What’s Possible with Sigma: 8 Analytics Use Cases Customers Love

From marketing and finance to sales and operations, the decisions teams must make and the challenges they face are nowhere near the same as they were ten, five, or even two years ago.

Unexpected events like the global COVID-19 pandemic, technological advancements such as the cloud, and the growth of data and its associated threats and requirements have changed business at its core.

The average adult now makes more than 35,000 decisions each and every day. Your company’s approach to data analytics must evolve to empower everyone to make accurate and informed decisions at the speed, scale, and level of granularity required by the world around us.

The good news? Sigma’s cloud-native analytics and business intelligence (BI) solution was purpose-built to enable companies to identify and navigate today’s toughest challenges and biggest opportunities.

Teams across industries use Sigma to easily conduct complex yet critical analyses to find the real-time answers they need to deliver business outcomes like reducing customer churn, improving operational efficiencies, and maximizing revenue.

From marketing spend attribution to supply chain optimization, this playbook digs into what’s possible with Sigma and the use cases our customers love the most.

Reimagining the Data Analytics Workflow

Before we dive into our most popular use cases, it’s important to first understand why status quo analytics no longer work, how Sigma is different from other BI solutions on the market, and what a modern analytics workflow should look like.

What the traditional analytics workflow looks like

Whether you’re a business domain expert or sit on the data/BI team, the following workflow will likely look familiar to you. Unfortunately, it’s hardly conducive to making agile, data-driven decisions in the face of sudden supply chain disruptions, new market share opportunities, or real-time customer demands.

How Sigma is different from other analytics tools

How do teams get stuck in this outdated analytics workflow? About 62% of companies say self-service BI tools, or tools that enable line of business workers to generate insights independently, are essential to their success.

These companies are investing billions of dollars in solutions that claim to deliver on this vision — and what they’re getting are surface-level dashboards, month-long BI request queues, and risky data extracts. In other words, companies are buying into the promise of self-service analytics, but the paradigm has fallen painfully short.

These traditional self-service BI solutions fail to deliver for 3 key reasons:

  1. Retrofitted for the Cloud
    They weren’t built for the cloud or to leverage the full advantage and power of the cloud data platform. Access to data inside Snowflake Data Cloud, Amazon Redshift, or Google BigQuery is limited and requires extensive pre-modeling.
  2. Scale Limitations
    They’re unable to scale to support the volume and variety of data generated today. Data must be extracted, summarized, or aggregated for analysis, which prevents teams from drilling into dashboards and reports at a granular level.
  3. Coding Skills Required
    They require SQL or proprietary code to join in new data sources, ask ad hoc questions, and do complex analysis. The vast majority of workers lack these skills and are forced to resort to using the tool they know best: the spreadsheet.

In contrast, Sigma is redefining self-service analytics in a way that enables companies to reimagine the traditional data analytics workflow.

Sigma is different from other BI solutions in 3 key ways:

Sigma was born in — not retrofitted for — the cloud, and purpose-built to harness the compute power and security of the cloud data platform. It provides teams with direct, governed access to all of the data in Snowflake, RedShift, and BigQuery for analysis — no pre-modeling required.

Uniquely Scalable
Sigma leverages the unlimited scale and speed of the cloud data platform to crunch through billions of rows of live data in seconds. Data never leaves the warehouse or has to be summarized or aggregated for analysis, so teams are able to easily drill down to row-level detail as needed.

Familiar User Interface
Sigma gives everyone the power of SQL through its spreadsheet-like interface, which converts familiar, Excel-like formulas and functions to optimized SQL so no technical or coding skills are required. Sigma eliminates limiting, risky extracts and accelerates time to insight by up to 90%.

What a modern analytics workflow looks like

Because Sigma delivers on the promise of true self-service BI and empowers anyone to do ad hoc investigative analysis, companies are able to realize the full value of their cloud data platforms, the data they have collected, and even their employees.

This effectively transforms the traditional analytics workflow and cuts the number of steps it takes for business teams to move from question to answer in half:

  • STEP 1 A business domain expert from marketing, finance, sales, etc. has a question OR wants to drill into the data underneath an existing dashboard from Tableau or other visualization tool.
  • STEP 2 They open their cloud-native analytics tool to get direct, governed access to all of the live data inside their cloud data platform.
  • STEP 3 They use the spreadsheet-like interface to join data sources together, calculate, filter, sort, do what-if analysis, create visualizations, collaborate with teammates, and get the answers they need. This process takes anywhere from 30 seconds to a couple of minutes depending on the complexity of their analysis.
  • STEP 3.5 The BI team cheers while enjoying the freedom to work on the more challenging, strategic, and innovative data projects they love.

8 Analytics Use Cases Sigma Customers Love

With a clear understanding of how Sigma has empowered companies to completely reimagine the traditional data analytics workflow, it’s time to dig into 8 specific use cases our customers love most in more detail.

Marketing Spend Attribution

What it is

Marketing spend attribution is the science of determining which touch points, channels, and messages along the customer journey have the greatest impact on conversion. The goal is to identify the tactics and initiatives that generate the highest return on investment (ROI) to refine marketing strategy, efficiently allocate spending, and accurately forecast results.

Who cares about it

  1. Marketing teams across all industries — Marketers need to know how the money they’re spending is impacting the bottom line so they can better predict outcomes, defend performance, and course-correct in real-time.
  2. Sales teams across all industries — Sales teams want to know how many viable leads to expect from marketing within a given timeframe so they can roll up more accurate forecasts.
  3. Executives across all industries — Business leaders expect marketing teams to invest the company’s money wisely and maximize positive returns over time.

Which business outcomes it drives

  • Minimize customer acquisition costs
  • Increase marketing and sales conversion rates
  • Maximize the return on marketing spend

Why it matters now more than ever

The average customer journey now consists of more than 60 touch points along the path to conversion. With so many potential points of influence, it’s more difficult and critical than ever for teams to pinpoint which marketing efforts are moving the needle to invest their budget and resources accordingly.

Where traditional analytics falls short

Each prospect and customer interaction creates dozens of data points. Over time, this adds up to millions or even billions of rows of data that must be analyzed at once for accurate insights. Spreadsheets tap out at around a million rows, and most BI tools crash under this load.

Marketing attribution requires an end-to-end view of the customer journey all the way through sales to customer success. Marketers alone use an average of 12 applications — getting a complete picture means joining data across dozens if not hundreds of disparate data sources. This is a complex and code-heavy modeling exercise with traditional analytics tools.

Marketing attribution dashboards are common, but typically display KPIs at an aggregate level across entire channels or campaigns. Digging into the data underpinning the dashboard to answer follow-up questions or get a more granular view into individual ad or messaging performance is not possible without BI assistance.

How Sigma makes it possible

  • Because Sigma was built to leverage the compute power of cloud data platforms, it effortlessly crunches through billions of data points in seconds — everything from prospect zip codes to products purchased to cost-per-click.
  • Joining data from across marketing automation platforms, CRMs, and even CSVs is easy for anyone with Sigma. Even semi-structured JSON data can be parsed and joined into an analysis in just a few clicks via Sigma’s spreadsheet UI. BI teams also have the option of “pre-joining” or linking various data sources marketers may or may not want to include in their attribution analysis.
  • Sigma offers its own visualization tools, as well as works alongside traditional dashboard solutions like Tableau. Because all data is accessed live in its entirety directly from the cloud data platform, marketers can click directly into the data underneath the dashboard to investigate data down to the individual ad or asset level in Sigma’s spreadsheet UI.

The Sigma marketing team’s own go-to-market dashboard with attribution metrics

Success story

Yesware, a popular sales productivity platform, used Sigma’s spreadsheet UI to join four years of marketing pageview and product trial data in just a few days — without ever typing a single line of code.

First, the team matched every single site pageview and tracking event with anonymous user IDs. Once a user was identified through a trial signup, they backfilled the data and mapped these anonymous users to known email addresses.

Next, Yesware combined data from, Google Analytics, Salesforce, Zendesk, and Google and Facebook ads for a complete view of user behavior at each stage of the funnel.

Sigma gave them the power to analyze, optimize, and attribute ROI at every touchpoint, resulting in a 50% reduction in customer acquisition cost.

Want to keep reading?

Learn about embedded analytics, product/service performance reporting, and 5 other use cases Sigma customers love!