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6 Steps to Use Big Data for Successful Marketing Measurement

Read here how to reach data-readiness for successful marketing measurement.

March 29, 2022

Engaging in modern marketing across channels, markets, and target audiences produces significant marketing metrics and data load. To make absolute sense of your marketing activities, you need to make the most of the available data. Consistent marketing data flow and monitoring are quintessential in a campaign, channel, and budget optimisation. However, successfully implementing Big Data requires a few steps to ensure quality. And it comes with certain limitations and discrepancies as well. Different sources assign different names to the same metrics, fragmented data types slow down the analysis, and manual insertion requires hours of repetitive work that may lead to mistakes.  

Objective Platform works with leading brands in marketing and helps them turn data into insights. We support them in implementing data into their marketing processes by ensuring that all relevant data is synchronised for the most efficient marketing performance measurement. Specifically, we developed a unified marketing measurement solution that combines data, modelling, and decision-making in one platform. To offer our clients the most refined marketing insights, we make sure that we make the most out of their data. Even though you can always hire or train someone to do this manually, Objective Platform opts for the automated approach. That way, you save time, eliminate errors, have access to more information in a shorter time, and create a scalable way of working. Objective Platform takes care of the configuration, integration, and performance of the system for you. So, your marketing teams can start to make proper decisions based on the readily available data.  

To increase the impact of your marketing and promote growth, you need to align your data. Thankfully, there are 6 steps to follow for a successful data implementation. Continue reading to find them out.  

1. Data extraction  

The very first step involves understanding your data sources. Marketing metrics include data from multiple sources (Social ad platforms, demand-side platforms, CRM & CSM systems, web analytics software, and (Paid) Search platforms). So, you need to define the sources you want to extract data from. Then, you can start looking into the data offered by these sources to continue with the harmonisation. That includes the data structures, data labels, the type of information, and the relationships between them. This is the step where you understand which transformations are required.  

2. Data Aggregation  

The second phase sees the execution of the transformations mentioned above, starting with data aggregation. During this process, you search, gather, unify, and transform the data into marketing reports. This is where you start understanding how your datasets compare to each other. You can now aggregate the data based on your parameters for comparison and categorisation.  

3. Data Cleansing  

Data-driven marketing is very often oriented towards unstructured or useless data. At this stage, you proceed with the data cleansing to ensure that you do not make marketing decisions using outdated, inaccurate, or incomplete data structures. Objective Platform puts in place an automated process where your data is scanned for syntax errors, fragmented data, and typos. Then, our specialists proceed with the correction of the abovementioned outliers.  

4. Data Filtering  

When you have cleaned all your data structures, you need to ensure that you use the correct data for your purposes. This is where data filtering comes to the rescue. During this step, you refine the datasets and eliminate duplicate and irrelevant bits. To do so, you need to decide which rows, columns, and fields you want to see in each dataset.  

5. Data Integrations  

Once you’ve cleaned and refined your data, you can begin merging the various datasets into a single structure. Unifying the datasets coming from multiple sources is the most crucial part of the data implementation for UMM. And it is arguably one of the benefits of this process.  

6. Data validation  

Data accuracy and structure is essential for accurate marketing insights. For this reason, it’s not enough only to refine the data once. You need to set automated rules and algorithms that constantly verify the quality of your data and notify you of any discrepancies. In case of an outlier, the user is alerted and fixes any errors.  

Objective Platform is a unified marketing measurement solution that helps brands increase the impact and accountability of their marketing across channels and campaigns. Our data implementation process ensures the creation of a single source of truth with:  

  • Automated data intake & validation from 200+ data sources.  
  • Easy data validation to ensure consistency.  
  • Data harmonisation for a unified view of all relevant metrics.  
  • Use of the data for model configuration in the Unified Measurement Framework for your business.  

Read here how we helped Staatslotterij turn their data into insights.

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