Why Data Analytics is an Essential Addition to Your Marketing Toolbox

Information is at our fingertips, but it is frustrating to look through every single detail manually. This is where Data Analytics sparks up the room.

Before the age of information, ads grabbed attention and drove sales with limited room for scrutiny. Today, buyers have access to endless data that they can cross reference. This has made the market very fragmented and less predictable.

Marketers are bound to struggle with endless streams of metrics and analytics because, at one point, it becomes monotonous. Today we will be discussing how data analytics can help you make smarter marketing decisions.

Sifting Through Your Data

B2B digital marketing lets you dive deep into critical marketing data sources. This feature enhances campaign performance and return on investment (ROI). Aberdeen found out that companies with thoroughly put-out content management processes outperform those without them. Developing the essential elements of a marketing plan is crucial for achieving long-term success. It involves understanding your target audience and defining clear objectives for your campaigns. By leveraging data-driven insights, businesses can effectively allocate resources and optimize their marketing strategies.

It is also reported that the average website conversion of those firms are nearly twice that of regular firms. Additionally, average click-through rates are 30% higher.

It is easier to have a proper understanding of customer behavior by properly examining marketing data. Because it allows for informed decision making and strategic planning, the data retrieved from these analytics should be used to identify and follow up on MQLs. Understanding what drives marketing qualified leads will significantly ease your marketing efforts.

Stepping Up

The true potential of B2B analytics lies in its actionable insights. Industry data shows that a large number of B2B marketers use organizational data to measure digital marketing success. Almost 65% of the reports state that analytics has revenues of over 10%.

Analytics lets businesses collect data from miscellaneous marketing channels. This information can also be shared across teams. Many CRM tools offer mobile apps, making them more accessible. This way, all members of the enterprise can get updates on the go.

Becoming a Data-Driven Organization

To become a data-driven B2B company in the true sense, it’s important to collect data with purpose in mind. For this, you will need to plan:

• Understand and establish clear business goals
• Ask the right questions
• Measure relevant metrics

Establishing Business Goals

Clearly understood business goals act like your north star in the roadmap of B2B success. Improving sales, getting more customers, making better ads, no matter what you want to achieve, having a goalpost in mind helps you focus.

However, the problem is that companies often come up with broad goals. Due to them being so vague and undefined, the projects face the risk of being mishandled. Every move you make should have a core objective. Make measurable and specific goals like:

• Increasing website traffic by 10% in the next quarter
• Boosting email sign-ups by 400 in the next two months

Think of data as a massive toolbox. Without knowing what you’re building, you might be holding a wrench when you really need a screwdriver.

Asking the Right Questions

The quality of your analytics depends on the quality of questions. Once you know ‘what’ you want to achieve, you should start to consider the ‘how.’ Remember, questions work as the bridge between your dreams and achievements.

You can opt for two categories of questions— strategic and operational. The strategic ones should focus on the big picture, and the operational ones should include specific details. But that’s just half the battle won. To make the right decisions, you need to analyze user interaction.

User Behavior Data

Focus on server-side tracking for digital metrics due to increasing browser restrictions on third-party cookies. Client-side methods can lead to data loss, affecting marketing evaluations.

It’s time you integrate server-side tracking. It uses cookies controlled by your domain. This method showed a 30% reattribution of ‘direct/none’ traffic and a 12% increase in returning users. This ensures accurate CPA and ROAS for marketers and correct acquisition attribution for analysts, boosting their value in marketing campaigns.

The next step is to document every measurement and tracking from businesses. This documentation helps you avoid future mishaps and confusion. Even though, on the surface, it seems like a lot of paperwork, it saves a lot of time in the long run. You can use Excel or Google Sheets to do this for your clients.

Image via MeasuresofSuccess

Also, there’s this notion of believing that everything related to data is up to the analysts. You would be wrong to think that. Analysts can’t handle product or website changes. Draw the line of responsibilities and educate your entire group on how to help. This way, everyone will know what to do.

Cost Data

When working with ad platform data, it’s crucial to provide detailed information for effective marketing strategies. Without specific data, like details about each ad and keywords, marketing teams might resort to using data directly from ad platforms, disrupting your data setup. Ensuring they have the necessary details helps maintain data integrity and improves ad performance.

Creating custom connectors for handling platform data is a significant task. APIs require regular maintenance, and business users often underestimate the ongoing effort required. While they might initially appreciate new data, they may not understand the continuous work needed to keep it running smoothly.

In conclusion, if you want to do well, use your resources to their full extent. Know what your business appreciates and let clients know. Build your analytical strategy from the information gained.

Digital analysts don’t need a lot of skills up their sleeves. Data warehouses like BigQuery aren’t that complicated to handle. If you are looking for a wider range of possibilities, opt for a warehouse in the next step of your analytical roadmap.