Find your Way in the Jungle of Data Analysis Tools
I have since a year been obsessing about startups and especially their management of metrics and KPIs, as you can see on my website startupaction.co. It has led me to understand that knowing which KPIs to measure is not the first problem to tackle when being a data-driven startup. The first issue is to collect and access data, assuring its relevance and automation. That is the reason why I have moved down in the data analysis value chain to also help startups discover the many fantastic tools that exist out there to achieve accessible, reliable and automated data.
If you want to be business intelligence but don’t know where to start, this guide is for you. You might not need to hire a data analyst right away; these tools can help you get good access to your data and automate your dashboards and reporting. Depending on your knowledge, budget, and availability, different solutions might be right for you.
Let’s make a metaphor in the form of a cake (because, you know, we all like cake!). You can compare these tools to buying a ready-made vs making a homemade cake. You can probably buy a very nice cake ready-made, no efforts needed, in the store, but it might not be exactly as you prefer it, but it is a cheap and quick solution. Often, a ready-made cake from a nice bakery is at least as good as homemade, even though, you can’t get the exact characteristics that you look for. But, if you have baking skills and the time to spend on buying all the ingredients and making the cake from scratch, you could get a cake perfectly fit your needs.
What I mean is that, when you are an early-stage startup, it might be advantageous to go for the ready-made tool that has short set-up times and demand little knowledge. For later-stage startups, someone responsible for data could build something more tailored with tools such as Tableau, Looker, or Periscope Data. If you are starting out and don’t have millions of users, it is probably not necessary to invest in a team solely responsible for data.
Automated data analysis is a puzzle of different tools doing different things, and depending on your needs, skills and business model you should put together certain tools. When quickly googling for BI tools you discover the muddle of tools available. But how do you know which ones are best for you? I’ve put myself in the shoes of an early-stage startup founder and went out searching in the jungle. Lack of time and money is something that characterizes many founders, which has therefore been two important factors in my research. Anyhow, expect to invest between 100–500 USD per month to build up a perfect BI infrastructure.
It might sound hefty for a seed-stage startup, but when comparing that number to a data analyst costing maybe 5–10K USD a month, it’s peanuts! On top of this, don’t forget that your improved decision-making based on data can improve your revenues. Let’s think of an example: If you get a better insight to your product analytics, you might be able to improve your conversion rate from download to sign-up with 20 %, if all other metrics stay equal, your revenue will then also improve by 20 %!
Let’s get started! Here underneath you find all the recommended tools sorted by what they do.
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The Product Analysts
These solutions are very important to work with as you develop your product and improve retention and conversion rate. Thanks to these tools, you can find out what your customers want. If looking back at the cake metaphor, we could say that these solutions are similar to buying a ready-made cake that is very good in itself. The first time you log in, all your funnels and cohorts are already there. It could be advantageous, though, to add your own topping in the form of complementary tools to please your entire team.
Typically, these tools answer questions like
“Who are my best customers and what features do they love?”
“How do I get more customers and engage more deeply with the ones I have?”
“How can I keep customers around longer and earn more from them?”
I recommend to use the Segment, so you can easily switch between these tools, in case you wouldn’t be satisfied with your choice.
To get the most out of these tools (except Google Analytics), it is recommended to have at least 100 B2B users or 2000 B2C users to have enough data to analyze. Before reaching that mass, it is better to work with more qualitative data, such as surveys, interviews, or focus groups.
Google Analytics — We have all heard of it and it is, indeed, a fantastic tool. Its biggest advantage is that it is free. It is super easy to get started with and therefore is something to implement first thing when publishing a website. As long as your online business is only a website in the style of e-commerce or lead creation, Google Analytics is your perfect tool to track data. The most valuable information sources are funnels, cohorts, and marketing attribution (where do your best visitors come from?). If you instead have an app or anything else than a website, I recommend you to keep on reading to check out other product analytics tools.
Mixpanel — Is largely widespread among startups and is the most commonly used product analytics tool. It is available for both web and app. The most useful features include analysis of engagement, funnel, user profiles, and cohorts. This tool gives you access to all the data you need to know to improve your conversion rates and drive retention and revenue. “Mixpanel is the best tool for non-tech guys to get a feeling about what’s happening with their customers really fast. As soon as the events are correctly set up, it’s literally plugged and play” adds Nicolas Reboud, co-founder and CEO of Shine, who has been using Mixpanel since the launch of his fintech app.
What makes Mixpanel cutting edge is that they are developing machine learning features to help you find out the behaviour of your users with the highest retention or conversion, something you usually need a data scientist to understand. Anyhow, I have heard hesitant feedback of users who have tested this function.
Compared to Google Analytics, Mixpanel is more customizable and also allows you to send targeted messages to your users (and measure the response). To know which marketing source your users come from (marketing attribution), Google Analytics is easier and more automatic, even though it’s not impossible to set up in Mixpanel.
It is free to try it out if you have less than 5 million data points and less than 10k active users per month. To get full access with 1M data point or less per month, prices start at 999$/year for the engagement plan (to find out what users do) and 999$/year for the people plan (to find who your users are). Prices then quickly increase as you increase the number of data points.
Amplitude — Is very similar to Mixpanel, but as Mixpanel quickly gets more expensive with scale, Amplitude’s price increase is less steep as you begin to host more users. Compared to Mixpanel’s 5 million free data points, you have 10 million with Amplitude. On the other hand, you don’t have the advanced analytics functions, even though you should have enough to work with as you start off. Amplitude has recently started a new program offering startups the full Growth Plan at 750$/month. The large disadvantage of Amplitude is that it is not possible to connect to any of the data visualizers (see below), neither directly nor with Zapier. This means that you’ll have to build the connection yourself or pick another tool.
Other similar tools that you can check out are Kissmetrics, Heap.
The AB-testers
AB-testing, also called split testing, is a powerful method to optimize your business. It is an integral part of the testing culture promoted in the startups building bible “The Lean Startup”. AB-testing is the best way to improve conversion rates anywhere in your funnel, from ad design to check-out. It ultimately improves your revenue without making you increase your marketing spending, magic! Unfortunately, not all AB-testing platforms want to work with startups, for example, Optimizely and Convert.com demand minimum visitor numbers of 100k+. Here, I have listed the AB-testing tools fit for startups.
Google Optimize — Google launched this service about a year ago and it has proven to be really useful for AB-testing. With Google Analytics and Google Tag Manager, you can easily install Google Optimize and quickly be up and running with tests. Christoffer Petterson, Head of Growth at Minna Technologies, is one of the growth hackers who find Google Optimize really useful as he says “Our fintech app has 170 000 registered users, and for us Optimize is a great tool for AB-testing”.
VWO — When you have grown out of Google Optimize and are looking for something more advanced you should check out VWO. With VWO you don’t only have access to an AB-testing platform, but also heatmaps, target testing and their library of conversion best practices. With 49$ per month, you get access to their platform and all the basic features listed above. For this price, you can run about 5 tests per month. Recently, they seem to have started offering AB-testing on mobile apps, but not much is communicated on this matter.
Taplytics — If you have an app, Taplytics is the most cost-efficient alternative to get started with AB-testing. In Taplytics, you can run code-free AB-tests, test features and see the effect on retention, and control roll-outs. If you have less than 5K MAUs you can start with their free version, and for the full version you are charged 39$ per month for every 1000 MAUs.
Apptimize — This is, as you hear in the name, also for AB-testing mobile apps and seems very similar to Taplytics in terms of features. The big difference is the pricing — Apptimize costs 995$ per month up until 100k MAUs — which means plenty of room to grow.
The Subscription Analysts
When you are running a subscription startup, there are a lot of interesting and fundamental revenue-related metrics that can be identified only by using payment data. Thanks to these tools, you can super easily get access to your churn, retention, MRR etc without knowing how to calculate these. Unfortunately, since they only rely on your data from payment platforms such as Stripe, the data stays quite shallow. If we go back to the cake metaphor, getting a subscription analysis tool is like buying an excellent looking cake ready to be eaten. When tasting it, you realize that it is quite simple and you might after a while feel like you want something with more layers. So in summary, you should install a Subscription Analyst at the moment you signup your first subscribing customer since it is so easy and gives you so much value. But it could be good to complement with a tool that lets you analyze your engagement metrics (see the Product Analysts listed above) to understand why you see certain trends in your financial data.
Baremetrics — They connect with most payment solutions and is very nice looking and easy to use. You literally get all your high-level KPIs at the click of a button. The largest value that many startups see is the forecasting feature since it can be annoying and long to calculate yourself. What is truly unique about Baremetrics is their benchmarking feature, they are the only tool I have heard of that access the data of their users and turn this into valuable insights to the same users.
Baremetrics offers no freemium version and pricing depends on your MRR, up to $10k costs 50$ per month.
Chartmogul — As Baremetrics, Chartmogul connects with most payment solutions. What is different though, is the ability to connect more data thanks to the Zapier integration. When segmenting your data in Chartmogul, you can for example identify which marketing channels your most valuable customers come from. That possibility gives you a bit more depth compared to many other Subscription Analysts to help you answer the whys. The team at Chartmogul is working on a forecast feature, but it is not yet in place.
Chartmogul is free until reaching 10k in MRR, so there is really no reason to not plug it in and start using it from the moment you onboard your first customer. If your startup is part of one of their accelerator program partners, you can get a monthly reduction.
Other similar solutions are MRR.io, FirstOfficer, Exploratory and Profitwell (free).
The Data Visualizers
These are the tools that will allow your whole team to automate the KPI reporting and give you access to all the data that you accumulate from other tools. The Data Visualizers can be used for automated, customized dashboards and ad-hoc searches. These tools also make it easy to share data with investors or other stakeholders through email or URL links. If you are one of the many startups that feel like your data analysis is scattered and unstructured, this is the type of tool that you need. With these tools, you can connect the results you see in your Product Analyst with your marketing or sales activities.
Klipfolio — This tool is an incredibly flexible tool that can get extremely powerful. It is your centralized access to all of your company’s numbers. Doing the connections between the data sources and Klipfolio are very easy, as long as it is part of their very long list of connectors. So you can get started without any need of assistance from the tech team. You can either choose to use their template dashboards, but I recommend you to develop your own dashboards optimized for your business and goals. To learn how to do this, I recommend you to check out the article on “How to Get Started With Metrics in 5 Steps”
Klipfolio reminds you of some extent to Excel, as you analyze data with the help of formulas. The biggest difference is that Klipfolio updates itself with the most recent results and makes it easy to share the analysis. But exactly as Excel, Klipfolio takes some time getting used to and requires a learning curve. On the other hand, the customer service helps you get started, “When I needed to build my first Klip, it wasn’t as daunting as I have first believed. Clicking on their support button, I got instant step-by-step human help on how to configure the Klip to display our business data.” says Shirley Johansson, Growth CMO at Handiscover.
The pricing is very startup-friendly as it starts at 29$ per month for a team of 4 users. As you start to increase the size of your team, the 99$ plan including 20 dashboards is recommended.
Data Studio — One more time, Google strikes with their presence in the data analytics space by providing a free data visualizer. Unfortunately, it is very limited in use since it only automatically updates the data coming from Google products, so: Analytics, Adwords, DoubleClick, YouTube and Sheets. By using Google Sheets, you can manually update other data that you want to include in your dashboards, but as we know manual work is not sustainable and can quickly get time-consuming. Another alternative is subscribing to Supermetrics, that helps you to automatically connect a few other data sources, such as Facebook, Linkedin and Twitter.
Geckoboard — This tool has specialized in designing dashboards that appear on TV screens in the office. They offer a wide arrange of integrations. The price for an unlimited number of users is 149$ per month.
Other similar tools that you can check out are: Cyfe (cheap!), Data Hero, Grow, Microsoft Power BI.
The All-in-One Tools
The All-in-One Tools are incredibly flexible and powerful if they are well installed. If we go back to the cake metaphor, using these tools is like buying your ingredients and making the cake all from scratch. For sure, you will get exactly what you want but you need someone with skills in SQL to spend some time on setting it up properly. When it is in place, these tools that I have picked out here are fairly easy to use since the graphs are created using drag and drop. I recommend you to work with these tools if your customers are not interacting with you through a traditional platform (app or website) and you, therefore, need to build your analytics infrastructure from scratch.
Chartio — Is a highly recommended tool and I was actually hesitating on putting it under the data visualizers since it is kind of a hybrid. They have a list of 80+ directly connected data sources, and if you stick to these, you can be up and running without spending a minute on coding. In that case, Chartio can be used as a data visualizer. If you want to work with other data sources, Chartio also integrates with connectors, such as Segment. The interface allows for both drag and drop analysis in interactive mode and an SQL mode. Chartio is great if you’re a fast-growing startup since it fits small teams with little or no SQL experience but stays relevant as you grow into a more mature company with data analysts and data scientists.
Their biggest drawback is their secrecy around pricing, you have to do a 15-minute call with someone in sales to find out about the price. I literally have no idea if they charge 10$ or 1000$ per month.
Tableau — This is a very popular tool and is used by both larger enterprises and startups. On the other hand, you have to manually create all the connections between your data sources and Tableau. When it is in place, it is very easy to use thanks to the drag and drop function that also allows for easy segmenting. The pricing is straightforward at 42$ per user per month.
Other tools in this category, but less easy to use for business users include Bime Analytics (Zendesk), Looker, Periscope Data.
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As you can see, there is plenty to choose from. What is best for you depends completely on your business and your team. What I would recommend most startups anyhow is to install two things:
- Segment, or a similar basic layer for automation
- A suitable data visualizer
Then, I would recommend installing whatever is best for you around these two keystones. You might find Mixpanel, Amplitude, Chartmogul or other marketing or sales-oriented tools that haven’t been covered in this article as most needed to run your business.
As there are so many alternatives out there, I find it incredibly important to properly plan which tools to include in your stack. Moreover, it will be of your advantage if you research the tools and make sure that they fit with each other before signing up for anything. Make a sketch of your data flows to figure out which tools you need to get the data where you want it to make it accessible for analysis.
Hopefully, I have managed to clarify the mess of business intelligence and data analysis tools for startups. It would be great to hear your comments however you agree or disagree with anything I’ve said regarding these products. If you have tips on any great tools that I might have missed, it would be fantastic to hear your input! See ya! melinda@startupaction.co
