Unveiling Data Insights: The Methodology and Use Case of Marketing Data Collection in Digital Marketing and Market Research
After you have executed your marketing campaigns, it is crucial to assess how they performed. In order to do this in an effective manner, you must make use of a solution that consolidates and analyzes data. Nevertheless, how can you be certain that the monitoring and primary data collection methods are accurate and dependable enough to guarantee the accuracy of your evaluations?
Have you ever questioned the reliability of a performance measure in your report? Is that KPI really showing how well your marketing strategies are performing, or does it suggest a mistake in tracking or an unexpected filter? If you said “yes” to the first question, it means you have doubts about the accuracy of the data you are collecting. You can certainly double-check everything later, immediately after examining the particular KPI, but this procedure consumes a significant amount of time, and if there was a tracking mistake, any type of data could be lost permanently.
The best way to eliminate doubts about your data’s quality is to establish a data quality process that identifies and corrects anomalies as they occur. To optimize the supervision of the collected data, you should follow these three steps:
Adopting a Consistent Approach for Data Collection
No need to worry – it’s not as complex as it may appear. Simplifying the terms used and organizing the relevant data structures becomes possible when you bring together all the digital marketing data, which includes customer data and requests from various teams. For instance, the team responsible for acquiring new customers might want to keep track of the number of new clients, while the CRM team is interested in monitoring the number of purchases made by each customer. In this scenario, the shared aim is to monitor the customer count, their level of experience, and the number of “purchase” engagements. You can accomplish this centralization all at once or adjust it annually, taking into account the requirements of each marketing team and the corresponding business goals.
For instance, if you offer two different services, like “bank” and “insurance,” or “transport ticket” and “luggage service,” make sure to mention these distinctions during the data collection process, in the names of your marketing campaigns, on relevant pages of your website, and when triggering e-commerce conversions (you can use abbreviations when appropriate!). Additionally, specify the marketing device’s objective or the desired positioning in the conversion funnel. Is it a campaign targeting prospects (at the top of the funnel, in the “upper-funnel”) or existing customers familiar with the brand (in the “lower-funnel”)?
Once you’ve established the list of needs and corresponding objectives, agree on the abbreviations and communicate them to all the acquisition and analytics teams. If the list includes key elements like country or campaign (a limited number), relevant to all teams, maintaining the standardization over time will be easier.
Streamlining Data Collection with Automated Reports
Standardizing data effectively simplifies anomaly monitoring. You can now set up a process to monitor the percentage of non-standardized data you collect. Whether it’s an uncategorized marketing lever (traffic landing in an “others” channel on your report or data management tool dashboard) or an uncategorized transaction, tracking volumes of unclassified data helps identify problems and provides a complete list of anomalies to address.
To automate this process, create scheduled reports (daily, weekly, monthly) using dynamic formulas, such as on protected Excel spreadsheets or Google Sheets. Set an acceptable threshold (for instance, less than 10%) and monitor categories that exceed it.
However, remember that categorized data is not always reliable. It’s crucial to keep an eye on critical thresholds and judge variations compared to the previous period. One way to do this is through a dashboard with KPIs displaying evolution variations. A quick weekly check of a clear and centralized dashboard can save time, especially during the balance sheet period. Adding a weekly comment in your customer data platform tool allows you to better understand the reasons behind significant developments and consider them when interpreting KPIs.
Implementing Trigger Rules to Promptly Address Deviations
Being proactively informed is essential to correct any anomalies that may arise over time. If possible, automate email alerts (as is possible on the Wizaly attribution and analysis platform) for marketing campaigns with significant challenges. However, triggering alerts should remain an exceptional action to avoid distraction or inundating your inbox with additional emails. Consider setting up trigger rules like:
- “More than 10% uncategorized daily traffic”
- “No display impressions during the campaign period”
- “A critical drop in transactions of more than 70% compared to the average of the past week”
By following these steps, you can optimize your method of data collection and ensure the data’s quality and reliability for performance analysis of your marketing and media campaigns.
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