4 Must-Have Analytics Features Every Startup Needs
Senior Content Marketing Manager, Sigma
As a startup, you follow a different playbook than enterprise companies. You don’t have the luxury of extra time to grow slowly. You have milestones to reach as you rapidly scale out your business.
The growth playbook that works for the enterprise doesn’t work for you. And the BI tools made for them, designed to function with on-prem servers, don’t either. You must become more data-driven to fuel your next leg of growth, outmaneuver the competition, and confidently steer your business strategy. But you can’t do it with an insufficient BI solution that wasn’t built with today’s startups (and modern cloud technology) in mind.
In this post, we explore the key analytics features a startup needs to achieve a data-driven culture, using limited budget and human resources.
First, look to the cloud
The cloud offers incredible speed, near-infinite scalability, collaboration, and the flexibility you need as a startup. Your systems and software probably already live in the cloud, which is why your analytics and BI tool should too.
Without a BI solution that was built for the modern cloud data warehouse (CDW) and SaaS tools, you can’t take advantage of the the CDW’s power — or the vast amounts of data your systems and software produce. To generate timely insights, you need to access real-time data in a variety of formats, like JSON.
Beyond the need to efficiently connect with your CDW and access data from your cloud-based software tools, you should also be thinking about collaboration— a necessity for any data-driven culture. This means that every person in the company, regardless of their technical skills, should be able to use your BI tool and run their own analysis. If people are relying on your data team for reports and operating in silos, they won’t be able to take advantage of each other’s perspectives and expertise. This is especially true if they’re using Google Sheets and Excel, which have limited capabilities. These spreadsheets also create real security vulnerabilities as they get shared and passed around.
Modern cloud-native BI tools can help you overcome these obstacles. They connect directly to the cloud data warehouse and offer secure collaboration functionality. Users can share reports and dashboards with one another, participate in collaborative data modeling, and build upon each other’s work. Some tools, like Sigma, also enable business users to work in a familiar interface that doesn’t require technical skills since SQL is auto-generated —based on user inputs — in the background.
Cloud-native tools also allow you to achieve faster time-to-value because they’re easier and quicker to set up, require less maintenance, and have leverage near-infinite computing power for faster querying. And they do all of this at a lower cost than traditional BI tools.
See why tapping into the capabilities of your CDW is vital for growth and ROI — check out Is Your BI Tool Maximizing the Value of Your Startup’s Snowflake Investment?
4 analytics features startups can’t live without
Now that you understand how the right cloud-native analytics and BI solution can help your company become data-driven quickly and efficiently, how can you identify which solutions will do the job? Here are the four essential analytics features your startup needs.
Interactive dashboards and visualization
Human brains process visuals 60,000 times faster than they do text. Data visualization is one of the best ways to absorb large amounts of information, present data to key stakeholders, and tell a compelling story.
While some people are wired differently, most of us can’t easily understand complex statistical models or digest large datasets. But nearly everyone is adept at spotting patterns in visualized data. This is why all analytics tools offer dashboard functionality. Done right, data visualizations give viewers insight into the trends, goals, and metrics impacting a business.
But not all dashboards are created equal. Static dashboards provide a high-level view that shows what’s happening. They don’t allow users to ask follow-up questions to uncover why things are happening. You need to know what’s driving the fact that sales slowed in the Midwest in June or the number of MQLs dropped dramatically in May or the quantity of customer service requests skyrocketed in Q2. To solve a problem, you must understand why an event has occurred.
When using a static dashboard, leaders in your sales, marketing, and finance teams have to go to the data team for a report that provides answers to their follow-up questions. And because 71% of business users aren’t getting their data needs met in a timely fashion, decisions are delayed and opportunities are missed. And in some cases, business leaders are making decisions blind because their reports are unavailable when they need them.
Real-time, interactive dashboards, on the other hand, allow users to dive deeper, either through exploring the underlying dataset itself or by applying dynamic filters and parameters to the dashboard to get deeper insights. You’ll also want a solution that doesn’t require manually writing SQL to create interactive data visualization dashboards and manipulate them. You’ll experience much faster speed to insights when your business and non-technical users can create their own dashboards instead of relying on data teams each time a change is needed.
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Read our top 5 tips for using Sigma to generate dynamic, interactive dashboards for your organization.
Dashboards should also be easily shareable — either through embedding or public share links. You may need to share insights not only internally across teams, but also externally with partners and customers. Which brings us to our next key feature.
Embedded analytics functionality has several meaningful benefits, but two stand out as especially important for startups. First, it encourages people to look to data more frequently because it’s made available in their most-used software tools and convenient to their workflows. Second, embedding increases efficiency. People can get the data they need without switching back and forth between SaaS apps, and they don’t need to go to the data team for access.
Look for embedded dashboard functionality that can be customized according to each user’s needs via permissions set in the BI tool. Your users will need the ability to see or change specific data views in the dashboard or visualization.
For more specifics on what to look for in embedding functionality, see Look for These Must-Have Features in Your Next Embedded Analytics Platform
Get the complete rundown in our Definitive Guide to Embedded Analytics and Reports.
If you rely on websites, SaaS tools, mobile apps, social media, or IoT devices, your company is likely sitting on a wealth of semi-structured data, such as JSON. The JSON format has become the standard for data coming out of mobile devices, web applications, online services, and sensors. Unstructured and semi-structured data now make up 80% of the data collected by enterprises, and that number will continue to rise as these services and tools become more popular.
Your JSON data is a treasure trove if you can harness it effectively. You can identify patterns and emerging trends and gain insights that aren’t accessible any other way. But if you’re relying on a traditional BI tool that wasn’t built for the modern cloud data warehouse with its ability to quickly process this data, you’ll face roadblocks.
Look for BI software that makes it possible to easily identify and parse relevant JSON fields without having to write SQL. This way, even business users without technical skills can create data views that unlock the value of semi-structured data. You’ll also want to be able to join JSON with existing datasets for deeper analysis.
Domain experts can now parse JSON, join it with other structured data, and generate insights to drive better decisions with Sigma. Read our eBook.
Last-mile data modeling
By the time data gets to the analysis stage, it’s already been collected, transformed, and modeled at the warehouse layer. But semantic data modeling and final clean-up is often necessary before it’s useful.
Line-of-business teams are the ones closest to the data their tools and processes are generating. But with traditional BI, they’re typically excluded from the data modeling conversation simply because they lack data access and coding skills. Data teams know data, but they don’t have the perspective that the business teams have— so their models are often based on guesswork. Much back-and-forth is needed to get a model to a place where it’s relevant and usable, which is both time-consuming and inefficient.
Look for a tool that gives business users freedom in the “last mile” — where they can explore ad hoc ideas without waiting on data teams to update the central model. Sales, marketing, and finance leaders should be able to contribute to building highly-contextual models by adding definitions and calculations without the need to write SQL.
These models should also be easy to update as data processes evolve. The collections of modeled data can then serve as reusable bases for more detailed analyses by various teams in the future. Some tools, like Sigma, also allow data teams to pre-model joins between data sources and models, giving non-technical users a guided, endorsed path for exploration.
Sigma’s collaborative, visual data modeling approach brings data experts and business teams together to build centralized models that make data usable and insightful for everyone.
Startups need analytics features that support their playbook
Ultimately, without an analytics and BI tool that’s built for the startup playbook, you’ll hinder your speed and efficiency and miss out on competitive advantages. This is why choosing the right BI tool is so important — it’s like ensuring you have the best gear for the game.
Learn more about how you can use analytics and BI to scale your startup by checking out The Definitive Guide to Analytics and BI for Startups.