As marketers and data analysts, you’ll deal with vast amounts of data. Getting a single view over all this data can be time-consuming and daunting — that's why businesses often lean on data automation tools to speed the process up while maintaining data quality.
In this blog post, we'll explore what data automation is, its benefits, what can be automated, and the challenges that come with implementing data automation.
What is data automation?
Data automation refers to the use of technology and software to automate the process of collecting, organizing, and analyzing data.
By automating repetitive tasks such as data entry, data processing, and data analysis, marketers and data analysts can free up time to focus on higher-value activities such as developing marketing strategies and making data-driven decisions.
What can be automated with data automation?
Data automation can make marketers' lives much easier by automating various tasks, including:
Data automation tools can collect data from various sources such as social media platforms, website analytics, and customer relationship management (CRM) systems.
Data Transformation and Enrichment
Data automation can transform data from different sources into a unified format, enabling easy analysis and visualization. For example, converting currencies from different campaigns, or grouping similar metrics which are given different names by different platforms (e.g. price and costs).
Data automation tools can analyze data and generate reports, dashboards, and insights that can guide your marketing efforts.
Data automation Vs. ETL/ELT
ETL stands for ‘extract, transform and load’, and describes a three-step process of extracting data from a source, transforming it so it is cleaned, harmonized, and can be compared with other data sources, and then loading it into a target database such as a data warehouse or BI tool.
You can read more about this in our blog about ETL Vs. ELT.
While ETL/ELT describes a process that could be done manually - you could export CSV files from all your different data sources, manually convert all the numbers, copy and paste them into new columns, add in meta-data, clean up inconsistent naming, and then upload it all to a database - more commonly this automated using ETL or ELT tools.
However, while ETL or ELT is commonly an automated data process, the concept of data automation is much broader focusing on automating the entire data journey. This includes processes like ETL/ELT but also all data processes from data collection right through to visualization, analysis, and even data governance.
Benefits of data automation
So what does that mean in concrete terms — what benefits can marketers and analysts get from automating their data?
- Freeing up time
One massive benefit of data automation is that it can save marketers hours of reporting time, enabling you to focus on high-value activities such as developing marketing strategies.
- Reducing errors
Data automation can also reduce the number of errors that come with manual data entry and processing. Higher quality data means better decisions are being made to optimize your activities and stretch your budget further, while also building trust in your data. Without this trust that comes from having high-quality data, few employees will act on data insights.
- Make data-driven decisions faster to optimize budget
The speed at which data automation tools work means that they can be made much more quickly. It’s much easier to make decisions and course-correct on a campaign if you have a clear view of marketing performance across all your channels. This means spotting opportunities for channels that are performing well and giving them a boost, but it also means catching anomalies like a huge spike in CPC for certain AdWords. By catching these kinds of budget drains early on, you can avoid wasted ad spend.
Challenges in implementing data automation
Implementing data automation comes with several challenges, most of which can be broken down into three categories.
Data automation tools can be expensive, and if you already have a complex reporting process with multiple tools that you’re working around, finding a tool that integrates easily with all of this can be tricky.
However, as the evidence continues to grow that data automation can bring huge competitive advantages, investing in connecting up data across your team and your company isn’t the leap of faith it once was. The benefits are fast becoming too valuable for competitive organizations to ignore.
Tech alone isn’t enough to ensure a solid data automation strategy. Data automation tools require expertise to operate, which can be a challenge for organizations lacking data analysts or IT staff. In fact, research has uncovered that while 85% of CMOs recognize the ability to make data-driven decisions as a critical competitive advantage, a lack of data skills on the team is a key barrier to investing in the data automation tools to make this happen.
Setting up an automated data workflow is one thing - but how do you make sure that it’s actually reaching the right people, and impacting decision-making in a positive way?
Data democratization is the framework that ensures workflows are built to contribute to wider business KPIs. Basically, data democratization means all employees, including non-specialists with lower data literacy levels are able to access and gather accurate data about the business from a single source of truth on their own without any outside help.
You can find out more about how to implement data democratization here.
"You might have the greatest tech stack in the world feeding you business-changing forecasts on your ad spending and delivering real-time performance data, but if this isn’t translating to actions, then it’s useless."
Alexander Igelsböck, CEO, Adverity
Conclusion: the importance of data automation
Data automation can provide immense benefits to marketers and data analysts. It can save time, reduce errors, increase efficiency, and provide real-time insights into your marketing efforts. Instead of waiting days for a report, marketers can act quickly to spot opportunities for campaigns that are performing well, while dialing back budget on campaigns that aren’t delivering ROI.
While there are challenges to implementing data automation, the risks of waiting to build a data-driven business while competitors capitalize by using data automation tools are fast becoming too great for marketers to ignore.