5 Reasons Spreadsheets Hold Back Data Analytics in Marketing

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Rachel Serpa

Director of Content Marketing, Sigma

If you’re a marketer, you’re all too familiar with spreadsheets. Chances are you have one open on your desktop right now. Most marketers rely on spreadsheets to track metrics, analyze data, and visualize trends — they don’t have time to wait on their overloaded data team to deliver insights for daily decision-making. Whether you’re reporting the quarter’s MQL count, analyzing campaign performance, or building a pivot table to compare website visitors to conversions, spreadsheets allow you to (mostly) get the job done.

While many marketers use spreadsheets for marketing data analytics, the reality is that spreadsheets aren’t ideal. It’s likely you’ve already run up against their limitations and recognized their security vulnerabilities. Or you may have even ended up with inaccurate insights due to simple mistakes or outdated data.

Spreadsheets are problematic, and marketers are realizing this. If you Google “spreadsheets for marketers,” you’ll see 69,200,000 results offering tips and templates to get more out of your spreadsheets. Everyone is looking for a hack to make spreadsheets work better for marketing analytics — but these hacks can’t work miracles. In this post, we explore five reasons you may want to ditch the spreadsheet and adopt a cloud analytics tool (like Sigma) instead.

 Spreadsheets have scale and performance limitations

Spreadsheets are fine when you’re working with few data sources and small data sets. But growing companies generate a lot of data from disparate sources. If you don’t already, you’ll soon have valuable data coming from your SaaS software stack, ad platforms, social media, and proprietary systems or products. Massive amounts of data in varying formats completely overwhelm spreadsheet-based workflows.

For one thing, you quickly run into row and column limitations — not to mention Google’s 20MB limit on uploaded spreadsheet files. If you’re working with large datasets, you need capacity for millions (and sometimes billions) of rows. So you’ll need to break up datasets and analyze them separately. This siloing means you can’t get a holistic perspective, often leading to overlooked issues or misleading conclusions. Using Google Sheets or Excel for marketing analytics just doesn’t work when dealing with Big Data.

Even if you’re able to stay within the size and row/column limitations of Excel and Google Sheets, running complex analyses eats up compute power. You’ll experience significant delays, wasting time waiting for these tools to catch up. Cloud data warehouses like Snowflake and Redshift have incredible processing power, making analysis using a modern, cloud-native analytics tool near-instantaneous. You need the ability to connect to a cloud data warehouse with nimble processing capabilities that stores all types of data.

 Spreadsheets aren’t ideal for joining multiple data sets

Marketing data is typically stored across several systems, software programs, and platforms. You join datasets coming from HubSpot, Salesforce, Drift, and ZenDesk, for example, to see the whole picture of a trend, opportunity, or customer journey.

Trying to combine these datasets in Excel or Google Sheets is a nightmare. Most are incomplete, feature proprietary or inconsistently named metrics that are difficult to reconcile, or formatted in a way that’s challenging to work with. Maybe you’re dealing with duplicate records or the improper parsing of record fields from different platforms.

To get data ready for deep analysis and reporting, you have to go through a series of time-consuming and headache-inducing tasks. You end up pasting a bunch of spreadsheets to a single workbook and then striving to untangle differently-labeled columns and disparate values. Spreadsheets weren’t designed for analyzing multiple large datasets, and it shows.

 Spreadsheets make it difficult to collaborate

The best decisions are born from diverse people bringing their unique perspectives and ideas to the table. The sales and customer service teams have insights that you need. And you have insights that they need. Collaborating means more data points and a fuller picture. And getting everyone contributing to the analytics conversation is only the beginning. Insights must be acted upon before they’re useful, so you need to be able to share discoveries with others in your company.

But it’s incredibly challenging to collaborate with colleagues using spreadsheets. Sure, Google Sheets and Office 365 make collaboration easier than desktop-based software did. But spreadsheets are fundamentally designed for one-person management. Collaboration functionality is limited and cumbersome because it’s bolted onto a UX built for the individual.

When you try to collaborate, problems crop up — someone makes changes or deletes an analysis. You then have to go through the version history hunting for the one you need (which doesn’t include other changes and additions that were beneficial). You’re soon pulling out your hair as you try to update an older version to fix someone’s unsuccessful attempt to contribute.


Read our buyer’s guide to building a modern analytics stack and learn how you can take advantage of the cloud data warehouse. 

 Spreadsheets often contain out-of-date, inaccurate data

By nature, spreadsheets are a snapshot (extract) of data from one specific point in time. They don’t offer a way to easily update the data that analyses were based upon. Data that was valid and relevant on Monday morning may not be by Tuesday afternoon in today’s always-on market. So the resulting insights may be inaccurate.

Using a spreadsheet, if you want up-to-date information, you have to re-dump data. Because spreadsheet analysis is a manual process (and because spreadsheets are slow, due to the limitations we described in the first point), you can’t work fast enough to generate insights immediately after an extract. For reliable analytics, you need a tool that connects directly to the data warehouse so data is always live and updated in real-time.

 Spreadsheets are a data governance and security risk

When it comes to security, spreadsheets are a vulnerability. Once you extract data from a BI tool to a spreadsheet, there’s no way to ensure that people are using the information in a spreadsheet in a compliant manner. The information is also vulnerable to misuse or hacking when sitting around in a collection of spreadsheets.

Even a simple mistake can result in significant costs to a company. Who can forget the BlackRock fiasco of last year? The breach resulted from an employee accidentally posting a link to company spreadsheets containing confidential information about thousands of clients. Spreadsheets risk damaging careers and reputations. And they can have huge financial costs as a company seeks to mitigate damage.

For better data analytics in marketing, look to cloud-native analytics software

Fortunately, there’s an alternative to Google Sheets and Excel for marketing analytics. Modern cloud-native analytics platforms that connect directly to cloud data warehouses allow you to generate accurate insights from real-time data, get more efficient, and keep your data secure at the same time. Cloud-native solutions for marketing data analytics solve all the challenges spreadsheets present — and more.

And you don’t have to give up the spreadsheet interface you love to get the benefits of a modern analytics platform. Using Sigma’s intuitive spreadsheet-like UI, you can work with data just as you would in Excel or Google Sheets without the scaling issues, security risks, and other problems associated with spreadsheets.

Find out more about how a modern marketing analytics platform like Sigma can empower your team. Check out The Definitive Guide to Modern Marketing Analytics & BI.

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