9 criteria for driving business results with analytics in 2022

Even before Google sent brands and publishers slow-walking to wean themselves off third-party cookies back in early 2020, both the buy- and sell-side had a data problem. 

The issue has been that publishers and brands have historically managed audience data in siloed systems. Therefore, critical information surrounding ad revenue, subscriptions, content engagement, and customer profiles is all stored separately. 

However, to create truly relevant experiences for consumers, any digital businesses must be able to tie all this data together in privacy-compliant ways to achieve a full picture of the customer journey. The IT department no longer governs data and analytics to the degree that it once did. So, commercial teams like marketing, sales and finance now have the opportunity to more heavily influence these areas than ever before.

Time to get your data analytics in order

Next year will be the last full one brands and publishers have before third-party cookies expire. So it is the perfect time to fully get your data analytics in order. Here are nine criteria to consider when rethinking your strategy.

1. The ability to customize your data model

To begin piecing together data from multiple touchpoints, it's important to first introduce a unified data model approach across the organization. A tailored data model that covers the entirety of a business's objectives as well as those of the different company stakeholders provides access to a reliable 360-degree view of customer data. This enables any team that needs to tap into the data to create immediate value, improving speed to market and the ability to react to trends faster.

2. Access to live, quality data

Whether you want to integrate with other technologies or enlist your data science team to work on a special project, you want to ensure you have streamlined access to fully denormalized, real-time data. This reduces query time and improves targeting and personalization, while avoiding the costly joining of disparate databases.

3. Enriched data that does deeper

Make sure you can automatically correct, enhance and remove data based on third-party metadata and advanced processing rules, with no retagging necessary. This will allow you to do more with your behavioral data to explore different perspectives that can inform your business decisions.

4. A universal tag for data hygiene and cleanliness 

Tag health is critical for proper data cleanliness and consistency. Many businesses have multiple tags running. That increases the number of server calls and overall time spent on tag management. By instead leveraging one universal tag, you can duplicate traffic across various sites to a virtual site with 100% accuracy and for half the cost.

5. No data sampling

Data sampling is the practice of analyzing a subset of your traffic data, which is used to estimate the overall results. Instead of gathering all the data, you only get access to a limited sample. That means that any analysis you carry out after that will be an assumption based on existing patterns. Having a complete set of data to analyze boosts accuracy and can unlock previously undiscovered audiences.

6. Compliance with all privacy regulations

This might seem like a no-brainer, but with evolving and emerging laws, it’s easy to fall into violation when it comes to data privacy. Ensure whatever tool you work with is compliant across all of the global privacy regulations and that you can tweak your consent model as needed.

7. Integration across your stack

Your data is only as good as it is useful. If you are using disparate systems to manage and activate it, there is a chance of data loss, inaccurate customer views and privacy non-compliance. Ensuring interoperability across all systems streamlines execution and management while reducing business risk.

8. Democratization of data

Once you know your data is clean and accurate, make it available to everyone in your business who needs to act on it. You want to keep the end user experience in mind when choosing the right tools. Whether you use dashboards, data exploration tools, smart alerts when anomalies occur or direct API feeds for personalization, make sure they are user-friendly.

9. Professional services help

Even if you have an in-house analytics team, ensuring all of your data flows through your systems well might require additional support. The best technology vendors will have robust professional services teams that can help you implement your analytics strategy. This includes determining your KPIs and measurement approach in addition to best practices that drive both compliance and results.  
It’s prime time to harness the true power of all the data at your disposal. With the right technology and talent, you can fast be on your way to turning insights into action that drives additional business value — more website traffic, subscriber, and revenues.