For the vast majority of companies, acquiring data is not the issue. It’s structuring, organizing and operationalizing that data. In this blog, we share the top 4 data challenges SaaS companies face, and how to fix them.
The world is full of data. It is predicted that, by 2025, there will be 175 zettabytes of data in the world, up from 44 zettabytes in 2020. Google alone processes more than 20 petabytes of data every single day, which includes 3.5 billion search queries.
The average company was managing 162.9TB of data back in 2016, with the average SMB managing 47.81 TB. This number was expected to double in volume by 2018, so you can only imagine how much data the average business is holding onto today.
With great data comes great responsibility, and many businesses are facing major challenges when it comes to protecting, operationalizing, and working with the data they collect. In this article, we discuss the four key data challenges that today’s business operators face, along with practical tips on how you can overcome these issues.
Challenge #1: You can’t find the data or insights you need in time
Between customer, website, product, transactional, marketing, and support, more often than not businesses have so much data that they struggle to find what they need when they need it.
When you can’t find the data points you need in time, your business will face several challenges:
Making data-driven decisions about marketing and product initiatives becomes impossible or too time-consuming
Interactions with customers are less personalized
Identifying growth opportunities is difficult
Answering complex questions from investors and other stakeholders becomes difficult
It might feel like the sheer volume of data is the problem. But more often than not, the bigger problem is the way your data is stored. When you have information stored in separate databases that do not communicate with one another, each department is looking at different sets of data and they can never access the whole story. It’s like reading chapter 18 of a book and expecting to understand how a central character got to where they are. Unless you can access chapter one, you’ll simply never know.
When your data is in silos, it’s incredibly difficult to maintain structural integrity and consistency across every data set. This means that, even after you go through a lengthy process to get the data (ticket to your data analyst, SQL query, CSV download…) you’ll have a bunch of CSV files that can’t be easily combined. And even when you do the work to combine your files and draw your insights, there’s a high likelihood you’re looking at inaccurate or incomplete data.
How to put an end to data silos:
Put an end to data silos by adding a customer data platform like Ortto to your tech stack. A CDP will bring data from marketing, sales, product, operations, finance, and support together to help your team find the data they need, when they need it. Ortto gives you access to simplified business intelligence, reporting and dashboards with built-in revenue attribution so you can answer difficult questions like:
Which product actions lead to conversions?
Which events or activities indicate customers are at-risk to churn?
What is the impact of customer support on MRR/CLV?
Are my campaigns driving MRR/CLV?
Which advertising partners are driving the highest quality leads?
When looking for a CDP to put an end to data silos, remember that your primary goal is accessibility to data and the ability to find the data you need. Look for a solution that offers intuitive and easy-to-use reporting and dashboards, as well as robust filtering and segmentation capabilities. Ortto was built to be an accessible solution, so we’ve ensured anyone, in any department, regardless of their experience with data, can easily build reports and build dynamic segments using any combination of demographic, firmographic, behavioral, event-based and transactional data.
Sign in or sign up to integrate your data sources and put an end to data silos for good.
Challenge #2: Your data is inaccurate, incomplete, or outdated
If you feel you have too much data, in too many silos, it’s likely some of that data is inaccurate, incomplete, or simply outdated. When a business is collecting data from different places, storing that data in different platforms, and does not have a standard way of capturing and updating data, it is easy for information to fall through the cracks, leading to inaccuracies.
When your data is inaccurate, everything you do with that data is at risk. For example:
Personalized content does not speak to the customer’s real situation
Marketing insights drawn from data are inaccurate or do not tell the whole story, leading to wastage in ad spend
Product insights are inaccurate or do not tell the whole story, making prioritization of new features or updates difficult
Benchmarks, goals, and progress towards KPIs are inaccurate
Sales and support do not have full context for customer interactions
Over time, these data mishaps can lead to a company-wide distrust in data. When this happens, it can become very difficult to restore trust in the data and inspire teams to make data-driven decisions, even after the problem has been fixed. The sooner you overcome this data challenge, the better off you’ll be.
How to fix inaccurate, incomplete, or outdated data:
Without good data input practices, your output will never be reliable. Start by eliminating the need for manual data entry wherever you can and creating clear, simple systems of manual data input where necessary. Use integrations to ensure your data platforms are speaking to one another and a change in one area is instantly reflected across the board.
Your CDP should be your central source of truth for all departments across the business. With all your data platforms connected through no-code integrations, updates, manual or otherwise, will be captured in real-time.
If you don’t yet have a data enrichment process in place, now is the time to start. There are a range of options when it comes to data enrichment, including audience surveys and forms where your customers and audience complete their data themselves, lawfully acquiring relevant third-party data to complement your existing first-party data, or using a third-party data enrichment platform like Clearbit.
Ortto customers can use Zapier to connect their CDP to their Clearbit account to keep their records up to date. Our data enrichment deep dive will show you how it's done and provides 10 real-world examples of how data enrichment can help you grow.
Challenge #3: You are not meeting data security and privacy standards
To put consumers back in control of their data, Europe’s General Data Protection Rules (GDPR) came into force in May 2018 — and these changes created an immediate impact on the data world.
Any business with any customer base in Europe was forced to reconsider the way they communicate with clients and handle their data — or face fines up to 4% of their annual global revenue. And no matter how big or small your business is, no-one is immune to non-compliance. To put it into perspective, Google was slapped with a huge $57 million fine by CNIL, France’s data-protection watchdog group (NY Times).
GDPR may have the most attention, but compliance does not end there. Any business operating in California needs to be California Consumer Privacy Act (CCPA) compliant and System and Organization Controls 2 (SOC 2) compliance, while voluntary, is something that more and more businesses are prioritizing.
Non-compliance to privacy laws is one piece of the puzzle. Any business handling large amounts of data should also work to ensure that the data they are collecting and the way that data is being stored follows best-practice security protocols.
How to keep your data secure
Data security starts with data collection. Ensure that your data sources are secure, and that all data you acquire is legally obtained.
When it comes to your existing data, it is crucial to stay proactive and futureproof security blind spots. Every company should have a clear data security practice in place, including a data usage policy, control over access to sensitive data, implementing change management and database audience, using data encryption, backing up your data, and identifying and classifying sensitive data. Any employee who handles data in any capacity should go through security and privacy training to ensure data is always handled correctly.
Vet the security and privacy standards of every data-storing platform in your tech stack and avoid any platform that does not meet your standards. At Ortto, we offer enterprise-level security features and are GDPR, CCPA, and SOC2 compliant to ensure data security.
Review your existing compliance processes in the context of GDPR and evaluate the visibility of your current tech stack, especially security software, compliance tools, and vendor management – basically, anything data related. And if you’re using email marketing in your customer journeys, you need to make sure you’re GDPR-compliant. In addition to obtaining your contacts’ consent before emailing them, you must also respect their personal data.
When you are dealing with large volumes of customer data, staying compliant and protecting your data is business critical.
Challenge #4: You don’t know how to operationalize the data
Some businesses have data that is unified and well-structured, but when it comes to actually using that data for decision making, prioritizing specific initiatives or identifying opportunities, their teams just don’t know where to start.
This is what we’re referring to when we say ‘operationalizing data’ — taking all that information and turning it into something actionable. When a business lacks the ability to operationalize data, the data is rendered useless and you risk missing out on major opportunities that your competitors could spot and run with.
If the three challenges above have not been addressed, they will be contributing to the problem. If they have, there may be other things at play, like:
Lack of trust in the data
No singular source of data truth
Lack of confidence in reading and interpreting data
No data-driven culture in the organization
Lack of data ownership and process
How to overcome roadblocks around operationalizing data:
Let’s assume you’ve followed all of our advice above, you have your data unified and structured in a CDP like Ortto, and you are still struggling to make good use of it. Often, rather than trying to solve all your business problems at once, it is best to identify one specific opportunity using data and work through each process issue that arises one by one.
Next, find an individual or small team of people who are comfortable with data, and task them with owning this end-to-end. They will be the people who spearhead the initiative, sell it into the relevant team, and keep it moving forward.
Once the necessary data has been compiled and insights have been pulled, your task owners should work closely with the team using the data day-to-day (often marketing or sales) to figure out what the process looks like, and answer questions along the way.
An early win can mean the difference between team-wide trust and hesitation, so focus on a project that helps the team reach their goals. Once success is proven with one project, you’ll be well on your way to building a data-driven culture. Nothing motivates like a win.
The final word
Big data can come with big headaches. Ortto is an intuitive, accessible customer data platform that unifies your data to unlock insights. With easy-to-build, visual reports and dashboards, built-in revenue attribution, and robust filtering capabilities, Ortto enables every team and individual to make data-driven decisions.