless to say, you should begin tracking your financial costs and benefits from day one, too. As an eCommerce business, make sure to track the GMV (Gross Merchandise Volume). For other services or offers, you can use free or low-cost tools that will track any income, such as daily subscription metrics. This is an essential insight that will help you make smarter decisions once you reach the later developmental stages.
Finally, don’t think too much and don’t spend money on many different specialized tools that you might not even need. First, reach your initial milestones, then invest in more advanced analytical solutions. In fact, Google Analytics will be more than enough for a long time.
Reaching the early stage means your business and your team are both growing. During the early stage, you might scale up to 50 employees. This is a big number that most startups never mature beyond. Depending on your goals and your product, the early stage can last for a long time. To make sure you don’t get stuck there forever, you’ll need more advanced analytics.
In this stage, your marketing team should track the UTM (Urchin Tracking Module) for all digital campaigns. This is basically a code that you attach to any URL so that it can generate Google Analytics data such as tracking the progress of your campaign across different platforms.
Customer Relationship Management (CRM) software is also very useful for understanding your customers better and tracking the performance of your sales reps. Beyond this, you should track customer loyalty and satisfaction. One of the most common ways to do this is through surveys that ask customers how likely they are to recommend your product to other people. This and similar questions make up the so-called Net Promoter Score (NPS).
As you grow and your revenue increases, you can hire an experienced analytics professional and set up a more serious data infrastructure. To do this, you might look up data warehouses, ETL, and BI tools. Your analytics professional should know these things and help you make smarter strategic decisions. They should have experience within the industry and take specific actions that will give your company a competitive advantage. When there are bigger challenges ahead, and you can afford it, hire a consultant to advise you on particular issues regarding analytics.
Reaching the milestone of 50 to 150 employees is a major accomplishment, but unfortunately, it doesn’t mean you have proven your worth on the market. In fact, this is the period when you’ll reach an even bigger market, with even higher demands, and where long-standing competitors can quickly crush you if you make mistakes.
How can analytics help you during this period?
This is the crucial moment when you go past the engagement analytics and focus all your efforts on growth. If you can afford to expand your team, you might want to hire growth hackers to bring more insights into your marketing team.
However, more importantly, this is also a moment when you should hire a data scientist, so you can engage in more serious analytical processes, such as SQL-based data modeling.
The quality of your analytics team will be a defining factor for your future growth or stagnation. Therefore, establishing an effective team that works well together and exceeds your desired results is of the essence.
Finally, improve your forecasts by choosing powerful forecasting models that reliably prove their effectiveness.
The growth stage is where you enter a more stable period. This is because getting to the growth stage means you’ve found a good team and have powerful analytical insights to back you up. So, what do you do from here on? Again, you focus on growth, but this time by analyzing your future needs and coming up with answers on how to satisfy them.
You can grow your analytical team, but not at the expense of your current performance. This means that adding new members to the team should be carefully managed, so it doesn’t interfere but it rather complements the work your analysts have been doing so far. Also, think about how your analytics team is structured and how you can improve that structure to make them even more productive.
Of course, you shouldn’t forget to test your data and follow up everything with documentation. As your company grows, it will be harder to keep track of everything, so to make sure everyone sticks to their responsibilities, ask them to document their activities and results.
Before we end this section, let us just say that while this is a good generalization of how your analytics should progress over time, it’s not a guide that you should blindly follow. Think of it as one example or one possible path you can take, but not the only one. This is because, at the end of the day, there is no universal recipe for success or 4 metrics that would work for absolutely everyone! That’s not realistic. You need to start from the very basics, such as Google Analytics, and figure out what works best for your startup and your goals over time.
We’ve mentioned a couple of times that Google Analytics is probably the first contact with analytics every founder will have at the start of their entrepreneurial journey. And, until they reach a stage where they can hire analytics experts, they’ll probably stay mainly on Google Analytics and perhaps combine it with some additional built-in tools. Therefore, it’s only logical for us to examine Google Analytics in more detail and discuss what’s most important in using it.
Google Analytics is a web analytics service, developed by, you guessed it, Google. They launched the service back in 2005 and took the world by storm. Today, it’s almost unimaginable for a business to succeed online without tracking its progress through Google Analytics.
Google Analytics provides all the fundamental statistics and analytical tools for SEO and other marketing purposes. It monitors website performance and collects customer insights by tracking their online behavior. Beyond that, Google Analytics (GA) tracks:
GA also includes powerful data visualization and monitoring tools, data filtering, funnel analysis, and predictive analytics. This, coupled with its ability to integrate with most popular tools for more specialized analyses, gives GA an unparalleled competitive advantage over other analytics tools available on the market.
The good thing about GA is that it’s so popular that learning resources are in abundance - even free ones! Anyone who wants to learn how to use GA can start by investing some time and effort. Having said that, if you’re a complete beginner, you should know that the most basic and essential metrics in GA include:
Keep in mind that GA continuously evolves and includes new, improved ways of tracking your online presence and key performance indicators (KPIs). Therefore, we recommend that you check out what’s new before diving into the analytics numbers.
Until now, we’ve talked mainly about the importance of analytics and how different metrics can give us insights that set founders on the path to success. However, it’s equally important to contextualize the numbers generated by analytical tools, so that we don’t lose the big picture chasing numbers.
What does this mean?
It means that there needs to be a balance. Data from analytical tools is incredibly important, but it shouldn’t go against common sense. Let’s explain this with an example. Let’s say that your ad is working and you’re receiving a lot of traffic to your website, and even your revenue is up. This is great, but it only tells half of the story. Another insight is a qualitative evaluation of the ad that, unfortunately, can’t be measured with numbers. For instance, ask yourself whether the ad is memorable. Does it provoke positive emotions in customers? Is it relatable? Do customers think about your product when they’re not seeing the ad? If the ad doesn’t bring something more, then the moment you stop running it, people will forget about your brand, which is not sustainable.
A similar issue, which is a lot more common, comes from the unwillingness to make changes when things are working. For example, you might see good numbers and conclude that you don’t need to improve or change your website or product. However, not keeping up with trends and staying behind in your comfort zone will sooner or later affect the revenue.
So, to sum up, use analytics carefully and within the context of other qualitative indicators that you can’t track as easily. Think about their purpose and how they help you improve, rather than whether you need to stop moving.
What will help you contextualize analytics even further and look at them more meaningfully is knowing their purpose. Different analytics can be divided based on the purpose they serve in four basic categories: descriptive, diagnostic, predictive, and prescriptive analytics.
Descriptive analytics answer the question: what happened? They describe user behavior, website performance, or how many people your ad has reached. These are all events that happened in the past, thanks to which we can conclude whether we’ve reached our goals, whether things went as we expected, or whether we identified some problems. However, descriptive analytics don’t answer the question why. They’re not powerful enough to reveal what caused a problem, this is where diagnostic analytics come into play.
To be able to analyse why things didn’t work as expected, or maybe what the cause of your sudden success was (so you can repeat it), you need to measure descriptive data against other indicators to find answers, i.e. determine the causes.
For instance, to determine why you missed your net profit target for a particular type of product, you can analyse how different subcategories performed while comparing their characteristics. Let’s say you’re selling kitchen appliances online. If a type of product is not selling well across all models and prices, it might indicate that you missed your target audience for that product. However, if you look even further down, you might notice that a specific model performs significantly worse than others, or people only buy it within a certain price range. This will tell you whether you need to improve the performance of a particular model, refine your target audience, or invest in higher or lower price models, depending on your customers’ needs.
As the name suggests, predictive analytics answer the question: what is most likely to happen? These numbers are always estimates based on descriptive and diagnostic data over a certain period of time and form expectations for your company’s performance in the future. However, gathering insights about the market, your customers’ behavior, and your competitors, should also help you predict future trends - one of the most valuable insights when deciding on where to invest your resources.
Predictive analytics can be done by summing up descriptive and diagnostic insights, but today, most companies rely on advanced and sophisticated machine learning algorithms.
However, keep in mind that forecasts only work in a stable environment, so make sure you’re continuously optimizing the tools you have.
Finally, the most complex type of analysis is prescriptive analysis, which aims to answer the question: what actions do I need to take to eliminate the current problem and future risk, and grab an upcoming opportunity? The prescriptive analysis is the final stage of business analytics that uses advanced tools such as graph analysis, simulation, complex event processing, neural networks, and recommendation engines.
Today, prescriptive analysis in action is seen in autonomous vehicles that use complex calculations to determine when and where they need to turn, stop, or speed up to safely bring their passenger to their desired destination.
In businesses, these types of analytics can help you see patterns and identify customer needs before they’re even aware they have them. This way, you can leverage that and develop innovative products that will open up new markets.
Well, you should definitely use all of them, and basically, the four types of analytics mentioned in this article are ordered by complexity, which means using analytics of a higher complexity requires the use of lower complexity analytical processes first. You can’t use predictive analytics without descriptive analytics, just as you can’t use prescriptive analytics without predictive or diagnostics analytics.
Moreover, to answer the question, the stage of your company is an important factor. If you’re in your founding stage, descriptive analytics might do the trick, and as you grow, you can progress to more complex solutions.
However, keep in mind that progressing and using more advanced tools is a must! According to the 2016 Global Data and Analytics Survey: Big Decisions, predictive analysis dominated in the “Highly data-driven decision-making” category, which you might remember from our section on the importance of analytics where we revealed that data-driven companies perform far better than their competitors.
While this was quite a lengthy article, we’re aware that we’re just scratching the surface of the field of analytics. Therefore, for everyone that’s interested in learning more, we highly recommend the following books:
Big data is changing the world as we speak. New and more sophisticated technologies emerge every day trying to track and make sense of all of our activities online. Users want personalized products, services, and solutions that answer very specific needs. To be able to position your brand in such a demanding market, you have to understand and utilize analytics.
Hopefully, our article gave you a good idea on how to start, progress, and use different types of analytics in your business. However, there’s so much more to learn. To explore more about this topic, follow the resources we shared in our previous section. On the other hand, if you want to keep up with new trends, practices, and learn more about entrepreneurship in general, visit our blog and subscribe to receive new content from us!