Data Analytics for Startups: All the Must-Knows
Startup founders are often too preoccupied with building a product, and they tend to put off analytics for later. But this might not be the best idea as analytics can aid a startup in identifying a proper growth path, getting to know the users, and making better decisions.
Although the process may be intimidating for many business owners who are just beginning their journey, it isn't rocket science. Proper analytics are a "must-have" for any company that wants to succeed.
This page is devoted to analytics for startups. We'll discuss why this process matters, when to start using analytics, and how to adopt a data strategy.
What Is Startup Analytics and Why Is It Important
Your startup is like a live and fragile organism. It needs lots of care and attention to grow big and successful. And to be sure that you're doing everything right, you should monitor multiple signals and "health signs", showcasing its progress.
Data analytics for startups implies the process of collecting and analyzing information to help make business decisions and plans and take action. It is crucial to do so both when you're starting a startup and growing it. Implementing tools like dbt macros, which streamline data transformation and analysis processes, can significantly enhance the efficiency and effectiveness of your data analytics efforts
When Should You Start Paying Attention to Startup Analytics?
Taking analytics seriously as early as possible is considered a best practice. It isn't an activity that you should leave for later or eventually "grow into".
On the contrary, you can use analytics as leverage to facilitate business growth. If you don't postpone this work, you'll safeguard yourself from fatal startup mistakes early on and have a better chance to avoid wrong decisions based on guessing.
Analytics can help you during every stage, from the discovery phase and creating a product roadmap to MVP development and the work you'll do after the launch.
It seems quite logical to make use of data for these purposes, yet data analytics often becomes a roadblock or barrier. This happens because many people find analytics too challenging or fear misinterpreting the information and making the wrong calls. The reason for that is that data analytics is often perceived as something too confusing. For instance, the tracked metrics may be poorly organized or require specific knowledge or too much time that an early-stage startup doesn't have to spare. Yet, luckily, there exist modern analytics solutions like Mixpanel or Amplitude that provide an essential kit for even those who aren't too analytics-savvy.
What else can put the brake on startup analytics adoption? The variety of possible metrics to track can bring many startup owners and newbie entrepreneurs up short.
It's sort of like watching over puppies: keeping an eye on each one may be tough in itself as they'll most likely be moving around chaotically, each in their own direction. But putting them in a "fenced area" will make the task manageable and give you much more control. What do we mean by that? You must be positive regarding what customer and product data you're tracking and why you're doing so.
In one of our previous articles, we talked about how metrics differ from KPIs and how the set worth tracking will differ from business to business, depending on its stage, product type, goals, plans, and many other factors. Plus, we explained how to select a relevant set of KPIs and metrics to measure a startup's product performance:
What Are the Benefits of Startup Analytics?
By pursuing the data-driven approach and monitoring your analytics timely, you'll get to fill in many blanks and gain insights that'll be essential for your business. For instance:
- your startup's overall performance;
- how well you're doing in terms of achieving your set goals;
- how to improve your product;
- your customers' behavior;
- the demand for your product;
- which startup marketing strategies and sales techniques work (or don't);
- whether you're moving towards finding product-market fit;
- what are the emerging trends;
- what are the problematic areas;
- among other things.
Startups are prone to iterations. And having such knowledge in a quickly changing environment empowers startups to make data-backed decisions. This can positively impact the business strategy, help mitigate risks, allow you to make more realistic predictions, set goals, and aid in startup scaling and product growth.
With reliable data at hand, you'll be much more confident about what to prioritize, what needs change, which activities to invest in more or drop, and where you're moving in general. Thanks to startup analytics, you'll also know:
- how your product is perceived by customers;
- how to enhance your offering;
- which features to work on;
- how to optimize your internal processes;
- which markets to expand to;
- whether you need a business pivot;
- and a lot more.
How to Adopt Startup Analytics in 3 Steps
If you're considering diving deeper into data analytics capabilities or aiming to formalize your expertise, mastering data analysis can significantly impact your startup’s strategy and execution. Achieving a Data Analyst certification on DataCamp ensures that your skills are industry recognized, providing a solid basis for making informed decisions, optimizing operations, and enhancing product offerings based on real-world industry practices.
Using data analytics as a startup's strategic tool can be a wise choice regardless of your size or stage of startup development. And the best part is that you don't necessarily need a designated team to handle the data. Let's go over a few fundamental steps to help your startup launch its analytics.
Step 1: Determine What You're Trying to Achieve
First and foremost, think about your business goals and objectives. The key point here is to base your analytics strategy on your core aims.
Then try to outline what you ultimately need data analytics for and how you'll use it. What kind of data can help you reach your goals? What problems should it help you solve? Which questions will it allow you to answer?
Say, you want to monitor how effective your Product Hunt launch was. Or you would like to know how much value users are gaining from your product or service, then you may look at various engagement metrics. For instance, a high average session duration can signal that users are actively interacting with the product and that you're on the right product-led growth path (i.e., are building a worthy product that presents value to your users).
Finalize your goals and shortlist the corresponding metrics that can indicate your performance, success, or failure. You may first aim at metrics that'll reflect your acquisition, activation, and revenue and then give attention to retention and referral. But the suitable set of metrics should and will change over time. Plus, don't forget to establish the time frames for each to get tangible results.
Step 2: Set Up Analytics Tools
To begin with, you can go for Google Analytics. The website has pretty straightforward setup instructions. After getting a tracking ID and embedding analytics into your solution, you may continue making tweaks, indicating what you want to track and which goals and flows matter to you most.
When you are all set, you can think about strengthening your analytics stack by linking up tools, such as Mixpanel or Amplitude. Before settling on an option, you should pay attention to the ease of integration with your existing environment, as well as the simplicity of maintenance and usability. On the bright side, free trials are usually available for you to test the waters.
Step 3: Monitor Your Data and Take Action
As you begin receiving data, it's time to investigate and interpret the results you've obtained over a specific time period. You can hire someone for the role (for instance, delegate this responsibility to a Data Analyst or Product Manager).
But if you decide not to hire anyone at this point, don't be shy to discuss the findings with various team members to generate hypotheses, determine the optimal startup growth strategy, and create an action plan. With more people on the team involved in analysis, decision-making may accelerate.
Be on the lookout for changes and make respective adjustments to your plan, product, or activities when necessary. Then repeat this step when the next time frame ends, i.e., measure the results again, discuss, and make changes.
Startup Analytics: Tips and Best Practices
Here are a few additional recommendations that can aid your startup in using analytics to your benefit even more.
1. Pay Attention to the Metrics That Matter
Which metrics have the most impact on your business decisions? Limiting yourself to the set that'll truly bring value is reasonable. Less is more in this case, as data hoarding can become an unneeded distraction. Additionally, prioritize hybrid multicloud data security to ensure the protection and integrity of your critical business metrics.
Note that peeking at what your competitors are tracking and trying to copy-cat their strategy is not a good idea; it simply might be an irrelevant waste of time. Your products are different, so you need your own set of metrics, OKRs and KPIs.
The bottom line is that you should keep only those metrics that can aid in empowering your strategy. Just as with the lean startup framework, it is advisable to go with lean startup analytics, that is, those with a laser focus on your goals and the most important questions on the agenda.
2. Check Your Analytics Regularly
It makes sense to do your best to habitually look into your analytics, ideally, on a daily basis. If you do so once in several weeks, you'll fail to see the complete picture and really understand what's going on.
It's fine if some days show declines and others display upswings. Your task is to stay on the lookout with your hand on the pulse to avoid unpleasant surprises.
3. Make Data Comprehension Easy for Everyone
Equipping your team with enhanced and accessible data reporting (when every digit and figure is clear and understandable) brings many advantages. Therefore, consider using data visualization like dashboards to assist your teams in quickly comprehending the incoming information. This way, even non-business analysts will stay informed and have the possibility to use data to their benefit. Here's an example of an employee engagement dashboard you can check out.
4. Keep Running Tests
When you think your analytics strategy and product are as good as done, you're probably wrong since there's always room for improvement. There are likely ways to improve your performance, tweak usability, and boost your pages. So put in the time to run A/B tests or use other MVP testing methods to continue moving forward.
Common Mistakes with Startup Analytics
Below, we'd also like to bring up a few things that a startup shouldn't be doing with analytics. This can also help you get the most out of your effort.
1. Don't Collect Data for the Sake of It
If you're not doing anything with the knowledge that's provided by your incoming data, then what's the point of even collecting it? Can you put to use all the data that's being tracked?
Data analytics provide food for thought and should be used to drive change and make decisions. For instance, you can fall back on data when working on product feature prioritization or planning the work that matters most at a given time. So, focus on the metrics that add value to your startup most and avoid wasting time and resources on the rest.
2. Don't Pay Attention to Vanity Metrics Too Much
Vanity metrics are the numbers that look fascinating on the screen yet don't always stand for something truly worthwhile business-wise. For example, considering a high number of website visitors, impressions, or video views a product or MVP success isn't exactly the right way to go. Alternatively, looking at the number of daily active viewers instead of the overall website traffic would be much more meaningful.
Once again, you should be monitoring those metrics that can reflect the real state of your performance and the realistic startup valuation, not those that seemingly make you feel good about your activities. Filter out the "noise" and leave only accurate analytics.
3. Don't Jump to Conclusions Too Soon
It's way too common for startup owners to panic when they see the first signs of "turbulence" in their analytics. But before you rush to take immediate action, take some time to evaluate and interpret the data and observe the trends. Ask yourself, "Is this change significant enough for us to act on?"
You might be having a bad day in terms of analytics, that's fine. So, keep an eye out for the changes instead of putting in the effort to solve an issue that might not even be there.
Final Thoughts on Startup Analytics
Tangible data that you can fall back on may become the foundation of your business strategy and core decisions. Using analytics as leverage instead of relying on gut feelings can be a rational way to approach a startup's launch and fuel its further growth. This way, you'll have a better understanding of your customers, the market, what to change, and where to move next.
Getting started with data analytics may be intimidating for a startup. So if you need help with the analytics setup, don't be shy to contact Upsilon. We can give you a hand with analytics system integration (such as Mixpanel or Amplitude). Plus, we provide data visualization services and can assist you in transforming your data into a visually accessible and intuitive tool fitted with interactive dashboards and customizable reports that every team member can easily manage.
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