Data-Driven Decisions – The Catalyst for SaaS Success

Big data. We’ve all heard the buzzword. Even more so as of late. 

Organizations big and small boast of leveraging data to their advantage, but the reality is most don’t have access to it, know how to appropriately analyze it, or what to do with it once deciphered. It’s true, some SaaS companies are built upon truly game-changing ideas, but more often than not, the most successful SaaS brands become so due to effective execution.

Success in today’s fast paced, information rich battlefield of business is largely the result of diligent planning, and intelligent decision making and execution driven by data. 

In a data-driven world, limitations, inconsistencies and gaps in data can often result in:

  • Inefficient operations
  • Poorly optimized processes
  • Ineffective prioritization of objectives
  • Lost revenue
  • And in dire cases, complete failure

But this doesn’t have to be the case. SaaS companies can embrace data in more effective ways to drive performance and steer the helm of their ship (so to speak). And for those businesses looking for a competitive edge, business intelligence can level the playing field against better positioned, funded or established competitors. 

Read on to learn more about how business intelligence is the new frontier in SaaS growth, optimization, revenue and profit.

Defining Reporting and Analysis Requirements

Ok, so you’re sold on your SaaS needing data to make informed, cost effective decisions that will help give you an edge and propel your brand forward. But what’s next?

Before a data strategy can be put in place, you’ll need to clearly define the types of requirements you have for both reporting and analysis. 

For example, do you need sales insights, customer journey data, marketing and growth KPIs? The answer to this question is unique to your SaaS and current objectives, but keep it in mind as we move forward.

When coming up with your reporting and analysis requirements you’ll need to define three critical elements:

  1. Events that generate data
  2. Measurements of that data
  3. Parameters of that data

Events

Simply put, these are the actions or processes you want to record data for. Examples may include events such as:

  • Sales
  • Cancellations
  • Support ticket responses
  • Web traffic
  • And more…

Measurements 

Measurements represent the actual numbers generated from those events above. For example, sales events may generate gross revenue and profits. Whereas cancellations or refunds may generate a loss of MRR or an increase in churn rates. The result, or measurement, will be expressed in a number. Here you will define what those numbers represent, and the value assigned to them (i.e. USD/currency, etc.). Some measurements will be simple to calculate, others may take into account data from multiple events or combine the data from different types of events to get the numbers you need to track.

Parameters

Parameters are one of the most important aspects of this whole data strategy. Think of parameters as the ways in which you may want to pull and segment data in order to answer specific questions.

For example, you may want to segment “sales data” by:

  • Customer type 
  • Marketing channel that generated the sale
  • Country of origin
  • Product / service
  • Profit margin
  • And more…

As you can see, this part of your planning might take a little doing, but it pays to think it through. Parameters established during this phase will be used by your developers later on in order to build processes and systems for gathering and filtering the data per your requirements in order to generate or develop insights that make sense to your organizational objectives.

Combined Data Warehousing – SaaS Intelligence Powerhouse

Sure, segmented data has its place, and can be an effective tool within independent business units or departments. But even in those cases the data provides but a small window into your SaaS’s overall operational effectiveness.

In order to make more effective cross-departmental correlations and causations, as well as ensure singular momentum towards overall objectives, you must first pull all of your SaaS’s data into a single data warehouse.

Take the customer journey for example. As it relates to churn and LTV, a customer that begins their journey at a certain stage, or is interacted with in a specific way, may impact the performance or engagements with that same customer farther down the path. In another example, actions taken in the customer onboarding department may impact the performance of the support department farther down the line. While these examples are simple illustrations at best, they can be applied to the most complex of backend processes and operational objectives.

This is why effective data-driven decision making is best made when you have ALL the facts in hand, and a true oversight of the big picture. 

Beware: Spreadsheet Paralysis can be Crippling 

Data is good. But data you can’t effectively and efficiently decipher to gain actionable intelligence for decision making can be crippling. This is especially true for smaller SaaS brands that may not have the internal resources to effectively gather intelligence from each tool or department for analysis.

What happens in those cases tends to be a disorganized and inconsistent self-reporting operating procedure in which each departmental head or assigned employee reports on key performance metrics, by spreadsheet or whatever available format they can muster together.

The end result is an entangled mess that even a rocket scientist would have trouble deciphering. Remember, data is meant to IMPROVE processes and the speed at which you can make decisions that further your objectives, not slow it down.

As such, care needs to be taken to streamline both the collection and interpretation of data. If your SaaS is limited on resources, start with the KPI’s or department that maters the most to your current and most imperative objectives. Establish data channels and analysis procedures for this first, expanding later on to other KPIs, systems or departments as it makes sense to do so.

Choosing the Right Tools for the Job

In construction there is a saying that “the tool makes the man”. With SaaS businesses, the tools make the brand! While some custom solutions will likely be needed, there are a broad range of integrative apps and products out there for data collection, analysis, interpretation and reporting, both for your brand, as well as competitive intelligence on those you’re up against. 

Let’s break down how to select the right options for the job…

1. Self-Service Reporting

Not all tools are created equal. And some don’t allow for the ability for you to simply jump in, place some filters and generate a report on the fly. However, this is a useful feature that most SaaS companies will need.

2. Drilling Down

Basic data can provide broad insights into what’s going on. But sometimes, oftentimes, you need to dig a little deeper, peeling the layers of the onion so to speak to get to the real meat of the situation. This is where the ability to drill down your data becomes vitally important.

Drill down analysis features you should look for include:

  • Grouping
  • Pivot
  • Slice; and
  • Drill-through

3. Painting a Picture – reporting & visualization 

Reports are great, but as they say, a picture is worth 1000 words…and a graph? Worth 10,000 more. Data visualization in the way of charts and graphs allows you to identify gaps and spot trends with ease. Visualization also makes it easier for less technically inclined individuals to digest the information in a way that makes sense to them.

4. Command Central

When you’re commanding your SaaS ship, keeping a close eye on the state of the union at any given time is important. This is where dashboards come in handy. They can provide you with situational awareness of the given state of things at any moment in time…often in real time (or close to it), bringing in data from multiple sources and departments into one easy to assess station.

5. Report Scheduling

As an SaaS, you and your team are on the move non-stop. Having to remember to sit down and pull a report each time it’s needed can be a real bottle-neck, or at the very least, a major frustration. The tool you choose for your data should allow you to define and schedule reports to be sent (by email or link) to those that need access. 

6. Integration and Compatibility 

We can’t always have our cake and eat it too, but when it’s possible, finding tools that integrate and play nice with your current tech stack is a major plus and certainly something to consider.

7. Mobile Support 

In the past, mobile support was a luxury….but in today’s mobile driven world with all of us “on the go”, mobile support has quickly become an essential element of any reporting tool. Whether via a dedicated app or simply a mobile friendly web interface, you’ll want to make sure the data intelligence tools you select are capable of being ran from mobile devices and tablets.

8. Security

As a SaaS provider, a major concern should be the safety and security of your users and their data, as well as proprietary data internal to your organization. Third party tools you utilize should have clearly defined security measures and privacy policies in place, as well as encryption protocols and off-site backups.

Closing Thoughts 

If your SaaS isn’t using data to make informed decisions on a daily basis, you may as well be asking the Magical 8-ball what your brand should be focusing on. Intelligent use of the right data at the right times can provide your organization with the critical insight it needs to operate and grow efficiently and productively, allocating resources to the areas where you’re bound to get the most benefit.

Further, data and competitive intelligence on the competition can provide insight into what other major players are doing to be successful, and you can use these insights to incorporate those same strategies into your SaaS.

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