Data is the life blood of any SaaS company. Data will entitle “youve got to” make better decisions and help you originate faster. However, few corporations fix the most of their existing data or get access to the data they need.

This guide is meant to help you go from zero to analytics skillful as soon as possible. It doesn’t subject if you’re starting from scratch or if you’re simply are seeking to grade up your existing data strategy. We’ll help you get access to the revelations you need to grow your SaaS business.

D.I.G.: Our process for data strategy

The process we use is called D.I.G. We have experimented and refined this methodology over the past three years across more than 40 projects. After uttering every gaffe imaginable, we now know what it takes to implement a data strategy successfully.

D.I.G. stands for ๐Ÿ˜› TAGEND

Discover : Which metrics and KPIs should you road? Implement: Which tools do you need to collect accurate data? Grow: Which reports or dashboards do you need to create?

dig saas data framework

D.I.G. is an iterative process that you can run over and over again. For this guide, we’ll focus on setting up a solid foundation. We’ll too give you some advanced ideas at the end of this affix for those who are ready.

Let’s start with Discover: characterizing the index of metrics and KPIs that you should track.

Discover: Which metrics and KPIs should you road?

Before we start using implements or writing system, we need to know which metrics to track and why we were just trying to road them. This is a business discourse and not a technical one.

One of the most common corrects that we interpret fellowships start is bouncing this stair and assuming they already know what they want to move. For example, I was on a bellow recently with a company that was struggling to get basic insights from their network app. They knew high-level figures like sign-ups but couldn’t burrow deeper into their onboarding move or retention.

On our call, the company told me about all the technical question they had come across and how its own development squad didn’t seem to know how to do the most basic circumstances. While that may have been true, I knew that the most pressing question was that they didn’t know what they wanted to track–they couldn’t alter their business needs into concrete KPIs and metrics.

Instead, they asked for unclear message like “track our onboarding performance” or “track user retention.” Most growing crews struggle with uncertain petitions, so–for that fellowship and all others–we need to obligate the KPIs as clear as possible.

The first step is to define our KPIs across the customer journey.

KPIs for “the consumers ” jaunt

The customer journey is the series of steps that a used must take to become a patron. There are different frameworks out there, but we like Pirate Metrics since it aligns quite well with how SaaS commodities are built and marketed.

pirate metrics framework

Our journey makes lieu across the following stages: Acquisition, Activation, Retention, Revenue, and Referral. For the different stages, we want to schedule the most important point metrics and KPIs, and a few other things.

We’ll plan our thoughts into official documents called a Measurement Plan.( You can download our template by making a transcript of the Google Doc .)

The document looks like this for the different stages ๐Ÿ˜› TAGEND

saas data plan

We start with the business any issues that we want to answer. Then, we move on to business objectives, then to metrics and KPIs. We tend to use metrics and KPIs interchangeably, but in this document, KPIs are the one or two quantities that tell us how well we are doing at the present stage; metrics provision more detailed information on the overall performance.

Consider the company I mentioned in the previous section: They wanted to “track our onboarding conduct, ” which is ambiguous. They needed to break that down into the different categories in the Measurement Plan above.

The prime KPI is the overall shift pace through the pour( e.g. 50% of users end the move ), but we also have other metrics that can help us understand the journey ๐Ÿ˜› TAGEND

First app open( first step of the pour) Average app conference Sign-ups into the free experiment( happens at the end of the onboarding)

We can also listing the way in which we are going to be able segment our data, the targets we want to set, and the tools we’ll need. As you can see above, most KPIs are business focused–not technical.

A special note on segmentation: This is where the magic of data happens, so spend some time “ve been thinking about” this ingredient. We move three different kinds of segmentation ๐Ÿ˜› TAGEND

Demographic: Message about the subscribers, like their location, device info, etc. Marketing attribution: Which canal or expedition raised the subscribers to us? Behavior: This is specific to your concoction. For instance, if a customer can create an accounting through Google or Facebook, this can become a segmentation option.

Some stages may not be relevant to your busines right now. For lesson, you may not have a referral program in place, so you can ricochet that theatre and come back to it another time.

Fleshing out the present document can convert indistinct requirements into concrete next steps. Business stakeholders will understand the role of data, and technical stakeholders can start to think about what data to accumulate to deliver on these metrics and KPIs.

Once you ended both documents, you’re ready to move on to the Implement stage.

Implement: Which implements do you need to collect accurate data?

Most companies tend to start at the present stage. This is the “sexy” stage because we get to talk about tools and cool aspects. The objective of this stair is to figure out which implements we need to way the data in our Measurement Plan.

Adopts the right tools for your company

There are hundreds of options when it comes to implements. Electing among them is to be able to exciting( if you like research) or overwhelming. Either direction, you should think about the following four happens before choosing any implement ๐Ÿ˜› TAGEND

Budget: Do you need enterprise carry? How much are you willing to spend on tools on a monthly or annual basis? Internal capabilities: Does your squad know languages like SQL? If not, then you need tools that can make it easy to create reports/ dashboards without it. Role in the load: You won’t find a implement that can do everything you need. Instead, you’ll need to create a stack of different tools. You’ll naturally have some overlap, but you want to minimize it as much as possible.

When thinking of your stack, there are a few lists that you need to fill to get a complete picture of your produce. I’ll explain the categories and a few favourite recommendations. You can start with these recommendations but too look for alternatives that might be better suited to your company.

Data abstraction: Instead of implementing five different tools, how are you able streamline your data implementation efforts–so it can be done once and then sent7 to all five tools? Options like and mParticle fit here. Marketing attribution: Which marketing campaigns or channels drive the best users? Ideally, you want to track this data through “the consumers ” jaunt instead of stopping at the upper part of the funnel. Options like Google Analytics( web traffic) and Appsflyer or Branch( portable attribution) fit now. User demeanor: What are users doing within your produce? Are they completing the onboarding process or use a specific facet? Think retention, date, and concoction habit. Alternatives like Heap and Amplitude fit now. In-app messaging: What is the best channel to mail targeted sends to your users? These letters can be SMS, email, push notifications, or in-app letters. Alternatives like Intercom and Braze fit now. Revenue metrics: What is the best practice to track your SaaS revenue metrics like Monthly Recurring Revenue( MRR ), Annual Recurring Revenue( ARR ), churn, etc .? This gets a special category since these metrics tend to come from your remittance processing provider. Alternatives like Recurly and Chargify fit now. Qualitative data: What is the best direction to move qualitative data like conference enters, Net Promoter Score( NPS ), or surveys? Ideally, you demand a implement that lets you do multiple things( e.g. heatmaps, time recordings, investigations, etc .) Alternatives like Hotjar( network) and Appsee( mobile) fit now.

Educating a technical plan for implementation

Once you know which tools you want to use, prepare a technical plan for your development squad. This is typically called a “tracking plan” and synopsis all the technical details that your blooming team needs to take care of. You can find templates for moving programmes immediately from Mixpanel, and Amplitude.

Here’s what the document was like ๐Ÿ˜› TAGEND

data plan implementation

This document is critical because it determines what data actually get implemented.( I could write a entire affix on how to replenish one out .) Likewise, most companionships have scarce increase epoch, so this document were able to has become a time saver or a duration suck for your developers.

Here are some general guidelines to get it right ๐Ÿ˜› TAGEND

Think of happenings as wars within your produce. Indicating up is an action that can be translated into an happening called “Sign Up.” Aim to implement 5-10 occurrences in your first round. You can always apply more later on, but you want to get a perceptible make before asking for more increase season. Try to captivate as much data as possible within the affair owneds. Qualities help you describe specific actions that users take. In our “Sign Up” example, we might have properties like:

Reputation: Ruben Ugarte Email: ruben @randomdomain. com Authentication Method: Google Plan: Free

User attributes or properties help you describe the user. You can use them to captivate things like spot data( municipal, country, and sphere) or specific occasions about your commodity, like receipt or behavioral traits.

If you want to dive deeper into how to form these documents, here’s a 15 -minute video in which I tread you through all the details ๐Ÿ˜› TAGEND

Once you finalize your tracking program, work with your improvement team to get into product. After a few weeks, you’ll be ready to move on to the Grow step.

Grow: Which reports or dashboards do you need to create?

The Grow gradation is the dessert of our dinner. If you followed the previous steps suitably, it is desirable to rather simple. The objective is to create the necessary reports or dashboards to imagine the metrics and KPIs from the Discover step utilizing appropriate tools from the Implement step.

How you compose these reports or dashboards depends on the tools you selected, but here are a few universal guidelines.

Public: Consider who will use this report. Dashboards for a CMO versus your sell squad can be quite different. The CMO dashboard will focus on a handful of metrics like Customer Acquisition Cost, Lifetime Value, and ROI; it likely will show progress towards targets( quarterly, monthly, etc ). The marketing squad dashboard will show the performance of specific market expeditions, execution across specific segments, and other granular metrics. Prioritized metrics: In our Measurement Plan, we prioritized the most important KPIs and metrics. Our reports and dashboards should show those options. Less is more. Comparisons: Remember that a number by itself doesn’t mean much. It advantages making once we sacrifice it situation, which we can do by likening it to a previous periods of time( e.g. this month vs. last month) or by likening it against a target( e.g. current advancement vs. expected change ). Cohort useds: To find changes over time accurately, it’s helpful to cohort users. The simplest lane to do this is to cohort customers by sign-up date( e.g. all users who signed up during September ). Grouping users is all-important as you boost with data. Segmentation: As I mentioned during the course of its Discover step, segmentation is where the spell happens. Ideally, you already took this into account in your moving plan–this is when you derive the honors. Utter it easy to slice your data within such reports or dashboards.

Don’t forget training and deployment

Before “youre finished”, make some time to think about training and deployment. This doesn’t have to be complex. The aim is for your team to use the data. To do that, they need training on how the data is structured and how to use the tools you implemented.

We recommend that, at a minimum, you do three concepts ๐Ÿ˜› TAGEND

Team periods: These are general seminars for your part squad that mask the basics. Run 1-3 of these conferences over a few months. One-on-one sessions: These sessions should be geared toward specific individuals and such reports they care about. Run 3-5 of these times over a few months as well. Slack channel: If you use Slack( or something similar ), create a path dedicated to analytics. Parties can announce their questions and get immediate answers and explanations.

That’s it. This is how you set a foot in place or improve existing data struggles. Once you surmount these first few steps, you can undertake more advanced ideas–like the ones in the next section.

Bonus round: Advanced hypothesis

The D.I.G. process is meant to be run over and over again. For our patrons who have a solid foundation in place, we work on more advanced new ideas and exercisings. Here are a few to consider ๐Ÿ˜› TAGEND


Baseline and targets: What is a good changeover rate? What is “good” retention? Develop your baseline metrics, then appoint targets for any experimentations you run. You require historic data before creating baselines, which will help you specify reasonable targets. User personas/ groups: Who are the different used radicals within your produce? Who characterizes as a “power user”? How can you convert normal users into superpower consumers? Just like above, this is necessary data in order to be allowed to group users. This is a more advanced edition of the cohort idea mentioned earlier.


Internal processes: To properly maintain data over period, install internal characters for who will take possession of personal data implementation. Generally, this person is a developer who works closely with the marketing and product units.


In-app messaging: How can messages drive action and retention? What should be the reasoning for setting up and testing these words? A/B testing: Now that you have data, deploy A/ B experiments across key sections like onboarding, retention, and date. Baseline/Target reporting: Formerly you make your baselines and targets, compute them to your key reports. This is a great way to add context to reports and track advancement.

One final level: Consider these advanced thoughts exclusively after you get the basics right. Move before you can run.


Let’s finish by going back to the company I mentioned in the first illustration. After going through these steps, they lastly got access to the penetrations they needed to understand their product.

They started with expansive askings( e.g. “track our used retention” ), then converted those needs into specific KPIs and metrics exercising the Measurement Plan record. They moved that into a technical tracking propose, which their development squad enforced. As it turned out, their developers were quite capable–they just needed better instructions.

Finally, they created the right reports and dashboards for their busines. Coming the first two steps right realise the final one a breeze. Now they waste their occasion thinking of more advanced ideas to get even more price from their data.

The post SaaS Data Planning: A Start-to-Finish Guide to Implementation saw first on CXL.

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